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Pant B, Gumel AB. Mathematical assessment of the roles of age heterogeneity and vaccination on the dynamics and control of SARS-CoV-2. Infect Dis Model 2024; 9:828-874. [PMID: 38725431 PMCID: PMC11079469 DOI: 10.1016/j.idm.2024.04.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2023] [Revised: 04/10/2024] [Accepted: 04/11/2024] [Indexed: 05/12/2024] Open
Abstract
The COVID-19 pandemic, caused by SARS-CoV-2, disproportionately affected certain segments of society, particularly the elderly population (which suffered the brunt of the burden of the pandemic in terms of severity of the disease, hospitalization, and death). This study presents a generalized multigroup model, with m heterogeneous sub-populations, to assess the population-level impact of age heterogeneity and vaccination on the transmission dynamics and control of the SARS-CoV-2 pandemic in the United States. Rigorous analysis of the model for the homogeneous case (i.e., the model with m = 1) reveal that its disease-free equilibrium is globally-asymptotically stable for two special cases (with perfect vaccine efficacy or negligible disease-induced mortality) whenever the associated reproduction number is less than one. The model has a unique and globally-asymptotically stable endemic equilibrium, for special a case, when the associated reproduction threshold exceeds one. The homogeneous model was fitted using the observed cumulative mortality data for the United States during three distinct waves (Waves A (October 17, 2020 to April 5, 2021), B (July 9, 2021 to November 7, 2021) and C (January 1, 2022 to May 7, 2022)) chosen to align with time periods when the Alpha, Delta and Omicron were, respectively, the predominant variants in the United States. The calibrated model was used to derive a theoretical expression for achieving vaccine-derived herd immunity (needed to eliminate the disease in the United States). It was shown that, using the one-group homogeneous model, vaccine-derived herd immunity is not attainable during Wave C of the pandemic in the United States, regardless of the coverage level of the fully-vaccinated individuals. Global sensitivity analysis was carried out to determine the parameters of the model that have the most influence on the disease dynamics and burden. These analyses reveal that control and mitigation strategies that may be very effective during one wave may not be so very effective during the other wave or waves. However, strategies that target asymptomatic and pre-symptomatic infectious individuals are shown to be consistently effective across all waves. To study the impact of the disproportionate effect of COVID-19 on the elderly population, we considered the heterogeneous model for the case where the total population is subdivided into the sub-populations of individuals under 65 years of age and those that are 65 and older. The resulting two-group heterogeneous model, which was also fitted using the cumulative mortality data for wave C, was also rigorously analysed. Unlike for the case of the one-group model, it was shown, for the two-group model, that vaccine-derived herd immunity can indeed be achieved during Wave C of the pandemic if at least 61% of the populace is fully vaccinated. Thus, this study shows that adding age heterogeneity into a SARS-CoV-2 vaccination model with homogeneous mixing significantly reduces the level of vaccination coverage needed to achieve vaccine-derived herd immunity (specifically, for the heterogeneous model, herd-immunity can be attained during Wave C if a moderate proportion of susceptible individuals are fully vaccinated). The consequence of this result is that vaccination models for SARS-CoV-2 that do not explicitly account for age heterogeneity may be overestimating the level of vaccine-derived herd immunity threshold needed to eliminate the SARS-CoV-2 pandemic.
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Affiliation(s)
- Binod Pant
- Department of Mathematics, University of Maryland, College Park, MD, 20742, USA
| | - Abba B. Gumel
- Department of Mathematics, University of Maryland, College Park, MD, 20742, USA
- Department of Mathematics and Applied Mathematics, University of Pretoria, Pretoria, 0002, South Africa
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Glaser N, Diexer S, Klee B, Purschke O, Binder M, Frese T, Girndt M, Höll J, Moor I, Rosendahl J, Gekle M, Sedding D, Mikolajczyk R, Gottschick C. The contribution of SARS-CoV-2 to the burden of acute respiratory infections in winter season 2022/2023: results from the DigiHero study. Int J Infect Dis 2024; 144:107057. [PMID: 38631507 DOI: 10.1016/j.ijid.2024.107057] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2024] [Revised: 04/10/2024] [Accepted: 04/10/2024] [Indexed: 04/19/2024] Open
Abstract
OBJECTIVES In winter of 2022/2023 SARS-CoV-2 had developed into one of many seasonal respiratory pathogens, causing an additional burden of acute respiratory infections (ARIs). Although testing was still widely used, many positive tests were not reported for the official statistics. Using data from a population-based cohort, we aimed to investigate the contribution of SARS-CoV-2 to the burden of ARI. METHODS Over 70,000 participants of the German population-based DigiHero study were invited to a questionnaire about the number and time point of ARI and SARS-CoV-2 test results in winter 2022/2023. We calculated the incidence of non-severe acute respiratory syndrome (SARS) ARI, the additional contribution of SARS-CoV-2, and extrapolated the age-specific estimates to obtain the total burden of SARS-CoV-2 in Germany. RESULTS For the winter of 2022/2023, 37,708 participants reported 54,813 ARIs, including 9358 SARS-CoV-2 infections. This translated into a cumulative incidence of 145 infections/100 persons for all ARIs, 120 infections/100 persons for non-SARS ARI, and 25 infections/100 persons for SARS ARI (+21%). CONCLUSIONS Our estimate for ARI related to SARS-CoV-2 is consistent with the difference in all ARI between pre-pandemic years and 2022/2023. This additional burden should be considered, particularly, with respect to the implications for the work force.
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Affiliation(s)
- Nadine Glaser
- Institute for Medical Epidemiology, Biometrics and Informatics (IMEBI), Interdisciplinary Centre for Health Sciences, Medical Faculty of the Martin Luther University Halle-Wittenberg, Halle (Saale), Germany
| | - Sophie Diexer
- Institute for Medical Epidemiology, Biometrics and Informatics (IMEBI), Interdisciplinary Centre for Health Sciences, Medical Faculty of the Martin Luther University Halle-Wittenberg, Halle (Saale), Germany
| | - Bianca Klee
- Institute for Medical Epidemiology, Biometrics and Informatics (IMEBI), Interdisciplinary Centre for Health Sciences, Medical Faculty of the Martin Luther University Halle-Wittenberg, Halle (Saale), Germany
| | - Oliver Purschke
- Institute for Medical Epidemiology, Biometrics and Informatics (IMEBI), Interdisciplinary Centre for Health Sciences, Medical Faculty of the Martin Luther University Halle-Wittenberg, Halle (Saale), Germany
| | - Mascha Binder
- Department of Internal Medicine IV, Oncology/Hematology, Martin Luther University Halle-Wittenberg, Halle (Saale), Germany; Medical Oncology, University Hospital Basel, Basel, Switzerland
| | - Thomas Frese
- Institute of General Practice and Family Medicine, Interdisciplinary Centre for Health Sciences, Medical Faculty of the Martin Luther University Halle-Wittenberg, Halle (Saale), Germany
| | - Matthias Girndt
- Department of Internal Medicine II, Martin Luther University Halle-Wittenberg, Halle (Saale), Germany
| | - Jessica Höll
- Paediatric Haematology and Oncology, Martin Luther University Halle-Wittenberg, Halle (Saale), Germany
| | - Irene Moor
- Institute for Medical Sociology, Martin Luther University Halle-Wittenberg, Halle (Saale), Germany
| | - Jonas Rosendahl
- Department of Internal Medicine I, Martin Luther University Halle-Wittenberg, Halle (Saale), Germany
| | - Michael Gekle
- Julius-Bernstein-Institute of Physiology, Medical Faculty of the Martin Luther University Halle-Wittenberg, Halle (Saale), Germany
| | - Daniel Sedding
- Mid-German Heart Centre, Department of Cardiology and Intensive Care Medicine, University Hospital, Martin Luther University Halle-Wittenberg, Halle (Saale), Germany
| | - Rafael Mikolajczyk
- Institute for Medical Epidemiology, Biometrics and Informatics (IMEBI), Interdisciplinary Centre for Health Sciences, Medical Faculty of the Martin Luther University Halle-Wittenberg, Halle (Saale), Germany.
| | - Cornelia Gottschick
- Institute for Medical Epidemiology, Biometrics and Informatics (IMEBI), Interdisciplinary Centre for Health Sciences, Medical Faculty of the Martin Luther University Halle-Wittenberg, Halle (Saale), Germany
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Veneti L, Robberstad B, Steens A, Forland F, Winje BA, Vestrheim DF, Jarvis CI, Gimma A, Edmunds WJ, Van Zandvoort K, de Blasio BF. Social contact patterns during the early COVID-19 pandemic in Norway: insights from a panel study, April to September 2020. BMC Public Health 2024; 24:1438. [PMID: 38811933 PMCID: PMC11137890 DOI: 10.1186/s12889-024-18853-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2023] [Accepted: 05/14/2024] [Indexed: 05/31/2024] Open
Abstract
BACKGROUND During the COVID-19 pandemic, many countries adopted social distance measures and lockdowns of varying strictness. Social contact patterns are essential in driving the spread of respiratory infections, and country-specific measurements are needed. This study aimed to gain insights into changes in social contacts and behaviour during the early pandemic phase in Norway. METHODS We conducted an online panel study among a nationally representative sample of Norwegian adults by age and gender. The panel study included six data collections waves between April and September 2020, and 2017 survey data from a random sample of the Norwegian population (including children < 18 years old) were used as baseline. The market research company Ipsos was responsible for carrying out the 2020 surveys. We calculated mean daily contacts, and estimated age-stratified contact matrices during the study period employing imputation of child-to-child contacts. We used the next-generation method to assess the relative reduction of R0 and compared the results to reproduction numbers estimated for Norway during the 2020 study period. RESULTS Over the six waves in 2020, 5 938 observations/responses were registered from 1 718 individuals who reported data on 22 074 contacts. The mean daily number of contacts among adults varied between 3.2 (95%CI 3.0-3.4) to 3.9 (95%CI 3.6-4.2) across the data collection waves, representing a 67-73% decline compared to pre-pandemic levels (baseline). Fewer contacts in the community setting largely drove the reduction; the drop was most prominent among younger adults. Despite gradual easing of social distance measures during the survey period, the estimated population contact matrices remained relatively stable and displayed more inter-age group mixing than at baseline. Contacts within households and the community outside schools and workplaces contributed most to social encounters. Using the next-generation method R0 was found to be roughly 25% of pre-pandemic levels during the study period, suggesting controlled transmission. CONCLUSION Social contacts declined significantly in the months following the March 2020 lockdown, aligning with implementation of stringent social distancing measures. These findings contribute valuable empirical information into the social behaviour in Norway during the early pandemic, which can be used to enhance policy-relevant models for addressing future crises when mitigation measures might be implemented.
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Affiliation(s)
- Lamprini Veneti
- Department of Infection Control and Preparedness, Norwegian Institute of Public Health, Lovisenberggata 8, Oslo, 0456, Norway.
| | - Bjarne Robberstad
- Department of Global Public Health and Primary Care, University of Bergen, Bergen, Norway
| | - Anneke Steens
- Department of Infection Control and Vaccine, Norwegian Institute of Public Health, Oslo, Norway
| | - Frode Forland
- Department of Infection Control and Preparedness, Norwegian Institute of Public Health, Lovisenberggata 8, Oslo, 0456, Norway
| | - Brita A Winje
- Department of Infection Control and Vaccine, Norwegian Institute of Public Health, Oslo, Norway
| | - Didrik F Vestrheim
- Department of Infection Control and Vaccine, Norwegian Institute of Public Health, Oslo, Norway
| | - Christopher I Jarvis
- Centre for Mathematical Modelling of Infectious Diseases, Department of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, UK
| | - Amy Gimma
- Centre for Mathematical Modelling of Infectious Diseases, Department of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, UK
| | - W John Edmunds
- Centre for Mathematical Modelling of Infectious Diseases, Department of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, UK
| | - Kevin Van Zandvoort
- Centre for Mathematical Modelling of Infectious Diseases, Department of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, UK
| | - Birgitte Freiesleben de Blasio
- Department of Method Development and Analytics, Norwegian Institute of Public Health, Oslo, Norway
- Oslo Center for Biostatistics and Epidemiology, Department of Biostatistics, Institute of Basic Medical Sciences, University of Oslo, Oslo, Norway
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Pasquale DK, Welsh W, Bentley-Edwards KL, Olson A, Wellons MC, Moody J. Homophily and social mixing in a small community: Implications for infectious disease transmission. PLoS One 2024; 19:e0303677. [PMID: 38805519 PMCID: PMC11132460 DOI: 10.1371/journal.pone.0303677] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2023] [Accepted: 04/29/2024] [Indexed: 05/30/2024] Open
Abstract
Community mixing patterns by sociodemographic traits can inform the risk of epidemic spread among groups, and the balance of in- and out-group mixing affects epidemic potential. Understanding mixing patterns can provide insight about potential transmission pathways throughout a community. We used a snowball sampling design to enroll people recently diagnosed with SARS-CoV-2 in an ethnically and racially diverse county and asked them to describe their close contacts and recruit some contacts to enroll in the study. We constructed egocentric networks of the participants and their contacts and assessed age-mixing, ethnic/racial homophily, and gender homophily. The total size of the egocentric networks was 2,544 people (n = 384 index cases + n = 2,160 recruited peers or other contacts). We observed high rates of in-group mixing among ethnic/racial groups compared to the ethnic/racial proportions of the background population. Black or African-American respondents interacted with a wider range of ages than other ethnic/racial groups, largely due to familial relationships. The egocentric networks of non-binary contacts had little age diversity. Black or African-American respondents in particular reported mixing with older or younger family members, which could increase the risk of transmission to vulnerable age groups. Understanding community mixing patterns can inform infectious disease risk, support analyses to predict epidemic size, or be used to design campaigns such as vaccination strategies so that community members who have vulnerable contacts are prioritized.
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Affiliation(s)
- Dana K. Pasquale
- Department of Population Health Sciences, Duke University School of Medicine, Durham, North Carolina, United States of America
- Department of Sociology, Duke University, Durham, North Carolina, United States of America
- Duke Network Analysis Center, Social Science Research Institute, Duke University, Durham, North Carolina, United States of America
| | - Whitney Welsh
- Social Science Research Institute, Duke University, Durham, North Carolina, United States of America
| | - Keisha L. Bentley-Edwards
- Samuel DuBois Cook Center on Social Equity, Duke University, Durham, North Carolina, United States of America
| | - Andrew Olson
- Duke AI Health, Duke University School of Medicine, Durham, North Carolina, United States of America
| | - Madelynn C. Wellons
- Department of Sociology, Duke University, Durham, North Carolina, United States of America
- Duke Network Analysis Center, Social Science Research Institute, Duke University, Durham, North Carolina, United States of America
| | - James Moody
- Department of Sociology, Duke University, Durham, North Carolina, United States of America
- Duke Network Analysis Center, Social Science Research Institute, Duke University, Durham, North Carolina, United States of America
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Tran-Kiem C, Paredes MI, Perofsky AC, Frisbie LA, Xie H, Kong K, Weixler A, Greninger AL, Roychoudhury P, Peterson JM, Delgado A, Halstead H, MacKellar D, Dykema P, Gamboa L, Frazar CD, Ryke E, Stone J, Reinhart D, Starita L, Thibodeau A, Yun C, Aragona F, Black A, Viboud C, Bedford T. Fine-scale spatial and social patterns of SARS-CoV-2 transmission from identical pathogen sequences. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.05.24.24307811. [PMID: 38826243 PMCID: PMC11142302 DOI: 10.1101/2024.05.24.24307811] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/04/2024]
Abstract
Pathogen genomics can provide insights into disease transmission patterns, but new methods are needed to handle modern large-scale pathogen genome datasets. Genetically proximal viruses indicate epidemiological linkage and are informative about transmission events. Here, we leverage pairs of identical sequences using 114,298 SARS-CoV-2 genomes collected via sentinel surveillance from March 2021 to December 2022 in Washington State, USA, with linked age and residence information to characterize fine-scale transmission. The location of pairs of identical sequences is highly consistent with expectations from mobility and social contact data. Outliers in the relationship between genetic and mobility data can be explained by SARS-CoV-2 transmission between postal codes with male prisons, consistent with transmission between prison facilities. Transmission patterns between age groups vary across spatial scales. Finally, we use the timing of sequence collection to understand the age groups driving transmission. This work improves our ability to characterize transmission from large pathogen genome datasets.
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Affiliation(s)
- Cécile Tran-Kiem
- Vaccine and Infectious Diseases Division, Fred Hutchinson Cancer Center, Seattle, WA, USA
| | - Miguel I. Paredes
- Vaccine and Infectious Diseases Division, Fred Hutchinson Cancer Center, Seattle, WA, USA
- Department of Epidemiology, University of Washington, Seattle, WA, USA
| | - Amanda C. Perofsky
- Brotman Baty Institute, University of Washington, Seattle, WA, USA
- Fogarty International Center, National Institutes of Health, Bethesda, MD, USA
| | | | - Hong Xie
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, WA, USA
| | - Kevin Kong
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, WA, USA
| | - Amelia Weixler
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, WA, USA
| | - Alexander L. Greninger
- Vaccine and Infectious Diseases Division, Fred Hutchinson Cancer Center, Seattle, WA, USA
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, WA, USA
| | - Pavitra Roychoudhury
- Vaccine and Infectious Diseases Division, Fred Hutchinson Cancer Center, Seattle, WA, USA
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, WA, USA
| | | | - Andrew Delgado
- Washington State Department of Health, Shoreline, WA, USA
| | - Holly Halstead
- Washington State Department of Health, Shoreline, WA, USA
| | - Drew MacKellar
- Washington State Department of Health, Shoreline, WA, USA
| | - Philip Dykema
- Washington State Department of Health, Shoreline, WA, USA
| | - Luis Gamboa
- Brotman Baty Institute, University of Washington, Seattle, WA, USA
| | - Chris D. Frazar
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
| | - Erica Ryke
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
| | - Jeremy Stone
- Brotman Baty Institute, University of Washington, Seattle, WA, USA
| | - David Reinhart
- Brotman Baty Institute, University of Washington, Seattle, WA, USA
| | - Lea Starita
- Brotman Baty Institute, University of Washington, Seattle, WA, USA
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
| | | | - Cory Yun
- Washington State Department of Health, Shoreline, WA, USA
| | - Frank Aragona
- Washington State Department of Health, Shoreline, WA, USA
| | - Allison Black
- Washington State Department of Health, Shoreline, WA, USA
| | - Cécile Viboud
- Fogarty International Center, National Institutes of Health, Bethesda, MD, USA
| | - Trevor Bedford
- Vaccine and Infectious Diseases Division, Fred Hutchinson Cancer Center, Seattle, WA, USA
- Howard Hughes Medical Institute, Seattle, WA, USA
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Ahern S, Browne J, Murphy A, Teljeur C, Ryan M. An economic evaluation and incremental analysis of the cost effectiveness of three universal childhood varicella vaccination strategies for Ireland. Vaccine 2024; 42:3321-3332. [PMID: 38609807 DOI: 10.1016/j.vaccine.2024.04.027] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2024] [Revised: 04/04/2024] [Accepted: 04/05/2024] [Indexed: 04/14/2024]
Abstract
BACKGROUND The cost effectiveness of childhood varicella vaccination is uncertain, as evidenced by variation in national health policies. Within the European Economic Area (EEA), only 10 of 30 countries offer universally funded childhood varicella vaccination. This study estimates the cost effectiveness of universal childhood varicella vaccination for one EEA country (Ireland), highlighting the difference in cost effectiveness between alternative vaccination strategies. METHODS An age-structured dynamic transmission model, simulating varicella zoster virus transmission, was developed to analyse the impact of three vaccination strategies; one-dose at 12 months old, two-dose at 12 and 15 months old (short-interval), and two-dose at 12 months and five years old (long-interval). The analysis adopted an 80-year time horizon and considered payer and societal perspectives. Clinical effectiveness was based on cases of varicella and subsequently herpes zoster and post-herpetic neuralgia avoided, and outcomes were expressed in quality-adjusted life-years (QALYs). Costs were presented in 2022 Irish Euro and cost effectiveness was interpreted with reference to a willingness-to-pay threshold of €20,000 per QALY gained. RESULTS From the payer perspective, the incremental cost-effectiveness ratio (ICER) for a one-dose strategy, compared with no vaccination, was estimated at €8,712 per QALY gained. The ICER for the next least expensive strategy, two-dose long-interval, compared with one-dose, was estimated at €45,090 per QALY gained. From a societal perspective, all three strategies were cost-saving compared with no vaccination; the two-dose short-interval strategy dominated, yielding the largest cost savings and health benefits. Results were stable across a range of sensitivity and scenario analyses. CONCLUSION A one-dose strategy was highly cost effective from the payer perspective, driven by a reduction in hospitalisations. Two-dose strategies were cost saving from the societal perspective. These results should be considered alongside other factors such as acceptability of a new vaccine within the overall childhood immunisation schedule, programme objectives and budget impact.
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Affiliation(s)
- Susan Ahern
- School of Public Health, College of Medicine and Health, University College Cork, College Road, Cork, Ireland; Health Information and Quality Authority, Smithfield, Dublin 7, Ireland.
| | - John Browne
- School of Public Health, College of Medicine and Health, University College Cork, College Road, Cork, Ireland.
| | - Aileen Murphy
- Department of Economics, Cork University Business School, University College Cork, College Road, Cork, Ireland.
| | - Conor Teljeur
- Health Information and Quality Authority, Smithfield, Dublin 7, Ireland.
| | - Máirín Ryan
- Health Information and Quality Authority, Smithfield, Dublin 7, Ireland; Department of Pharmacology & Therapeutics, Trinity College Dublin, Trinity Health Sciences, James Street, Dublin 8, Ireland.
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Giannini F, Hogan AB, Sarna M, Glass K, Moore HC. Modelling respiratory syncytial virus age-specific risk of hospitalisation in term and preterm infants. BMC Infect Dis 2024; 24:510. [PMID: 38773455 PMCID: PMC11110433 DOI: 10.1186/s12879-024-09400-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2023] [Accepted: 05/13/2024] [Indexed: 05/23/2024] Open
Abstract
BACKGROUND Respiratory syncytial virus (RSV) is the most common cause of acute lower respiratory infections in children worldwide. The highest incidence of severe disease is in the first 6 months of life, with infants born preterm at greatest risk for severe RSV infections. The licensure of new RSV therapeutics (a long-acting monoclonal antibody and a maternal vaccine) in Europe, USA, UK and most recently in Australia, has driven the need for strategic decision making on the implementation of RSV immunisation programs. Data driven approaches, considering the local RSV epidemiology, are critical to advise on the optimal use of these therapeutics for effective RSV control. METHODS We developed a dynamic compartmental model of RSV transmission fitted to individually-linked population-based laboratory, perinatal and hospitalisation data for 2000-2012 from metropolitan Western Australia (WA), stratified by age and prior exposure. We account for the differential risk of RSV-hospitalisation in full-term and preterm infants (defined as < 37 weeks gestation). We formulated a function relating age, RSV exposure history, and preterm status to the risk of RSV-hospitalisation given infection. RESULTS The age-to-risk function shows that risk of hospitalisation, given RSV infection, declines quickly in the first 12 months of life for all infants and is 2.6 times higher in preterm compared with term infants. The hospitalisation risk, given infection, declines to < 10% of the risk at birth by age 7 months for term infants and by 9 months for preterm infants. CONCLUSIONS The dynamic model, using the age-to-risk function, characterises RSV epidemiology for metropolitan WA and can now be extended to predict the impact of prevention measures. The stratification of the model by preterm status will enable the comparative assessment of potential strategies in the extended model that target this RSV risk group relative to all-population approaches. Furthermore, the age-to-risk function developed in this work has wider relevance to the epidemiological characterisation of RSV.
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Affiliation(s)
- Fiona Giannini
- Wesfarmers Centre of Vaccines and Infectious Diseases, Telethon Kids Institute, University of Western Australia, 15 Hospital Ave, Nedlands, WA, 6009, Australia.
| | - Alexandra B Hogan
- School of Population Health, The University of New South Wales, Sydney, NSW, 2052, Australia
| | - Mohinder Sarna
- Wesfarmers Centre of Vaccines and Infectious Diseases, Telethon Kids Institute, University of Western Australia, 15 Hospital Ave, Nedlands, WA, 6009, Australia
- School of Population Health, Curtin University, Perth, WA, 6002, Australia
| | - Kathryn Glass
- Wesfarmers Centre of Vaccines and Infectious Diseases, Telethon Kids Institute, University of Western Australia, 15 Hospital Ave, Nedlands, WA, 6009, Australia
- National Centre for Epidemiology and Population Health, The Australian National University, 62 Mills Rd, Acton ACT, 2601, Australia
| | - Hannah C Moore
- Wesfarmers Centre of Vaccines and Infectious Diseases, Telethon Kids Institute, University of Western Australia, 15 Hospital Ave, Nedlands, WA, 6009, Australia
- School of Population Health, Curtin University, Perth, WA, 6002, Australia
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8
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Manna A, Koltai J, Karsai M. Importance of social inequalities to contact patterns, vaccine uptake, and epidemic dynamics. Nat Commun 2024; 15:4137. [PMID: 38755162 PMCID: PMC11099065 DOI: 10.1038/s41467-024-48332-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2023] [Accepted: 04/29/2024] [Indexed: 05/18/2024] Open
Abstract
Individuals' socio-demographic and economic characteristics crucially shape the spread of an epidemic by largely determining the exposure level to the virus and the severity of the disease for those who got infected. While the complex interplay between individual characteristics and epidemic dynamics is widely recognised, traditional mathematical models often overlook these factors. In this study, we examine two important aspects of human behaviour relevant to epidemics: contact patterns and vaccination uptake. Using data collected during the COVID-19 pandemic in Hungary, we first identify the dimensions along which individuals exhibit the greatest variation in their contact patterns and vaccination uptake. We find that generally higher socio-economic groups of the population have a higher number of contacts and a higher vaccination uptake with respect to disadvantaged groups. Subsequently, we propose a data-driven epidemiological model that incorporates these behavioural differences. Finally, we apply our model to analyse the fourth wave of COVID-19 in Hungary, providing valuable insights into real-world scenarios. By bridging the gap between individual characteristics and epidemic spread, our research contributes to a more comprehensive understanding of disease dynamics and informs effective public health strategies.
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Affiliation(s)
- Adriana Manna
- Department of Network and Data Science, Central European University, Quellenstraße 51, Vienna, 1100, Austria
| | - Júlia Koltai
- National Laboratory for Health Security, HUN-REN Centre for Social Sciences, Tóth Kálmán utca 4, Budapest, 1097, Hungary
- Department of Social Research Methodology, Faculty of Social Sciences, Eötvös Loránd University, Pázmány Péter sétány 1/A, Budapest, 1117, Hungary
| | - Márton Karsai
- Department of Network and Data Science, Central European University, Quellenstraße 51, Vienna, 1100, Austria.
- National Laboratory for Health Security, HUN-REN Rényi Institute of Mathematics, Reáltanoda utca 13-15, Budapest, 1053, Hungary.
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Reichmuth ML, Heron L, Beutels P, Hens N, Low N, Althaus CL. Social contacts in Switzerland during the COVID-19 pandemic: Insights from the CoMix study. Epidemics 2024; 47:100771. [PMID: 38821037 DOI: 10.1016/j.epidem.2024.100771] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2024] [Revised: 04/29/2024] [Accepted: 05/07/2024] [Indexed: 06/02/2024] Open
Abstract
To mitigate the spread of SARS-CoV-2, the Swiss government enacted restrictions on social contacts from 2020 to 2022. In addition, individuals changed their social contact behavior to limit the risk of COVID-19. In this study, we aimed to investigate the changes in social contact patterns of the Swiss population. As part of the CoMix study, we conducted a survey consisting of 24 survey waves from January 2021 to May 2022. We collected data on social contacts and constructed contact matrices for the age groups 0-4, 5-14, 15-29, 30-64, and 65 years and older. We estimated the change in contact numbers during the COVID-19 pandemic to a synthetic pre-pandemic contact matrix. We also investigated the association of the largest eigenvalue of the social contact and transmission matrices with the stringency of pandemic measures, the effective reproduction number (Re), and vaccination uptake. During the pandemic period, 7084 responders reported an average number of 4.5 contacts (95% confidence interval, CI: 4.5-4.6) per day overall, which varied by age and survey wave. Children aged 5-14 years had the highest number of contacts with 8.5 (95% CI: 8.1-8.9) contacts on average per day and participants that were 65 years and older reported the fewest (3.4, 95% CI: 3.2-3.5) per day. Compared with the pre-pandemic baseline, we found that the 15-29 and 30-64 year olds had the largest reduction in contacts. We did not find statistically significant associations between the largest eigenvalue of the social contact and transmission matrices and the stringency of measures, Re, or vaccination uptake. The number of social contacts in Switzerland fell during the COVID-19 pandemic and remained below pre-pandemic levels after contact restrictions were lifted. The collected social contact data will be critical in informing modeling studies on the transmission of respiratory infections in Switzerland and to guide pandemic preparedness efforts.
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Affiliation(s)
- Martina L Reichmuth
- Institute of Social and Preventive Medicine, University of Bern, Bern, Switzerland
| | - Leonie Heron
- Institute of Social and Preventive Medicine, University of Bern, Bern, Switzerland
| | - Philippe Beutels
- Centre for Health Economic Research and Modelling Infectious Diseases, Vaccine and Infectious Disease Institute, Antwerp, Belgium
| | - Niel Hens
- Centre for Health Economic Research and Modelling Infectious Diseases, Vaccine and Infectious Disease Institute, Antwerp, Belgium; Data Science Institute, I-BioStat, Hasselt University, Hasselt, Belgium
| | - Nicola Low
- Institute of Social and Preventive Medicine, University of Bern, Bern, Switzerland; Multidisciplinary Center for Infectious Diseases, University of Bern, Bern, Switzerland
| | - Christian L Althaus
- Institute of Social and Preventive Medicine, University of Bern, Bern, Switzerland; Multidisciplinary Center for Infectious Diseases, University of Bern, Bern, Switzerland.
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Wang M, Wang C, Gui G, Guo F, Zha R, Sun H. Social contacts patterns relevant to the transmission of infectious diseases in Suzhou, China following the COVID-19 epidemic. JOURNAL OF HEALTH, POPULATION, AND NUTRITION 2024; 43:58. [PMID: 38725055 PMCID: PMC11080078 DOI: 10.1186/s41043-024-00555-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 03/18/2024] [Accepted: 04/27/2024] [Indexed: 05/12/2024]
Abstract
BACKGROUND The COVID-19 pandemic has profoundly affected human social contact patterns, but there is limited understanding regarding the post-pandemic social contact patterns. Our objective is to quantitatively assess social contact patterns in Suzhou post-COVID-19. METHODS We employed a diary design and conducted social contact surveys from June to October 2023, utilizing paper questionnaires. A generalized linear model was utilized to analyze the relationship between individual contacts and covariates. We examined the proportions of contact type, location, duration, and frequency. Additionally, age-related mixed matrices were established. RESULTS The participants reported an average of 11.51 (SD 5.96) contact numbers and a total of 19.78 (SD 20.94) contact numbers per day, respectively. The number of contacts was significantly associated with age, household size, and the type of week. Compared to the 0-9 age group, those in the 10-19 age group reported a higher number of contacts (IRR = 1.12, CI: 1.01-1.24), while participants aged 20 and older reported fewer (IRR range: 0.54-0.67). Larger households (5 or more) reported more contacts (IRR = 1.09, CI: 1.01-1.18) and fewer contacts were reported on weekends (IRR = 0.95, CI: 0.90-0.99). School had the highest proportion of contact durations exceeding 4 h (49.5%) and daily frequencies (90.4%), followed by home and workplace. The contact patterns exhibited clear age-assortative mixing, with Q indices of 0.27 and 0.28. CONCLUSIONS We assessed the characteristics of social contact patterns in Suzhou, which are essential for parameterizing models of infectious disease transmission. The high frequency and intensity of contacts among school-aged children should be given special attention, making school intervention policies a crucial component in controlling infectious disease transmission.
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Affiliation(s)
- Mengru Wang
- School of Public Health, Jiangsu Key Laboratory of Preventive and Translational Medicine for Geriatric Diseases, MOE Key Laboratory of Geriatric Diseases and Immunology, Suzhou Medical College of Soochow University, Suzhou, Jiangsu, 215123, P.R. China
| | - Congju Wang
- Suzhou High-tech Zone Center for Disease Control and Prevention, Suzhou, 215011, P.R. China
| | - Guoping Gui
- Suzhou High-tech Zone Center for Disease Control and Prevention, Suzhou, 215011, P.R. China
| | - Feng Guo
- Suzhou High-tech Zone Center for Disease Control and Prevention, Suzhou, 215011, P.R. China
| | - Risheng Zha
- Suzhou High-tech Zone Center for Disease Control and Prevention, Suzhou, 215011, P.R. China
| | - Hongpeng Sun
- School of Public Health, Jiangsu Key Laboratory of Preventive and Translational Medicine for Geriatric Diseases, MOE Key Laboratory of Geriatric Diseases and Immunology, Suzhou Medical College of Soochow University, Suzhou, Jiangsu, 215123, P.R. China.
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11
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Kummer A, Zhang J, Jiang C, Litvinova M, Ventura P, Garcia M, Vespignani A, Wu H, Yu H, Ajelli M. Evaluating Seasonal Variations in Human Contact Patterns and Their Impact on the Transmission of Respiratory Infectious Diseases. Influenza Other Respir Viruses 2024; 18:e13301. [PMID: 38733199 PMCID: PMC11087848 DOI: 10.1111/irv.13301] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2023] [Revised: 04/10/2024] [Accepted: 04/11/2024] [Indexed: 05/13/2024] Open
Abstract
BACKGROUND Human contact patterns are a key determinant driving the spread of respiratory infectious diseases. However, the relationship between contact patterns and seasonality as well as their possible association with the seasonality of respiratory diseases is yet to be clarified. METHODS We investigated the association between temperature and human contact patterns using data collected through a cross-sectional diary-based contact survey in Shanghai, China, between December 24, 2017, and May 30, 2018. We then developed a compartmental model of influenza transmission informed by the derived seasonal trends in the number of contacts and validated it against A(H1N1)pdm09 influenza data collected in Shanghai during the same period. RESULTS We identified a significant inverse relationship between the number of contacts and the seasonal temperature trend defined as a spline interpolation of temperature data (p = 0.003). We estimated an average of 16.4 (95% PrI: 15.1-17.5) contacts per day in December 2017 that increased to an average of 17.6 contacts (95% PrI: 16.5-19.3) in January 2018 and then declined to an average of 10.3 (95% PrI: 9.4-10.8) in May 2018. Estimates of influenza incidence obtained by the compartmental model comply with the observed epidemiological data. The reproduction number was estimated to increase from 1.24 (95% CI: 1.21-1.27) in December to a peak of 1.34 (95% CI: 1.31-1.37) in January. The estimated median infection attack rate at the end of the season was 27.4% (95% CI: 23.7-30.5%). CONCLUSIONS Our findings support a relationship between temperature and contact patterns, which can contribute to deepen the understanding of the relationship between social interactions and the epidemiology of respiratory infectious diseases.
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Affiliation(s)
- Allisandra G. Kummer
- Laboratory for Computational Epidemiology and Public Health, Department of Epidemiology and BiostatisticsIndiana University School of Public HealthBloomingtonIndianaUSA
| | - Juanjuan Zhang
- Shanghai Institute of Infectious Disease and Biosecurity, Department of Epidemiology, School of Public HealthFudan UniversityShanghaiChina
- Department of Epidemiology, School of Public HealthFudan University, Key Laboratory of Public Health Safety, Ministry of EducationShanghaiChina
| | - Chenyan Jiang
- Shanghai Municipal Center for Disease Control and PreventionShanghaiChina
| | - Maria Litvinova
- Laboratory for Computational Epidemiology and Public Health, Department of Epidemiology and BiostatisticsIndiana University School of Public HealthBloomingtonIndianaUSA
| | - Paulo C. Ventura
- Laboratory for Computational Epidemiology and Public Health, Department of Epidemiology and BiostatisticsIndiana University School of Public HealthBloomingtonIndianaUSA
| | - Marc A. Garcia
- Lerner Center for Public Health Promotion, Aging Studies Institute, Department of Sociology, and Maxwell School of Citizenship & Public AffairsSyracuse UniversitySyracuseNew YorkUSA
| | - Alessandro Vespignani
- Laboratory for the Modeling of Biological and Socio‐technical SystemsNortheastern UniversityBostonMassachusettsUSA
| | - Huanyu Wu
- Shanghai Municipal Center for Disease Control and PreventionShanghaiChina
| | - Hongjie Yu
- Shanghai Institute of Infectious Disease and Biosecurity, Department of Epidemiology, School of Public HealthFudan UniversityShanghaiChina
- Department of Epidemiology, School of Public HealthFudan University, Key Laboratory of Public Health Safety, Ministry of EducationShanghaiChina
| | - Marco Ajelli
- Laboratory for Computational Epidemiology and Public Health, Department of Epidemiology and BiostatisticsIndiana University School of Public HealthBloomingtonIndianaUSA
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Mendes D, Machira Krishnan S, O'Brien E, Padgett T, Harrison C, Strain WD, Manca A, Ustianowski A, Butfield R, Hamson E, Reynard C, Yang J. Modelling COVID-19 Vaccination in the UK: Impact of the Autumn 2022 and Spring 2023 Booster Campaigns. Infect Dis Ther 2024; 13:1127-1146. [PMID: 38662331 PMCID: PMC11098993 DOI: 10.1007/s40121-024-00965-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2024] [Accepted: 03/21/2024] [Indexed: 04/26/2024] Open
Abstract
INTRODUCTION The delivery of COVID-19 vaccines was successful in reducing hospitalizations and mortality. However, emergence of the Omicron variant resulted in increased virus transmissibility. Consequently, booster vaccination programs were initiated to decrease the risk of severe disease and death among vulnerable members of the population. This study aimed to estimate the effects of the booster program and alternative vaccination strategies on morbidity and mortality due to COVID-19 in the UK. METHOD A Susceptible-Exposed-Infectious-Recovered (SEIR) model was used to assess the impact of several vaccination strategies on severe outcomes associated with COVID-19, including hospitalizations, mortality, National Health Service (NHS) capacity quantified by hospital general ward and intensive care unit (ICU) bed days, and patient productivity. The model accounted for age-, risk- and immunity-based stratification of the UK population. Outcomes were evaluated over a 48-week time horizon from September 2022 to August 2023 considering the actual UK autumn 2022/spring 2023 booster campaigns and six counterfactual strategies. RESULTS The model estimated that the autumn 2022/spring 2023 booster campaign resulted in a reduction of 18,921 hospitalizations and 1463 deaths, compared with a no booster scenario. Utilization of hospital bed days due to COVID-19 decreased after the autumn 2022/spring 2023 booster campaign. Expanding the booster eligibility criteria and improving uptake improved all outcomes, including averting twice as many ICU admissions, preventing more than 20% additional deaths, and a sevenfold reduction in long COVID, compared with the autumn 2022/spring 2023 booster campaign. The number of productive days lost was reduced by fivefold indicating that vaccinating a wider population has a beneficial impact on the morbidities associated with COVID-19. CONCLUSION Our modelling demonstrates that the autumn 2022/spring 2023 booster campaign reduced COVID-19-associated morbidity and mortality. Booster campaigns with alternative eligibility criteria warrant consideration in the UK, given their potential to further reduce morbidity and mortality as future variants emerge.
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Affiliation(s)
| | | | - Esmé O'Brien
- Health Economics and Outcomes Research Ltd, Cardiff, UK
| | | | - Cale Harrison
- Health Economics and Outcomes Research Ltd, Cardiff, UK
| | | | | | - Andrew Ustianowski
- Manchester University Foundation Trust, University of Manchester, Manchester, UK
| | | | | | | | - Jingyan Yang
- Pfizer Inc, New York, USA
- Institute for Social and Economic Research and Policy, Columbia University, New York, USA
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Taube JC, Susswein Z, Colizza V, Bansal S. Respiratory disease contact patterns in the US are stable but heterogeneous. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.04.26.24306450. [PMID: 38712118 PMCID: PMC11071567 DOI: 10.1101/2024.04.26.24306450] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/08/2024]
Abstract
Background Contact plays a critical role in infectious disease transmission. Characterizing heterogeneity in contact patterns across individuals, time, and space is necessary to inform accurate estimates of transmission risk, particularly to explain superspreading, predict age differences in vulnerability, and inform social distancing policies. Current respiratory disease models often rely on data from the 2008 POLYMOD study conducted in Europe, which is now outdated and potentially unrepresentative of behavior in the US. We seek to understand the variation in contact patterns across spatial scales and demographic and social classifications, whether there is seasonality to contact patterns, and what social behavior looks like at baseline in the absence of an ongoing pandemic. Methods We analyze spatiotemporal non-household contact patterns across 11 million survey responses from June 2020 - April 2021 post-stratified on age and gender to correct for sample representation. To characterize spatiotemporal heterogeneity in respiratory contact patterns at the county-week scale, we use generalized additive models. In the absence of pre-pandemic data on contact in the US, we also use a regression approach to produce baseline contact estimates to fill this gap. Findings Although contact patterns varied over time during the pandemic, contact is relatively stable after controlling for disease. We find that the mean number of non-household contacts is spatially heterogeneous regardless of disease. There is additional heterogeneity across age, gender, race/ethnicity, and contact setting, with mean contact decreasing with age and lower in women. The contacts of white individuals and contacts at work or social events change the most under increased national incidence. Interpretation We develop the first county-level estimates of non-pandemic contact rates for the US that can fill critical gaps in parameterizing disease models. Our results identify that spatiotemporal, demographic, and social heterogeneity in contact patterns is highly structured, informing the risk landscape of respiratory disease transmission in the US.
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Affiliation(s)
- Juliana C. Taube
- Department of Biology, Georgetown University, Washington, DC, USA
| | - Zachary Susswein
- Department of Biology, Georgetown University, Washington, DC, USA
| | | | - Shweta Bansal
- Department of Biology, Georgetown University, Washington, DC, USA
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14
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Bali Y, Bajiya VP, Tripathi JP, Mubayi A. Exploring data sources and mathematical approaches for estimating human mobility rates and implications for understanding COVID-19 dynamics: a systematic literature review. J Math Biol 2024; 88:67. [PMID: 38641762 DOI: 10.1007/s00285-024-02082-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2022] [Revised: 03/06/2024] [Accepted: 03/19/2024] [Indexed: 04/21/2024]
Abstract
Human mobility, which refers to the movement of people from one location to another, is believed to be one of the key factors shaping the dynamics of the COVID-19 pandemic. There are multiple reasons that can change human mobility patterns, such as fear of an infection, control measures restricting movement, economic opportunities, political instability, etc. Human mobility rates are complex to estimate as they can occur on various time scales, depending on the context and factors driving the movement. For example, short-term movements are influenced by the daily work schedule, whereas long-term trends can be due to seasonal employment opportunities. The goal of the study is to perform literature review to: (i) identify relevant data sources that can be used to estimate human mobility rates at different time scales, (ii) understand the utilization of variety of data to measure human movement trends under different contexts of mobility changes, and (iii) unraveling the associations between human mobility rates and social determinants of health affecting COVID-19 disease dynamics. The systematic review of literature was carried out to collect relevant articles on human mobility. Our study highlights the use of three major sources of mobility data: public transit, mobile phones, and social surveys. The results also provides analysis of the data to estimate mobility metrics from the diverse data sources. All major factors which directly and indirectly influenced human mobility during the COVID-19 spread are explored. Our study recommends that (a) a significant balance between primitive and new estimated mobility parameters need to be maintained, (b) the accuracy and applicability of mobility data sources should be improved, (c) encouraging broader interdisciplinary collaboration in movement-based research is crucial for advancing the study of COVID-19 dynamics among scholars from various disciplines.
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Affiliation(s)
- Yogesh Bali
- Department of Mathematics, Central University of Rajasthan, Kishangarh, Ajmer, 305817, India
| | - Vijay Pal Bajiya
- Department of Mathematics, Central University of Rajasthan, Kishangarh, Ajmer, 305817, India
| | - Jai Prakash Tripathi
- Department of Mathematics, Central University of Rajasthan, Kishangarh, Ajmer, 305817, India.
| | - Anuj Mubayi
- Intercollegiate Biomathematics Alliance, Illinois State University, Normal, USA
- Kalam Institute of Health Technology, Visakhapatnam, India
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15
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Vandendijck Y, Gressani O, Faes C, Camarda CG, Hens N. Cohort-based smoothing methods for age-specific contact rates. Biostatistics 2024; 25:521-540. [PMID: 36940671 DOI: 10.1093/biostatistics/kxad005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2022] [Revised: 02/24/2023] [Accepted: 03/05/2023] [Indexed: 03/23/2023] Open
Abstract
The use of social contact rates is widespread in infectious disease modeling since it has been shown that they are key driving forces of important epidemiological parameters. Quantification of contact patterns is crucial to parameterize dynamic transmission models and to provide insights on the (basic) reproduction number. Information on social interactions can be obtained from population-based contact surveys, such as the European Commission project POLYMOD. Estimation of age-specific contact rates from these studies is often done using a piecewise constant approach or bivariate smoothing techniques. For the latter, typically, smoothness is introduced in the dimensions of the respondent's and contact's age (i.e., the rows and columns of the social contact matrix). We propose a smoothing constrained approach-taking into account the reciprocal nature of contacts-introducing smoothness over the diagonal (including all subdiagonals) of the social contact matrix. This modeling approach is justified assuming that when people age their contact behavior changes smoothly. We call this smoothing from a cohort perspective. Two approaches that allow for smoothing over social contact matrix diagonals are proposed, namely (i) reordering of the diagonal components of the contact matrix and (ii) reordering of the penalty matrix ensuring smoothness over the contact matrix diagonals. Parameter estimation is done in the likelihood framework by using constrained penalized iterative reweighted least squares. A simulation study underlines the benefits of cohort-based smoothing. Finally, the proposed methods are illustrated on the Belgian POLYMOD data of 2006. Code to reproduce the results of the article can be downloaded on this GitHub repository https://github.com/oswaldogressani/Cohort_smoothing.
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Affiliation(s)
- Yannick Vandendijck
- Interuniversity Institute for Biostatistics and Statistical Bioinformatics (I-BioStat), Data Science Institute, Hasselt University, Hasselt, Belgium
| | - Oswaldo Gressani
- Interuniversity Institute for Biostatistics and Statistical Bioinformatics (I-BioStat), Data Science Institute, Hasselt University, Hasselt, Belgium
| | - Christel Faes
- Interuniversity Institute for Biostatistics and Statistical Bioinformatics (I-BioStat), Data Science Institute, Hasselt University, Hasselt, Belgium
| | - Carlo G Camarda
- French Institute for Demographic Studies (INED), Aubervilliers, France
| | - Niel Hens
- Interuniversity Institute for Biostatistics and Statistical Bioinformatics (I-BioStat), Data Science Institute, Hasselt University, Hasselt, Belgium and Centre for Health Economics Research and Modelling Infectious Diseases, Vaxinfectio, University of Antwerp, Antwerp, Belgium
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Goodfellow L, van Leeuwen E, Eggo RM. COVID-19 inequalities in England: a mathematical modelling study of transmission risk and clinical vulnerability by socioeconomic status. BMC Med 2024; 22:162. [PMID: 38616257 DOI: 10.1186/s12916-024-03387-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/11/2023] [Accepted: 04/10/2024] [Indexed: 04/16/2024] Open
Abstract
BACKGROUND The COVID-19 pandemic resulted in major inequalities in infection and disease burden between areas of varying socioeconomic deprivation in many countries, including England. Areas of higher deprivation tend to have a different population structure-generally younger-which can increase viral transmission due to higher contact rates in school-going children and working-age adults. Higher deprivation is also associated with a higher presence of chronic comorbidities, which were convincingly demonstrated to be risk factors for severe COVID-19 disease. These two major factors need to be combined to better understand and quantify their relative importance in the observed COVID-19 inequalities. METHODS We used UK Census data on health status and demography stratified by decile of the Index of Multiple Deprivation (IMD), which is a measure of socioeconomic deprivation. We calculated epidemiological impact using an age-stratified COVID-19 transmission model, which incorporated different contact patterns and clinical health profiles by decile. To separate the contribution of each factor, we considered a scenario where the clinical health profile of all deciles was at the level of the least deprived. We also considered the effectiveness of school closures and vaccination of over 65-year-olds in each decile. RESULTS In the modelled epidemics in urban areas, the most deprived decile experienced 9% more infections, 13% more clinical cases, and a 97% larger peak clinical size than the least deprived; we found similar inequalities in rural areas. Twenty-one per cent of clinical cases and 16% of deaths in England observed under the model assumptions would not occur if all deciles experienced the clinical health profile of the least deprived decile. We found that more deaths were prevented in more affluent areas during school closures and vaccination rollouts. CONCLUSIONS This study demonstrates that both clinical and demographic factors synergise to generate health inequalities in COVID-19, that improving the clinical health profile of populations would increase health equity, and that some interventions can increase health inequalities.
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Affiliation(s)
- Lucy Goodfellow
- Centre for Mathematical Modelling of Infectious Diseases, London School of Hygiene and Tropical Medicine, London, WC14 7HT, UK.
| | - Edwin van Leeuwen
- Centre for Mathematical Modelling of Infectious Diseases, London School of Hygiene and Tropical Medicine, London, WC14 7HT, UK
- Modelling and Economics Unit and NIHR Health Protection Research Unit in Modelling and Health Economics, UK Health Security Agency, London, NW9 5EQ, UK
| | - Rosalind M Eggo
- Centre for Mathematical Modelling of Infectious Diseases, London School of Hygiene and Tropical Medicine, London, WC14 7HT, UK
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Gruhn S, Batram M, Wick M, Langevin E, Scholz S, Greiner W, Damm O. Modelling the Public Health Impact of MenACWY and MenC Adolescent Vaccination Strategies in Germany. Infect Dis Ther 2024; 13:907-920. [PMID: 38570446 PMCID: PMC11058744 DOI: 10.1007/s40121-024-00958-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2024] [Accepted: 03/05/2024] [Indexed: 04/05/2024] Open
Abstract
INTRODUCTION Invasive meningococcal disease (IMD) causes significant mortality and long-term sequelae. This study assesses the potential public health impact of adolescent vaccination strategies employing MenACWY and MenC vaccines in Germany, where the existing meningococcal immunisation programme predominantly involves MenC administration in toddlers. METHODS A dynamic transmission model was developed to simulate the carriage of five meningococcal serogroup compartments (AY/B/C/W/Other) from 2019 until 2060 within 1-year age groups from 0 to 99 years of age. IMD cases were estimated based on case-carrier ratios. The model considered vaccine effectiveness against carriage acquisition and IMD. RESULTS The model predicts that introducing MenACWY adolescent vaccination could lead to a considerable reduction in IMD incidence, with the potential to prevent up to 65 cases per year and a cumulative total of 1467 cases by 2060. This decrease, mainly driven by herd effects, would result in a reduction of IMD incidence across all age groups, regardless of vaccination age. Furthermore, implementing MenACWY vaccination in adolescents is projected to decrease annual MenACWY-related IMD mortality by up to 64%, equating to an overall prevention of 156 IMD deaths by 2060. These protective outcomes are expected to culminate in approximately 2250 life years gained (LYG) throughout the model's projected time horizon. In contrast, the adoption of MenC vaccination in adolescents is predicted to have minimal influence on both IMD incidence and mortality, as well as on LYG. CONCLUSION The results of this study demonstrate that implementing MenACWY vaccination for adolescents in Germany is likely to notably reduce IMD incidence and mortality across age groups. However, the introduction of MenC adolescent vaccination shows only limited impact. Considering the extensive healthcare resources typically required for IMD management, these findings suggest the potential for economic benefits associated with the adoption of MenACWY adolescent vaccination, warranting further cost-effectiveness analysis.
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Affiliation(s)
- Sebastian Gruhn
- Department for Health Economics and Health Care Management, School of Public Health, Bielefeld University, Universitätsstraße 25, 33615, Bielefeld, Germany.
| | - Manuel Batram
- Vandage GmbH, Detmolder Straße 30, 33604, Bielefeld, Germany
| | - Moritz Wick
- Sanofi-Aventis Deutschland GmbH, Lützowstraße 107, 10785, Berlin, Germany
| | - Edith Langevin
- Sanofi Vaccines, 14 Espace Henry Vallee, 69007, Lyon, France
| | - Stefan Scholz
- Martin-Luther-University Halle-Wittenberg, Magdeburgerstr. 20, 06112, Halle (Saale)., Germany
| | - Wolfgang Greiner
- Department for Health Economics and Health Care Management, School of Public Health, Bielefeld University, Universitätsstraße 25, 33615, Bielefeld, Germany
| | - Oliver Damm
- Sanofi-Aventis Deutschland GmbH, Lützowstraße 107, 10785, Berlin, Germany
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Jitsuk NC, Chadsuthi S, Modchang C. Vaccination strategies impact the probability of outbreak extinction: A case study of COVID-19 transmission. Heliyon 2024; 10:e28042. [PMID: 38524580 PMCID: PMC10958689 DOI: 10.1016/j.heliyon.2024.e28042] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2023] [Revised: 03/10/2024] [Accepted: 03/11/2024] [Indexed: 03/26/2024] Open
Abstract
Mass vaccination has proven to be an effective control measure for mitigating the transmission of infectious diseases. Throughout history, various vaccination strategies have been employed to control infections and terminate outbreaks. In this study, we utilized the transmission of COVID-19 as a case study and constructed a stochastic age-structured compartmental model to investigate the effectiveness of different vaccination strategies. Our analysis focused on estimating the outbreak extinction probability under different vaccination scenarios in both homogeneous and heterogeneous populations. Notably, we found that population heterogeneity can enhance the likelihood of outbreak extinction at varying levels of vaccine coverage. Prioritizing vaccinations for individuals with higher infection risk was found to maximize outbreak extinction probability and reduce overall infections, while allocating vaccines to those with higher mortality risk has been proven more effective in reducing deaths. Moreover, our study highlighted the significance of booster doses as the vaccine effectiveness wanes over time, showing that they can significantly enhance the extinction probability and mitigate disease transmission.
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Affiliation(s)
- Natcha C. Jitsuk
- Biophysics Group, Department of Physics, Faculty of Science, Mahidol University, Bangkok, 10400, Thailand
- Center for Disease Modeling, Faculty of Science, Mahidol University, Bangkok, 10400, Thailand
| | - Sudarat Chadsuthi
- Center for Disease Modeling, Faculty of Science, Mahidol University, Bangkok, 10400, Thailand
- Department of Physics, Research Center for Academic Excellence in Applied Physics, Faculty of Science, Naresuan University, Phitsanulok, 65000, Thailand
| | - Charin Modchang
- Biophysics Group, Department of Physics, Faculty of Science, Mahidol University, Bangkok, 10400, Thailand
- Center for Disease Modeling, Faculty of Science, Mahidol University, Bangkok, 10400, Thailand
- Centre of Excellence in Mathematics, MHESI, Bangkok, 10400, Thailand
- Thailand Center of Excellence in Physics, Ministry of Higher Education, Science, Research and Innovation, 328 Si Ayutthaya Road, Bangkok, 10400, Thailand
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Seprianus, Nuraini N, Saputro SW. A computational model of epidemic process with three variants on a synthesized human interaction network. Sci Rep 2024; 14:7470. [PMID: 38553546 DOI: 10.1038/s41598-024-58162-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2023] [Accepted: 03/26/2024] [Indexed: 04/02/2024] Open
Abstract
Virus mutations give rise to new variants that cause multiple waves of pandemics and escalate the infected number of individuals. In this paper, we develop both a simple random network that we define as a synthesized human interaction network and an epidemiological model based on the microscopic process of disease spreading to describe the epidemic process with three variants in a population with some features of social structure. The features of social structure we take into account in the model are the average number of degrees and the frequency of contacts. This paper shows many computational results from several scenarios both in varying network structures and epidemiological parameters that cannot be obtained numerically by using the compartmental model.
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Affiliation(s)
- Seprianus
- Department of Mathematics, Institut Teknologi Bandung, Bandung, Indonesia.
| | - Nuning Nuraini
- Department of Mathematics, Institut Teknologi Bandung, Bandung, Indonesia
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20
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Han Z, Wang Y, Gao S, Sun G, Wang H. Final epidemic size of a two-community SIR model with asymmetric coupling. J Math Biol 2024; 88:51. [PMID: 38551684 DOI: 10.1007/s00285-024-02073-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2023] [Revised: 02/11/2024] [Accepted: 02/29/2024] [Indexed: 04/02/2024]
Abstract
Communities are commonly not isolated but interact asymmetrically with each other, allowing the propagation of infectious diseases within the same community and between different communities. To reveal the impact of asymmetrical interactions and contact heterogeneity on disease transmission, we formulate a two-community SIR epidemic model, in which each community has its contact structure while communication between communities occurs through temporary commuters. We derive an explicit formula for the basic reproduction number R 0 , give an implicit equation for the final epidemic size z, and analyze the relationship between them. Unlike the typical positive correlation between R 0 and z in the classic SIR model, we find a negatively correlated relationship between counterparts of our model deviating from homogeneous populations. Moreover, we investigate the impact of asymmetric coupling mechanisms on R 0 . The results suggest that, in scenarios with restricted movement of susceptible individuals within a community, R 0 does not follow a simple monotonous relationship, indicating that an unbending decrease in the movement of susceptible individuals may increase R 0 . We further demonstrate that network contacts within communities have a greater effect on R 0 than casual contacts between communities. Finally, we develop an epidemic model without restriction on the movement of susceptible individuals, and the numerical simulations suggest that the increase in human flow between communities leads to a larger R 0 .
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Affiliation(s)
- Zhimin Han
- School of Mathematics and Physics, China University of Geosciences, Wuhan, 430074, Hubei, China
| | - Yi Wang
- School of Mathematics and Physics, China University of Geosciences, Wuhan, 430074, Hubei, China
| | - Shan Gao
- Department of Mathematical and Statistical Sciences, University of Alberta, Edmonton, AB, T6G 2G1, Canada
- Interdisciplinary Lab for Mathematical Ecology and Epidemiology, University of Alberta, Edmonton, AB, T6G 2G1, Canada
| | - Guiquan Sun
- School of Mathematics, North University of China, Taiyuan, 030051, Shanxi, China
| | - Hao Wang
- Department of Mathematical and Statistical Sciences, University of Alberta, Edmonton, AB, T6G 2G1, Canada.
- Interdisciplinary Lab for Mathematical Ecology and Epidemiology, University of Alberta, Edmonton, AB, T6G 2G1, Canada.
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21
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Grover EN, Buchwald AG, Ghosh D, Carlton EJ. Does behavior mediate the effect of weather on SARS-CoV-2 transmission? Evidence from cell-phone data. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.03.26.24304854. [PMID: 38585859 PMCID: PMC10996765 DOI: 10.1101/2024.03.26.24304854] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/09/2024]
Abstract
Background There is growing evidence that weather alters SARS-CoV-2 transmission, but it remains unclear what drives the phenomenon. One prevailing hypothesis is that people spend more time indoors in cooler weather, leading to increased spread of SARS-CoV-2 related to time spent in confined spaces and close contact with others. However, the evidence in support of that hypothesis is limited and, at times, conflicting. Objectives We aim to evaluate the extent to which weather impacts COVID-19 via time spent away-from-home in indoor spaces, as compared to a direct effect of weather on COVID-19 hospitalization, independent of mobility. Methods We use a mediation framework, and combine daily weather, COVID-19 hospital surveillance, cellphone-based mobility data and building footprints to estimate the relationship between daily indoor and outdoor weather conditions, mobility, and COVID-19 hospitalizations. We quantify the direct health impacts of weather on COVID-19 hospitalizations and the indirect effects of weather via time spent indoors away-from-home on COVID-19 hospitalizations within five Colorado counties between March 4th 2020 and January 31st 2021. Results We found evidence that changes in 12-day lagged hospital admissions were primarily via the direct effects of weather conditions, rather than via indirect effects by which weather changes time spent indoors away-from-home. Sensitivity analyses evaluating time at home as a mediator were consistent with these conclusions. Discussion Our findings do not support the hypothesis that weather impacted SARS-CoV-2 transmission via changes in mobility patterns during the first year of the pandemic. Rather, weather appears to have impacted SARS-CoV-2 transmission primarily via mechanisms other than human movement. We recommend further analysis of this phenomenon to determine whether these findings generalize to current SARS-CoV-2 transmission dynamics and other seasonal respiratory pathogens.
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Affiliation(s)
- Elise N. Grover
- Department of Environmental and Occupational Health, Colorado School of Public Health, University of Colorado Anschutz Medical Campus, Aurora, USA
| | - Andrea G. Buchwald
- Center for Vaccine Development and Global Health, University of Maryland School of Medicine, Baltimore, MD, United States
| | - Debashis Ghosh
- Department of Biostatistics & Informatics, Colorado School of Public Health, University of Colorado Anschutz Medical Campus, Aurora, USA
| | - Elizabeth J. Carlton
- Department of Environmental and Occupational Health, Colorado School of Public Health, University of Colorado Anschutz Medical Campus, Aurora, USA
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22
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Dall’Amico L, Kleynhans J, Gauvin L, Tizzoni M, Ozella L, Makhasi M, Wolter N, Language B, Wagner RG, Cohen C, Tempia S, Cattuto C. Estimating household contact matrices structure from easily collectable metadata. PLoS One 2024; 19:e0296810. [PMID: 38483886 PMCID: PMC10939291 DOI: 10.1371/journal.pone.0296810] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2023] [Accepted: 12/18/2023] [Indexed: 03/17/2024] Open
Abstract
Contact matrices are a commonly adopted data representation, used to develop compartmental models for epidemic spreading, accounting for the contact heterogeneities across age groups. Their estimation, however, is generally time and effort consuming and model-driven strategies to quantify the contacts are often needed. In this article we focus on household contact matrices, describing the contacts among the members of a family and develop a parametric model to describe them. This model combines demographic and easily quantifiable survey-based data and is tested on high resolution proximity data collected in two sites in South Africa. Given its simplicity and interpretability, we expect our method to be easily applied to other contexts as well and we identify relevant questions that need to be addressed during the data collection procedure.
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Affiliation(s)
| | - Jackie Kleynhans
- National Institute for Communicable Diseases of the National Health Laboratory Service, Johannesburg, South Africa
- School of Public Health, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Laetitia Gauvin
- ISI Foundation, Turin, Italy
- Institute for Research on sustainable Development, UMR215 PRODIG, Aubervilliers, France
| | - Michele Tizzoni
- ISI Foundation, Turin, Italy
- Department of Sociology and Social Research, University of Trento, Trento, Italy
| | | | - Mvuyo Makhasi
- National Institute for Communicable Diseases of the National Health Laboratory Service, Johannesburg, South Africa
| | - Nicole Wolter
- National Institute for Communicable Diseases of the National Health Laboratory Service, Johannesburg, South Africa
- School of Pathology, University of the Witwatersrand, Johannesburg, South Africa
| | - Brigitte Language
- Unit for Environmental Science and Management, Climatology Research Group, North-West University, Potchefstroom, South Africa
| | - Ryan G. Wagner
- MRC/Wits Rural Public Health and Health Transitions Research Unit (Agincourt), Agincourt, South Africa
| | - Cheryl Cohen
- National Institute for Communicable Diseases of the National Health Laboratory Service, Johannesburg, South Africa
- School of Public Health, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Stefano Tempia
- National Institute for Communicable Diseases of the National Health Laboratory Service, Johannesburg, South Africa
- School of Public Health, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Ciro Cattuto
- ISI Foundation, Turin, Italy
- Department of Informatics, University of Turin, Turin, Italy
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23
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Kanté DSI, Jebrane A, Boukamel A, Hakim A. Morocco's population contact matrices: A crowd dynamics-based approach using aggregated literature data. PLoS One 2024; 19:e0296740. [PMID: 38483954 PMCID: PMC10939283 DOI: 10.1371/journal.pone.0296740] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2023] [Accepted: 12/18/2023] [Indexed: 03/17/2024] Open
Abstract
Estimation of contact patterns is often based on questionnaires and time-use data. The results obtained using these methods have been used extensively over the years and recently to predict the spread of the COVID-19 pandemic. They have also been used to test the effectiveness of non-pharmaceutical measures such as social distance. The latter is integrated into epidemiological models by multiplying contact matrices by control functions. We present a novel method that allows the integration of social distancing and other scenarios such as panic. Our method is based on a modified social force model. The model is calibrated using data relating to the movements of individuals and their interactions such as desired walking velocities and interpersonal distances as well as demographic data. We used the framework to assess contact patterns in different social contexts in Morocco. The estimated matrices are extremely assortative and exhibit patterns similar to those observed in other studies including the POLYMOD project. Our findings suggest social distancing would reduce the numbers of contacts by 95%. Further, we estimated the effect of panic on contact patterns, which indicated an increase in the number of contacts of 11%. This approach could be an alternative to questionnaire-based methods in the study of non-pharmaceutical measures and other specific scenarios such as rush hours. It also provides a substitute for estimating children's contact patterns which are typically assessed through parental proxy reporting in surveys.
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Affiliation(s)
- Dramane Sam Idris Kanté
- Complex Systems and Interactions Team, Ecole Centrale Casablanca, Bouskoura, Morocco
- LAMAI, Faculty of Sciences and Technology, Cadi Ayyad University, Marrakesh, Morocco
| | - Aissam Jebrane
- Complex Systems and Interactions Team, Ecole Centrale Casablanca, Bouskoura, Morocco
| | - Adnane Boukamel
- Complex Systems and Interactions Team, Ecole Centrale Casablanca, Bouskoura, Morocco
| | - Abdelilah Hakim
- LAMAI, Faculty of Sciences and Technology, Cadi Ayyad University, Marrakesh, Morocco
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24
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Schumacher J, Kühne L, Brüssermann S, Geisler B, Jäckle S. COVID-19 isolation and quarantine orders in Berlin-Reinickendorf (Germany): How many, how long and to whom? PLoS One 2024; 19:e0271848. [PMID: 38466677 PMCID: PMC10927113 DOI: 10.1371/journal.pone.0271848] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2022] [Accepted: 02/08/2024] [Indexed: 03/13/2024] Open
Abstract
Isolating COVID-19 cases and quarantining their close contacts can prevent COVID-19 transmissions but also inflict harm. We analysed isolation and quarantine orders by the local public health agency in Berlin-Reinickendorf (Germany) and their dependence on the recommendations by the Robert Koch Institute, the national public health institute. Between 3 March 2020 and 18 December 2021 the local public health agency ordered 24 603 isolations (9.2 per 100 inhabitants) and 45 014 quarantines (17 per 100 inhabitants) in a population of 266 123. The mean contacts per case was 1.9. More days of quarantine per 100 inhabitants were ordered for children than for adults: 4.1 for children aged 0-6, 5.2 for children aged 7-17, 0.9 for adults aged 18-64 and 0.3 for senior citizens aged 65-110. The mean duration for isolation orders was 10.2 and for quarantine orders 8.2 days. We calculated a delay of 4 days between contact and quarantine order. 3484 contact persons were in quarantine when they developed an infection. This represents 8% of all individuals in quarantine and 14% of those in isolation. Our study quantifies isolation and quarantine orders, shows that children had been ordered to quarantine more than adults and that there were fewer school days lost to isolation or quarantine as compared to school closures. Our results indicate that the recommendations of the Robert Koch Institute had an influence on isolation and quarantine duration as well as contact identification and that the local public health agency was not able to provide rigorous contact tracing, as the mean number of contacts was lower than the mean number of contacts per person known from literature. Additionally, a considerable portion of the population underwent isolation or quarantine, with a notable number of cases emerging during the quarantine period.
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Affiliation(s)
- Jakob Schumacher
- Local Public Health Agency, Berlin, Germany
- Robert Koch Institute, Berlin, Germany
| | - Lisa Kühne
- Leibniz Institute for Prevention Research and Epidemiology - BIPS, Bremen, Germany
| | - Sophia Brüssermann
- Leibniz Institute for Prevention Research and Epidemiology - BIPS, Bremen, Germany
| | - Benjamin Geisler
- Fraunhofer Institute for Digital Medicine MEVIS, Lübeck, Germany
| | - Sonja Jäckle
- Fraunhofer Institute for Digital Medicine MEVIS, Lübeck, Germany
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25
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Gonzalez-Parra G, Mahmud MS, Kadelka C. Learning from the COVID-19 pandemic: a systematic review of mathematical vaccine prioritization models. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.03.04.24303726. [PMID: 38496570 PMCID: PMC10942533 DOI: 10.1101/2024.03.04.24303726] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/19/2024]
Abstract
As the world becomes ever more connected, the chance of pandemics increases as well. The recent COVID-19 pandemic and the concurrent global mass vaccine roll-out provides an ideal setting to learn from and refine our understanding of infectious disease models for better future preparedness. In this review, we systematically analyze and categorize mathematical models that have been developed to design optimal vaccine prioritization strategies of an initially limited vaccine. As older individuals are disproportionately affected by COVID-19, the focus is on models that take age explicitly into account. The lower mobility and activity level of older individuals gives rise to non-trivial trade-offs. Secondary research questions concern the optimal time interval between vaccine doses and spatial vaccine distribution. This review showcases the effect of various modeling assumptions on model outcomes. A solid understanding of these relationships yields better infectious disease models and thus public health decisions during the next pandemic.
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Affiliation(s)
- Gilberto Gonzalez-Parra
- Instituto de Matemática Multidisciplinar, Universitat Politècnica de València, València, Spain
- Department of Mathematics, New Mexico Tech, 801 Leroy Place, Socorro, 87801, NM, USA
| | - Md Shahriar Mahmud
- Department of Mathematics, Iowa State University, 411 Morrill Rd, Ames, 50011, IA, USA
| | - Claus Kadelka
- Department of Mathematics, Iowa State University, 411 Morrill Rd, Ames, 50011, IA, USA
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26
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Park HJ, Gonsalves GS, Tan ST, Kelly JD, Rutherford GW, Wachter RM, Schechter R, Paltiel AD, Lo NC. Comparing frequency of booster vaccination to prevent severe COVID-19 by risk group in the United States. Nat Commun 2024; 15:1883. [PMID: 38448400 PMCID: PMC10917753 DOI: 10.1038/s41467-024-45549-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2023] [Accepted: 01/26/2024] [Indexed: 03/08/2024] Open
Abstract
There is a public health need to understand how different frequencies of COVID-19 booster vaccines may mitigate the risk of severe COVID-19, while accounting for waning of protection and differential risk by age and immune status. By analyzing United States COVID-19 surveillance and seroprevalence data in a microsimulation model, here we show that more frequent COVID-19 booster vaccination (every 6-12 months) in older age groups and the immunocompromised population would effectively reduce the burden of severe COVID-19, while frequent boosters in the younger population may only provide modest benefit against severe disease. In persons 75+ years, the model estimated that annual boosters would reduce absolute annual risk of severe COVID-19 by 199 (uncertainty interval: 183-232) cases per 100,000 persons, compared to a one-time booster vaccination. In contrast, for persons 18-49 years, the model estimated that annual boosters would reduce this risk by 14 (10-19) cases per 100,000 persons. Those with prior infection had lower benefit of more frequent boosting, and immunocompromised persons had larger benefit. Scenarios with emerging variants with immune evasion increased the benefit of more frequent variant-targeted boosters. This study underscores the benefit of considering key risk factors to inform frequency of COVID-19 booster vaccines in public health guidance and ensuring at least annual boosters in high-risk populations.
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Affiliation(s)
- Hailey J Park
- Division of Infectious Diseases and Geographic Medicine, Department of Medicine, Stanford University, Stanford, CA, USA
| | - Gregg S Gonsalves
- Department of Epidemiology of Microbial Diseases and Public Health Modeling Unit, Yale School of Public Health, New Haven, CT, USA
| | - Sophia T Tan
- Division of Infectious Diseases and Geographic Medicine, Department of Medicine, Stanford University, Stanford, CA, USA
| | - J Daniel Kelly
- Department of Epidemiology and Biostatistics, University of California, San Francisco, San Francisco, CA, USA
- San Francisco Veterans Affairs Medical Center, San Francisco, CA, USA
- F.I. Proctor Foundation, University of California, San Francisco, San Francisco, CA, USA
- Department of Medicine, University of California, San Francisco, San Francisco, CA, USA
- Institute for Global Health Sciences, University of California, San Francisco, San Francisco, CA, USA
| | - George W Rutherford
- Department of Epidemiology and Biostatistics, University of California, San Francisco, San Francisco, CA, USA
- Institute for Global Health Sciences, University of California, San Francisco, San Francisco, CA, USA
| | - Robert M Wachter
- Department of Medicine, University of California, San Francisco, San Francisco, CA, USA
| | | | - A David Paltiel
- Department of Health Policy and Management and Public Health Modeling Unit, Yale School of Public Health, New Haven, CT, USA
| | - Nathan C Lo
- Division of Infectious Diseases and Geographic Medicine, Department of Medicine, Stanford University, Stanford, CA, USA.
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27
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Hu Y, Yan R, Yin X, Gong E, Xin X, Gao A, Shi X, Wang J, Xue H, Feng L, Zhang J. Effectiveness of Multifaceted Strategies to Increase Influenza Vaccination Uptake: A Cluster Randomized Trial. JAMA Netw Open 2024; 7:e243098. [PMID: 38526493 PMCID: PMC10964116 DOI: 10.1001/jamanetworkopen.2024.3098] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/21/2023] [Accepted: 01/26/2024] [Indexed: 03/26/2024] Open
Abstract
Importance Influenza vaccination rates remain low among primary school students and vary by school in Beijing, China. Theory-informed, multifaceted strategies are needed to improve influenza vaccination uptake. Objective To evaluate the effectiveness of multifaceted strategies in improving influenza vaccination uptake among primary school students. Design, Setting, and Participants This cluster randomized trial was conducted from September 2022 to May 2023 across primary schools in Beijing, China. Schools were allocated randomly in a 1:1 ratio to multifaceted strategies or usual practice. Schools were deemed eligible if the vaccination rates in the 2019 to 2020 season fell at or below the district-wide average for primary schools. Eligible participants included students in grades 2 and 3 with no medical contraindications for influenza vaccination. Intervention The multifaceted strategies intervention involved system-level planning and coordination (eg, developing an implementation blueprint, building social norms, and enhancing supervision), school-level training and educating school implementers (eg, conducting a 1-hour training and developing educational materials), and individual-level educating and reminding students and parents (eg, conducting educational activities and sending 4 reminders about vaccination). Main Outcomes and Measures The primary outcomes were influenza vaccination uptake at school reported by school clinicians as well as overall vaccine uptake either at school or outside of school as reported by parents at 3 months. Generalized linear mixed models were used for analysis. Results A total of 20 schools were randomized. One intervention school and 2 control schools did not administer vaccination on school grounds due to COVID-19, resulting in a total of 17 schools (9 intervention and 8 control). There was a total of 1691 students aged 7 to 8 years (890 male [52.6%]; 801 female [47.4%]) including 915 in the intervention group and 776 in the control group. Of all participants, 848 (50.1%) were in grade 2, and 1209 (71.5%) were vaccinated in the 2021 to 2022 season. Participants in the intervention and control groups shared similar characteristics. At follow-up, of the 915 students in the intervention group, 679 (74.5%) received a vaccination at school, and of the 776 students in the control group, 556 (71.7%) received a vaccination at school. The overall vaccination rates were 76.0% (695 of 915 students) for the intervention group and 71.3% (553 of 776 students) for the control group. Compared with the control group, there was significant improvement of vaccination uptake at school (odds ratio, 1.40; 95% CI, 1.06-1.85; P = .02) and overall uptake (odds ratio, 1.49; 95% CI, 1.12-1.99; P = .01) for the intervention group. Conclusions and Relevance In this study, multifaceted strategies showed modest effectiveness in improving influenza vaccination uptake among primary school students, which provides a basis for the implementation of school-located vaccination programs of other vaccines in China, and in other countries with comparable programs. Trial registration Chinese Clinical Trial Registry: ChiCTR2200062449.
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Affiliation(s)
- Yiluan Hu
- School of Population Medicine and Public Health, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - Ruijie Yan
- School of Population Medicine and Public Health, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - Xuejun Yin
- School of Population Medicine and Public Health, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
- The George Institute for Global Health, University of New South Wales, Newtown, New South Wales, Australia
| | - Enying Gong
- School of Population Medicine and Public Health, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - Xin Xin
- Faculty of Psychology, Beijing Normal University, Beijing, China
| | - Aiyu Gao
- Dongcheng Primary and Secondary School Health Care Center, Beijing, China
| | - Xiaoyan Shi
- Dongcheng Primary and Secondary School Health Care Center, Beijing, China
| | - Jing Wang
- Department of Infectious Disease, Dongcheng Center for Disease Control and Prevention, Beijing, China
| | - Hao Xue
- Stanford Center on China’s Economy and Institutions, Stanford University, Stanford, California
| | - Luzhao Feng
- School of Population Medicine and Public Health, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - Juan Zhang
- School of Population Medicine and Public Health, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
- Research Unit of Population Health, Faculty of Medicine, University of Oulu, Oulu, Finland
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28
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Moore S, Cavany S, Perkins TA, España GFC. Projecting the future impact of emerging SARS-CoV-2 variants under uncertainty: Modeling the initial Omicron outbreak. Epidemics 2024; 47:100759. [PMID: 38452455 DOI: 10.1016/j.epidem.2024.100759] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2023] [Revised: 01/26/2024] [Accepted: 03/01/2024] [Indexed: 03/09/2024] Open
Abstract
Over the past several years, the emergence of novel SARS-CoV-2 variants has led to multiple waves of increased COVID-19 incidence. When the Omicron variant emerged, there was considerable concern about its potential impact in the winter of 2021-2022 due to its increased fitness. However, there was also considerable uncertainty regarding its likely impact due to questions about its relative transmissibility, severity, and degree of immune escape. We sought to evaluate the ability of an agent-based model to forecast incidence in the context of this emerging pathogen variant. To project COVID-19 cases and deaths in Indiana, we calibrated our model to COVID-19 hospitalizations, deaths, and test-positivity rates through November 2021, and then projected COVID-19 incidence through April 2022 under four different scenarios that covered the plausible ranges of Omicron's severity, transmissibility, and degree of immune escape. Our initial projections from December 2021 through March 2022 indicated that under a pessimistic scenario with high disease severity, the peak in weekly COVID-19 deaths in Indiana would be larger than the previous peak in December 2020. However, retrospective analyses indicate that Omicron's severity was closer to the optimistic scenario, and even though cases and hospitalizations reached a new peak, fewer deaths occurred than during the previous peak. According to our results, Omicron's rapid spread was consistent with a combination of higher transmissibility and immune escape relative to earlier variants. Our updated projections starting in January 2022 accurately predicted that cases would peak in mid-January and decline rapidly over the next several months. The performance of our projections shows that following the emergence of a new pathogen variant, models can help quantify the potential range of outbreak magnitudes and trajectories. Agent-based models are particularly useful in these scenarios because they can efficiently track individual vaccination and infection histories with multiple variants with varying degrees of cross-protection.
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Affiliation(s)
- Sean Moore
- Department of Biological Sciences and Eck Institute for Global Health, University of Notre Dame, Notre Dame, IN 46556, United States.
| | - Sean Cavany
- Department of Biological Sciences and Eck Institute for Global Health, University of Notre Dame, Notre Dame, IN 46556, United States
| | - T Alex Perkins
- Department of Biological Sciences and Eck Institute for Global Health, University of Notre Dame, Notre Dame, IN 46556, United States
| | - Guido Felipe Camargo España
- Department of Biological Sciences and Eck Institute for Global Health, University of Notre Dame, Notre Dame, IN 46556, United States
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29
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Jacobsen S, Faber M, Altmann B, Mas Marques A, Bock CT, Niendorf S. Impact of the COVID-19 pandemic on norovirus circulation in Germany. Int J Med Microbiol 2024; 314:151600. [PMID: 38246091 DOI: 10.1016/j.ijmm.2024.151600] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2023] [Revised: 12/14/2023] [Accepted: 01/15/2024] [Indexed: 01/23/2024] Open
Abstract
Human norovirus is a major cause of viral gastroenteritis in all age groups. The virus is constantly and rapidly changing, allowing mutations and recombination events to create great diversity of circulating viruses. With the start of the COVID-19 pandemic in 2020, a wide range of public health measures were introduced worldwide to control human-to-human transmission of SARS-CoV-2. In Germany, control measures such as distance rules, contact restrictions, personal protection equipment as well as intensive hand hygiene were introduced. To better understand the effect of the measures to control the COVID-19 pandemic on incidence and the molecular epidemiological dynamics of norovirus outbreaks in Germany, we analyzed national notification data between July 2017 and December 2022 and characterized norovirus sequences circulating between January 2018 and December 2022. Compared to a reference period before the pandemic, the incidence of notified norovirus gastroenteritis decreased by 89.7% to 9.6 per 100,000 during the 2020/2021 norovirus season, corresponding to an incidence rate ratio (IRR) of 0.10. Samples from 539 outbreaks were genotyped in two regions of the viral genome from pre-pandemic (January 2018 to February 2020) and samples from 208 outbreaks during pandemic time period (March 2020 to December 2022). As expected, norovirus outbreaks were mainly found in child care facilities and nursing homes. In total, 36 genotypes were detected in the study period. A high proportion of recombinant strains (86%) was found in patients, the proportion of detected recombinant viruses did not vary between the pre-pandemic and pandemic phase. The proportion of the predominant recombinant strain GII.4 Sydney[P16] was unchanged before pandemic and during pandemic at 37.5%. The diversity of most common genotypes in nursing homes and child care facilities showed a different proportion of genotypes causing outbreaks. In nursing homes as well as in child care facilities GII.4 Sydney[P16] was predominant during the whole study period. Compared to the nursing homes, a greater variety of genotypes at the expense of GII.4 Sydney[P16] was detected in child care facilities. Furthermore, the overall proportion of recombinant strain GII.3[P12] increased during the pandemic, due to outbreaks in child care facilities. The COVID-19 pandemic had a high impact on the occurrence of sporadic cases and norovirus outbreaks in Germany, leading to a near suppression of the typical norovirus winter season following the start of the pandemic. The number of norovirus-associated outbreak samples sent to the Consultant Laboratory dropped by 63% during the pandemic. We could not identify a clear influence on circulating norovirus genotypes. The dominance of GII.4 Sydney recombinant strains was independent from the pandemic. Further studies are needed to follow up on the diversity of less predominant genotypes to see if the pandemic could have acted as a bottleneck to the spread of previously minoritized genotypes like GII.3[P12].
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Affiliation(s)
- Sonja Jacobsen
- Consultant Laboratory for Norovirus, Department of Infectious Diseases, Robert Koch Institute, 13353 Berlin, Germany
| | - Mirko Faber
- Department of Infectious Disease Epidemiology, Robert Koch Institute, 13353 Berlin, Germany
| | - Britta Altmann
- Department of Infectious Disease, Robert Koch Institute, 13353 Berlin, Germany
| | - Andreas Mas Marques
- Consultant Laboratory for Norovirus, Department of Infectious Diseases, Robert Koch Institute, 13353 Berlin, Germany
| | - C-Thomas Bock
- Department of Infectious Disease, Robert Koch Institute, 13353 Berlin, Germany
| | - Sandra Niendorf
- Consultant Laboratory for Norovirus, Department of Infectious Diseases, Robert Koch Institute, 13353 Berlin, Germany.
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Yang W, Shaman J. Reconciling the efficacy and effectiveness of masking on epidemic outcomes. J R Soc Interface 2024; 21:20230666. [PMID: 38442856 PMCID: PMC10914508 DOI: 10.1098/rsif.2023.0666] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2023] [Accepted: 02/07/2024] [Indexed: 03/07/2024] Open
Abstract
During the COVID-19 pandemic, mask wearing in public settings has been a key control measure. However, the reported effectiveness of masking has been much lower than laboratory measures of efficacy, leading to doubts on the utility of masking. Here, we develop an agent-based model that comprehensively accounts for individual masking behaviours and infectious disease dynamics, and test the impact of masking on epidemic outcomes. Using realistic inputs of mask efficacy and contact data at the individual level, the model reproduces the lower effectiveness as reported in randomized controlled trials. Model results demonstrate that transmission within households, where masks are rarely used, can substantially lower effectiveness, and reveal the interaction of nonlinear epidemic dynamics, control measures and potential measurement biases. Overall, model results show that, at the individual level, consistent masking can reduce the risk of first infection and, over time, reduce the frequency of repeated infection. At the population level, masking can provide direct protection to mask wearers, as well as indirect protection to non-wearers, collectively reducing epidemic intensity. These findings suggest it is prudent for individuals to use masks during an epidemic, and for policymakers to recognize the less-than-ideal effectiveness of masking when devising public health interventions.
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Affiliation(s)
- Wan Yang
- Department of Epidemiology, Mailman School of Public Health, Columbia University Medical Center, New York, NY, USA
- Herbert Irving Comprehensive Cancer Center, Columbia University Medical Center, New York, NY, USA
| | - Jeffrey Shaman
- Department of Environmental Health Sciences, Mailman School of Public Health, Columbia University Medical Center, New York, NY, USA
- Columbia Climate School, Columbia University, New York, NY, USA
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31
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Bekker-Nielsen Dunbar M. Transmission matrices used in epidemiologic modelling. Infect Dis Model 2024; 9:185-194. [PMID: 38249428 PMCID: PMC10796975 DOI: 10.1016/j.idm.2023.11.009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2023] [Revised: 11/24/2023] [Accepted: 11/26/2023] [Indexed: 01/23/2024] Open
Abstract
Mixing matrices are included in infectious disease models to reflect transmission opportunities between population strata. These matrices were originally constructed on the basis of theoretical considerations and most of the early work in this area originates from research on sexually transferred diseases in the 80s, in response to AIDS. Later work in the 90s populated these matrices on the basis of survey data gathered to capture transmission risks for respiratory diseases. We provide an overview of developments in the construction of matrices for capturing transmission opportunities in populations. Such transmission matrices are useful for epidemiologic modelling to capture within and between stratum transmission and can be informed from theoretical mixing assumptions, informed by empirical evidence gathered through investigation as well as generated on the basis of data. Links to summary measures and threshold conditions are also provided.
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Affiliation(s)
- M. Bekker-Nielsen Dunbar
- Centre for Research on Pandemics & Society, OsloMet – Oslo Metropolitan University, HG536, Holbergs gate 1, Oslo, 0166, Norway
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32
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Hodgson D, Wilkins N, van Leeuwen E, Watson CH, Crofts J, Flasche S, Jit M, Atkins KE. Protecting infants against RSV disease: an impact and cost-effectiveness comparison of long-acting monoclonal antibodies and maternal vaccination. THE LANCET REGIONAL HEALTH. EUROPE 2024; 38:100829. [PMID: 38476752 PMCID: PMC10928299 DOI: 10.1016/j.lanepe.2023.100829] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/04/2023] [Revised: 12/12/2023] [Accepted: 12/14/2023] [Indexed: 03/14/2024]
Abstract
Background Two new products for preventing Respiratory Syncytial Virus (RSV) in young children have been licensed: a single-dose long-acting monoclonal antibody (la-mAB) and a maternal vaccine (MV). To facilitate the selection of new RSV intervention programmes for large-scale implementation, this study provides an assessment to compare the costs of potential programmes with the health benefits accrued. Methods Using an existing dynamic transmission model, we compared maternal vaccination to la-mAB therapy against RSV in England and Wales by calculating the impact and cost-effectiveness. We calibrated a statistical model to the efficacy trial data to accurately capture their immune waning and estimated the impact of seasonal and year-round programmes for la-mAB and MV programmes. Using these impact estimates, we identified the most cost-effective programme across pricing and delivery cost assumptions. Findings For infants under six months old in England and Wales, a year-round MV programme with 60% coverage would avert 32% (95% CrI 22-41%) of RSV hospital admissions and a year-round la-mAB programme with 90% coverage would avert 57% (95% CrI 41-69%). The MV programme has additional health benefits for pregnant women, which account for 20% of the population-level health burden averted. A seasonal la-mAB programme could be cost-effective for up to £84 for purchasing and administration (CCPA) and a seasonal MV could be cost-effective for up to £80 CCPA. Interpretation This modelling and cost-effectiveness analysis has shown that both the long-acting monoclonal antibodies and the maternal vaccine could substantially reduce the burden of RSV disease in the infant population. Our analysis has informed JCVI's recommendations for an RSV immunisation programme to protect newborns and infants. Funding National Institute for Health Research.
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Affiliation(s)
- David Hodgson
- Centre of Mathematical Modelling of Infectious Diseases, London School of Hygiene and Tropical Medicine, London, UK
| | | | - Edwin van Leeuwen
- Centre of Mathematical Modelling of Infectious Diseases, London School of Hygiene and Tropical Medicine, London, UK
- UK Health Security Agency, London, UK
| | | | | | - Stefan Flasche
- Centre of Mathematical Modelling of Infectious Diseases, London School of Hygiene and Tropical Medicine, London, UK
| | - Mark Jit
- Centre of Mathematical Modelling of Infectious Diseases, London School of Hygiene and Tropical Medicine, London, UK
| | - Katherine E. Atkins
- Centre of Mathematical Modelling of Infectious Diseases, London School of Hygiene and Tropical Medicine, London, UK
- Centre for Global Health, Usher Institute, Edinburgh Medical School, University of Edinburgh, UK
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33
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Persoons R, Sensi M, Prasse B, Van Mieghem P. Transition from time-variant to static networks: Timescale separation in N-intertwined mean-field approximation of susceptible-infectious-susceptible epidemics. Phys Rev E 2024; 109:034308. [PMID: 38632755 DOI: 10.1103/physreve.109.034308] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2023] [Accepted: 02/15/2024] [Indexed: 04/19/2024]
Abstract
We extend the N-intertwined mean-field approximation (NIMFA) for the susceptible-infectious-susceptible (SIS) epidemiological process to time-varying networks. Processes on time-varying networks are often analyzed under the assumption that the process and network evolution happen on different timescales. This approximation is called timescale separation. We investigate timescale separation between disease spreading and topology updates of the network. We introduce the transition times [under T]̲(r) and T[over ¯](r) as the boundaries between the intermediate regime and the annealed (fast changing network) and quenched (static network) regimes, respectively, for a fixed accuracy tolerance r. By analyzing the convergence of static NIMFA processes, we analytically derive upper and lower bounds for T[over ¯](r). Our results provide insights and bounds on the time of convergence to the steady state of the static NIMFA SIS process. We show that, under our assumptions, the upper-transition time T[over ¯](r) is almost entirely determined by the basic reproduction number R_{0} of the network. The value of the upper-transition time T[over ¯](r) around the epidemic threshold is large, which agrees with the current understanding that some real-world epidemics cannot be approximated with the aforementioned timescale separation.
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Affiliation(s)
- Robin Persoons
- Faculty of Electrical Engineering, Mathematics and Computer Science, Delft University of Technology, P.O. Box 5031, 2600 GA Delft, The Netherlands
| | - Mattia Sensi
- MathNeuro Team, Inria at Université Côte d'Azur, 2004 Rte des Lucioles, 06410 Biot, France
- Department of Mathematical Sciences "G. L. Lagrange", Politecnico di Torino, Corso Duca degli Abruzzi 24, 10129 Torino, Italy
| | - Bastian Prasse
- European Centre for Disease Prevention and Control (ECDC), Gustav III's Boulevard 40, 169 73 Solna, Sweden
| | - Piet Van Mieghem
- Faculty of Electrical Engineering, Mathematics and Computer Science, Delft University of Technology, P.O. Box 5031, 2600 GA Delft, The Netherlands
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Lamghari A, Kanté DSI, Jebrane A, Hakim A. Modeling the impact of distancing measures on infectious disease spread: a case study of COVID-19 in the Moroccan population. MATHEMATICAL BIOSCIENCES AND ENGINEERING : MBE 2024; 21:4370-4396. [PMID: 38549332 DOI: 10.3934/mbe.2024193] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/02/2024]
Abstract
This paper explores the impact of various distancing measures on the spread of infectious diseases, focusing on the spread of COVID-19 in the Moroccan population as a case study. Contact matrices, generated through a social force model, capture population interactions within distinct activity locations and age groups. These matrices, tailored for each distancing scenario, have been incorporated into an SEIR model. The study models the region as a network of interconnected activity locations, enabling flexible analysis of the effects of different distancing measures within social contexts and between age groups. Additionally, the method assesses the influence of measures targeting potential superspreaders (i.e., agents with a very high contact rate) and explores the impact of inter-activity location flows, providing insights beyond scalar contact rates or survey-based contact matrices. The results suggest that implementing intra-activity location distancing measures significantly reduces in the number of infected individuals relative to the act of imposing restrictions on individuals with a high contact rate in each activity location. The combination of both measures proves more advantageous. On a regional scale, characterized as a network of interconnected activity locations, restrictions on the movement of individuals with high contact rates was found to result in a $ 2 \% $ reduction, while intra-activity location-based distancing measures was found to achieve a $ 44 \% $ reduction. The combination of these two measures yielded a $ 48\% $ reduction.
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Affiliation(s)
- Abdelkarim Lamghari
- LAMAI, Faculty of Sciences and Technics, Department of Mathematics, Cadi Ayyad University, Marrakesh 40140, Morocco
| | - Dramane Sam Idris Kanté
- LAMAI, Faculty of Sciences and Technics, Department of Mathematics, Cadi Ayyad University, Marrakesh 40140, Morocco
- Centrale Casablanca, Complex Systems and Interactions Research Center, Ville Verte, Bouskoura 27182, Morocco
| | - Aissam Jebrane
- Centrale Casablanca, Complex Systems and Interactions Research Center, Ville Verte, Bouskoura 27182, Morocco
| | - Abdelilah Hakim
- LAMAI, Faculty of Sciences and Technics, Department of Mathematics, Cadi Ayyad University, Marrakesh 40140, Morocco
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35
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Nagpal S, Kumar R, Noronha RF, Kumar S, Gupta D, Amarchand R, Gosain M, Sharma H, Menon GI, Krishnan A. Seasonal variations in social contact patterns in a rural population in north India: Implications for pandemic control. PLoS One 2024; 19:e0296483. [PMID: 38386667 PMCID: PMC10883557 DOI: 10.1371/journal.pone.0296483] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/09/2023] [Accepted: 12/11/2023] [Indexed: 02/24/2024] Open
Abstract
Social contact mixing patterns are critical to model the transmission of communicable diseases, and have been employed to model disease outbreaks including COVID-19. Nonetheless, there is a paucity of studies on contact mixing in low and middle-income countries such as India. Furthermore, mathematical models of disease outbreaks do not account for the temporal nature of social contacts. We conducted a longitudinal study of social contacts in rural north India across three seasons and analysed the temporal differences in contact patterns. A contact diary survey was performed across three seasons from October 2015-16, in which participants were queried on the number, duration, and characteristics of contacts that occurred on the previous day. A total of 8,421 responses from 3,052 respondents (49% females) recorded characteristics of 180,073 contacts. Respondents reported a significantly higher number and duration of contacts in the winter, followed by the summer and the monsoon season (Nemenyi post-hoc, p<0.001). Participants aged 0-9 years and 10-19 years of age reported the highest median number of contacts (16 (IQR 12-21), 17 (IQR 13-24) respectively) and were found to have the highest node centrality in the social network of the region (pageranks = 0.20, 0.17). A large proportion (>80%) of contacts that were reported in schools or on public transport involved physical contact. To the best of our knowledge, our study is the first from India to show that contact mixing patterns vary by the time of the year and provides useful implications for pandemic control. We compared the differences in the number, duration and location of contacts by age-group and gender, and studied the impact of the season, age-group, employment and day of the week on the number and duration of contacts using multivariate negative binomial regression. We created a social network to further understand the age and gender-specific contact patterns, and used the contact matrices in each season to parameterise a nine-compartment agent-based model for simulating a COVID-19 epidemic in each season. Our results can be used to parameterize more accurate mathematical models for prediction of epidemiological trends of infections in rural India.
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Affiliation(s)
| | - Rakesh Kumar
- All India Institute of Medical Sciences, New Delhi, India
| | | | - Supriya Kumar
- Bill and Melinda Gates Foundation, Seattle, WA, United States of America
| | | | | | - Mudita Gosain
- All India Institute of Medical Sciences, New Delhi, India
| | | | | | - Anand Krishnan
- All India Institute of Medical Sciences, New Delhi, India
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36
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Zhao W, Wang X, Tang B. The impacts of spatial-temporal heterogeneity of human-to-human contacts on the extinction probability of infectious disease from branching process model. J Theor Biol 2024; 579:111703. [PMID: 38096979 DOI: 10.1016/j.jtbi.2023.111703] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2023] [Revised: 11/26/2023] [Accepted: 12/07/2023] [Indexed: 12/18/2023]
Abstract
In this study, we focus on the impacts of spatial-temporal heterogeneity of human-to-human contacts on the spread of infectious diseases and develop a multi-type branching process model by introducing random human-to-human contact mode into a structured population. We provide the general formulas of the generation size, extinction probability, and basic reproduction number of the proposed branching process model. The result shows that the natural temporal heterogeneity (i.e. random contacts over time) can lead to a higher extinction probability while remains the same basic reproduction number and generation size. This is also numerically verified by choosing the real contact distributions from different circumstances of four countries. In addition, we observe a non-monotonic pattern of the differences, against the transmission probability and the mean contact rate, between the extinction probabilities under the constant and random contact patterns. Given the spatial heterogeneity, we show that it can contribute to the increase of basic reproduction number, but also increase the extinction probability of the infectious disease. This study adds novel insights to the course of the impact of heterogeneity on the transmission dynamics and also provides additional evidence for the limited role of reproduction numbers.
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Affiliation(s)
- Wuqiong Zhao
- School of Mathematics and Statistics, Xi'an Jiaotong University, Xi'an 710049, PR China.
| | - Xia Wang
- School of Mathematics and Statistics, Shaanxi Normal University, Xi'an 710119, PR China.
| | - Biao Tang
- School of Mathematics and Statistics, Xi'an Jiaotong University, Xi'an 710049, PR China.
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37
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Hamilton MA, Knight J, Mishra S. Examining the Influence of Imbalanced Social Contact Matrices in Epidemic Models. Am J Epidemiol 2024; 193:339-347. [PMID: 37715459 PMCID: PMC10840077 DOI: 10.1093/aje/kwad185] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2022] [Revised: 06/16/2023] [Accepted: 09/12/2023] [Indexed: 09/17/2023] Open
Abstract
Transmissible infections such as those caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spread according to who contacts whom. Therefore, many epidemic models incorporate contact patterns through contact matrices. Contact matrices can be generated from social contact survey data. However, the resulting matrices are often imbalanced, such that the total number of contacts reported by group A with group B do not match those reported by group B with group A. We examined the theoretical influence of imbalanced contact matrices on the estimated basic reproduction number (R0). We then explored how imbalanced matrices may bias model-based epidemic projections using an illustrative simulation model of SARS-CoV-2 with 2 age groups (<15 and ≥15 years). Models with imbalanced matrices underestimated the initial spread of SARS-CoV-2, had later time to peak incidence, and had smaller peak incidence. Imbalanced matrices also influenced cumulative infections observed per age group, as well as the estimated impact of an age-specific vaccination strategy. Stratified transmission models that do not consider contact balancing may generate biased projections of epidemic trajectory and the impact of targeted public health interventions. Therefore, modeling studies should implement and report methods used to balance contact matrices for stratified transmission models.
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Affiliation(s)
| | | | - Sharmistha Mishra
- Correspondence to Dr. Sharmistha Mishra, Department of Medicine, University of Toronto, Li Ka Shing Knowledge Institute, Unity Health Toronto, 209 Victoria Street, Toronto M5B 1T8, Canada (e-mail: )
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38
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Peng A, Bosco S, Simmons AE, Tuite AR, Fisman DN. Impact of community mask mandates on SARS-CoV-2 transmission in Ontario after adjustment for differential testing by age and sex. PNAS NEXUS 2024; 3:pgae065. [PMID: 38463611 PMCID: PMC10923507 DOI: 10.1093/pnasnexus/pgae065] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/30/2023] [Accepted: 01/29/2024] [Indexed: 03/12/2024]
Abstract
Mask use for prevention of respiratory infectious disease transmission is not new but has proven controversial during the SARS-CoV-2 pandemic. In Ontario, Canada, irregular regional introduction of community mask mandates in 2020 created a quasi-experiment useful for evaluating the impact of such mandates; however, Ontario SARS-CoV-2 case counts were likely biased by testing focused on long-term care facilities and healthcare workers. We developed a regression-based method that allowed us to adjust cases for under-testing by age and gender. We evaluated mask mandate effects using count-based regression models with either unadjusted cases, or testing-adjusted case counts, as dependent variables. Models were used to estimate mask mandate effectiveness, and the fraction of SARS-CoV-2 cases, severe outcomes, and costs, averted by mask mandates. Models using unadjusted cases as dependent variables identified modest protective effects of mask mandates (range 31-42%), with variable statistical significance. Mask mandate effectiveness in models predicting test-adjusted case counts was higher, ranging from 49% (95% CI 44-53%) to 76% (95% CI 57-86%). The prevented fraction associated with mask mandates was 46% (95% CI 41-51%), with 290,000 clinical cases, 3,008 deaths, and loss of 29,038 quality-adjusted life years averted from 2020 June to December, representing $CDN 610 million in economic wealth. Under-testing in younger individuals biases estimates of SARS-CoV-2 infection risk and obscures the impact of public health preventive measures. After adjustment for under-testing, mask mandates emerged as highly effective. Community masking saved substantial numbers of lives, and prevented economic costs, during the SARS-CoV-2 pandemic in Ontario, Canada.
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Affiliation(s)
- Amy Peng
- Dalla Lana School of Public Health, University of Toronto, 155 College Street, Toronto, ON M5T 3M7, Canada
| | - Savana Bosco
- Dalla Lana School of Public Health, University of Toronto, 155 College Street, Toronto, ON M5T 3M7, Canada
| | - Alison E Simmons
- Dalla Lana School of Public Health, University of Toronto, 155 College Street, Toronto, ON M5T 3M7, Canada
| | - Ashleigh R Tuite
- Dalla Lana School of Public Health, University of Toronto, 155 College Street, Toronto, ON M5T 3M7, Canada
- Centre for Immunization Programs, Public Health Agency of Canada, 130 Colonnade Road, Ottawa, ON K1A 0K9, Canada
| | - David N Fisman
- Dalla Lana School of Public Health, University of Toronto, 155 College Street, Toronto, ON M5T 3M7, Canada
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39
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Boldea O, Alipoor A, Pei S, Shaman J, Rozhnova G. Age-specific transmission dynamics of SARS-CoV-2 during the first 2 years of the pandemic. PNAS NEXUS 2024; 3:pgae024. [PMID: 38312225 PMCID: PMC10837015 DOI: 10.1093/pnasnexus/pgae024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/24/2023] [Accepted: 01/09/2024] [Indexed: 02/06/2024]
Abstract
During its first 2 years, the SARS-CoV-2 pandemic manifested as multiple waves shaped by complex interactions between variants of concern, non-pharmaceutical interventions, and the immunological landscape of the population. Understanding how the age-specific epidemiology of SARS-CoV-2 has evolved throughout the pandemic is crucial for informing policy decisions. In this article, we aimed to develop an inference-based modeling approach to reconstruct the burden of true infections and hospital admissions in children, adolescents, and adults over the seven waves of four variants (wild-type, Alpha, Delta, and Omicron BA.1) during the first 2 years of the pandemic, using the Netherlands as the motivating example. We find that reported cases are a considerable underestimate and a generally poor predictor of true infection burden, especially because case reporting differs by age. The contribution of children and adolescents to total infection and hospitalization burden increased with successive variants and was largest during the Omicron BA.1 period. However, the ratio of hospitalizations to infections decreased with each subsequent variant in all age categories. Before the Delta period, almost all infections were primary infections occurring in naive individuals. During the Delta and Omicron BA.1 periods, primary infections were common in children but relatively rare in adults who experienced either reinfections or breakthrough infections. Our approach can be used to understand age-specific epidemiology through successive waves in other countries where random community surveys uncovering true SARS-CoV-2 dynamics are absent but basic surveillance and statistics data are available.
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Affiliation(s)
- Otilia Boldea
- Department of Econometrics and OR, Tilburg School of Economics and Management, Tilburg University, Tilburg 5037 AB, The Netherlands
| | - Amir Alipoor
- Department of Econometrics and OR, Tilburg School of Economics and Management, Tilburg University, Tilburg 5037 AB, The Netherlands
| | - Sen Pei
- Department of Environmental Health Sciences, Mailman School of Public Health, Columbia University, New York, NY 10032, USA
| | - Jeffrey Shaman
- Department of Environmental Health Sciences, Mailman School of Public Health, Columbia University, New York, NY 10032, USA
- Columbia Climate School, Columbia University, New York, NY 10025, USA
| | - Ganna Rozhnova
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht 3584 CX, The Netherlands
- Center for Complex Systems Studies (CCSS), Utrecht University, Utrecht 3584 CE, The Netherlands
- Faculdade de Ciências, Universidade de Lisboa, Lisbon PT1749-016, Portugal
- BioISI—Biosystems & Integrative Sciences Institute, Faculdade de Ciências, Universidade de Lisboa, Lisbon PT1749-016, Portugal
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40
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Richard DM, Lipsitch M. What's next: using infectious disease mathematical modelling to address health disparities. Int J Epidemiol 2024; 53:dyad180. [PMID: 38145617 PMCID: PMC10859128 DOI: 10.1093/ije/dyad180] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2023] [Accepted: 12/14/2023] [Indexed: 12/27/2023] Open
Affiliation(s)
- Danielle M Richard
- Center for Forecasting and Outbreak Analytics, Centers for Disease Control and Prevention, Atlanta, GA, USA
| | - Marc Lipsitch
- Center for Forecasting and Outbreak Analytics, Centers for Disease Control and Prevention, Atlanta, GA, USA
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
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41
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Briga M, Goult E, Brett TS, Rohani P, Domenech de Cellès M. Maternal pertussis immunization and the blunting of routine vaccine effectiveness: a meta-analysis and modeling study. Nat Commun 2024; 15:921. [PMID: 38297003 PMCID: PMC10830464 DOI: 10.1038/s41467-024-44943-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2023] [Accepted: 01/10/2024] [Indexed: 02/02/2024] Open
Abstract
A key goal of pertussis control is to protect infants too young to be vaccinated, the age group most vulnerable to this highly contagious respiratory infection. In the last decade, maternal immunization has been deployed in many countries, successfully reducing pertussis in this age group. Because of immunological blunting, however, this strategy may erode the effectiveness of primary vaccination at later ages. Here, we systematically reviewed the literature on the relative risk (RR) of pertussis after primary immunization of infants born to vaccinated vs. unvaccinated mothers. The four studies identified had ≤6 years of follow-up and large statistical uncertainty (meta-analysis weighted mean RR: 0.71, 95% CI: 0.38-1.32). To interpret this evidence, we designed a new mathematical model with explicit blunting mechanisms and evaluated maternal immunization's short- and long-term impact on pertussis transmission dynamics. We show that transient dynamics can mask blunting for at least a decade after rolling out maternal immunization. Hence, the current epidemiological evidence may be insufficient to rule out modest reductions in the effectiveness of primary vaccination. Irrespective of this potential collateral cost, we predict that maternal immunization will remain effective at protecting unvaccinated newborns, supporting current public health recommendations.
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Affiliation(s)
- Michael Briga
- Infectious Disease Epidemiology Group, Max Planck Institute for Infection Biology, Berlin, Germany.
| | - Elizabeth Goult
- Infectious Disease Epidemiology Group, Max Planck Institute for Infection Biology, Berlin, Germany
| | - Tobias S Brett
- Odum School of Ecology, University of Georgia, Athens, GA, 30602, USA
- Department of Infectious Diseases, College of Veterinary Medicine, University of Georgia, Athens, GA, 30602, USA
| | - Pejman Rohani
- Odum School of Ecology, University of Georgia, Athens, GA, 30602, USA
- Department of Infectious Diseases, College of Veterinary Medicine, University of Georgia, Athens, GA, 30602, USA
- Center of Ecology of Infectious Diseases, University of Georgia, Athens, GA, 30602, USA
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He C, Norton D, Temte JL, Barlow S, Goss M, Temte E, Bell C, Chen G, Uzicanin A. Effect of planned school breaks on student absenteeism due to influenza-like illness in school aged children-Oregon School District, Wisconsin September 2014-June 2019. Influenza Other Respir Viruses 2024; 18:e13244. [PMID: 38235373 PMCID: PMC10792089 DOI: 10.1111/irv.13244] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2023] [Revised: 12/05/2023] [Accepted: 12/10/2023] [Indexed: 01/19/2024] Open
Abstract
Background School-aged children and school reopening dates have important roles in community influenza transmission. Although many studies evaluated the impact of reactive closures during seasonal and pandemic influenza outbreaks on medically attended influenza in surrounding communities, few assess the impact of planned breaks (i.e., school holidays) that coincide with influenza seasons, while accounting for differences in seasonal peak timing. Here, we analyze the effects of winter and spring breaks on influenza risk in school-aged children, measured by student absenteeism due to influenza-like illness (a-ILI). Methods We compared a-ILI counts in the 2-week periods before and after each winter and spring break over five consecutive years in a single school district. We introduced a "pseudo-break" of 9 days' duration between winter and spring break each year when school was still in session to serve as a control. The same analysis was applied to each pseudo-break to support any findings of true impact. Results We found strong associations between winter and spring breaks and a reduction in influenza risk, with a nearly 50% reduction in a-ILI counts post-break compared with the period before break, and the greatest impact when break coincided with increased local influenza activity while accounting for possible temporal and community risk confounders. Conclusions These findings suggest that brief breaks of in-person schooling, such as planned breaks lasting 9-16 calendar days, can effectively reduce influenza in schools and community spread. Additional analyses investigating the impact of well-timed shorter breaks on a-ILI may determine an optimal duration for brief school closures to effectively suppress community transmission of influenza.
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Affiliation(s)
- Cecilia He
- University of WisconsinMadisonWisconsinUSA
| | | | | | | | | | | | | | | | - Amra Uzicanin
- Centers for Disease Control and PreventionAtlantaGeorgiaUSA
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Joshi K, Scholz S, Maschio M, Kohli M, Lee A, Fust K, Ultsch B, Van de Velde N, Beck E. Clinical impact and cost-effectiveness of the updated COVID-19 mRNA Autumn 2023 vaccines in Germany. J Med Econ 2024; 27:39-50. [PMID: 38050685 DOI: 10.1080/13696998.2023.2290388] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/18/2023] [Accepted: 11/29/2023] [Indexed: 12/06/2023]
Abstract
OBJECTIVES To assess the potential clinical impact and cost-effectiveness of coronavirus disease 2019 (COVID-19) mRNA vaccines updated for Autumn 2023 in adults aged ≥60 years and high-risk persons aged 30-59 years in Germany over a 1-year analytic time horizon (September 2023-August 2024). METHODS A compartmental Susceptible-Exposed-Infected-Recovered model was updated and adapted to the German market. Numbers of symptomatic infections, a number of COVID-19 related hospitalizations and deaths, costs, and quality-adjusted life-years (QALYs) gained were calculated using a decision tree model. The incremental cost-effectiveness ratio of an Autumn 2023 Moderna updated COVID-19 (mRNA-1273.815) vaccine was compared to no additional vaccination. Potential differences between the mRNA-1273.815 and the Autumn Pfizer-BioNTech updated COVID-19 (XBB.1.5 BNT162b2) vaccines, as well as societal return on investment for the mRNA-1273.815 vaccine relative to no vaccination, were also examined. RESULTS Compared to no autumn vaccination, the mRNA-1273.815 campaign is predicted to prevent approximately 1,697,900 symptomatic infections, 85,400 hospitalizations, and 4,100 deaths. Compared to an XBB.1.5 BNT162b2 campaign, the mRNA-1273.815 campaign is also predicted to prevent approximately 90,100 symptomatic infections, 3,500 hospitalizations, and 160 deaths. Across both analyses we found the mRNA-1273.815 campaign to be dominant. CONCLUSIONS The mRNA-1273.815 vaccine can be considered cost-effective relative to the XBB.1.5 BNT162b2 vaccine and highly likely to provide more benefits and save costs compared to no vaccine in Germany, and to offer high societal return on investment.
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Affiliation(s)
| | | | | | - Michele Kohli
- Quadrant Health Economics Inc, Cambridge, ON, Canada
| | - Amy Lee
- Quadrant Health Economics Inc, Cambridge, ON, Canada
| | - Kelly Fust
- Quadrant Health Economics Inc, Cambridge, ON, Canada
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Deva A, Madhavi B, Kumar Nagaiah S, Pm B. Prevalence and Characteristics of Influenza Cases From 2017 to 2019 at a Tertiary Care Teaching Hospital in Karnataka. Cureus 2024; 16:e53205. [PMID: 38425607 PMCID: PMC10902608 DOI: 10.7759/cureus.53205] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 01/27/2024] [Indexed: 03/02/2024] Open
Abstract
Introduction Influenza virus is a significant human pathogen causing severe acute respiratory illness (SARI) associated with significant mortality worldwide. The H1N1 Influenza virus that caused a pandemic in 2009 continued to cause periodic epidemics worldwide, with new variants posing significant public health problems. The present study was carried out to determine the prevalence and characteristics of influenza at a tertiary care teaching hospital. Methods From 2017 to 2019, respiratory samples from suspected cases of influenza belonging to category C received at the microbiology laboratory were transported to Manipal Centre for Virus Research, Manipal, in the cold chain for testing of influenza virus by real-time reverse transcriptase polymerase chain reaction (rRT-PCR) as per CDC guidelines. The microbiological reports were collected and evaluated. The details of patients positive for influenza were analyzed for demographic and clinical characteristics. Results During the study period, 172 samples from SARI patients were tested, out of which 44 patients were positive for the influenza virus, accounting for a prevalence of 25.58%; 84% (n=37) of the cases were infected with H1N1 influenza virus, and the other 11.36% (n=5) and 4.54% (n=2) cases yielded H1N2 and H1N3 influenza virus, respectively. Among 44 patients, 56.81% (n=25) were females and 43.18% (n=19) were males. Most of the patients, 65.9% (n=29), were between 40 and 60 years old. The predominant presenting symptoms were fever in 81.81% (n=36) patients, breathlessness in 56.8% (n=25) patients, and cough in 54.54% (n=24) patients. Twelve (27.27%) patients had acute severe respiratory distress syndrome (ARDS). A significant mortality rate of 22.72% (n=10) was noted in the study. Conclusion A significant prevalence of influenza was noted in the study at 25.58%. Along with the H1N1 Influenza virus, the new strains detected in our region were H1N2 and H1N3 influenza viruses. Regular surveillance is important in the early detection of cases, for timely management, to reduce mortality, and to take measures to prevent the spread of this important infectious disease.
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Affiliation(s)
- Anitha Deva
- Department of Microbiology, Sri Devaraj Urs Medical College, Sri Devaraj Urs Academy of Higher Education and Research, Kolar, IND
| | - Bindu Madhavi
- Department of Microbiology, Sri Devaraj Urs Medical College, Sri Devaraj Urs Academy of Higher Education and Research, Kolar, IND
| | - Suresh Kumar Nagaiah
- Department of Anesthesiology and Critical Care, Sri Devaraj Urs Medical College, Sri Devaraj Urs Academy of Higher Education and Research, Kolar, IND
| | - Beena Pm
- Department of Microbiology, Sri Devaraj Urs Medical College, Sri Devaraj Urs Academy of Higher Education and Research, Kolar, IND
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Alarid-Escudero F, Andrews JR, Goldhaber-Fiebert JD. Effects of Mitigation and Control Policies in Realistic Epidemic Models Accounting for Household Transmission Dynamics. Med Decis Making 2024; 44:5-17. [PMID: 37953597 DOI: 10.1177/0272989x231205565] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2023]
Abstract
BACKGROUND Compartmental infectious disease (ID) models are often used to evaluate nonpharmaceutical interventions (NPIs) and vaccines. Such models rarely separate within-household and community transmission, potentially introducing biases in situations in which multiple transmission routes exist. We formulated an approach that incorporates household structure into ID models, extending the work of House and Keeling. DESIGN We developed a multicompartment susceptible-exposed-infectious-recovered-susceptible-vaccinated (MC-SEIRSV) modeling framework, allowing nonexponentially distributed duration in exposed and infectious compartments, that tracks within-household and community transmission. We simulated epidemics that varied by community and household transmission rates, waning immunity rate, household size (3 or 5 members), and numbers of exposed and infectious compartments (1-3 each). We calibrated otherwise identical models without household structure to the early phase of each parameter combination's epidemic curve. We compared each model pair in terms of epidemic forecasts and predicted NPI and vaccine impacts on the timing and magnitude of the epidemic peak and its total size. Meta-analytic regressions characterized the relationship between household structure inclusion and the size and direction of biases. RESULTS Otherwise similar models with and without household structure produced equivalent early epidemic curves. However, forecasts from models without household structure were biased. Without intervention, they were upward biased on peak size and total epidemic size, with biases also depending on the number of exposed and infectious compartments. Model-estimated NPI effects of a 60% reduction in community contacts on peak time and size were systematically overestimated without household structure. Biases were smaller with a 20% reduction NPI. Because vaccination affected both community and household transmission, their biases were smaller. CONCLUSIONS ID models without household structure can produce biased outcomes in settings in which within-household and community transmission differ. HIGHLIGHTS Infectious disease models rarely separate household transmission from community transmission. The pace of household transmission may differ from community transmission, depends on household size, and can accelerate epidemic growth.Many infectious disease models assume exponential duration distributions for infected states. However, the duration of most infections is not exponentially distributed, and distributional choice alters modeled epidemic dynamics and intervention effectiveness.We propose a mathematical framework for household and community transmission that allows for nonexponential duration times and a suite of interventions and quantified the effect of accounting for household transmission by varying household size and duration distributions of infected states on modeled epidemic dynamics.Failure to include household structure induces biases in the modeled overall course of an epidemic and the effects of interventions delivered differentially in community settings. Epidemic dynamics are faster and more intense in populations with larger household sizes and for diseases with nonexponentially distributed infectious durations. Modelers should consider explicitly incorporating household structure to quantify the effects of non-pharmaceutical interventions (e.g., shelter-in-place).
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Affiliation(s)
- Fernando Alarid-Escudero
- Department of Health Policy, School of Medicine, Stanford University, Stanford, CA, USA
- Center for Health Policy, Freeman Spogli Institute, Stanford University, Stanford, CA, USA
| | - Jason R Andrews
- Department of Medicine, School of Medicine, Stanford University, Stanford, CA, USA
| | - Jeremy D Goldhaber-Fiebert
- Department of Health Policy, School of Medicine, Stanford University, Stanford, CA, USA
- Center for Health Policy, Freeman Spogli Institute, Stanford University, Stanford, CA, USA
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Bokányi E, Vizi Z, Koltai J, Röst G, Karsai M. Real-time estimation of the effective reproduction number of COVID-19 from behavioral data. Sci Rep 2023; 13:21452. [PMID: 38052841 PMCID: PMC10698193 DOI: 10.1038/s41598-023-46418-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2023] [Accepted: 10/31/2023] [Indexed: 12/07/2023] Open
Abstract
Monitoring the effective reproduction number [Formula: see text] of a rapidly unfolding pandemic in real-time is key to successful mitigation and prevention strategies. However, existing methods based on case numbers, hospital admissions or fatalities suffer from multiple measurement biases and temporal lags due to high test positivity rates or delays in symptom development or administrative reporting. Alternative methods such as web search and social media tracking are less directly indicating epidemic prevalence over time. We instead record age-stratified anonymous contact matrices at a daily resolution using a longitudinal online-offline survey in Hungary during the first two waves of the COVID-19 pandemic. This approach is innovative, cheap, and provides information in near real-time for estimating [Formula: see text] at a daily resolution. Moreover, it allows to complement traditional surveillance systems by signaling periods when official monitoring infrastructures are unreliable due to observational biases.
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Affiliation(s)
- Eszter Bokányi
- Institute of Logic, Language and Computation, University of Amsterdam, 1090GE, Amsterdam, The Netherlands
| | - Zsolt Vizi
- National Laboratory for Health Security, University of Szeged, Szeged, 6720, Hungary
| | - Júlia Koltai
- National Laboratory for Health Security, Centre for Social Sciences, Budapest, 1097, Hungary
- Faculty of Social Sciences, Eötvös Loránd University, Budapest, 1117, Hungary
| | - Gergely Röst
- National Laboratory for Health Security, University of Szeged, Szeged, 6720, Hungary
| | - Márton Karsai
- Department of Network and Data Science, Central European University, 1100, Vienna, Austria.
- National Laboratory for Health Security, Alfréd Rényi Institute of Mathematics, Budapest, 1053, Hungary.
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Patón M, Acuña JM, Rodríguez J. Evaluation of vaccine rollout strategies for emerging infectious diseases: A model-based approach including protection attitudes. Infect Dis Model 2023; 8:1032-1049. [PMID: 37674584 PMCID: PMC10477745 DOI: 10.1016/j.idm.2023.07.012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2023] [Revised: 07/28/2023] [Accepted: 07/30/2023] [Indexed: 09/08/2023] Open
Abstract
Vaccine allocation strategies become crucial during vaccine shortages, especially in the face of potential outbreaks of new infectious diseases, as witnessed during the COVID-19 pandemic. To address this, a specialized compartmental model is created, which simulates an emerging infectious disease similar to COVID-19. This model divides the population into different age groups and is used to compare various vaccine prioritisation approaches, aiming to minimize the total number of fatalities. The model is an improvement upon previous ones as it incorporates essential behavioural factors and is adapted to account for the protective effects of vaccination against both disease infection and transmission. It takes into account human behaviors such as mask-wearing and social distancing by utilizing specific parameters related to self-protection, awareness levels, and the frequency of daily person-to-person interactions within each age group. Furthermore, a novel method for dynamic vaccine prioritisation was introduced in this study. This approach is model-independent and relies on the dynamic R number. It is the first time such a method has been developed, offering a decision-making approach that is not tied to any specific model. This innovation provides a flexible and adaptable strategy for determining vaccine priorities based on real-time data and the current state of the outbreak. Our findings reveal crucial insights into vaccine allocation strategies. When the daily rollout rates are fast (0.75% or higher) and children are eligible for vaccination, prioritising groups with high daily person-to-person interactions can lead to substantial reductions in total fatalities (up to approximately 40% lower). On the other hand, if rollout rates are slower and overall vaccination coverage is high, focusing on vaccinating elders emerges as the most effective strategy, resulting in up to approximately 10% fewer fatalities. However, the scenario changes significantly when children are not eligible for vaccination, as they constitute a highly interactive population group. In this case, the differences between priority strategies become smaller. With fast daily rollout rates, prioritisation based on interactions achieves only a 7% reduction in total fatalities, while a slower rollout with vaccination of elders first leads to an approximately 11% reduction in fatalities compared to the scenario where children are eligible for vaccination. The impact of behavioural parameters is equally critical. When the self-protection levels exercised by the population are low, it significantly affects the optimal vaccine prioritisation strategy to be followed, making it essential to consider behavioural factors in decision-making.
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Affiliation(s)
- Mauricio Patón
- Department of Chemical Engineering, College of Engineering, Khalifa University, SAN Campus PO Box 127788, Abu Dhabi, United Arab Emirates
| | - Juan M. Acuña
- Department of Epidemiology and Public Health, College of Medicine. Khalifa University, PO Box 127788, Abu Dhabi, United Arab Emirates
| | - Jorge Rodríguez
- Department of Chemical Engineering, College of Engineering, Khalifa University, SAN Campus PO Box 127788, Abu Dhabi, United Arab Emirates
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Bents SJ, Viboud C, Grenfell BT, Hogan AB, Tempia S, von Gottberg A, Moyes J, Walaza S, Hansen C, Cohen C, Baker RE. Modeling the impact of COVID-19 nonpharmaceutical interventions on respiratory syncytial virus transmission in South Africa. Influenza Other Respir Viruses 2023; 17:e13229. [PMID: 38090227 PMCID: PMC10710953 DOI: 10.1111/irv.13229] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2023] [Revised: 09/25/2023] [Accepted: 11/11/2023] [Indexed: 12/18/2023] Open
Abstract
Background The South African government employed various nonpharmaceutical interventions (NPIs) to reduce the spread of SARS-CoV-2. Surveillance data from South Africa indicates reduced circulation of respiratory syncytial virus (RSV) throughout the 2020-2021 seasons. Here, we use a mechanistic transmission model to project the rebound of RSV in the two subsequent seasons. Methods We fit an age-structured epidemiological model to hospitalization data from national RSV surveillance in South Africa, allowing for time-varying reduction in RSV transmission during periods of COVID-19 circulation. We apply the model to project the rebound of RSV in the 2022 and 2023 seasons. Results We projected an early and intense outbreak of RSV in April 2022, with an age shift to older infants (6-23 months old) experiencing a larger portion of severe disease burden than typical. In March 2022, government alerts were issued to prepare the hospital system for this potentially intense outbreak. We then assess the 2022 predictions and project the 2023 season. Model predictions for 2023 indicate that RSV activity has not fully returned to normal, with a projected early and moderately intense wave. We estimate that NPIs reduced RSV transmission between 15% and 50% during periods of COVID-19 circulation. Conclusions A wide range of NPIs impacted the dynamics of the RSV outbreaks throughout 2020-2023 in regard to timing, magnitude, and age structure, with important implications in a low- and middle-income countries (LMICs) setting where RSV interventions remain limited. More efforts should focus on adapting RSV models to LMIC data to project the impact of upcoming medical interventions for this disease.
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Affiliation(s)
- Samantha J. Bents
- Fogarty International Center, National Institutes of HealthBethesdaMarylandUSA
| | - Cécile Viboud
- Fogarty International Center, National Institutes of HealthBethesdaMarylandUSA
| | - Bryan T. Grenfell
- Department of Ecology and Evolutionary BiologyPrinceton UniversityPrincetonNew JerseyUSA
| | - Alexandra B. Hogan
- School of Population HealthUniversity of New South WalesSydneyNew South WalesAustralia
| | - Stefano Tempia
- Centre for Respiratory Diseases and MeningitisNational Institute for Communicable Diseases of the National Health Laboratory ServiceJohannesburgSouth Africa
- School of Public Health, Faculty of Health SciencesUniversity of WitwatersrandJohannesburgSouth Africa
| | - Anne von Gottberg
- Centre for Respiratory Diseases and MeningitisNational Institute for Communicable Diseases of the National Health Laboratory ServiceJohannesburgSouth Africa
- School of Pathology, Faculty of Health SciencesUniversity of WitwatersrandJohannesburgSouth Africa
- Department of Pathology, Faculty of Health SciencesUniversity of Cape TownCape TownSouth Africa
| | - Jocelyn Moyes
- Centre for Respiratory Diseases and MeningitisNational Institute for Communicable Diseases of the National Health Laboratory ServiceJohannesburgSouth Africa
- School of Public Health, Faculty of Health SciencesUniversity of WitwatersrandJohannesburgSouth Africa
| | - Sibongile Walaza
- Centre for Respiratory Diseases and MeningitisNational Institute for Communicable Diseases of the National Health Laboratory ServiceJohannesburgSouth Africa
- School of Public Health, Faculty of Health SciencesUniversity of WitwatersrandJohannesburgSouth Africa
| | - Chelsea Hansen
- Fogarty International Center, National Institutes of HealthBethesdaMarylandUSA
- Brotman Baty InstituteUniversity of WashingtonSeattleWashingtonUSA
- PandemiX Center, Department of Science & EnvironmentRoskilde UniversityRoskildeDenmark
| | - Cheryl Cohen
- Centre for Respiratory Diseases and MeningitisNational Institute for Communicable Diseases of the National Health Laboratory ServiceJohannesburgSouth Africa
- School of Public Health, Faculty of Health SciencesUniversity of WitwatersrandJohannesburgSouth Africa
| | - Rachel E. Baker
- School of Public HealthBrown UniversityProvidenceRhode IslandUSA
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Gao S, Dai X, Wang L, Perra N, Wang Z. Epidemic Spreading in Metapopulation Networks Coupled With Awareness Propagation. IEEE TRANSACTIONS ON CYBERNETICS 2023; 53:7686-7698. [PMID: 36054390 DOI: 10.1109/tcyb.2022.3198732] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
Understanding the feedback loop that links the spatiotemporal spread of infectious diseases and human behavior is an open problem. To study this problem, we develop a multiplex framework that couples epidemic spreading across subpopulations in a metapopulation network (i.e., physical layer) with the spreading of awareness about the epidemic in a communication network (i.e., virtual layer). We explicitly study the interactions between the mobility patterns across subpopulations and the awareness propagation among individuals. We analyze the coupled dynamics using microscopic Markov chains (MMCs) equations and validate the theoretical results via Monte Carlo (MC) simulations. We find that with the spreading of awareness, reducing human mobility becomes more effective in mitigating the large-scale epidemic. We also investigate the influence of varying topological features of the physical and virtual layers and the correlation between the connectivity and local population size per subpopulation. Overall the proposed modeling framework and findings contribute to the growing literature investigating the interplay between the spatiotemporal spread of epidemics and human behavior.
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Vynnycky E, Knapp JK, Papadopoulos T, Cutts FT, Hachiya M, Miyano S, Reef SE. Estimates of the global burden of Congenital Rubella Syndrome, 1996-2019. Int J Infect Dis 2023; 137:149-156. [PMID: 37690575 PMCID: PMC10689248 DOI: 10.1016/j.ijid.2023.09.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2023] [Revised: 08/18/2023] [Accepted: 09/05/2023] [Indexed: 09/12/2023] Open
Abstract
OBJECTIVES Many countries introduced rubella-containing vaccination (RCV) after 2011, following changes in recommended World Health Organization (WHO) vaccination strategies and external support. We evaluated the impact of these introductions. METHODS We estimated the country-specific, region-specific, and global Congenital Rubella Syndrome (CRS) incidence during 1996-2019 using mathematical modeling, including routine and campaign vaccination coverage and seroprevalence data. RESULTS In 2019, WHO African and Eastern Mediterranean regions had the highest estimated CRS incidence (64 [95% confidence intervals (CI): 24-123] and 27 [95% CI: 4-67] per 100,000 live births respectively), where nearly half of births occur in countries that have introduced RCV. Other regions, where >95% of births occurred in countries that had introduced RCV, had a low estimated CRS incidence (<1 [95% CI: <1 to 8] and <1 [95% CI: <1 to 12] per 100,000 live births in South-East Asia [SEAR] and the Western Pacific [WPR] respectively, and similarly in Europe and the Americas). The estimated number of CRS births globally declined by approximately two-thirds during 2010-2019, from 100,000 (95% CI: 54,000-166,000) to 32,000 (95% CI: 13,000-60,000), representing a 73% reduction since 1996, largely following RCV introductions in WPR and SEAR, where the greatest reductions occurred. CONCLUSIONS Further reductions can occur by introducing RCV in remaining countries and maintaining high RCV coverage.
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Affiliation(s)
- Emilia Vynnycky
- Statistics Modelling and Economics Department, United Kingdom Health Security Agency, London, UK; Department of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, UK; TB Modelling Group and Centre for Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, London, UK.
| | - Jennifer K Knapp
- Global Immunization Division, Centers for Disease Control and Prevention, Atlanta, Georgia, USA
| | - Timos Papadopoulos
- Statistics Modelling and Economics Department, United Kingdom Health Security Agency, London, UK
| | - Felicity T Cutts
- Department of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, UK
| | - Masahiko Hachiya
- Bureau of International Health Cooperation, National Center for Global Health and Medicine, Toyama, Shinjuku-ku, Tokyo, Japan
| | - Shinsuke Miyano
- Bureau of International Health Cooperation, National Center for Global Health and Medicine, Toyama, Shinjuku-ku, Tokyo, Japan
| | - Susan E Reef
- Global Immunization Division, Centers for Disease Control and Prevention, Atlanta, Georgia, USA
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