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Cai Y, Wang W, Yu L, Wang R, Sun GQ, Kummer AG, Ventura PC, Lv J, Ajelli M, Liu QH. Assessing the effectiveness of test-trace-isolate interventions using a multi-layered temporal network. Infect Dis Model 2025; 10:775-786. [PMID: 40201709 PMCID: PMC11978373 DOI: 10.1016/j.idm.2025.03.005] [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: 02/05/2025] [Revised: 03/05/2025] [Accepted: 03/11/2025] [Indexed: 04/10/2025] Open
Abstract
In the early stage of an infectious disease outbreak, public health strategies tend to gravitate towards non-pharmaceutical interventions (NPIs) given the time required to develop targeted treatments and vaccines. One of the most common NPIs is Test-Trace-Isolate (TTI). One of the factors determining the effectiveness of TTI is the ability to identify contacts of infected individuals. In this study, we propose a multi-layer temporal contact network to model transmission dynamics and assess the impact of different TTI implementations, using SARS-CoV-2 as a case study. The model was used to evaluate TTI effectiveness both in containing an outbreak and mitigating the impact of an epidemic. We estimated that a TTI strategy based on home isolation and testing of both primary and secondary contacts can contain outbreaks only when the reproduction number is up to 1.3, at which the epidemic prevention potential is 88.2% (95% CI: 87.9%-88.5%). On the other hand, for higher value of the reproduction number, TTI is estimated to noticeably mitigate disease burden but at high social costs (e.g., over a month in isolation/quarantine per person for reproduction numbers of 1.7 or higher). We estimated that strategies considering quarantine of contacts have a larger epidemic prevention potential than strategies that either avoid tracing contacts or require contacts to be tested before isolation. Combining TTI with other social distancing measures can improve the likelihood of successfully containing an outbreak but the estimated epidemic prevention potential remains lower than 50% for reproduction numbers higher than 2.1. In conclusion, our model-based evaluation highlights the challenges of relying on TTIs to contain an outbreak of a novel pathogen with characteristics similar to SARS-CoV-2, and that the estimated effectiveness of TTI depends on the way contact patterns are modeled, supporting the relevance of obtaining comprehensive data on human social interactions to improve preparedness.
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Affiliation(s)
- Yunyi Cai
- College of Computer Science, Sichuan University, Chengdu, China
| | - Weiyi Wang
- College of Computer Science, Sichuan University, Chengdu, China
| | - Lanlan Yu
- College of Computer Science, Sichuan University, Chengdu, China
| | - Ruixiao Wang
- College of Computer Science, Sichuan University, Chengdu, China
| | - Gui-Quan Sun
- Department of Mathematics, North University of China, Taiyuan, China
- Complex Systems Research Center, Shanxi University, Taiyuan, China
| | - Allisandra G. Kummer
- Laboratory for Computational Epidemiology and Public Health, Department of Epidemiology and Biostatistics, School of Public Health, Indiana University Bloomington, Bloomington, IN, United States of America
| | - Paulo C. Ventura
- Laboratory for Computational Epidemiology and Public Health, Department of Epidemiology and Biostatistics, School of Public Health, Indiana University Bloomington, Bloomington, IN, United States of America
| | - Jiancheng Lv
- College of Computer Science, Sichuan University, Chengdu, China
| | - Marco Ajelli
- Laboratory for Computational Epidemiology and Public Health, Department of Epidemiology and Biostatistics, School of Public Health, Indiana University Bloomington, Bloomington, IN, United States of America
| | - Quan-Hui Liu
- College of Computer Science, Sichuan University, Chengdu, China
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2
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Ashcroft T, McSwiggan E, Agyei-Manu E, Nundy M, Atkins N, Kirkwood JR, Ben Salem Machiri M, Vardhan V, Lee B, Kubat E, Ravishankar S, Krishan P, De Silva U, Iyahen EO, Rostron J, Zawiejska A, Ogarrio K, Harikar M, Chishty S, Mureyi D, Evans B, Duval D, Carville S, Brini S, Hill J, Qureshi M, Simmons Z, Lyell I, Kavoi T, Dozier M, Curry G, Ordóñez-Mena JM, de Lusignan S, Sheikh A, Theodoratou E, McQuillan R. Effectiveness of non-pharmaceutical interventions as implemented in the UK during the COVID-19 pandemic: a rapid review. J Public Health (Oxf) 2025:fdaf017. [PMID: 40037637 DOI: 10.1093/pubmed/fdaf017] [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: 07/23/2024] [Revised: 01/14/2025] [Accepted: 01/26/2025] [Indexed: 03/06/2025] Open
Abstract
BACKGROUND Although non-pharmaceutical inventions (NPIs) were used globally to control the spread of COVID-19, their effectiveness remains uncertain. We aimed to assess the evidence on NPIs as implemented in the UK, to allow public health bodies to prepare for future pandemics. METHODS We used rapid systematic methods (search date: January 2024) to identify, critically appraise and synthesize interventional, observational and modelling studies reporting on NPI effectiveness in the UK. RESULTS Eighty-five modelling, nine observational and three interventional studies were included. Modelling studies had multiple quality issues; six of the 12 non-modelling studies were high quality. The best available evidence was for test and release strategies for case contacts (moderate certainty), which was suggestive of a protective effect. Although evidence for school-related NPIs and universal lockdown was also suggestive of a protective effect, this evidence was considered low certainty. Evidence certainty for the remaining NPIs was very low or inconclusive. CONCLUSION The validity and reliability of evidence on the effectiveness of NPIs as implemented in the UK during the COVID-19 pandemic is weak. To improve evidence generation and support decision-making during future pandemics or other public health emergencies, it is essential to build evaluation into the design of public health interventions.
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Affiliation(s)
- T Ashcroft
- Usher Institute, Centre for Global Health, University of Edinburgh, Edinburgh EH16 4UX, UK
| | - E McSwiggan
- Usher Institute, Centre for Population Health Sciences, University of Edinburgh, Edinburgh EH16 4UX, UK
| | - E Agyei-Manu
- Usher Institute, Centre for Global Health, University of Edinburgh, Edinburgh EH16 4UX, UK
| | - M Nundy
- Usher Institute, Centre for Global Health, University of Edinburgh, Edinburgh EH16 4UX, UK
| | - N Atkins
- Usher Institute, Centre for Global Health, University of Edinburgh, Edinburgh EH16 4UX, UK
| | - J R Kirkwood
- Usher Institute, Centre for Global Health, University of Edinburgh, Edinburgh EH16 4UX, UK
- Usher Institute, Centre for Medical Informatics, University of Edinburgh, Edinburgh EH16 4UX, UK
| | - M Ben Salem Machiri
- Usher Institute, Centre for Global Health, University of Edinburgh, Edinburgh EH16 4UX, UK
| | - V Vardhan
- Usher Institute, Centre for Global Health, University of Edinburgh, Edinburgh EH16 4UX, UK
| | - B Lee
- Usher Institute, Centre for Global Health, University of Edinburgh, Edinburgh EH16 4UX, UK
| | - E Kubat
- Usher Institute, Centre for Global Health, University of Edinburgh, Edinburgh EH16 4UX, UK
| | - S Ravishankar
- Usher Institute, Centre for Global Health, University of Edinburgh, Edinburgh EH16 4UX, UK
| | - P Krishan
- Usher Institute, Centre for Global Health, University of Edinburgh, Edinburgh EH16 4UX, UK
| | - U De Silva
- Usher Institute, Centre for Global Health, University of Edinburgh, Edinburgh EH16 4UX, UK
| | - E O Iyahen
- Usher Institute, Centre for Global Health, University of Edinburgh, Edinburgh EH16 4UX, UK
| | - J Rostron
- Usher Institute, Centre for Global Health, University of Edinburgh, Edinburgh EH16 4UX, UK
| | - A Zawiejska
- Usher Institute, Centre for Global Health, University of Edinburgh, Edinburgh EH16 4UX, UK
| | - K Ogarrio
- Usher Institute, Centre for Global Health, University of Edinburgh, Edinburgh EH16 4UX, UK
- School of Public Health and Tropical Medicine-Department of Social, Behavioral, and Population Sciences, Tulane University, New Orleans, LA 70112, USA
| | - M Harikar
- Usher Institute, Centre for Global Health, University of Edinburgh, Edinburgh EH16 4UX, UK
| | - S Chishty
- Usher Institute, Centre for Global Health, University of Edinburgh, Edinburgh EH16 4UX, UK
| | - D Mureyi
- Usher Institute, Centre for Global Health, University of Edinburgh, Edinburgh EH16 4UX, UK
| | - B Evans
- Science Evidence Review Team, Research, Evidence and Knowledge Division, UKHSA, London E14 4PU, UK
| | - D Duval
- Science Evidence Review Team, Research, Evidence and Knowledge Division, UKHSA, London E14 4PU, UK
| | - S Carville
- Clinical and Public Health Response Evidence Review Team, Clinical and Public Health, UKHSA, London E14 4PU, UK
| | - S Brini
- Clinical and Public Health Response Evidence Review Team, Clinical and Public Health, UKHSA, London E14 4PU, UK
| | - J Hill
- Clinical and Public Health Response Evidence Review Team, Clinical and Public Health, UKHSA, London E14 4PU, UK
| | - M Qureshi
- Clinical and Public Health Response Evidence Review Team, Clinical and Public Health, UKHSA, London E14 4PU, UK
| | - Z Simmons
- Science Evidence Review Team, Research, Evidence and Knowledge Division, UKHSA, London E14 4PU, UK
| | - I Lyell
- Health Protection Operation, UKHSA, London E14 4PU, UK
| | - T Kavoi
- Clinical and Public Health Response Evidence Review Team, Clinical and Public Health, UKHSA, London E14 4PU, UK
| | - M Dozier
- Information Services, University of Edinburgh, Edinburgh EH3 9DR, UK
| | - G Curry
- Usher Institute, Centre for Population Health Sciences, University of Edinburgh, Edinburgh EH16 4UX, UK
| | - J M Ordóñez-Mena
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford OX2 6GG, UK
| | - S de Lusignan
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford OX2 6GG, UK
- Royal College of General Practitioners (RCGP), Research and Surveillance Centre, London NW1 2FB, UK
| | - A Sheikh
- Usher Institute, Centre for Medical Informatics, University of Edinburgh, Edinburgh EH16 4UX, UK
- Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford OX2 6GG, UK
| | - E Theodoratou
- Usher Institute, Centre for Global Health, University of Edinburgh, Edinburgh EH16 4UX, UK
| | - R McQuillan
- Usher Institute, Centre for Global Health, University of Edinburgh, Edinburgh EH16 4UX, UK
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Alhamlan FS, Al-Qahtani AA. SARS-CoV-2 Variants: Genetic Insights, Epidemiological Tracking, and Implications for Vaccine Strategies. Int J Mol Sci 2025; 26:1263. [PMID: 39941026 PMCID: PMC11818319 DOI: 10.3390/ijms26031263] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2024] [Revised: 01/04/2025] [Accepted: 01/09/2025] [Indexed: 02/16/2025] Open
Abstract
The emergence of SARS-CoV-2 variants has significantly impacted the global response to the COVID-19 pandemic. This review examines the genetic diversity of SARS-CoV-2 variants, their roles in epidemiological tracking, and their influence on viral fitness. Variants of concern (VOCs) such as Alpha, Beta, Gamma, Delta, and Omicron have demonstrated increased transmissibility, altered pathogenicity, and potential resistance to neutralizing antibodies. Epidemiological tracking of these variants is crucial for understanding their spread, informing public health interventions, and guiding vaccine development. The review also explores how specific mutations in the spike protein and other genomic regions contribute to viral fitness, affecting replication efficiency, immune escape, and transmission dynamics. By integrating genomic surveillance data with epidemiological and clinical findings, this review provides a comprehensive overview of the ongoing evolution of SARS-CoV-2 and its implications for public health strategies and new vaccine development.
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Affiliation(s)
- Fatimah S. Alhamlan
- Department of Infection and Immunity, Research Centre, King Faisal Specialist Hospital & Research Centre, 11211 Riyadh, Saudi Arabia;
- Department of Microbiology and Immunology, College of Medicine, Alfaisal University, 11211 Riyadh, Saudi Arabia
| | - Ahmed A. Al-Qahtani
- Department of Infection and Immunity, Research Centre, King Faisal Specialist Hospital & Research Centre, 11211 Riyadh, Saudi Arabia;
- Department of Microbiology and Immunology, College of Medicine, Alfaisal University, 11211 Riyadh, Saudi Arabia
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Kengne Kamga LS, Voordouw ACG, De Vries MC, Timen A, Koopmans MPG. Key factors determining the development of SARS-CoV-2 testing strategies in EU countries: a mixed-methods study. BMJ PUBLIC HEALTH 2025; 3:e001269. [PMID: 40099133 PMCID: PMC11911672 DOI: 10.1136/bmjph-2024-001269] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/04/2024] [Accepted: 01/29/2025] [Indexed: 03/19/2025]
Abstract
Background The WHO and the European Center for Disease Prevention and Control (ECDC) advocated for extensive testing as a crucial pillar in managing the COVID-19 pandemic. Yet, public health emergency responses varied across European countries. In particular, there were differences in the national laboratory capacities and diagnostic testing strategies. This study was conducted during the pandemic to identify the key factors in developing national, SARS-CoV-2 testing strategies across a selection of European countries. Methods A mixed-methods study, comprising an interview phase and a survey phase, was performed. First, laboratory, policy-making and/or public health experts from different European countries were interviewed between 8 January 2021 and 19 March 2021, to review the development and implementation of national testing strategies.Second, a cross-sectional survey was conducted among ECDC National Focal Points (NFP) for Preparedness and Response and/or Microbiology between July and October 2022 to validate the interview findings. Results 12 European experts were interviewed and identified the following key factors determining the development of the national SARS-COV-2 testing strategies in their countries: (1) changing testing goals over time, (2) the prevailing epidemiological situation, (3) testing capacities, (4) availability of reference laboratories, (5) supply and stockpiling of testing material, (6) availability of human resources and (7) quality management standards across laboratories. The experts interviewed stressed the important role of stockpile management, the existence of expert networks, as well as the centralisation of decision-making. Lastly, determining the actors responsible for the testing strategy and putting in place 'coordination, accountability and governance' proved to be pivotal.The survey outcome with 15 European NFPs demonstrated that the testing strategies generally changed over time to include a broader group of individuals. Furthermore, the actors 'Ministry of Health', 'Public health officials', 'National public health institutes' and 'National Expert and/or advisory groups' were selected as key players by survey respondents. Conclusions In general, the scope of the testing strategy in European countries included in this study expanded as the pandemic progressed. This study identified key factors discussed by European experts interviewed that contributed to the development of SARS-CoV-2 testing strategies across European countries.
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Affiliation(s)
- L S Kengne Kamga
- Centre for Infectious Disease Control, National Institute for Public Health and the Environment, Bilthoven, Netherlands
- Athena Institute, VU Amsterdam, Amsterdam, Netherlands
| | - A C G Voordouw
- Center for Infectious Disease Research, Diagnostics and Laboratory Surveillance, National Institute for Public Health and the Environment, Bilthoven, Netherlands
| | - M C De Vries
- Center for Infectious Disease Research, Diagnostics and Laboratory Surveillance, National Institute for Public Health and the Environment, Bilthoven, Netherlands
| | - A Timen
- Centre for Infectious Disease Control, National Institute for Public Health and the Environment, Bilthoven, Netherlands
- Athena Institute, VU Amsterdam, Amsterdam, Netherlands
- Primary and Community Care, Radboud University Medical Center, Nijmegen, Netherlands
| | - M P G Koopmans
- Department of Viroscience, Erasmus Medical Center, Rotterdam, Netherlands
- Pandemic and Disaster Preparedness Centre, Rotterdam, Netherlands
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5
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Dyer CM, Negoescu AT, Borchert M, Harter C, Kühn A, Dambach P, Marx M. Contact Tracing Different Age Groups During the COVID-19 Pandemic: Retrospective Study From South-West Germany. Online J Public Health Inform 2024; 16:e54578. [PMID: 39471373 PMCID: PMC11558225 DOI: 10.2196/54578] [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: 11/16/2023] [Revised: 06/27/2024] [Accepted: 07/22/2024] [Indexed: 11/01/2024] Open
Abstract
BACKGROUND Contact tracing was implemented in many countries during the COVID-19 pandemic to prevent disease spread, reduce mortality, and avoid overburdening health care systems. In several countries, including Germany, new systems were needed to trace potentially infected individuals. OBJECTIVE Using data collected in the Rhine-Neckar and Heidelberg (RNK/HD) districts in southwest Germany (population: 706,974), this study examines the overall effectiveness and efficiency of contact tracing in different age groups and stages of the pandemic. METHODS From January 27, 2020, to April 30, 2022, the RNK/HD Health Authority collected data on COVID-19 infections, quarantines, and deaths. Data on infection, quarantine, and death was grouped by age (young: 0-19 years; adult: 20-65 years; and senior citizens: >65 years) and pandemic phase (infectious wave plus subsequent lull periods) and analyzed for proportion, risk, and relative risk (RR). The overall effectiveness and efficiency of contact tracing were determined by calculating quarantine sensitivity (proportion of the infected population captured in quarantine), positive predictive value (PPV; proportion of the quarantined population that was infected), and the weighted Fβ-score (combined predictive performance). RESULTS Of 706,974 persons living in RNK/HD during the study period, 192,175 (27.2%) tested positive for SARS-CoV-2, 74,810 (10.4%) were quarantined, and 932 (0.132%) died following infection. Compared with adults, the RR of infection was lower among senior citizens (0.401, 95% CI 0.395-0.407) and while initially lower for young people, was ultimately higher for young people across all 5 phases (first-phase RR 0.502, 95% CI 0.438-0.575; all phases RR 1.35, 95% CI 1.34-1.36). Of 932 COVID-19-associated deaths during the study period, 852 were senior citizens (91.4%), with no deaths reported among young people. Relative to adults, senior citizens had the lowest risk of quarantine (RR 0.436, 95% CI 0.424-0.448), while young people had the highest RR (2.94, 95% CI 2.90-2.98). The predictive performance of contact tracing was highest during the second and third phases of the pandemic (Fβ-score=0.272 and 0.338, respectively). In the second phase of the pandemic, 5810 of 16,814 COVID-19 infections were captured within a total quarantine population of 39,687 (sensitivity 34.6%; PPV 14.6%). In the third phase of the pandemic, 3492 of 8803 infections were captured within a total quarantine population of 16,462 (sensitivity 39.7%; PPV 21.2%). CONCLUSIONS The use of quarantine aligned with increasing risks of COVID-19 infection and death. High levels of quarantine sensitivity before the introduction of the vaccine show how contact tracing systems became increasingly effective at capturing and quarantining the infected population. High levels of PPV and Fβ-scores indicate, moreover, that contact tracing became more efficient at identifying infected individuals. Additional analysis of transmission pathways is needed to evaluate the application of quarantine in relation to infection and death risks within specific age groups.
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Affiliation(s)
| | - Alexandra-Teodora Negoescu
- Rhein-Neckar District and Heidelberg City Public Health Authority, Heidelberg, Germany
- Medical Faculty, Heidelberg University, Heidelberg, Germany
| | - Matthias Borchert
- Rhein-Neckar District and Heidelberg City Public Health Authority, Heidelberg, Germany
| | - Christoph Harter
- Rhein-Neckar District and Heidelberg City Public Health Authority, Heidelberg, Germany
| | - Anne Kühn
- Rhein-Neckar District and Heidelberg City Public Health Authority, Heidelberg, Germany
| | - Peter Dambach
- Heidelberg Institute of Global Heath, University Hospital Heidelberg, University Heidelberg, Heidelberg, Germany
| | - Michael Marx
- Heidelberg Institute of Global Heath, University Hospital Heidelberg, University Heidelberg, Heidelberg, Germany
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6
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Faherty LJ, Nascimento de Lima P, Lim JZ, Roberts D, Karr S, Lawson E, Willis HH. Effects of non-pharmaceutical interventions on COVID-19 transmission: rapid review of evidence from Italy, the United States, the United Kingdom, and China. Front Public Health 2024; 12:1426992. [PMID: 39484353 PMCID: PMC11524874 DOI: 10.3389/fpubh.2024.1426992] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2024] [Accepted: 10/01/2024] [Indexed: 11/03/2024] Open
Abstract
Background Prior to the development of COVID-19 vaccines, policymakers instituted various non-pharmaceutical interventions (NPIs) to limit transmission. Prior studies have attempted to examine the extent to which these NPIs achieved their goals of containment, suppression, or mitigation of disease transmission. Existing evidence syntheses have found that numerous factors limit comparability across studies, and the evidence on NPI effectiveness during COVID-19 pandemic remains sparse and inconsistent. This study documents the magnitude and variation in NPI effectiveness in reducing COVID-19 transmission (i.e., reduction in effective reproduction rate [Reff] and daily contact rate) in Italy, the United States, the United Kingdom, and China. Methods Our rapid review and narrative synthesis of existing research identified 126 studies meeting our screening criteria. We selected four contexts with >5 articles to facilitate a meaningful synthesis. This step yielded an analytic sample of 61 articles that used data from China, Italy, the United Kingdom, and the United States. Results We found wide variation and substantial uncertainty around the effectiveness of NPIs at reducing disease transmission. Studies of a single intervention or NPIs that are the least stringent had estimated Reff reductions in the 10-50% range; those that examined so-called "lockdowns" were associated with greater Reff reductions that ranged from 40 to 90%, with many in the 70-80% range. While many studies reported on multiple NPIs, only six of the 61 studies explicitly used the framing of "stringency" or "mild versus strict" or "tiers" of NPIs, concepts that are highly relevant for decisionmakers. Conclusion Existing evidence suggests that NPIs reduce COVID-19 transmission by 40 to 90 percent. This paper documents the extent of the variation in NPI effectiveness estimates and highlights challenges presented by a lack of standardization in modeling approaches. Further research on NPI effectiveness at different stringency levels is needed to inform policy responses to future pandemics.
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Affiliation(s)
- Laura J. Faherty
- RAND Corporation, Boston, MA, United States
- Maine Medical Center, Portland, ME, United States
- Tufts University School of Medicine, Boston, MA, United States
| | | | - Jing Zhi Lim
- RAND Corporation, Santa Monica, CA, United States
| | | | - Sarah Karr
- RAND Corporation, Santa Monica, CA, United States
| | - Emily Lawson
- RAND Corporation, Santa Monica, CA, United States
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7
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Schmidt H, Lemmermann N, Linke M, Bikár SE, Runkel S, Schweiger-Seemann S, Gerber S, Michel A, Hankeln T, Veith M, Kohnen W, Plachter B. SARS-CoV-2 surveillance in a hospital and control of an outbreak on a geriatric ward using whole genome sequencing. Infect Prev Pract 2024; 6:100383. [PMID: 39886645 PMCID: PMC11780369 DOI: 10.1016/j.infpip.2024.100383] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2023] [Accepted: 06/28/2024] [Indexed: 02/01/2025] Open
Abstract
Background During the SARS-CoV-2 pandemic, dominant viral variants were repeatedly replaced by new variants with altered properties, frequently changing the dynamics of the infection event, as well as the effectiveness of vaccines and therapeutics. SARS-CoV-2 variant monitoring by whole genome sequencing was established at the University Medical Center Mainz, Germany to support patient management during the pandemic. Methods SARS-CoV-2 RNA samples from the University Medical Center were analysed weekly with whole genome sequencing. The genome sequences obtained were aligned with sequences from public databases to perform variant assignment. For classification purposes, phylogenetic trees were constructed to map the variant distribution in the clinical settings and the current outbreak events at that time. We describe the surveillance procedures using an example from a geriatric ward. Results For monitoring, a time series was created covering two years of the pandemic. The changes from the Alpha to the Delta and the Omicron variants of SARS-CoV-2 could thus be precisely observed. The increasingly rapid switch of Omicron subvariants in the recent past could be tracked. The elucidation of phylogenetic relationships between circulating strains allowed conclusions about transmission pathways. Using an example from a geriatric ward, we demonstrated how variant monitoring by whole genome sequencing supported the infection prevention and control procedures on a ward and contribute to the control of outbreaks. Conclusions This example of SARS-CoV-2 demonstrates the effectiveness of targeted, local monitoring by molecular variant analysis. The program proved to be instrumental in controlling an outbreak on a geriatric ward.
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Affiliation(s)
- Hanno Schmidt
- SARS-CoV-2 Sequencing Consortium, University Medical Center of the Johannes Gutenberg-University Mainz, Mainz, Germany
- Institute of Virology, University Medical Center of the Johannes Gutenberg-University Mainz, Mainz, Germany
| | - Niels Lemmermann
- SARS-CoV-2 Sequencing Consortium, University Medical Center of the Johannes Gutenberg-University Mainz, Mainz, Germany
- Institute of Virology, University Medical Center of the Johannes Gutenberg-University Mainz, Mainz, Germany
- Institute of Virology, Rheinische Friedrich Wilhelm University of Bonn, Bonn, Germany
| | - Matthias Linke
- SARS-CoV-2 Sequencing Consortium, University Medical Center of the Johannes Gutenberg-University Mainz, Mainz, Germany
- Institute of Human Genetics, University Medical Center of the Johannes Gutenberg-University Mainz, Mainz, Germany
| | - Sven-Ernö Bikár
- SARS-CoV-2 Sequencing Consortium, University Medical Center of the Johannes Gutenberg-University Mainz, Mainz, Germany
- StarSEQ GmbH, Mainz, Germany
| | - Stefan Runkel
- SARS-CoV-2 Sequencing Consortium, University Medical Center of the Johannes Gutenberg-University Mainz, Mainz, Germany
- Transfusion Centre, University Medical Center of the Johannes Gutenberg-University Mainz, Mainz, Germany
| | - Susann Schweiger-Seemann
- SARS-CoV-2 Sequencing Consortium, University Medical Center of the Johannes Gutenberg-University Mainz, Mainz, Germany
- Institute of Human Genetics, University Medical Center of the Johannes Gutenberg-University Mainz, Mainz, Germany
| | - Susanne Gerber
- SARS-CoV-2 Sequencing Consortium, University Medical Center of the Johannes Gutenberg-University Mainz, Mainz, Germany
- Institute of Human Genetics, University Medical Center of the Johannes Gutenberg-University Mainz, Mainz, Germany
| | - André Michel
- SARS-CoV-2 Sequencing Consortium, University Medical Center of the Johannes Gutenberg-University Mainz, Mainz, Germany
- Health Care Department, University Medical Center of the Johannes Gutenberg-University Mainz, Mainz, Germany
| | - Thomas Hankeln
- SARS-CoV-2 Sequencing Consortium, University Medical Center of the Johannes Gutenberg-University Mainz, Mainz, Germany
- Institute of Organismal and Molecular Evolutionary Biology, Johannes Gutenberg-University Mainz, Mainz, Germany
| | - Marina Veith
- Center for General Medicine and Geriatrics, University Medical Center of the Johannes Gutenberg-University Mainz, Mainz, Germany
| | - Wolfgang Kohnen
- SARS-CoV-2 Sequencing Consortium, University Medical Center of the Johannes Gutenberg-University Mainz, Mainz, Germany
- Department of Hygiene and Infection Prevention, University Medical Center of the Johannes Gutenberg-University Mainz, Mainz, Germany
| | - Bodo Plachter
- SARS-CoV-2 Sequencing Consortium, University Medical Center of the Johannes Gutenberg-University Mainz, Mainz, Germany
- Institute of Virology, University Medical Center of the Johannes Gutenberg-University Mainz, Mainz, Germany
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8
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Wang Z, Yang P, Wang R, Ferretti L, Zhao L, Pei S, Wang X, Jia L, Zhang D, Liu Y, Liu Z, Wang Q, Fraser C, Tian H. Estimating the contribution of setting-specific contacts to SARS-CoV-2 transmission using digital contact tracing data. Nat Commun 2024; 15:6103. [PMID: 39030231 PMCID: PMC11271501 DOI: 10.1038/s41467-024-50487-7] [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: 12/03/2023] [Accepted: 07/09/2024] [Indexed: 07/21/2024] Open
Abstract
While many countries employed digital contact tracing to contain the spread of SARS-CoV-2, the contribution of cospace-time interaction (i.e., individuals who shared the same space and time) to transmission and to super-spreading in the real world has seldom been systematically studied due to the lack of systematic sampling and testing of contacts. To address this issue, we utilized data from 2230 cases and 220,878 contacts with detailed epidemiological information during the Omicron outbreak in Beijing in 2022. We observed that contact number per day of tracing for individuals in dwelling, workplace, cospace-time interactions, and community settings could be described by gamma distribution with distinct parameters. Our findings revealed that 38% of traced transmissions occurred through cospace-time interactions whilst control measures were in place. However, using a mathematical model to incorporate contacts in different locations, we found that without control measures, cospace-time interactions contributed to only 11% (95%CI: 10%-12%) of transmissions and the super-spreading risk for this setting was 4% (95%CI: 3%-5%), both the lowest among all settings studied. These results suggest that public health measures should be optimized to achieve a balance between the benefits of digital contact tracing for cospace-time interactions and the challenges posed by contact tracing within the same setting.
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Affiliation(s)
- Zengmiao Wang
- State Key Laboratory of Remote Sensing Science, Center for Global Change and Public Health, Faculty of Geographical Science, Beijing Normal University, Beijing, China
| | - Peng Yang
- Beijing Center for Disease Prevention and Control, Beijing, China
- Beijing Research Center for Respiratory Infectious Diseases, Beijing, China
| | - Ruixue Wang
- State Key Laboratory of Remote Sensing Science, Center for Global Change and Public Health, Faculty of Geographical Science, Beijing Normal University, Beijing, China
| | - Luca Ferretti
- Pandemic Sciences Institute, Nuffield Department of Medicine, University of Oxford, Oxford, UK
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - Lele Zhao
- Pandemic Sciences Institute, Nuffield Department of Medicine, University of Oxford, Oxford, UK
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - Shan Pei
- State Key Laboratory of Remote Sensing Science, Center for Global Change and Public Health, Faculty of Geographical Science, Beijing Normal University, Beijing, China
| | - Xiaoli Wang
- Beijing Center for Disease Prevention and Control, Beijing, China
- Beijing Research Center for Respiratory Infectious Diseases, Beijing, China
| | - Lei Jia
- Beijing Center for Disease Prevention and Control, Beijing, China
- Beijing Research Center for Respiratory Infectious Diseases, Beijing, China
| | - Daitao Zhang
- Beijing Center for Disease Prevention and Control, Beijing, China
- Beijing Research Center for Respiratory Infectious Diseases, Beijing, China
| | - Yonghong Liu
- Beijing Center for Disease Prevention and Control, Beijing, China
- Beijing Research Center for Respiratory Infectious Diseases, Beijing, China
| | - Ziyan Liu
- State Key Laboratory of Remote Sensing Science, Center for Global Change and Public Health, Faculty of Geographical Science, Beijing Normal University, Beijing, China
| | - Quanyi Wang
- Beijing Center for Disease Prevention and Control, Beijing, China.
- Beijing Research Center for Respiratory Infectious Diseases, Beijing, China.
| | - Christophe Fraser
- Pandemic Sciences Institute, Nuffield Department of Medicine, University of Oxford, Oxford, UK
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - Huaiyu Tian
- State Key Laboratory of Remote Sensing Science, Center for Global Change and Public Health, Faculty of Geographical Science, Beijing Normal University, Beijing, China.
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9
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Islam MS, Vogt F, King C, Sheel M. COVID-19 contact tracing and quarantine policies in the Indo-Pacific Region: A mixed-methods study of experiences of public health professionals. PLOS GLOBAL PUBLIC HEALTH 2024; 4:e0003121. [PMID: 38820343 PMCID: PMC11142539 DOI: 10.1371/journal.pgph.0003121] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/17/2023] [Accepted: 03/27/2024] [Indexed: 06/02/2024]
Abstract
Contact tracing and quarantine are valuable public health tools to prevent the transmission of SARS-CoV-2 and control the epidemic. Many low-and middle-income countries (LMICs) adopted global contact tracing and quarantine guidelines but were unable to contextualise the guidance into policies and practices that were relevant to their setting. Therefore, we examine contact tracing policies and practices in the Indo-Pacific region and the need to design context-specific policies. We conducted a mixed-methods study, including a cross-sectional online survey followed by key-informant interviews (KIIs). Using convenience snowball sampling, we invited public health professionals primarily involved in COVID-19 pandemic response from the Indo-Pacific region. We undertook descriptive analyses using counts and percentages for survey data and framework analysis for qualitative data. Seventy-seven public health professionals participated in the survey, of whom ten also participated in the KIIs. The study identified significant gaps between policies and the local contexts. Factors that broaden the gaps were limited knowledge of the changing dynamics of COVID-19 transmission, poor leadership, and coordination, little or no formal training on contact tracing, poor understanding of the guideline recommendations, limited resources, community resistance and mistrust, social stigmatisation and fear of being ostracised, and discrimination. This study revealed substantial disparities between policies and local contexts, significantly influencing policy implementation at national, provincial, and district levels across the studied countries. To bridge these gaps, we advocate for national contact tracing and quarantine guidelines explicitly addressing the quarantine needs of specific demographics, including children, pregnant women, prisoners, and individuals affected by social exclusion issues. Furthermore, we propose strengthening contact tracing training programs, urging revised guidelines to account for social, cultural, and infrastructural nuances influencing contact tracing and quarantine implementation. We also recommend engaging local NGOs, faith-based organisations, and local administrations to reinforce community connections and strengthen contact tracing.
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Affiliation(s)
- Md. Saiful Islam
- National Centre for Epidemiology and Population Health, ANU College of Health and Medicine, The Australian National University, Canberra, Australian Capital Territory, Australia
- School of Population Health, Faculty of Medicine and Health, University of New South Wales, Sydney, Australia
| | - Florian Vogt
- National Centre for Epidemiology and Population Health, ANU College of Health and Medicine, The Australian National University, Canberra, Australian Capital Territory, Australia
- School of Population Health, Faculty of Medicine and Health, University of New South Wales, Sydney, Australia
| | - Catherine King
- Sydney School of Public Health, Faculty of Medicine and Health, The University of Sydney, Sydney, New South Wales, Australia
- Sydney Infectious Diseases Institute, Faculty of Medicine and Health, The University of Sydney, Sydney, New South Wales, Australia
| | - Meru Sheel
- National Centre for Epidemiology and Population Health, ANU College of Health and Medicine, The Australian National University, Canberra, Australian Capital Territory, Australia
- Sydney School of Public Health, Faculty of Medicine and Health, The University of Sydney, Sydney, New South Wales, Australia
- Sydney Infectious Diseases Institute, Faculty of Medicine and Health, The University of Sydney, Sydney, New South Wales, Australia
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10
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Leblanc J, Dusserre-Telmon L, Chauvin A, Simon T, Sabbatini CE, Hemming K, Colizza V, Bérard L, Convert J, Lazazga S, Jegou C, Taibi N, Dautheville S, Zaghia D, Gerlier C, Domergue M, Larrouturou F, Bonnet F, Fontanet A, Salhi S, LeGoff J, Crémieux AC, On behalf of the DEPIST-COVID group, FHU IMPEC (Improving Emergency Care) group. Intensified screening for SARS-CoV-2 in 18 emergency departments in the Paris metropolitan area, France (DEPIST-COVID): A cluster-randomized, two-period, crossover trial. PLoS Med 2023; 20:e1004317. [PMID: 38060611 PMCID: PMC10735176 DOI: 10.1371/journal.pmed.1004317] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/26/2023] [Revised: 12/21/2023] [Accepted: 11/02/2023] [Indexed: 12/23/2023] Open
Abstract
BACKGROUND Asymptomatic and paucisymptomatic infections account for a substantial portion of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) transmissions. The value of intensified screening strategies, especially in emergency departments (EDs), in reaching asymptomatic and paucisymptomatic patients and helping to improve detection and reduce transmission has not been documented. The objective of this study was to evaluate in EDs whether an intensified SARS-CoV-2 screening strategy combining nurse-driven screening for asymptomatic/paucisymptomatic patients with routine practice (intervention) could contribute to higher detection of SARS-CoV-2 infections compared to routine practice alone, including screening for symptomatic or hospitalized patients (control). METHODS AND FINDINGS We conducted a cluster-randomized, two-period, crossover trial from February 2021 to May 2021 in 18 EDs in the Paris metropolitan area, France. All adults visiting the EDs were eligible. At the start of the first period, 18 EDs were randomized to the intervention or control strategy by balanced block randomization with stratification, with the alternative condition being applied in the second period. During the control period, routine screening for SARS-CoV-2 included screening for symptomatic or hospitalized patients. During the intervention period, in addition to routine screening practice, a questionnaire about risk exposure and symptoms and a SARS-CoV-2 screening test were offered by nurses to all remaining asymptomatic/paucisymptomatic patients. The primary outcome was the proportion of newly diagnosed SARS-CoV-2-positive patients among all adults visiting the 18 EDs. Primary analysis was by intention-to-treat. The primary outcome was analyzed using a generalized linear mixed model (Poisson distribution) with the center and center by period as random effects and the strategy (intervention versus control) and period (modeled as a weekly categorical variable) as fixed effects with additional adjustment for community incidence. During the intervention and control periods, 69,248 patients and 69,104 patients, respectively, were included for a total of 138,352 patients. Patients had a median age of 45.0 years [31.0, 63.0], and women represented 45.7% of the patients. During the intervention period, 6,332 asymptomatic/paucisymptomatic patients completed the questionnaire; 4,283 were screened for SARS-CoV-2 by nurses, leading to 224 new SARS-CoV-2 diagnoses. A total of 1,859 patients versus 2,084 patients were newly diagnosed during the intervention and control periods, respectively (adjusted analysis: 26.7/1,000 versus 26.2/1,000, adjusted relative risk: 1.02 (95% confidence interval (CI) [0.94, 1.11]; p = 0.634)). The main limitation of this study is that it was conducted in a rapidly evolving epidemiological context. CONCLUSIONS The results of this study showed that intensified screening for SARS-CoV-2 in EDs was unlikely to identify a higher proportion of newly diagnosed patients. TRIAL REGISTRATION Trial registration number: ClinicalTrials.gov NCT04756609.
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Affiliation(s)
- Judith Leblanc
- Sorbonne Université, INSERM, Pierre Louis Institute of Epidemiology and Public Health; Assistance Publique-Hôpitaux de Paris (AP-HP), Hôpital St Antoine, Clinical Research Platform Paris-East, Paris, France
| | | | - Anthony Chauvin
- AP-HP, Hôpital Lariboisière, Emergency department; Université Paris Cité, INSERM U942 MASCOT, Paris, France
| | - Tabassome Simon
- AP-HP, Hôpital St Antoine, Clinical Research Platform Paris-East; Sorbonne Université, Department of Clinical Pharmacology, Paris, France
| | - Chiara E. Sabbatini
- Sorbonne Université, INSERM, Pierre Louis Institute of Epidemiology and Public Health, Paris, France
| | - Karla Hemming
- University of Birmingham, Institute of Applied Health Research, Birmingham, United Kingdom
| | - Vittoria Colizza
- Sorbonne Université, INSERM, Pierre Louis Institute of Epidemiology and Public Health, Paris, France
| | - Laurence Bérard
- AP-HP, Hôpital St Antoine, Clinical Research Platform Paris-East, Paris, France
| | - Jérome Convert
- AP-HP, Hôpital Lariboisière, Emergency department, Paris, France
| | - Sonia Lazazga
- Centre Hospitalier de Gonesse, Emergency department, Gonesse, France
| | - Carole Jegou
- AP-HP, Hôpital Avicenne, Emergency department, Bobigny, France
| | - Nabila Taibi
- AP-HP, Hôpital Pitié-Salpêtrière, Emergency department, Paris, France
| | | | - Damien Zaghia
- AP-HP, Hôpital Beaujon, Emergency department, Clichy, France
| | - Camille Gerlier
- Hôpital Paris St Joseph, Emergency department, Paris, France
| | - Muriel Domergue
- AP-HP, Hôpital Européen Georges Pompidou, Emergency department, Paris, France
| | | | - Florence Bonnet
- AP-HP, Hôpital St Antoine, Emergency department, Paris, France
| | - Arnaud Fontanet
- Institut Pasteur, Emerging Diseases Epidemiology Unit; PACRI unit, Conservatoire National des Arts et Métiers, Paris, France
| | - Sarah Salhi
- AP-HP, Hôpital St Antoine, Clinical Research Platform Paris-East, Paris, France
| | - Jérome LeGoff
- Université Paris Cité, INSERM U976, INSIGHT Team; AP-HP, Hôpital St Louis, Virology Department, Paris, France
| | - Anne-Claude Crémieux
- AP-HP, Hôpital St Louis, Infectious Diseases Department; Université Paris Cité, FHU PROTHEE, Paris, France
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