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Guzzetta G, Marziano V, Mammone A, Siddu A, Ferraro F, Caraglia A, Maraglino F, Rezza G, Vespignani A, Longini I, Ajelli M, Merler S. The decline of the 2022 Italian mpox epidemic: Role of behavior changes and control strategies. Nat Commun 2024; 15:2283. [PMID: 38480715 PMCID: PMC10937928 DOI: 10.1038/s41467-024-46590-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2023] [Accepted: 03/01/2024] [Indexed: 03/17/2024] Open
Abstract
In 2022, a global outbreak of mpox occurred, predominantly impacting men who have sex with men (MSM). The rapid decline of this epidemic is yet to be fully understood. We investigated the Italian outbreak by means of an individual-based mathematical model calibrated to surveillance data. The model accounts for transmission within the MSM sexual contact network, in recreational and sex clubs attended by MSM, and in households. We indicate a strong spontaneous reduction in sexual transmission (61-87%) in affected MSM communities as the possible driving factor for the rapid decline in cases. The MSM sexual contact network was the main responsible for transmission (about 80%), with clubs and households contributing residually. Contact tracing prevented about half of the potential cases, and a higher success rate in tracing contacts could significantly amplify its effectiveness. Notably, immunizing the 23% of MSM with the highest sexual activity (10 or more partners per year) could completely prevent new mpox resurgences. This research underscores the importance of augmenting contact tracing, targeted immunization campaigns of high-risk groups, and fostering reactive behavioral changes as key strategies to manage and prevent the spread of emerging sexually transmitted pathogens like mpox within the MSM community.
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Affiliation(s)
- Giorgio Guzzetta
- Center for Health Emergencies, Bruno Kessler Foundation, Trento, Italy
| | | | - Alessia Mammone
- Health Prevention Directorate, Ministry of Health, Rome, Italy
| | - Andrea Siddu
- Health Prevention Directorate, Ministry of Health, Rome, Italy
| | | | - Anna Caraglia
- Health Prevention Directorate, Ministry of Health, Rome, Italy
| | | | - Giovanni Rezza
- Health Prevention Directorate, Ministry of Health, Rome, Italy
- Vita-Salute San Raffaele University, Milan, Italy
| | - Alessandro Vespignani
- Laboratory for the Modeling of Biological and Socio-Technical Systems, Northeastern University, Boston, MA, USA
| | - Ira Longini
- Department of Biostatistics, Colleges of Public Health and Health Professions, and Medicine, University of Florida, Gainesville, FL, USA
| | - Marco Ajelli
- Laboratory for Computational Epidemiology and Public Health, Department of Epidemiology and Biostatistics, Indiana University School of Public Health, Bloomington, IN, USA
| | - Stefano Merler
- Center for Health Emergencies, Bruno Kessler Foundation, Trento, Italy.
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2
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Howerton E, Contamin L, Mullany LC, Qin M, Reich NG, Bents S, Borchering RK, Jung SM, Loo SL, Smith CP, Levander J, Kerr J, Espino J, van Panhuis WG, Hochheiser H, Galanti M, Yamana T, Pei S, Shaman J, Rainwater-Lovett K, Kinsey M, Tallaksen K, Wilson S, Shin L, Lemaitre JC, Kaminsky J, Hulse JD, Lee EC, McKee CD, Hill A, Karlen D, Chinazzi M, Davis JT, Mu K, Xiong X, Pastore Y Piontti A, Vespignani A, Rosenstrom ET, Ivy JS, Mayorga ME, Swann JL, España G, Cavany S, Moore S, Perkins A, Hladish T, Pillai A, Ben Toh K, Longini I, Chen S, Paul R, Janies D, Thill JC, Bouchnita A, Bi K, Lachmann M, Fox SJ, Meyers LA, Srivastava A, Porebski P, Venkatramanan S, Adiga A, Lewis B, Klahn B, Outten J, Hurt B, Chen J, Mortveit H, Wilson A, Marathe M, Hoops S, Bhattacharya P, Machi D, Cadwell BL, Healy JM, Slayton RB, Johansson MA, Biggerstaff M, Truelove S, Runge MC, Shea K, Viboud C, Lessler J. Evaluation of the US COVID-19 Scenario Modeling Hub for informing pandemic response under uncertainty. Nat Commun 2023; 14:7260. [PMID: 37985664 PMCID: PMC10661184 DOI: 10.1038/s41467-023-42680-x] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2023] [Accepted: 10/17/2023] [Indexed: 11/22/2023] Open
Abstract
Our ability to forecast epidemics far into the future is constrained by the many complexities of disease systems. Realistic longer-term projections may, however, be possible under well-defined scenarios that specify the future state of critical epidemic drivers. Since December 2020, the U.S. COVID-19 Scenario Modeling Hub (SMH) has convened multiple modeling teams to make months ahead projections of SARS-CoV-2 burden, totaling nearly 1.8 million national and state-level projections. Here, we find SMH performance varied widely as a function of both scenario validity and model calibration. We show scenarios remained close to reality for 22 weeks on average before the arrival of unanticipated SARS-CoV-2 variants invalidated key assumptions. An ensemble of participating models that preserved variation between models (using the linear opinion pool method) was consistently more reliable than any single model in periods of valid scenario assumptions, while projection interval coverage was near target levels. SMH projections were used to guide pandemic response, illustrating the value of collaborative hubs for longer-term scenario projections.
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Affiliation(s)
- Emily Howerton
- The Pennsylvania State University, University Park, PA, USA.
| | | | - Luke C Mullany
- Johns Hopkins University Applied Physics Lab, Laurel, MD, USA
| | | | | | - Samantha Bents
- National Institutes of Health Fogarty International Center, Bethesda, MD, USA
| | - Rebecca K Borchering
- The Pennsylvania State University, University Park, PA, USA
- Centers for Disease Control and Prevention, Atlanta, GA, USA
| | - Sung-Mok Jung
- University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Sara L Loo
- Johns Hopkins University, Baltimore, MD, USA
| | | | | | | | - J Espino
- University of Pittsburgh, Pittsburgh, PA, USA
| | | | | | | | | | - Sen Pei
- Columbia University, New York, NY, USA
| | | | | | - Matt Kinsey
- Johns Hopkins University Applied Physics Lab, Laurel, MD, USA
| | - Kate Tallaksen
- Johns Hopkins University Applied Physics Lab, Laurel, MD, USA
| | - Shelby Wilson
- Johns Hopkins University Applied Physics Lab, Laurel, MD, USA
| | - Lauren Shin
- Johns Hopkins University Applied Physics Lab, Laurel, MD, USA
| | | | | | | | | | | | - Alison Hill
- Johns Hopkins University, Baltimore, MD, USA
| | - Dean Karlen
- University of Victoria, Victoria, BC, Canada
| | | | | | - Kunpeng Mu
- Northeastern University, Boston, MA, USA
| | | | | | | | | | - Julie S Ivy
- North Carolina State University, Raleigh, NC, USA
| | | | | | | | - Sean Cavany
- University of Notre Dame, Notre Dame, IN, USA
| | - Sean Moore
- University of Notre Dame, Notre Dame, IN, USA
| | | | | | | | | | | | - Shi Chen
- University of North Carolina at Charlotte, Charlotte, NC, USA
| | - Rajib Paul
- University of North Carolina at Charlotte, Charlotte, NC, USA
| | - Daniel Janies
- University of North Carolina at Charlotte, Charlotte, NC, USA
| | | | | | - Kaiming Bi
- University of Texas at Austin, Austin, TX, USA
| | | | | | | | | | | | | | | | - Bryan Lewis
- University of Virginia, Charlottesville, VA, USA
| | - Brian Klahn
- University of Virginia, Charlottesville, VA, USA
| | | | | | | | | | | | | | - Stefan Hoops
- University of Virginia, Charlottesville, VA, USA
| | | | - Dustin Machi
- University of Virginia, Charlottesville, VA, USA
| | - Betsy L Cadwell
- Centers for Disease Control and Prevention, Atlanta, GA, USA
| | - Jessica M Healy
- Centers for Disease Control and Prevention, Atlanta, GA, USA
| | | | | | | | | | - Michael C Runge
- U.S. Geological Survey Eastern Ecological Science Center, Laurel, MD, USA
| | - Katriona Shea
- The Pennsylvania State University, University Park, PA, USA
| | - Cécile Viboud
- National Institutes of Health Fogarty International Center, Bethesda, MD, USA.
| | - Justin Lessler
- University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
- Johns Hopkins University, Baltimore, MD, USA.
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Prasad PV, Steele MK, Reed C, Meyers LA, Du Z, Pasco R, Alfaro-Murillo JA, Lewis B, Venkatramanan S, Schlitt J, Chen J, Orr M, Wilson ML, Eubank S, Wang L, Chinazzi M, Pastore y Piontti A, Davis JT, Halloran ME, Longini I, Vespignani A, Pei S, Galanti M, Kandula S, Shaman J, Haw DJ, Arinaminpathy N, Biggerstaff M. Multimodeling approach to evaluating the efficacy of layering pharmaceutical and nonpharmaceutical interventions for influenza pandemics. Proc Natl Acad Sci U S A 2023; 120:e2300590120. [PMID: 37399393 PMCID: PMC10334766 DOI: 10.1073/pnas.2300590120] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2023] [Accepted: 05/21/2023] [Indexed: 07/05/2023] Open
Abstract
When an influenza pandemic emerges, temporary school closures and antiviral treatment may slow virus spread, reduce the overall disease burden, and provide time for vaccine development, distribution, and administration while keeping a larger portion of the general population infection free. The impact of such measures will depend on the transmissibility and severity of the virus and the timing and extent of their implementation. To provide robust assessments of layered pandemic intervention strategies, the Centers for Disease Control and Prevention (CDC) funded a network of academic groups to build a framework for the development and comparison of multiple pandemic influenza models. Research teams from Columbia University, Imperial College London/Princeton University, Northeastern University, the University of Texas at Austin/Yale University, and the University of Virginia independently modeled three prescribed sets of pandemic influenza scenarios developed collaboratively by the CDC and network members. Results provided by the groups were aggregated into a mean-based ensemble. The ensemble and most component models agreed on the ranking of the most and least effective intervention strategies by impact but not on the magnitude of those impacts. In the scenarios evaluated, vaccination alone, due to the time needed for development, approval, and deployment, would not be expected to substantially reduce the numbers of illnesses, hospitalizations, and deaths that would occur. Only strategies that included early implementation of school closure were found to substantially mitigate early spread and allow time for vaccines to be developed and administered, especially under a highly transmissible pandemic scenario.
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Affiliation(s)
- Pragati V. Prasad
- Applied Research and Modeling Team, Influenza Division, United States Centers for Disease Control and Prevention, Atlanta, GA30333
| | - Molly K. Steele
- Applied Research and Modeling Team, Influenza Division, United States Centers for Disease Control and Prevention, Atlanta, GA30333
| | - Carrie Reed
- Applied Research and Modeling Team, Influenza Division, United States Centers for Disease Control and Prevention, Atlanta, GA30333
| | - Lauren Ancel Meyers
- Section of Integrative Biology and Institute for Cellular and Molecular Biology, University of Texas at Austin, Austin, TX78712
| | - Zhanwei Du
- Section of Integrative Biology and Institute for Cellular and Molecular Biology, University of Texas at Austin, Austin, TX78712
| | - Remy Pasco
- Section of Integrative Biology and Institute for Cellular and Molecular Biology, University of Texas at Austin, Austin, TX78712
| | - Jorge A. Alfaro-Murillo
- Department of Biostatistics & Center for Infectious Disease Modeling and Analysis, Yale School of Public Health, New Haven, CT06510
| | - Bryan Lewis
- Biocomplexity Institute & Initiative, University of Virginia, Charlottesville, VA22911
| | | | - James Schlitt
- Biocomplexity Institute & Initiative, University of Virginia, Charlottesville, VA22911
| | - Jiangzhuo Chen
- Biocomplexity Institute & Initiative, University of Virginia, Charlottesville, VA22911
| | - Mark Orr
- Biocomplexity Institute & Initiative, University of Virginia, Charlottesville, VA22911
| | - Mandy L. Wilson
- Biocomplexity Institute & Initiative, University of Virginia, Charlottesville, VA22911
| | - Stephen Eubank
- Biocomplexity Institute & Initiative, University of Virginia, Charlottesville, VA22911
- Public Health Sciences, University of Virginia, Charlottesville, VA22903
| | - Lijing Wang
- Biocomplexity Institute & Initiative, University of Virginia, Charlottesville, VA22911
| | - Matteo Chinazzi
- Laboratory for the Modeling of Biological and Socio-technical Systems, Northeastern University, Boston, MA02115
| | - Ana Pastore y Piontti
- Laboratory for the Modeling of Biological and Socio-technical Systems, Northeastern University, Boston, MA02115
| | - Jessica T. Davis
- Laboratory for the Modeling of Biological and Socio-technical Systems, Northeastern University, Boston, MA02115
| | - M. Elizabeth Halloran
- Fred Hutchinson Cancer Research Center, Seattle, WA98109
- Department of Biostatistics, University of Washington, Seattle, WA98195
| | - Ira Longini
- Department of Biostatistics, College of Public Health and Health Professions, University of Florida, Gainesville, FL32603
| | - Alessandro Vespignani
- Laboratory for the Modeling of Biological and Socio-technical Systems, Northeastern University, Boston, MA02115
| | - Sen Pei
- Department of Environmental Health Sciences, Mailman School of Public Health, Columbia University, New York, NY10032
| | - Marta Galanti
- Department of Environmental Health Sciences, Mailman School of Public Health, Columbia University, New York, NY10032
| | - Sasikiran Kandula
- Department of Environmental Health Sciences, Mailman School of Public Health, Columbia University, New York, NY10032
| | - Jeffrey Shaman
- Department of Environmental Health Sciences, Mailman School of Public Health, Columbia University, New York, NY10032
| | - David J. Haw
- Medical Research Council Centre for Global Infectious Disease Analysis, Imperial College London, LondonSW7 2AZ, United Kingdom
| | - Nimalan Arinaminpathy
- Medical Research Council Centre for Global Infectious Disease Analysis, Imperial College London, LondonSW7 2AZ, United Kingdom
| | - Matthew Biggerstaff
- Applied Research and Modeling Team, Influenza Division, United States Centers for Disease Control and Prevention, Atlanta, GA30333
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Howerton E, Contamin L, Mullany LC, Qin M, Reich NG, Bents S, Borchering RK, Jung SM, Loo SL, Smith CP, Levander J, Kerr J, Espino J, van Panhuis WG, Hochheiser H, Galanti M, Yamana T, Pei S, Shaman J, Rainwater-Lovett K, Kinsey M, Tallaksen K, Wilson S, Shin L, Lemaitre JC, Kaminsky J, Hulse JD, Lee EC, McKee C, Hill A, Karlen D, Chinazzi M, Davis JT, Mu K, Xiong X, Piontti APY, Vespignani A, Rosenstrom ET, Ivy JS, Mayorga ME, Swann JL, España G, Cavany S, Moore S, Perkins A, Hladish T, Pillai A, Toh KB, Longini I, Chen S, Paul R, Janies D, Thill JC, Bouchnita A, Bi K, Lachmann M, Fox S, Meyers LA, Srivastava A, Porebski P, Venkatramanan S, Adiga A, Lewis B, Klahn B, Outten J, Hurt B, Chen J, Mortveit H, Wilson A, Marathe M, Hoops S, Bhattacharya P, Machi D, Cadwell BL, Healy JM, Slayton RB, Johansson MA, Biggerstaff M, Truelove S, Runge MC, Shea K, Viboud C, Lessler J. Informing pandemic response in the face of uncertainty. An evaluation of the U.S. COVID-19 Scenario Modeling Hub. medRxiv 2023:2023.06.28.23291998. [PMID: 37461674 PMCID: PMC10350156 DOI: 10.1101/2023.06.28.23291998] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 07/24/2023]
Abstract
Our ability to forecast epidemics more than a few weeks into the future is constrained by the complexity of disease systems, our limited ability to measure the current state of an epidemic, and uncertainties in how human action will affect transmission. Realistic longer-term projections (spanning more than a few weeks) may, however, be possible under defined scenarios that specify the future state of critical epidemic drivers, with the additional benefit that such scenarios can be used to anticipate the comparative effect of control measures. Since December 2020, the U.S. COVID-19 Scenario Modeling Hub (SMH) has convened multiple modeling teams to make 6-month ahead projections of the number of SARS-CoV-2 cases, hospitalizations and deaths. The SMH released nearly 1.8 million national and state-level projections between February 2021 and November 2022. SMH performance varied widely as a function of both scenario validity and model calibration. Scenario assumptions were periodically invalidated by the arrival of unanticipated SARS-CoV-2 variants, but SMH still provided projections on average 22 weeks before changes in assumptions (such as virus transmissibility) invalidated scenarios and their corresponding projections. During these periods, before emergence of a novel variant, a linear opinion pool ensemble of contributed models was consistently more reliable than any single model, and projection interval coverage was near target levels for the most plausible scenarios (e.g., 79% coverage for 95% projection interval). SMH projections were used operationally to guide planning and policy at different stages of the pandemic, illustrating the value of the hub approach for long-term scenario projections.
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Affiliation(s)
| | | | | | | | | | - Samantha Bents
- National Institutes of Health Fogarty International Center (NIH)
| | | | | | - Sara L Loo
- Johns Hopkins University Infectious Disease Dynamics (JHU-IDD)
| | - Claire P Smith
- Johns Hopkins University Infectious Disease Dynamics (JHU-IDD)
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | - Shi Chen
- University of North Carolina at Charlotte (UNCC)
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5
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Marziano V, Guzzetta G, Longini I, Merler S. Estimates of Serial Interval and Reproduction Number of Sudan Virus, Uganda, August-November 2022. Emerg Infect Dis 2023; 29:1429-1432. [PMID: 37347815 PMCID: PMC10310358 DOI: 10.3201/eid2907.221718] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/24/2023] Open
Abstract
We estimated the mean serial interval for Sudan virus in Uganda to be 11.7 days (95 CI% 8.2-15.8 days). Estimates for the 2022 outbreak indicate a mean basic reproduction number of 2.4-2.7 (95% CI 1.7-3.5). Estimated net reproduction numbers across districts suggest a marked spatial heterogeneity.
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6
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Li F, Li YY, Liu MJ, Fang LQ, Dean NE, Wong GWK, Yang XB, Longini I, Halloran ME, Wang HJ, Liu PL, Pang YH, Yan YQ, Liu S, Xia W, Lu XX, Liu Q, Yang Y, Xu SQ. Household transmission of SARS-CoV-2 and risk factors for susceptibility and infectivity in Wuhan: a retrospective observational study. Lancet Infect Dis 2021; 21:617-628. [PMID: 33476567 PMCID: PMC7833912 DOI: 10.1016/s1473-3099(20)30981-6] [Citation(s) in RCA: 141] [Impact Index Per Article: 47.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/18/2020] [Revised: 11/08/2020] [Accepted: 12/07/2020] [Indexed: 01/25/2023]
Abstract
BACKGROUND Wuhan was the first epicentre of COVID-19 in the world, accounting for 80% of cases in China during the first wave. We aimed to assess household transmissibility of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and risk factors associated with infectivity and susceptibility to infection in Wuhan. METHODS This retrospective cohort study included the households of all laboratory-confirmed or clinically confirmed COVID-19 cases and laboratory-confirmed asymptomatic SARS-CoV-2 infections identified by the Wuhan Center for Disease Control and Prevention between Dec 2, 2019, and April 18, 2020. We defined households as groups of family members and close relatives who did not necessarily live at the same address and considered households that shared common contacts as epidemiologically linked. We used a statistical transmission model to estimate household secondary attack rates and to quantify risk factors associated with infectivity and susceptibility to infection, accounting for individual-level exposure history. We assessed how intervention policies affected the household reproductive number, defined as the mean number of household contacts a case can infect. FINDINGS 27 101 households with 29 578 primary cases and 57 581 household contacts were identified. The secondary attack rate estimated with the transmission model was 15·6% (95% CI 15·2-16·0), assuming a mean incubation period of 5 days and a maximum infectious period of 22 days. Individuals aged 60 years or older were at a higher risk of infection with SARS-CoV-2 than all other age groups. Infants aged 0-1 years were significantly more likely to be infected than children aged 2-5 years (odds ratio [OR] 2·20, 95% CI 1·40-3·44) and children aged 6-12 years (1·53, 1·01-2·34). Given the same exposure time, children and adolescents younger than 20 years of age were more likely to infect others than were adults aged 60 years or older (1·58, 1·28-1·95). Asymptomatic individuals were much less likely to infect others than were symptomatic cases (0·21, 0·14-0·31). Symptomatic cases were more likely to infect others before symptom onset than after (1·42, 1·30-1·55). After mass isolation of cases, quarantine of household contacts, and restriction of movement policies were implemented, household reproductive numbers declined by 52% among primary cases (from 0·25 [95% CI 0·24-0·26] to 0·12 [0·10-0·13]) and by 63% among secondary cases (from 0·17 [0·16-0·18] to 0·063 [0·057-0·070]). INTERPRETATION Within households, children and adolescents were less susceptible to SARS-CoV-2 infection but were more infectious than older individuals. Presymptomatic cases were more infectious and individuals with asymptomatic infection less infectious than symptomatic cases. These findings have implications for devising interventions for blocking household transmission of SARS-CoV-2, such as timely vaccination of eligible children once resources become available. FUNDING National Natural Science Foundation of China, Fundamental Research Funds for the Central Universities, US National Institutes of Health, and US National Science Foundation.
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Affiliation(s)
- Fang Li
- Wuhan Center for Disease Control and Prevention, Wuhan, Hubei, China
| | - Yuan-Yuan Li
- School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Ming-Jin Liu
- Department of Biostatistics, College of Public Health and Health Professions & Emerging Pathogens Institute, University of Florida, Gainesville, FL, USA
| | - Li-Qun Fang
- State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, China
| | - Natalie E Dean
- Department of Biostatistics, College of Public Health and Health Professions & Emerging Pathogens Institute, University of Florida, Gainesville, FL, USA
| | - Gary W K Wong
- Department of Pediatrics, Faculty of Medicine, Chinese University of Hong Kong, Hong Kong Special Administrative Region, China
| | - Xiao-Bing Yang
- Wuhan Center for Disease Control and Prevention, Wuhan, Hubei, China
| | - Ira Longini
- Department of Biostatistics, College of Public Health and Health Professions & Emerging Pathogens Institute, University of Florida, Gainesville, FL, USA
| | - M Elizabeth Halloran
- Vaccine and Infectious Diseases Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA,Department of Biostatistics, University of Washington, Seattle, WA, USA
| | - Huai-Ji Wang
- Wuhan Center for Disease Control and Prevention, Wuhan, Hubei, China
| | - Pu-Lin Liu
- Wuhan Center for Disease Control and Prevention, Wuhan, Hubei, China
| | - Yan-Hui Pang
- Wuhan Center for Disease Control and Prevention, Wuhan, Hubei, China
| | - Ya-Qiong Yan
- Wuhan Center for Disease Control and Prevention, Wuhan, Hubei, China
| | - Su Liu
- Wuhan Center for Disease Control and Prevention, Wuhan, Hubei, China
| | - Wei Xia
- School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Xiao-Xia Lu
- Department of Respiratory Medicine, Wuhan Children's Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Qi Liu
- School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Yang Yang
- Department of Biostatistics, College of Public Health and Health Professions & Emerging Pathogens Institute, University of Florida, Gainesville, FL, USA,Dr Yang Yang, Department of Biostatistics, College of Public Health and Health Professions & Emerging Pathogens Institute, University of Florida, Gainesville, FL 32611, USA
| | - Shun-Qing Xu
- School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China,Correspondence to: Dr Shun-Qing Xu, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China
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7
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Affiliation(s)
- Philip Krause
- Center for Biologics Evaluation and Research, US Food and Drug Administration, Washington, DC, USA
| | - Thomas R Fleming
- Fred Hutchinson Cancer Centre, University of Washington, Seattle, WA, USA
| | - Ira Longini
- Department of Biostatistics, College of Public Health and Health Professions College of Medicine, University of Florida, Gainesville, FL, USA
| | | | - Richard Peto
- Nuffield Department of Population Health, University of Oxford, Oxford, UK
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8
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Jing QL, Liu MJ, Yuan J, Zhang ZB, Zhang AR, Dean NE, Luo L, Ma M, Longini I, Kenah E, Lu Y, Ma Y, Jalali N, Fang LQ, Yang ZC, Yang Y. Household Secondary Attack Rate of COVID-19 and Associated Determinants. medRxiv 2020. [PMID: 32511590 PMCID: PMC7276017 DOI: 10.1101/2020.04.11.20056010] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/04/2023]
Abstract
BACKGROUND As of April 2, 2020, the global reported number of COVID-19 cases has crossed over 1 million with more than 55,000 deaths. The household transmissibility of SARS-CoV-2, the causative pathogen, remains elusive. METHODS Based on a comprehensive contact-tracing dataset from Guangzhou, we estimated both the population-level effective reproductive number and individual-level secondary attack rate (SAR) in the household setting. We assessed age effects on transmissibility and the infectivity of COVID-19 cases during their incubation period. RESULTS A total of 195 unrelated clusters with 212 primary cases, 137 nonprimary (secondary or tertiary) cases and 1938 uninfected close contacts were traced. We estimated the household SAR to be 13.8% (95% CI: 11.1-17.0%) if household contacts are defined as all close relatives and 19.3% (95% CI: 15.5-23.9%) if household contacts only include those at the same residential address as the cases, assuming a mean incubation period of 4 days and a maximum infectious period of 13 days. The odds of infection among children (<20 years old) was only 0.26 (95% CI: 0.13-0.54) times of that among the elderly (≥60 years old). There was no gender difference in the risk of infection. COVID-19 cases were at least as infectious during their incubation period as during their illness. On average, a COVID-19 case infected 0.48 (95% CI: 0.39-0.58) close contacts. Had isolation not been implemented, this number increases to 0.62 (95% CI: 0.51-0.75). The effective reproductive number in Guangzhou dropped from above 1 to below 0.5 in about 1 week. CONCLUSION SARS-CoV-2 is more transmissible in households than SARS-CoV and MERS-CoV, and the elderly ≥60 years old are the most vulnerable to household transmission. Case finding and isolation alone may be inadequate to contain the pandemic and need to be used in conjunction with heightened restriction of human movement as implemented in Guangzhou.
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Affiliation(s)
- Qin-Long Jing
- Guangzhou Centre for Disease Control and Prevention, Guangzhou, Guangdong, P. R. China
| | - Ming-Jin Liu
- Department of Biostatistics, College of Public Health and Health Professions & Emerging Pathogens Institute, University of Florida, Gainesville, Florida, U. S. A
| | - Jun Yuan
- Guangzhou Centre for Disease Control and Prevention, Guangzhou, Guangdong, P. R. China
| | - Zhou-Bin Zhang
- Guangzhou Centre for Disease Control and Prevention, Guangzhou, Guangdong, P. R. China
| | - An-Ran Zhang
- Department of Biostatistics, College of Public Health and Health Professions & Emerging Pathogens Institute, University of Florida, Gainesville, Florida, U. S. A
- State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, P. R. China
- Department of Epidemiology, School of Public Health, Shandong University, Jinan, P. R. China
| | - Natalie E Dean
- Department of Biostatistics, College of Public Health and Health Professions & Emerging Pathogens Institute, University of Florida, Gainesville, Florida, U. S. A
| | - Lei Luo
- Guangzhou Centre for Disease Control and Prevention, Guangzhou, Guangdong, P. R. China
| | - Mengmeng Ma
- Guangzhou Centre for Disease Control and Prevention, Guangzhou, Guangdong, P. R. China
| | - Ira Longini
- Department of Biostatistics, College of Public Health and Health Professions & Emerging Pathogens Institute, University of Florida, Gainesville, Florida, U. S. A
| | - Eben Kenah
- Department of Biostatistics, School of Public Health, Ohio State University, Columbus, U. S. A
| | - Ying Lu
- Guangzhou Centre for Disease Control and Prevention, Guangzhou, Guangdong, P. R. China
| | - Yu Ma
- Guangzhou Centre for Disease Control and Prevention, Guangzhou, Guangdong, P. R. China
| | - Neda Jalali
- Department of Biostatistics, College of Public Health and Health Professions & Emerging Pathogens Institute, University of Florida, Gainesville, Florida, U. S. A
| | - Li-Qun Fang
- State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, P. R. China
| | - Zhi-Cong Yang
- Guangzhou Centre for Disease Control and Prevention, Guangzhou, Guangdong, P. R. China
| | - Yang Yang
- Department of Biostatistics, College of Public Health and Health Professions & Emerging Pathogens Institute, University of Florida, Gainesville, Florida, U. S. A
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9
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Yang Y, Lu Q, Liu M, Wang Y, Zhang A, Jalali N, Dean NE, Longini I, Halloran ME, Xu B, Zhang X, Wang L, Liu W, Fang L. Epidemiological and clinical features of the 2019 novel coronavirus outbreak in China.. [PMID: 0 DOI: 10.1101/2020.02.10.20021675] [Citation(s) in RCA: 148] [Impact Index Per Article: 37.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/24/2023]
Abstract
Our manuscript was based on surveillance cases of COVID-19 identified before January 26, 2020. As of February 20, 2020, the total number of confirmed cases in mainland China has reached 18 times of the number in our manuscript. While the methods and the main conclusions in our original analyses remain solid, we decided to withdraw this preprint for the time being, and will replace it with a more up-to-date version shortly. Should you have any comments or suggestions, please feel free to contact the corresponding author.
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10
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Wichmann O, Vannice K, Asturias EJ, de Albuquerque Luna EJ, Longini I, Lopez AL, Smith PG, Tissera H, Yoon IK, Hombach J. Live-attenuated tetravalent dengue vaccines: The needs and challenges of post-licensure evaluation of vaccine safety and effectiveness. Vaccine 2018; 35:5535-5542. [PMID: 28893477 DOI: 10.1016/j.vaccine.2017.08.066] [Citation(s) in RCA: 40] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2017] [Revised: 08/18/2017] [Accepted: 08/24/2017] [Indexed: 11/16/2022]
Abstract
Since December 2015, the first dengue vaccine has been licensed in several Asian and Latin American countries for protection against disease from all four dengue virus serotypes. While the vaccine demonstrated an overall good safety and efficacy profile in clinical trials, some key research questions remain which make risk-benefit-assessment for some populations difficult. As for any new vaccine, several questions, such as very rare adverse events following immunization, duration of vaccine-induced protection and effectiveness when used in public health programs, will be addressed by post-licensure studies and by data from national surveillance systems after the vaccine has been introduced. However, the complexity of dengue epidemiology, pathogenesis and population immunity, as well as some characteristics of the currently licensed vaccine, and potentially also future, live-attenuated dengue vaccines, poses a challenge for evaluation through existing monitoring systems, especially in low and middle-income countries. Most notable are the different efficacies of the currently licensed vaccine by dengue serostatus at time of first vaccination and by dengue virus serotype, as well as the increased risk of dengue hospitalization among young vaccinated children observed three years after the start of vaccination in one of the trials. Currently, it is unknown if the last phenomenon is restricted to younger ages or could affect also seronegative individuals aged 9years and older, who are included in the group for whom the vaccine has been licensed. In this paper, we summarize scientific and methodological considerations for public health surveillance and targeted post-licensure studies to address some key research questions related to live-attenuated dengue vaccines. Countries intending to introduce a dengue vaccine should assess their capacities to monitor and evaluate the vaccine's effectiveness and safety and, where appropriate and possible, enhance their surveillance systems accordingly. Targeted studies are needed, especially to better understand the effects of vaccinating seronegative individuals.
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Affiliation(s)
- Ole Wichmann
- World Health Organization, Department of Immunizations, Vaccines and Biologicals, Geneva, Switzerland; Robert Koch Institute, Berlin, Germany
| | - Kirsten Vannice
- World Health Organization, Department of Immunizations, Vaccines and Biologicals, Geneva, Switzerland
| | - Edwin J Asturias
- University of Colorado School of Medicine, Aurora, CO, United States; Colorado School of Public Health, Aurora, CO, United States
| | | | - Ira Longini
- University of Florida, Gainesville, FL, United States
| | - Anna Lena Lopez
- University of the Philippines Manila - National Institutes of Health, Manila, Philippines
| | - Peter G Smith
- MRC Tropical Epidemiology Group, London School of Hygiene & Tropical Medicine, London, United Kingdom
| | - Hasitha Tissera
- National Dengue Control Unit, Ministry of Health, Colombo, Sri Lanka
| | - In-Kyu Yoon
- International Vaccine Institute, Seoul, South Korea
| | - Joachim Hombach
- World Health Organization, Department of Immunizations, Vaccines and Biologicals, Geneva, Switzerland.
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11
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Wilder-Smith A, Longini I, Zuber PL, Bärnighausen T, Edmunds WJ, Dean N, Spicher VM, Benissa MR, Gessner BD. The public health value of vaccines beyond efficacy: methods, measures and outcomes. BMC Med 2017; 15:138. [PMID: 28743299 PMCID: PMC5527440 DOI: 10.1186/s12916-017-0911-8] [Citation(s) in RCA: 56] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/18/2017] [Accepted: 07/05/2017] [Indexed: 11/25/2022] Open
Abstract
BACKGROUND Assessments of vaccine efficacy and safety capture only the minimum information needed for regulatory approval, rather than the full public health value of vaccines. Vaccine efficacy provides a measure of proportionate disease reduction, is usually limited to etiologically confirmed disease, and focuses on the direct protection of the vaccinated individual. Herein, we propose a broader scope of methods, measures and outcomes to evaluate the effectiveness and public health impact to be considered for evidence-informed policymaking in both pre- and post-licensure stages. DISCUSSION Pre-licensure: Regulatory concerns dictate an individually randomised clinical trial. However, some circumstances (such as the West African Ebola epidemic) may require novel designs that could be considered valid for licensure by regulatory agencies. In addition, protocol-defined analytic plans for these studies should include clinical as well as etiologically confirmed endpoints (e.g. all cause hospitalisations, pneumonias, acute gastroenteritis and others as appropriate to the vaccine target), and should include vaccine-preventable disease incidence and 'number needed to vaccinate' as outcomes. Post-licensure: There is a central role for phase IV cluster randomised clinical trials that allows for estimation of population-level vaccine impact, including indirect, total and overall effects. Dynamic models should be prioritised over static models as the constant force of infection assumed in static models will usually underestimate the effectiveness and cost-effectiveness of the immunisation programme by underestimating indirect effects. The economic impact of vaccinations should incorporate health and non-health benefits of vaccination in both the vaccinated and unvaccinated populations, thus allowing for estimation of the net social value of vaccination. CONCLUSIONS The full benefits of vaccination reach beyond direct prevention of etiologically confirmed disease and often extend across the life course of a vaccinated person, prevent outcomes in the wider community, stabilise health systems, promote health equity, and benefit local and national economies. The degree to which vaccinations provide broad public health benefits is stronger than for other preventive and curative interventions.
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Affiliation(s)
- A Wilder-Smith
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Singapore. .,Institute of Public Health, University of Heidelberg, Heidelberg, Germany. .,London School of Hygiene and Tropical Medicine, London, UK.
| | - I Longini
- University of Florida, Gainesville, FL, USA
| | - P L Zuber
- World Health Organization, Geneva, Switzerland
| | - T Bärnighausen
- Institute of Public Health, University of Heidelberg, Heidelberg, Germany
| | - W J Edmunds
- London School of Hygiene and Tropical Medicine, London, UK
| | - N Dean
- University of Florida, Gainesville, FL, USA
| | | | - M R Benissa
- Institute of Global Health, University of Geneva, Geneva, Switzerland
| | - B D Gessner
- Agence de Médecine Preventive (AMP), Paris, France
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12
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Reiner RC, Achee N, Barrera R, Burkot TR, Chadee DD, Devine GJ, Endy T, Gubler D, Hombach J, Kleinschmidt I, Lenhart A, Lindsay SW, Longini I, Mondy M, Morrison AC, Perkins TA, Vazquez-Prokopec G, Reiter P, Ritchie SA, Smith DL, Strickman D, Scott TW. Quantifying the Epidemiological Impact of Vector Control on Dengue. PLoS Negl Trop Dis 2016; 10:e0004588. [PMID: 27227829 PMCID: PMC4881945 DOI: 10.1371/journal.pntd.0004588] [Citation(s) in RCA: 60] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [MESH Headings] [Grants] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022] Open
Affiliation(s)
- Robert C. Reiner
- Department of Epidemiology and Biostatistics, Indiana University Bloomington School of Public Health, Bloomington, Indiana, United States of America
- Fogarty International Center, National Institutes of Health, Bethesda, Maryland, United States of America
- * E-mail:
| | - Nicole Achee
- Department of Biological Sciences, Eck Institute for Global Health, University of Notre Dame, Notre Dame, Indiana, United States of America
| | - Roberto Barrera
- Centers for Disease Control and Prevention (CDC), San Juan, Puerto Rico
| | - Thomas R. Burkot
- Australian Institute of Tropical Health and Medicine, James Cook University, Cairns, Queensland, Australia
| | - Dave D. Chadee
- Department of Life Sciences, Faculty of Science and Agriculture, The University of the West Indies, St. Augustine Campus, St. Augustine, Trinidad and Tobago
| | - Gregor J. Devine
- QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - Timothy Endy
- Department of Medicine, Upstate Medical University of New York, Syracuse, New York, United States of America
| | - Duane Gubler
- Signature Research Program in Emerging Infectious Disease, Duke-NUS Medical School, Singapore
| | - Joachim Hombach
- Initiative for Vaccine Research, World Health Organization, Geneva, Switzerland
| | - Immo Kleinschmidt
- Tropical Epidemiology Group, Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, United Kingdom
- Department of Pathology, School of Health Sciences, University of Witwatersrand, Johannesburg, South Africa
| | - Audrey Lenhart
- Centers for Disease Control and Prevention, Center for Global Health/Division of Parasitic Diseases and Malaria/Entomology Branch, Atlanta, Georgia, United States of America
| | - Steven W. Lindsay
- Fogarty International Center, National Institutes of Health, Bethesda, Maryland, United States of America
- School of Biological and Biomedical Sciences, Durham University, Durham, United Kingdom
| | - Ira Longini
- Department of Biostatistics, University of Florida, Gainesville, Florida, United States of America
| | | | - Amy C. Morrison
- Department of Entomology and Nematology, University of California, Davis, California, United States of America
| | - T. Alex Perkins
- Fogarty International Center, National Institutes of Health, Bethesda, Maryland, United States of America
- Department of Biological Sciences, Eck Institute for Global Health, University of Notre Dame, Notre Dame, Indiana, United States of America
| | - Gonzalo Vazquez-Prokopec
- Department of Environmental Studies, Emory University, Atlanta, Georgia, United States of America
| | - Paul Reiter
- Department of Medical Entomology, Institut Pasteur, Paris, France
| | - Scott A. Ritchie
- College of Public Health, Medical, and Veterinary Sciences, Australian Institute of Tropical Health and Medicine, James Cook University, Cairns, Queensland, Australia
| | - David L. Smith
- Fogarty International Center, National Institutes of Health, Bethesda, Maryland, United States of America
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, Washington, United States of America
| | - Daniel Strickman
- Bill & Melinda Gates Foundation, Seattle, Washington, United States of America
| | - Thomas W. Scott
- Fogarty International Center, National Institutes of Health, Bethesda, Maryland, United States of America
- Department of Entomology and Nematology, University of California, Davis, California, United States of America
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13
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Alam MT, Weppelmann TA, Longini I, De Rochars VMB, Morris JG, Ali A. Increased isolation frequency of toxigenic Vibrio cholerae O1 from environmental monitoring sites in Haiti. PLoS One 2015; 10:e0124098. [PMID: 25853552 PMCID: PMC4390201 DOI: 10.1371/journal.pone.0124098] [Citation(s) in RCA: 31] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2014] [Accepted: 02/26/2015] [Indexed: 12/12/2022] Open
Abstract
Since the identification of the first cholera case in 2010, the disease has spread in epidemic form throughout the island nation of Haiti; as of 2014, about 700,000 cholera cases have been reported, with over 8,000 deaths. While case numbers have declined, the more fundamental question of whether the causative bacterium, Vibrio cholerae has established an environmental reservoir in the surface waters of Haiti remains to be elucidated. In a previous study conducted between April 2012 and March 2013, we reported the isolation of toxigenic V. cholerae O1 from surface waters in the Ouest Department. After a second year of surveillance (April 2013 to March 2014) using identical methodology, we observed a more than five-fold increase in the number of water samples containing culturable V. cholerae O1 compared to the previous year (1.7% vs 8.6%), with double the number of sites having at least one positive sample (58% vs 20%). Both seasonal water temperatures and precipitation were significantly related to the frequency of isolation. Our data suggest that toxigenic V. cholerae O1 are becoming more common in surface waters in Haiti; while the basis for this increase is uncertain, our findings raise concerns that environmental reservoirs are being established.
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Affiliation(s)
- Meer T. Alam
- Department of Environmental and Global Health, College of Public Health and Health Professions, University of Florida, Gainesville, Florida, United States of America
- Emerging Pathogens Institute, University of Florida, Gainesville, Florida, United States of America
| | - Thomas A. Weppelmann
- Department of Environmental and Global Health, College of Public Health and Health Professions, University of Florida, Gainesville, Florida, United States of America
- Emerging Pathogens Institute, University of Florida, Gainesville, Florida, United States of America
| | - Ira Longini
- Department of Biostatistics, Colleges of Medicine and Public Health and Health Professions, University of Florida, Gainesville, Florida, United States of America
| | - Valery Madsen Beau De Rochars
- Emerging Pathogens Institute, University of Florida, Gainesville, Florida, United States of America
- Department of Health Services Research Management and Policy, University of Florida, College of Public Health and Health Professions, Gainesville, Florida, United States of America
| | - John Glenn Morris
- Emerging Pathogens Institute, University of Florida, Gainesville, Florida, United States of America
- Department of Medicine, College of Medicine, University of Florida, Gainesville, Florida, United States of America
| | - Afsar Ali
- Department of Environmental and Global Health, College of Public Health and Health Professions, University of Florida, Gainesville, Florida, United States of America
- Emerging Pathogens Institute, University of Florida, Gainesville, Florida, United States of America
- * E-mail:
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Abstract
Background: The 2014 West African Ebola Outbreak is so far the largest and deadliest recorded in history. The affected countries, Sierra Leone, Guinea, Liberia, and Nigeria, have been struggling to contain and to mitigate the outbreak. The ongoing rise in confirmed and suspected cases, 2615 as of 20 August 2014, is considered to increase the risk of international dissemination, especially because the epidemic is now affecting cities with major commercial airports.
Method: We use the Global Epidemic and Mobility Model to generate stochastic, individual based simulations of epidemic spread worldwide, yielding, among other measures, the incidence and seeding events at a daily resolution for 3,362 subpopulations in 220 countries. The mobility model integrates daily airline passenger traffic worldwide and the disease model includes the community, hospital, and burial transmission dynamic. We use a multimodel inference approach calibrated on data from 6 July to the date of 9 August 2014. The estimates obtained were used to generate a 3-month ensemble forecast that provides quantitative estimates of the local transmission of Ebola virus disease in West Africa and the probability of international spread if the containment measures are not successful at curtailing the outbreak.
Results: We model the short-term growth rate of the disease in the affected West African countries and estimate the basic reproductive number to be in the range 1.5 − 2.0 (interval at the 1/10 relative likelihood). We simulated the international spreading of the outbreak and provide the estimate for the probability of Ebola virus disease case importation in countries across the world. Results indicate that the short-term (3 and 6 weeks) probability of international spread outside the African region is small, but not negligible. The extension of the outbreak is more likely occurring in African countries, increasing the risk of international dissemination on a longer time scale.
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Affiliation(s)
- Marcelo F C Gomes
- Laboratory for the Modeling of Biological and Socio-technical Systems, Northeastern University, Boston, Massachusetts, USA
| | - Ana Pastore Y Piontti
- Laboratory for the Modeling of Biological and Socio-technical Systems, Northeastern University, Boston, Massachusetts, USA
| | - Luca Rossi
- Institute for Scientific Interchange (ISI), Torino, Italy
| | - Dennis Chao
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, Washington, USA
| | - Ira Longini
- Department of Biostatistics, University of Florida, Gainesville, Florida, USA
| | - M Elizabeth Halloran
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center and Biostatistics, University of Washington, Seattle, Washington, USA
| | - Alessandro Vespignani
- Laboratory for the Modeling of Biological and Socio-Technical Systems, Northeastern University, Boston, Massachusetts, USA
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15
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Rashed SM, Azman AS, Alam M, Li S, Sack DA, Morris JG, Longini I, Siddique AK, Iqbal A, Huq A, Colwell RR, Sack RB, Stine OC. Genetic variation of Vibrio cholerae during outbreaks, Bangladesh, 2010-2011. Emerg Infect Dis 2014; 20:54-60. [PMID: 24377372 PMCID: PMC3884724 DOI: 10.3201/eid2001.130796] [Citation(s) in RCA: 18] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022] Open
Abstract
Most isolates are closely related, but genetic variation implies accelerated transmission of some lineages. Cholera remains a major public health problem. To compare the relative contribution of strains from the environment with strains isolated from patients during outbreaks, we performed multilocus variable tandem repeat analyses on samples collected during the 2010 and 2011 outbreak seasons in 2 geographically distinct areas of Bangladesh. A total of 222 environmental and clinical isolates of V. cholerae O1 were systematically collected from Chhatak and Mathbaria. In Chhatak, 75 of 79 isolates were from the same clonal complex, in which extensive differentiation was found in a temporally consistent pattern of successive mutations at single loci. A total of 59 isolates were collected from 6 persons; most isolates from 1 person differed by sequential single-locus mutations. In Mathbaria, 60 of 84 isolates represented 2 separate clonal complexes. The small number of genetic lineages in isolates from patients, compared with those from the environment, is consistent with accelerated transmission of some strains among humans during an outbreak.
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16
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Chao D, Halstead S, Halloran M, Longini I. A mathematical model for the control of dengue using vaccines. Int J Infect Dis 2012. [DOI: 10.1016/j.ijid.2012.05.985] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/28/2022] Open
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17
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Bhattacharya S, Black R, Bourgeois L, Clemens J, Cravioto A, Deen JL, Dougan G, Glass R, Grais RF, Greco M, Gust I, Holmgren J, Kariuki S, Lambert PH, Liu MA, Longini I, Nair GB, Norrby R, Nossal GJV, Ogra P, Sansonetti P, von Seidlein L, Songane F, Svennerholm AM, Steele D, Walker R. The Cholera Crisis in Africa. Science 2009; 324:885. [DOI: 10.1126/science.1173890] [Citation(s) in RCA: 33] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/02/2022]
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