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Wells CR, Pandey A, Moghadas SM, Fitzpatrick MC, Singer BH, Galvani AP. Evaluation of Strategies for Transitioning to Annual SARS-CoV-2 Vaccination Campaigns in the United States. Ann Intern Med 2024. [PMID: 38527289 DOI: 10.7326/m23-2451] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 03/27/2024] Open
Abstract
BACKGROUND The U.S. Food and Drug Administration has proposed administering annual SARS-CoV-2 vaccines. OBJECTIVE To evaluate the effectiveness of an annual SARS-CoV-2 vaccination campaign, quantify the health and economic benefits of a second dose provided to children younger than 2 years and adults aged 50 years or older, and optimize the timing of a second dose. DESIGN An age-structured dynamic transmission model. SETTING United States. PARTICIPANTS A synthetic population reflecting demographics and contact patterns in the United States. INTERVENTION Vaccination against SARS-CoV-2 with age-specific uptake similar to that of influenza vaccination. MEASUREMENTS Incidence, hospitalizations, deaths, and direct health care cost. RESULTS The optimal timing between the first and second dose delivered to children younger than 2 years and adults aged 50 years or older in an annual vaccination campaign was estimated to be 5 months. In direct comparison with a single-dose campaign, a second booster dose results in 123 869 fewer hospitalizations (95% uncertainty interval [UI], 121 994 to 125 742 fewer hospitalizations) and 5524 fewer deaths (95% UI, 5434 to 5613 fewer deaths), averting $3.63 billion (95% UI, $3.57 billion to $3.69 billion) in costs over a single year. LIMITATIONS Population immunity is subject to degrees of immune evasion for emerging SARS-CoV-2 variants. The model was implemented in the absence of nonpharmaceutical interventions and preexisting vaccine-acquired immunity. CONCLUSION The direct health care costs of SARS-CoV-2, particularly among adults aged 50 years or older, would be substantially reduced by administering a second dose 5 months after the initial dose. PRIMARY FUNDING SOURCE Natural Sciences and Engineering Research Council of Canada, Notsew Orm Sands Foundation, National Institutes of Health, Centers for Disease Control and Prevention, and National Science Foundation.
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Affiliation(s)
- Chad R Wells
- Center for Infectious Disease Modeling and Analysis, Yale School of Public Health, New Haven, Connecticut (C.R.W., A.P., A.P.G.)
| | - Abhishek Pandey
- Center for Infectious Disease Modeling and Analysis, Yale School of Public Health, New Haven, Connecticut (C.R.W., A.P., A.P.G.)
| | - Seyed M Moghadas
- Agent-Based Modelling Laboratory, York University, Toronto, Ontario, Canada (S.M.M.)
| | - Meagan C Fitzpatrick
- Center for Vaccine Development and Global Health, University of Maryland School of Medicine, Baltimore, Maryland (M.C.F.)
| | - Burton H Singer
- Emerging Pathogens Institute, University of Florida, Gainesville, Florida (B.H.S.)
| | - Alison P Galvani
- Center for Infectious Disease Modeling and Analysis, Yale School of Public Health, New Haven, Connecticut (C.R.W., A.P., A.P.G.)
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Mehrab Z, Stundal L, Venkatramanan S, Swarup S, Lewis B, Mortveit HS, Barrett CL, Pandey A, Wells CR, Galvani AP, Singer BH, Leblang D, Colwell RR, Marathe MV. An agent-based framework to study forced migration: A case study of Ukraine. PNAS Nexus 2024; 3:pgae080. [PMID: 38505694 PMCID: PMC10949908 DOI: 10.1093/pnasnexus/pgae080] [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] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/13/2023] [Accepted: 02/06/2024] [Indexed: 03/21/2024]
Abstract
The ongoing Russian aggression against Ukraine has forced over eight million people to migrate out of Ukraine. Understanding the dynamics of forced migration is essential for policy-making and for delivering humanitarian assistance. Existing work is hindered by a reliance on observational data which is only available well after the fact. In this work, we study the efficacy of a data-driven agent-based framework motivated by social and behavioral theory in predicting outflow of migrants as a result of conflict events during the initial phase of the Ukraine war. We discuss policy use cases for the proposed framework by demonstrating how it can leverage refugee demographic details to answer pressing policy questions. We also show how to incorporate conflict forecast scenarios to predict future conflict-induced migration flows. Detailed future migration estimates across various conflict scenarios can both help to reduce policymaker uncertainty and improve allocation and staging of limited humanitarian resources in crisis settings.
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Affiliation(s)
- Zakaria Mehrab
- Biocomplexity Institute & Initiative, University of Virginia, Charlottesville, VA 22904, USA
- Department of Computer Science, University of Virginia, Charlottesville, VA 22904, USA
| | - Logan Stundal
- Biocomplexity Institute & Initiative, University of Virginia, Charlottesville, VA 22904, USA
- Department of Political Science, University of Virginia, Charlottesville, VA 22904, USA
| | | | - Samarth Swarup
- Biocomplexity Institute & Initiative, University of Virginia, Charlottesville, VA 22904, USA
| | - Bryan Lewis
- Biocomplexity Institute & Initiative, University of Virginia, Charlottesville, VA 22904, USA
| | - Henning S Mortveit
- Biocomplexity Institute & Initiative, University of Virginia, Charlottesville, VA 22904, USA
- Department of Systems and Information Engineering, University of Virginia, Charlottesville, VA 22904, USA
| | - Christopher L Barrett
- Biocomplexity Institute & Initiative, University of Virginia, Charlottesville, VA 22904, USA
- Department of Computer Science, University of Virginia, Charlottesville, VA 22904, USA
| | - Abhishek Pandey
- Center for Infectious Disease Modeling and Analysis, Yale School of Public Health, New Haven, CT 06520, USA
| | - Chad R Wells
- Center for Infectious Disease Modeling and Analysis, Yale School of Public Health, New Haven, CT 06520, USA
| | - Alison P Galvani
- Center for Infectious Disease Modeling and Analysis, Yale School of Public Health, New Haven, CT 06520, USA
| | - Burton H Singer
- Emerging Pathogens Institute, University of Florida, Gainesville, FL 32610, USA
| | - David Leblang
- Department of Political Science, University of Virginia, Charlottesville, VA 22904, USA
| | - Rita R Colwell
- Center for Bioinformatics and Computational Biology, University of Maryland, College Park, MD 20742, USA
| | - Madhav V Marathe
- Biocomplexity Institute & Initiative, University of Virginia, Charlottesville, VA 22904, USA
- Department of Computer Science, University of Virginia, Charlottesville, VA 22904, USA
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3
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Pandey A, Wells CR, Stadnytskyi V, Moghadas SM, Marathe MV, Sah P, Crystal W, Meyers LA, Singer BH, Nesterova O, Galvani AP. Disease burden among Ukrainians forcibly displaced by the 2022 Russian invasion. Proc Natl Acad Sci U S A 2023; 120:e2215424120. [PMID: 36780515 PMCID: PMC9974407 DOI: 10.1073/pnas.2215424120] [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: 09/09/2022] [Accepted: 01/12/2023] [Indexed: 02/15/2023] Open
Abstract
The Russian invasion of Ukraine on February 24, 2022, has displaced more than a quarter of the population. Assessing disease burdens among displaced people is instrumental in informing global public health and humanitarian aid efforts. We estimated the disease burden in Ukrainians displaced both within Ukraine and to other countries by combining a spatiotemporal model of forcible displacement with age- and gender-specific estimates of cardiovascular disease (CVD), diabetes, cancer, HIV, and tuberculosis (TB) in each of Ukraine's 629 raions (i.e., districts). Among displaced Ukrainians as of May 13, we estimated that more than 2.63 million have CVDs, at least 615,000 have diabetes, and over 98,500 have cancer. In addition, more than 86,000 forcibly displaced individuals are living with HIV, and approximately 13,500 have TB. We estimated that the disease prevalence among refugees was lower than the national disease prevalence before the invasion. Accounting for internal displacement and healthcare facilities impacted by the conflict, we estimated that the number of people per hospital has increased by more than two-fold in some areas. As regional healthcare systems come under increasing strain, these estimates can inform the allocation of critical resources under shifting disease burdens.
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Affiliation(s)
- Abhishek Pandey
- Center for Infectious Disease Modeling and Analysis, Yale School of Public Health, New Haven, CT06520
| | - Chad R. Wells
- Center for Infectious Disease Modeling and Analysis, Yale School of Public Health, New Haven, CT06520
| | | | - Seyed M. Moghadas
- Agent-Based Modelling Laboratory, York University, Toronto, ON, Canada, M3J 1P3
| | - Madhav V. Marathe
- Network Systems Science and Advanced Computing Division, Biocomplexity Institute, University of Virginia, Charlottesville, VA22904
- Department of Computer Science, University of Virginia, Charlottesville, VA, 22904
| | - Pratha Sah
- Center for Infectious Disease Modeling and Analysis, Yale School of Public Health, New Haven, CT06520
| | - William Crystal
- Center for Infectious Disease Modeling and Analysis, Yale School of Public Health, New Haven, CT06520
| | | | - Burton H. Singer
- Emerging Pathogens Institute, University of Florida, Gainesville, FL32610
| | - Olena Nesterova
- Ukrainian Institute for Public Health Research, Public Health Center of the Ministry of Health of Ukraine, Kyiv, Ukraine04071
| | - Alison P. Galvani
- Center for Infectious Disease Modeling and Analysis, Yale School of Public Health, New Haven, CT06520
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4
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Vilches TN, Rafferty E, Wells CR, Galvani AP, Moghadas SM. Economic evaluation of COVID-19 rapid antigen screening programs in the workplace. BMC Med 2022; 20:452. [PMID: 36424587 PMCID: PMC9686464 DOI: 10.1186/s12916-022-02641-5] [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] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/25/2022] [Accepted: 10/26/2022] [Indexed: 11/25/2022] Open
Abstract
BACKGROUND Diagnostic testing has been pivotal in detecting SARS-CoV-2 infections and reducing transmission through the isolation of positive cases. We quantified the value of implementing frequent, rapid antigen (RA) testing in the workplace to identify screening programs that are cost-effective. METHODS To project the number of cases, hospitalizations, and deaths under alternative screening programs, we adapted an agent-based model of COVID-19 transmission and parameterized it with the demographics of Ontario, Canada, incorporating vaccination and waning of immunity. Taking into account healthcare costs and productivity losses associated with each program, we calculated the incremental cost-effectiveness ratio (ICER) with quality-adjusted life year (QALY) as the measure of effect. Considering RT-PCR testing of only severe cases as the baseline scenario, we estimated the incremental net monetary benefits (iNMB) of the screening programs with varying durations and initiation times, as well as different booster coverages of working adults. RESULTS Assuming a willingness-to-pay threshold of CDN$30,000 per QALY loss averted, twice weekly workplace screening was cost-effective only if the program started early during a surge. In most scenarios, the iNMB of RA screening without a confirmatory RT-PCR or RA test was comparable or higher than the iNMB for programs with a confirmatory test for RA-positive cases. When the program started early with a duration of at least 16 weeks and no confirmatory testing, the iNMB exceeded CDN$1.1 million per 100,000 population. Increasing booster coverage of working adults improved the iNMB of RA screening. CONCLUSIONS Our findings indicate that frequent RA testing starting very early in a surge, without a confirmatory test, is a preferred screening program for the detection of asymptomatic infections in workplaces.
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Affiliation(s)
- Thomas N Vilches
- Agent-Based Modelling Laboratory, York University, Toronto, Ontario, Canada
| | - Ellen Rafferty
- Institute of Health Economics, Edmonton, Alberta, Canada
| | - Chad R Wells
- Center for Infectious Disease Modeling and Analysis, Yale School of Public Health, New Haven, CT, USA
| | - Alison P Galvani
- Center for Infectious Disease Modeling and Analysis, Yale School of Public Health, New Haven, CT, USA
| | - Seyed M Moghadas
- Agent-Based Modelling Laboratory, York University, Toronto, Ontario, Canada.
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Wells CR, Gokcebel S, Pandey A, Galvani AP, Townsend JP. Testing for COVID-19 is Much More Effective When Performed Immediately Prior to Social Mixing. Int J Public Health 2022; 67:1604659. [PMID: 35967267 PMCID: PMC9363582 DOI: 10.3389/ijph.2022.1604659] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2021] [Accepted: 06/30/2022] [Indexed: 11/13/2022] Open
Abstract
Objective: To quantify the utility of RT-PCR and rapid antigen tests in preventing post-arrival transmission based on timing of the pre-departure test.Methods: We derived analytical expressions to compute post-arrival transmission when no test is performed, and when either an RT-PCR or any of 18 rapid antigen tests is performed at specified times before arrival. We determined the diagnostic sensitivity of the rapid antigen tests by propagating their RT-PCR percent positive agreement onto known RT-PCR diagnostic sensitivity.Results: Depending on the rapid antigen test used, conducting a rapid antigen test immediately before departure reduces post-arrival transmission between 37.4% (95% CrI: 28.2%–40.7%) and 46.7% (95% CrI:40.0%–49.3%), compared to a 31.1% (95% CrI: 26.3%–33.5%) reduction using an RT-PCR 12 h before arrival. Performance of each rapid antigen test differed by diagnostic sensitivity over the course of disease. However, these differences were smaller than those engendered by testing too early.Conclusion: Testing closer to arrival—ideally on the day of arrival—is more effective at reducing post-arrival transmission than testing earlier. Rapid antigen tests perform the best in this application due to their short turnaround time.
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Affiliation(s)
- Chad R. Wells
- Center for Infectious Disease Modeling and Analysis (CIDMA), Yale School of Public Health, New Haven, CT, United States
| | - Senay Gokcebel
- Yale School of Public Health, New Haven, CT, United States
- Grinnell College, Grinnell, IA, United States
| | - Abhishek Pandey
- Center for Infectious Disease Modeling and Analysis (CIDMA), Yale School of Public Health, New Haven, CT, United States
| | - Alison P. Galvani
- Center for Infectious Disease Modeling and Analysis (CIDMA), Yale School of Public Health, New Haven, CT, United States
| | - Jeffrey P. Townsend
- Department of Biostatistics, Yale School of Public Health, New Haven, CT, United States
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, United States
- Program in Microbiology, Yale University, New Haven, CT, United States
- *Correspondence: Jeffrey P. Townsend,
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Wells CR, Pandey A, Gokcebel S, Krieger G, Donoghue AM, Singer BH, Moghadas SM, Galvani AP, Townsend JP. Quarantine and serial testing for variants of SARS-CoV-2 with benefits of vaccination and boosting on consequent control of COVID-19. PNAS Nexus 2022; 1:pgac100. [PMID: 35909795 PMCID: PMC9335027 DOI: 10.1093/pnasnexus/pgac100] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/08/2022] [Accepted: 07/25/2022] [Indexed: 02/05/2023]
Abstract
Quarantine and serial testing strategies for a disease depend principally on its incubation period and infectiousness profile. In the context of COVID-19, these primary public health tools must be modulated with successive SARS CoV-2 variants of concern that dominate transmission. Our analysis shows that (1) vaccination status of an individual makes little difference to the determination of the appropriate quarantine duration of an infected case, whereas vaccination coverage of the population can have a substantial effect on this duration, (2) successive variants can challenge disease control efforts by their earlier and increased transmission in the disease time course relative to prior variants, and (3) sufficient vaccine boosting of a population substantially aids the suppression of local transmission through frequent serial testing. For instance, with Omicron, increasing immunity through vaccination and boosters-for instance with 100% of the population is fully immunized and at least 24% having received a third dose-can reduce quarantine durations by up to 2 d, as well as substantially aid in the repression of outbreaks through serial testing. Our analysis highlights the paramount importance of maintaining high population immunity, preferably by booster uptake, and the role of quarantine and testing to control the spread of SARS CoV-2.
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Affiliation(s)
- Chad R Wells
- Center for Infectious Disease Modeling and Analysis (CIDMA), Yale School of Public Health, New Haven, CT 06520, USA
| | - Abhishek Pandey
- Center for Infectious Disease Modeling and Analysis (CIDMA), Yale School of Public Health, New Haven, CT 06520, USA
| | - Senay Gokcebel
- Department of Biostatistics, Yale School of Public Health, New Haven, CT 06510, USA,Department of Biochemistry, Grinnell College, Grinnell, IA 50112, USA
| | - Gary Krieger
- NewFields E&E, Boulder, CO 80301, USA,Skaggs School of Pharmacy and Pharmaceutical Science, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA
| | - A Michael Donoghue
- Group HSE, BHP Group Ltd, 171 Collins Street, Melbourne, VIC 3000, Australia
| | - Burton H Singer
- Emerging Pathogens Institute, University of Florida, P.O. Box 100009, Gainesville, FL 32610, USA
| | - Seyed M Moghadas
- Agent-Based Modelling Laboratory, York University, Toronto, ON M3J 1P3, Canada
| | - Alison P Galvani
- Center for Infectious Disease Modeling and Analysis (CIDMA), Yale School of Public Health, New Haven, CT 06520, USA
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Affiliation(s)
- Chad R Wells
- Center for Infectious Disease Modeling and Analysis, Yale School of Public Health, New Haven, CT 06520, USA
| | - Alison P Galvani
- Center for Infectious Disease Modeling and Analysis, Yale School of Public Health, New Haven, CT 06520, USA.
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Wells CR, Pandey A, Fitzpatrick MC, Crystal WS, Singer BH, Moghadas SM, Galvani AP, Townsend JP. Quarantine and testing strategies to ameliorate transmission due to travel during the COVID-19 pandemic: a modelling study. Lancet Reg Health Eur 2022; 14:100304. [PMID: 35036981 PMCID: PMC8743228 DOI: 10.1016/j.lanepe.2021.100304] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 01/12/2023]
Abstract
BACKGROUND Numerous countries have imposed strict travel restrictions during the COVID-19 pandemic, contributing to a large socioeconomic burden. The long quarantines that have been applied to contacts of cases may be excessive for travel policy. METHODS We developed an approach to evaluate imminent countrywide COVID-19 infections after 0-14-day quarantine and testing. We identified the minimum travel quarantine duration such that the infection rate within the destination country did not increase compared to a travel ban, defining this minimum quarantine as "sufficient." FINDINGS We present a generalised analytical framework and a specific case study of the epidemic situation on November 21, 2021, for application to 26 European countries. For most origin-destination country pairs, a three-day or shorter quarantine with RT-PCR or antigen testing on exit suffices. Adaptation to the European Union traffic-light risk stratification provided a simplified policy tool. Our analytical approach provides guidance for travel policy during all phases of pandemic diseases. INTERPRETATION For nearly half of origin-destination country pairs analysed, travel can be permitted in the absence of quarantine and testing. For the majority of pairs requiring controls, a short quarantine with testing could be as effective as a complete travel ban. The estimated travel quarantine durations are substantially shorter than those specified for traced contacts. FUNDING EasyJet (JPT and APG), the Elihu endowment (JPT), the Burnett and Stender families' endowment (APG), the Notsew Orm Sands Foundation (JPT and APG), the National Institutes of Health (MCF), Canadian Institutes of Health Research (SMM) and Natural Sciences and Engineering Research Council of Canada EIDM-MfPH (SMM).
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Affiliation(s)
- Chad R. Wells
- Center for Infectious Disease Modeling and Analysis (CIDMA), Yale School of Public Health, New Haven, Connecticut, 06520, USA
| | - Abhishek Pandey
- Center for Infectious Disease Modeling and Analysis (CIDMA), Yale School of Public Health, New Haven, Connecticut, 06520, USA
| | - Meagan C. Fitzpatrick
- Center for Infectious Disease Modeling and Analysis (CIDMA), Yale School of Public Health, New Haven, Connecticut, 06520, USA
- Center for Vaccine Development and Global Health, University of Maryland School of Medicine, Baltimore, Maryland, 21201, USA
| | - William S. Crystal
- Center for Infectious Disease Modeling and Analysis (CIDMA), Yale School of Public Health, New Haven, Connecticut, 06520, USA
| | - Burton H. Singer
- Emerging Pathogens Institute, University of Florida, P.O. Box 100009, Gainesville, FL, 32610, USA
| | - Seyed M. Moghadas
- Agent-Based Modelling Laboratory, York University, Toronto, Ontario, Canada
| | - Alison P. Galvani
- Center for Infectious Disease Modeling and Analysis (CIDMA), Yale School of Public Health, New Haven, Connecticut, 06520, USA
- Department of Ecology and Evolutionary Biology, Yale University, New Haven, Connecticut, 06525, USA
| | - Jeffrey P. Townsend
- Department of Ecology and Evolutionary Biology, Yale University, New Haven, Connecticut, 06525, USA
- Department of Biostatistics, Yale School of Public Health, New Haven, Connecticut, 06510, USA
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, Connecticut, 06511, USA
- Program in Microbiology, Yale University, New Haven, Connecticut, 06511, USA
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Wells CR, Pandey A, Moghadas SM, Singer BH, Krieger G, Heron RJL, Turner DE, Abshire JP, Phillips KM, Michael Donoghue A, Galvani AP, Townsend JP. Comparative analyses of eighteen rapid antigen tests and RT-PCR for COVID-19 quarantine and surveillance-based isolation. Commun Med (Lond) 2022; 2:84. [PMID: 35822105 PMCID: PMC9271059 DOI: 10.1038/s43856-022-00147-y] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2021] [Accepted: 06/20/2022] [Indexed: 01/12/2023] Open
Abstract
Background Rapid antigen (RA) tests are being increasingly employed to detect SARS-CoV-2 infections in quarantine and surveillance. Prior research has focused on RT-PCR testing, a single RA test, or generic diagnostic characteristics of RA tests in assessing testing strategies. Methods We have conducted a comparative analysis of the post-quarantine transmission, the effective reproduction number during serial testing, and the false-positive rates for 18 RA tests with emergency use authorization from The United States Food and Drug Administration and an RT-PCR test. To quantify the extent of transmission, we developed an analytical mathematical framework informed by COVID-19 infectiousness, test specificity, and temporal diagnostic sensitivity data. Results We demonstrate that the relative effectiveness of RA tests and RT-PCR testing in reducing post-quarantine transmission depends on the quarantine duration and the turnaround time of testing results. For quarantines of two days or shorter, conducting a RA test on exit from quarantine reduces onward transmission more than a single RT-PCR test (with a 24-h delay) conducted upon exit. Applied to a complementary approach of performing serial testing at a specified frequency paired with isolation of positives, we have shown that RA tests outperform RT-PCR with a 24-h delay. The results from our modeling framework are consistent with quarantine and serial testing data collected from a remote industry setting. Conclusions These RA test-specific results are an important component of the tool set for policy decision-making, and demonstrate that judicious selection of an appropriate RA test can supply a viable alternative to RT-PCR in efforts to control the spread of disease.
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Affiliation(s)
- Chad R Wells
- Center for Infectious Disease Modeling and Analysis (CIDMA), Yale School of Public Health, New Haven, CT USA
| | - Abhishek Pandey
- Center for Infectious Disease Modeling and Analysis (CIDMA), Yale School of Public Health, New Haven, CT USA
| | - Seyed M Moghadas
- Agent-Based Modelling Laboratory, York University, Toronto, ON Canada
| | - Burton H Singer
- Emerging Pathogens Institute, University of Florida, Gainesville, FL USA
| | - Gary Krieger
- NewFields E&E, Boulder, CO USA.,Skaggs School of Pharmacy and Pharmaceutical Science, , University of Colorado Anschutz Medical Campus, Aurora, CO USA
| | | | | | | | | | | | - Alison P Galvani
- Center for Infectious Disease Modeling and Analysis (CIDMA), Yale School of Public Health, New Haven, CT USA
| | - Jeffrey P Townsend
- Department of Biostatistics, Yale School of Public Health, New Haven, CT USA.,Department of Ecology and Evolutionary Biology, Yale University, New Haven, CT USA.,Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT USA.,Program in Microbiology, Yale University, New Haven, CT USA
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Wells CR, Pandey A, Fitzpatrick MC, Crystal WS, Singer BH, Moghadas SM, Galvani AP, Townsend JP. Quarantine and testing strategies to ameliorate transmission due to travel during the COVID-19 pandemic: a modelling study. medRxiv 2021:2021.04.25.21256082. [PMID: 34729563 PMCID: PMC8562544 DOI: 10.1101/2021.04.25.21256082] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 01/12/2023]
Abstract
BACKGROUND Numerous countries imposed strict travel restrictions, contributing to the large socioeconomic burden during the COVID-19 pandemic. The long quarantines that apply to contacts of cases may be excessive for travel policy. METHODS We developed an approach to evaluate imminent countrywide COVID-19 infections after 0-14-day quarantine and testing. We identified the minimum travel quarantine duration such that the infection rate within the destination country did not increase compared to a travel ban, defining this minimum quarantine as "sufficient." FINDINGS We present a generalised analytical framework and a specific case study of the epidemic situation on November 21, 2021, for application to 26 European countries. For most origin-destination country pairs, a three-day or shorter quarantine with RT-PCR or antigen testing on exit suffices. Adaptation to the European Union traffic-light risk stratification provided a simplified policy tool. Our analytical approach provides guidance for travel policy during all phases of pandemic diseases. INTERPRETATION For nearly half of origin-destination country pairs analysed, travel can be permitted in the absence of quarantine and testing. For the majority of pairs requiring controls, a short quarantine with testing could be as effective as a complete travel ban. The estimated travel quarantine durations are substantially shorter than those specified for traced contacts. FUNDING EasyJet (JPT and APG), the Elihu endowment (JPT), the Burnett and Stender families' endowment (APG), the Notsew Orm Sands Foundation (JPT and APG), the National Institutes of Health (MCF), Canadian Institutes of Health Research (SMM) and Natural Sciences and Engineering Research Council of Canada EIDM-MfPH (SMM).
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Affiliation(s)
- Chad R. Wells
- Center for Infectious Disease Modeling and Analysis (CIDMA), Yale School of Public Health, New Haven, Connecticut 06520, USA
| | - Abhishek Pandey
- Center for Infectious Disease Modeling and Analysis (CIDMA), Yale School of Public Health, New Haven, Connecticut 06520, USA
| | - Meagan C. Fitzpatrick
- Center for Infectious Disease Modeling and Analysis (CIDMA), Yale School of Public Health, New Haven, Connecticut 06520, USA
- Center for Vaccine Development and Global Health, University of Maryland School of Medicine, Baltimore, Maryland, 21201, USA
| | - William S. Crystal
- Center for Infectious Disease Modeling and Analysis (CIDMA), Yale School of Public Health, New Haven, Connecticut 06520, USA
| | - Burton H. Singer
- Emerging Pathogens Institute, University of Florida, P.O. Box 100009, Gainesville, FL 32610, USA
| | | | - Alison P. Galvani
- Center for Infectious Disease Modeling and Analysis (CIDMA), Yale School of Public Health, New Haven, Connecticut 06520, USA
- Agent-Based Modelling Laboratory, York University, Toronto, Ontario, Canada
- Department of Ecology and Evolutionary Biology, Yale University, New Haven, Connecticut 06525, USA
| | - Jeffrey P. Townsend
- Department of Ecology and Evolutionary Biology, Yale University, New Haven, Connecticut 06525, USA
- Department of Biostatistics, Yale School of Public Health, New Haven, Connecticut 06510, USA
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, Connecticut 06511, USA
- Program in Microbiology, Yale University, New Haven, Connecticut 06511, USA
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Moghadas SM, Vilches TN, Zhang K, Wells CR, Shoukat A, Singer BH, Meyers LA, Neuzil KM, Langley JM, Fitzpatrick MC, Galvani AP. The Impact of Vaccination on Coronavirus Disease 2019 (COVID-19) Outbreaks in the United States. Clin Infect Dis 2021; 73:2257-2264. [PMID: 33515252 PMCID: PMC7929033 DOI: 10.1093/cid/ciab079] [Citation(s) in RCA: 251] [Impact Index Per Article: 83.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/25/2020] [Indexed: 01/08/2023] Open
Abstract
BACKGROUND Global vaccine development efforts have been accelerated in response to the devastating coronavirus disease 2019 (COVID-19) pandemic. We evaluated the impact of a 2-dose COVID-19 vaccination campaign on reducing incidence, hospitalizations, and deaths in the United States. METHODS We developed an agent-based model of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission and parameterized it with US demographics and age-specific COVID-19 outcomes. Healthcare workers and high-risk individuals were prioritized for vaccination, whereas children under 18 years of age were not vaccinated. We considered a vaccine efficacy of 95% against disease following 2 doses administered 21 days apart achieving 40% vaccine coverage of the overall population within 284 days. We varied vaccine efficacy against infection and specified 10% preexisting population immunity for the base-case scenario. The model was calibrated to an effective reproduction number of 1.2, accounting for current nonpharmaceutical interventions in the United States. RESULTS Vaccination reduced the overall attack rate to 4.6% (95% credible interval [CrI]: 4.3%-5.0%) from 9.0% (95% CrI: 8.4%-9.4%) without vaccination, over 300 days. The highest relative reduction (54%-62%) was observed among individuals aged 65 and older. Vaccination markedly reduced adverse outcomes, with non-intensive care unit (ICU) hospitalizations, ICU hospitalizations, and deaths decreasing by 63.5% (95% CrI: 60.3%-66.7%), 65.6% (95% CrI: 62.2%-68.6%), and 69.3% (95% CrI: 65.5%-73.1%), respectively, across the same period. CONCLUSIONS Our results indicate that vaccination can have a substantial impact on mitigating COVID-19 outbreaks, even with limited protection against infection. However, continued compliance with nonpharmaceutical interventions is essential to achieve this impact.
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Affiliation(s)
- Seyed M Moghadas
- Agent-Based Modelling Laboratory, York University, Toronto, Ontario, Canada
| | - Thomas N Vilches
- Institute of Mathematics, Statistics and Scientific Computing, University of Campinas, Campinas SP, Brazil
| | - Kevin Zhang
- Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
| | - Chad R Wells
- Center for Infectious Disease Modeling and Analysis (CIDMA), Yale School of Public Health, New Haven, Connecticut, USA
| | - Affan Shoukat
- Center for Infectious Disease Modeling and Analysis (CIDMA), Yale School of Public Health, New Haven, Connecticut, USA
| | - Burton H Singer
- Emerging Pathogens Institute, University of Florida, Gainesville, Florida, USA
| | - Lauren Ancel Meyers
- Department of Integrative Biology, The University of Texas at Austin, Austin, Texas, USA
| | - Kathleen M Neuzil
- Center for Vaccine Development and Global Health, University of Maryland School of Medicine, Baltimore, Maryland, USA
| | - Joanne M Langley
- Canadian Center for Vaccinology, Dalhousie University, IWK Health Centre and Nova Scotia Health Authority, Halifax, Nova Scotia, Canada
| | - Meagan C Fitzpatrick
- Center for Vaccine Development and Global Health, University of Maryland School of Medicine, Baltimore, Maryland, USA
| | - Alison P Galvani
- Center for Infectious Disease Modeling and Analysis (CIDMA), Yale School of Public Health, New Haven, Connecticut, USA
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12
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Affiliation(s)
- Chad R Wells
- Center for Infectious Disease Modeling and Analysis, Yale School of Public Health, New Haven, CT 06520, USA
| | - Alison P Galvani
- Center for Infectious Disease Modeling and Analysis, Yale School of Public Health, New Haven, CT 06520, USA.
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13
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Parpia AS, Martinez I, El-Sayed AM, Wells CR, Myers L, Duncan J, Collins J, Fitzpatrick MC, Galvani AP, Pandey A. Racial disparities in COVID-19 mortality across Michigan, United States. EClinicalMedicine 2021; 33:100761. [PMID: 33718849 PMCID: PMC7933264 DOI: 10.1016/j.eclinm.2021.100761] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/02/2020] [Revised: 02/03/2021] [Accepted: 02/03/2021] [Indexed: 12/22/2022] Open
Abstract
BACKGROUND Black populations in the United States are being disproportionately affected by the COVID-19 pandemic, but the increased mortality burden after accounting for health and other demographic characteristics is not well understood. We examined characteristics of individuals who died from COVID-19 in Michigan by race stratified by their age, sex and comorbidity prevalence to illustrate and understand this disparity in mortality risk. METHODS We evaluate COVID-19 mortality in Michigan by demographic and health characteristics, using individual-level linked death certificate and surveillance data collected by the Michigan Department of Health and Human Services from March 16 to October 26, 2020. We identified differences in demographics and comorbidity prevalence across race among individuals who died from COVID-19 and calculated mortality rates by age, sex, race, and number of comorbidities. FINDINGS Among the 6,065 COVID-19 related deaths in Michigan, Black individuals are experiencing 3·6 times the mortality rate of White individuals (p<0.001), with a mortality rate for Black individuals under 65 years without comorbidities that is 12·6 times that of their White counterparts (p<0.001). After accounting for age, race, sex, and number of comorbidities, we find that Black individuals in all strata are at higher risk of COVID-19 mortality than their White counterparts. INTERPRETATION Our findings demonstrate that Black populations are disproportionately burdened by COVID-19 mortality, even after accounting for demographic and underlying health characteristics. We highlight how disparities across race, which result from systemic racism, are compounded in crises. FUNDING ASP, AP and APG were funded by NSF Expeditions grant 1918784, NIH grant 1R01AI151176-01, NSF Rapid Response Research for COVID-19 grant RAPID-2027755, and the Notsew Orm Sands Foundation. MCF was supported by NIH grant K01AI141576.
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Affiliation(s)
- Alyssa S. Parpia
- Center for Infectious Disease Modeling and Analysis (CIDMA), Yale School of Public Health, New Haven, CT, United States
| | - Isabel Martinez
- Center for Infectious Disease Modeling and Analysis (CIDMA), Yale School of Public Health, New Haven, CT, United States
| | - Abdulrahman M. El-Sayed
- Department of Internal Medicine, University of Michigan Medical School, Ann Arbor, MI, United States
- Department of Public Health, Wayne State University, Detroit, MI, United States
| | - Chad R. Wells
- Center for Infectious Disease Modeling and Analysis (CIDMA), Yale School of Public Health, New Haven, CT, United States
| | - Lindsey Myers
- Division for Vital Records and Health Statistics, Michigan Department of Health and Human Services, Detroit, MI, United States
| | - Jeffrey Duncan
- Division for Vital Records and Health Statistics, Michigan Department of Health and Human Services, Detroit, MI, United States
| | - Jim Collins
- Division of Communicable Diseases, Michigan Department of Health and Human Services, Detroit, MI, United States
| | - Meagan C. Fitzpatrick
- Center for Infectious Disease Modeling and Analysis (CIDMA), Yale School of Public Health, New Haven, CT, United States
- University of Maryland School of Medicine, Baltimore, MD, United States
| | - Alison P. Galvani
- Center for Infectious Disease Modeling and Analysis (CIDMA), Yale School of Public Health, New Haven, CT, United States
| | - Abhishek Pandey
- Center for Infectious Disease Modeling and Analysis (CIDMA), Yale School of Public Health, New Haven, CT, United States
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14
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Wells CR, Townsend JP, Pandey A, Moghadas SM, Krieger G, Singer B, McDonald RH, Fitzpatrick MC, Galvani AP. Optimal COVID-19 quarantine and testing strategies. Nat Commun 2021; 12:356. [PMID: 33414470 PMCID: PMC7788536 DOI: 10.1038/s41467-020-20742-8] [Citation(s) in RCA: 110] [Impact Index Per Article: 36.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2020] [Accepted: 12/17/2020] [Indexed: 12/23/2022] Open
Abstract
For COVID-19, it is vital to understand if quarantines shorter than 14 days can be equally effective with judiciously deployed testing. Here, we develop a mathematical model that quantifies the probability of post-quarantine transmission incorporating testing into travel quarantine, quarantine of traced contacts with an unknown time of infection, and quarantine of cases with a known time of exposure. We find that testing on exit (or entry and exit) can reduce the duration of a 14-day quarantine by 50%, while testing on entry shortens quarantine by at most one day. In a real-world test of our theory applied to offshore oil rig employees, 47 positives were obtained with testing on entry and exit to quarantine, of which 16 had tested negative at entry; preventing an expected nine offshore transmission events that each could have led to outbreaks. We show that appropriately timed testing can make shorter quarantines effective.
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Affiliation(s)
- Chad R Wells
- Center for Infectious Disease Modeling and Analysis (CIDMA), Yale School of Public Health, New Haven, CT, 06520, USA
| | - Jeffrey P Townsend
- Department of Biostatistics, Yale School of Public Health, New Haven, CT, 06510, USA.
- Department of Ecology and Evolutionary Biology, Yale University, New Haven, CT, 06525, USA.
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, 06511, USA.
- Program in Microbiology, Yale University, New Haven, CT, 06511, USA.
| | - Abhishek Pandey
- Center for Infectious Disease Modeling and Analysis (CIDMA), Yale School of Public Health, New Haven, CT, 06520, USA
| | - Seyed M Moghadas
- Agent-Based Modelling Laboratory, York University, Toronto, ON, M3J 1P3, Canada
| | - Gary Krieger
- NewFields E&E, Boulder, CO, 80301, USA
- Skaggs School of Pharmacy and Pharmaceutical Science, University of Colorado Anschutz Medical Campus, Aurora, CO, 80045, USA
| | - Burton Singer
- Emerging Pathogens Institute, University of Florida, P.O. Box 100009, Gainesville, FL, 32610, USA
| | - Robert H McDonald
- Group Health, Safety and Environment; BHP, Melbourne, VIC, 3000, Australia
| | - Meagan C Fitzpatrick
- Center for Infectious Disease Modeling and Analysis (CIDMA), Yale School of Public Health, New Haven, CT, 06520, USA
- Center for Vaccine Development and Global Health, University of Maryland School of Medicine, Baltimore, MA, 21201, US
| | - Alison P Galvani
- Center for Infectious Disease Modeling and Analysis (CIDMA), Yale School of Public Health, New Haven, CT, 06520, USA
- Department of Ecology and Evolutionary Biology, Yale University, New Haven, CT, 06525, USA
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15
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Affiliation(s)
- Meagan C Fitzpatrick
- Center for Vaccine Development and Global Health, University of Maryland School of Medicine, University of Maryland, Baltimore, MD, USA; Center for Infectious Disease Modeling and Analysis, Yale School of Public Health, Yale University, New Haven, CT 06520, USA
| | - Abhishek Pandey
- Center for Infectious Disease Modeling and Analysis, Yale School of Public Health, Yale University, New Haven, CT 06520, USA
| | - Chad R Wells
- Center for Infectious Disease Modeling and Analysis, Yale School of Public Health, Yale University, New Haven, CT 06520, USA
| | - Pratha Sah
- Center for Infectious Disease Modeling and Analysis, Yale School of Public Health, Yale University, New Haven, CT 06520, USA
| | - Alison P Galvani
- Center for Infectious Disease Modeling and Analysis, Yale School of Public Health, Yale University, New Haven, CT 06520, USA.
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16
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Moghadas SM, Vilches TN, Zhang K, Wells CR, Shoukat A, Singer BH, Meyers LA, Neuzil KM, Langley JM, Fitzpatrick MC, Galvani AP. The impact of vaccination on COVID-19 outbreaks in the United States. medRxiv 2021:2020.11.27.20240051. [PMID: 33269359 PMCID: PMC7709178 DOI: 10.1101/2020.11.27.20240051] [Citation(s) in RCA: 46] [Impact Index Per Article: 15.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
Abstract
BACKGROUND Global vaccine development efforts have been accelerated in response to the devastating COVID-19 pandemic. We evaluated the impact of a 2-dose COVID-19 vaccination campaign on reducing incidence, hospitalizations, and deaths in the United States (US). METHODS We developed an agent-based model of SARS-CoV-2 transmission and parameterized it with US demographics and age-specific COVID-19 outcomes. Healthcare workers and high-risk individuals were prioritized for vaccination, while children under 18 years of age were not vaccinated. We considered a vaccine efficacy of 95% against disease following 2 doses administered 21 days apart achieving 40% vaccine coverage of the overall population within 284 days. We varied vaccine efficacy against infection, and specified 10% pre-existing population immunity for the base-case scenario. The model was calibrated to an effective reproduction number of 1.2, accounting for current non-pharmaceutical interventions in the US. RESULTS Vaccination reduced the overall attack rate to 4.6% (95% CrI: 4.3% - 5.0%) from 9.0% (95% CrI: 8.4% - 9.4%) without vaccination, over 300 days. The highest relative reduction (54-62%) was observed among individuals aged 65 and older. Vaccination markedly reduced adverse outcomes, with non-ICU hospitalizations, ICU hospitalizations, and deaths decreasing by 63.5% (95% CrI: 60.3% - 66.7%), 65.6% (95% CrI: 62.2% - 68.6%), and 69.3% (95% CrI: 65.5% - 73.1%), respectively, across the same period. CONCLUSIONS Our results indicate that vaccination can have a substantial impact on mitigating COVID-19 outbreaks, even with limited protection against infection. However, continued compliance with non-pharmaceutical interventions is essential to achieve this impact.
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Affiliation(s)
- Seyed M. Moghadas
- Agent-Based Modelling Laboratory, York University, Toronto, Ontario, M3J 1P3 Canada
| | - Thomas N. Vilches
- Institute of Mathematics, Statistics and Scientific Computing, University of Campinas, Campinas SP, Brazil
| | - Kevin Zhang
- Faculty of Medicine, University of Toronto, Toronto, Ontario, M5S 1A8 Canada
| | - Chad R. Wells
- Center for Infectious Disease Modeling and Analysis (CIDMA), Yale School of Public Health, New Haven, Connecticut, USA
| | - Affan Shoukat
- Center for Infectious Disease Modeling and Analysis (CIDMA), Yale School of Public Health, New Haven, Connecticut, USA
| | - Burton H. Singer
- Emerging Pathogens Institute, University of Florida, Gainesville, FL 32610, USA
| | - Lauren Ancel Meyers
- Department of Integrative Biology, The University of Texas at Austin, Austin, TX 78712 USA
| | - Kathleen M. Neuzil
- Center for Vaccine Development and Global Health, University of Maryland School of Medicine, 685 W Baltimore St, Baltimore, MD 21201 USA
| | - Joanne M. Langley
- Canadian Center for Vaccinology, Dalhousie University, IWK Health Centre and Nova Scotia Health Authority, Halifax, Nova Scotia, B3K 6R8 Canada
| | - Meagan C. Fitzpatrick
- Center for Vaccine Development and Global Health, University of Maryland School of Medicine, 685 W Baltimore St, Baltimore, MD 21201 USA
| | - Alison P. Galvani
- Center for Infectious Disease Modeling and Analysis (CIDMA), Yale School of Public Health, New Haven, Connecticut, USA
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Wells CR, Townsend JP, Pandey A, Moghadas SM, Krieger G, Singer B, McDonald RH, Fitzpatrick MC, Galvani AP. Optimal COVID-19 quarantine and testing strategies. medRxiv 2020:2020.10.27.20211631. [PMID: 33173923 PMCID: PMC7654919 DOI: 10.1101/2020.10.27.20211631] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/23/2022]
Abstract
As economic woes of the COVID-19 pandemic deepen, strategies are being formulated to avoid the need for prolonged stay-at-home orders, while implementing risk-based quarantine, testing, contact tracing and surveillance protocols. Given limited resources and the significant economic, public health, and operational challenges of the current 14-day quarantine recommendation, it is vital to understand if shorter but equally effective quarantine and testing strategies can be deployed. To quantify the probability of post-quarantine transmission upon isolation of a positive test, we developed a mathematical model in which we varied quarantine duration and the timing of molecular tests for three scenarios of entry into quarantine. Specifically, we consider travel quarantine, quarantine of traced contacts with an unknown time if infection, and quarantine of cases with a known time of exposure. With a one-day delay between test and result, we found that testing on exit (or entry and exit) can reduce the duration of a 14-day quarantine by 50%, while testing on entry shortened quarantine by at most one day. Testing on exit more effectively reduces post-quarantine transmission than testing upon entry. Furthermore, we identified the optimal testing date within quarantines of varying duration, finding that testing on exit was most effective for quarantines lasting up to seven days. As a real-world validation of these principles, we analyzed the results of 4,040 SARS CoV-2 RT-PCR tests administered to offshore oil rig employees. Among the 47 positives obtained with a testing on entry and exit strategy, 16 cases that previously tested negative at entry were identified, with no further cases detected among employees following quarantine exit. Moreover, this strategy successfully prevented an expected nine offshore transmission events stemming from cases who had tested negative on the entry test, each one a serious concern for initiating rapid spread and a disabling outbreak in the close quarters of an offshore rig. This successful outcome highlights that appropriately timed testing can make shorter quarantines more effective, thereby minimizing economic impacts, disruptions to operational integrity, and COVID-related public health risks.
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Affiliation(s)
- Chad R. Wells
- Center for Infectious Disease Modeling and Analysis (CIDMA), Yale School of Public Health, New Haven, CT 06520, USA
| | - Jeffrey P. Townsend
- Department of Biostatistics, Yale School of Public Health, New Haven, Connecticut 06510, USA
- Department of Ecology and Evolutionary Biology, Yale University, New Haven, Connecticut 06525, USA
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, Connecticut 06511, USA
- Program in Microbiology, Yale University, New Haven, Connecticut 06511, USA
| | - Abhishek Pandey
- Center for Infectious Disease Modeling and Analysis (CIDMA), Yale School of Public Health, New Haven, CT 06520, USA
| | - Seyed M. Moghadas
- Agent-Based Modelling Laboratory, York University, Toronto, Ontario, M3J 1P3 Canada
| | - Gary Krieger
- NewFields E&E Boulder, CO USA 80301 and Skaggs School of Pharmacy and Pharmaceutical Science, University of Colorado Anschutz Medical Campus
| | - Burton Singer
- Emerging Pathogens Institute, University of Florida, P.O. Box 100009, Gainesville, FL 32610, USA
| | - Robert H. McDonald
- Group Health, Safety and Environment; BHP; Melbourne, Victoria, Australia, 3000
| | - Meagan C. Fitzpatrick
- Center for Infectious Disease Modeling and Analysis (CIDMA), Yale School of Public Health, New Haven, CT 06520, USA
- Center for Vaccine Development and Global Health, University of Maryland School of Medicine, Baltimore, MD, 21201, USA
| | - Alison P. Galvani
- Center for Infectious Disease Modeling and Analysis (CIDMA), Yale School of Public Health, New Haven, CT 06520, USA
- Department of Ecology and Evolutionary Biology, Yale University, New Haven, Connecticut 06525, USA
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18
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Shoukat A, Wells CR, Langley JM, Singer BH, Galvani AP, Moghadas SM. Projection de la demande de lits de soins intensifs durant l’épidémie de COVID-19 au Canada. CMAJ 2020; 192:E1315-E1322. [PMID: 33106307 DOI: 10.1503/cmaj.200457-f] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 04/02/2020] [Indexed: 01/09/2023] Open
Affiliation(s)
- Affan Shoukat
- Center for Infectious Disease Modeling and Analysis (A. Shoukat, C. Wells, A. Galvani), École de santé publique de Yale, New Haven (Connecticut); Centre canadien de vaccinologie (J. Langley), Université Dalhousie, Centre de soins de santé IWK et Régie de la santé de la Nouvelle-Écosse (J. Langley), Halifax (Nouvelle-Écosse); Emerging Pathogens Institute (B. Singer), Université de Floride, Gainesville (Floride); Agent-Based Modelling Laboratory (S. Moghadas), Université York, Toronto (Ontario)
| | - Chad R Wells
- Center for Infectious Disease Modeling and Analysis (A. Shoukat, C. Wells, A. Galvani), École de santé publique de Yale, New Haven (Connecticut); Centre canadien de vaccinologie (J. Langley), Université Dalhousie, Centre de soins de santé IWK et Régie de la santé de la Nouvelle-Écosse (J. Langley), Halifax (Nouvelle-Écosse); Emerging Pathogens Institute (B. Singer), Université de Floride, Gainesville (Floride); Agent-Based Modelling Laboratory (S. Moghadas), Université York, Toronto (Ontario)
| | - Joanne M Langley
- Center for Infectious Disease Modeling and Analysis (A. Shoukat, C. Wells, A. Galvani), École de santé publique de Yale, New Haven (Connecticut); Centre canadien de vaccinologie (J. Langley), Université Dalhousie, Centre de soins de santé IWK et Régie de la santé de la Nouvelle-Écosse (J. Langley), Halifax (Nouvelle-Écosse); Emerging Pathogens Institute (B. Singer), Université de Floride, Gainesville (Floride); Agent-Based Modelling Laboratory (S. Moghadas), Université York, Toronto (Ontario)
| | - Burton H Singer
- Center for Infectious Disease Modeling and Analysis (A. Shoukat, C. Wells, A. Galvani), École de santé publique de Yale, New Haven (Connecticut); Centre canadien de vaccinologie (J. Langley), Université Dalhousie, Centre de soins de santé IWK et Régie de la santé de la Nouvelle-Écosse (J. Langley), Halifax (Nouvelle-Écosse); Emerging Pathogens Institute (B. Singer), Université de Floride, Gainesville (Floride); Agent-Based Modelling Laboratory (S. Moghadas), Université York, Toronto (Ontario)
| | - Alison P Galvani
- Center for Infectious Disease Modeling and Analysis (A. Shoukat, C. Wells, A. Galvani), École de santé publique de Yale, New Haven (Connecticut); Centre canadien de vaccinologie (J. Langley), Université Dalhousie, Centre de soins de santé IWK et Régie de la santé de la Nouvelle-Écosse (J. Langley), Halifax (Nouvelle-Écosse); Emerging Pathogens Institute (B. Singer), Université de Floride, Gainesville (Floride); Agent-Based Modelling Laboratory (S. Moghadas), Université York, Toronto (Ontario)
| | - Seyed M Moghadas
- Center for Infectious Disease Modeling and Analysis (A. Shoukat, C. Wells, A. Galvani), École de santé publique de Yale, New Haven (Connecticut); Centre canadien de vaccinologie (J. Langley), Université Dalhousie, Centre de soins de santé IWK et Régie de la santé de la Nouvelle-Écosse (J. Langley), Halifax (Nouvelle-Écosse); Emerging Pathogens Institute (B. Singer), Université de Floride, Gainesville (Floride); Agent-Based Modelling Laboratory (S. Moghadas), Université York, Toronto (Ontario)
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Abstract
Regions with insufficient vaccination have hindered worldwide poliomyelitis eradication, as they are vulnerable to sporadic outbreaks through reintroduction of the disease. Despite Israel's having been declared polio-free in 1988, a routine sewage surveillance program detected polio in 2013. To curtail transmission, the Israel Ministry of Health launched a vaccine campaign to vaccinate children-who had only received the inactivated polio vaccine-with the oral polio vaccine (OPV). Determining the degree of prosocial motivation in vaccination behavior is challenging because vaccination typically provides direct benefits to the individual as well as indirect benefits to the community by curtailing transmission. However, the Israel OPV campaign provides a unique and excellent opportunity to quantify and model prosocial vaccination as its primary objective was to avert transmission. Using primary survey data and a game-theoretical model, we examine and quantify prosocial behavior during the OPV campaign. We found that the observed vaccination behavior in the Israeli OPV campaign is attributable to prosocial behavior and heterogeneous perceived risk of paralysis based on the individual's comprehension of the prosocial nature of the campaign. We also found that the benefit of increasing comprehension of the prosocial nature of the campaign would be limited if even 24% of the population acts primarily from self-interest, as greater vaccination coverage provides no personal utility to them. Our results suggest that to improve coverage, communication efforts should also focus on alleviating perceived fears surrounding the vaccine.
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Affiliation(s)
- Chad R Wells
- Center for Infectious Disease Modeling and Analysis, Yale School of Public Health, New Haven, CT 06520
| | - Amit Huppert
- The Biostatistics & Biomathematics Unit, The Gertner Institute for Epidemiology and Health Policy Research, Sheba Medical Center, Tel Hashomer, 52621 Ramat Gan, Israel
- School of Public Health, The Sackler Faculty of Medicine, Tel-Aviv University, 69978 Tel Aviv, Israel
| | - Meagan C Fitzpatrick
- Center for Infectious Disease Modeling and Analysis, Yale School of Public Health, New Haven, CT 06520
- Center for Vaccine Development and Global Health, University of Maryland School of Medicine, Baltimore, MD 21201
| | - Abhishek Pandey
- Center for Infectious Disease Modeling and Analysis, Yale School of Public Health, New Haven, CT 06520
| | - Baruch Velan
- The Biostatistics & Biomathematics Unit, The Gertner Institute for Epidemiology and Health Policy Research, Sheba Medical Center, Tel Hashomer, 52621 Ramat Gan, Israel
| | - Burton H Singer
- Emerging Pathogens Institute, University of Florida, Gainesville, FL 32610;
| | - Chris T Bauch
- Department of Applied Mathematics, University of Waterloo, Waterloo, ON N2L 3G1, Canada
| | - Alison P Galvani
- Center for Infectious Disease Modeling and Analysis, Yale School of Public Health, New Haven, CT 06520
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20
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Affiliation(s)
- Chad R Wells
- Center for Infectious Disease Modeling and Analysis, Yale School of Public Health, Yale University, New Haven, CT, USA
| | - Jason K Stearns
- School for International Studies, Simon Fraser University, Vancouver, BC, Canada; Congo Research Group, Center on International Cooperation, New York University, New York, NY, USA
| | - Pascal Lutumba
- Department of Tropical Medicine, University of Kinshasa, Kinshasa, DR Congo
| | - Alison P Galvani
- Center for Infectious Disease Modeling and Analysis, Yale School of Public Health, Yale University, New Haven, CT, USA.
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21
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Wells CR, Fitzpatrick MC, Sah P, Shoukat A, Pandey A, El-Sayed AM, Singer BH, Moghadas SM, Galvani AP. Projecting the demand for ventilators at the peak of the COVID-19 outbreak in the USA. Lancet Infect Dis 2020; 20:1123-1125. [PMID: 32325039 PMCID: PMC7172723 DOI: 10.1016/s1473-3099(20)30315-7] [Citation(s) in RCA: 35] [Impact Index Per Article: 8.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Affiliation(s)
- Chad R Wells
- Center for Infectious Disease Modeling and Analysis, Yale School of Public Health, New Haven, CT 6510, USA
| | - Meagan C Fitzpatrick
- Center for Infectious Disease Modeling and Analysis, Yale School of Public Health, New Haven, CT 6510, USA; Center for Vaccine Development and Global Health, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Pratha Sah
- Center for Infectious Disease Modeling and Analysis, Yale School of Public Health, New Haven, CT 6510, USA
| | - Affan Shoukat
- Center for Infectious Disease Modeling and Analysis, Yale School of Public Health, New Haven, CT 6510, USA
| | - Abhishek Pandey
- Center for Infectious Disease Modeling and Analysis, Yale School of Public Health, New Haven, CT 6510, USA
| | - Abdulrahman M El-Sayed
- Department of Internal Medicine, University of Michigan Medical School, Ann Arbor, MI, USA; Department of Public Health, Wayne State University, Detroit, MI, USA
| | - Burton H Singer
- Emerging Pathogens Institute, University of Florida, Gainesville, FL, USA
| | - Seyed M Moghadas
- Agent-Based Modelling Laboratory, York University, Toronto, ON, Canada
| | - Alison P Galvani
- Center for Infectious Disease Modeling and Analysis, Yale School of Public Health, New Haven, CT 6510, USA.
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Moghadas SM, Shoukat A, Fitzpatrick MC, Wells CR, Sah P, Pandey A, Sachs JD, Wang Z, Meyers LA, Singer BH, Galvani AP. Projecting hospital utilization during the COVID-19 outbreaks in the United States. Proc Natl Acad Sci U S A 2020; 117:9122-9126. [PMID: 32245814 PMCID: PMC7183199 DOI: 10.1073/pnas.2004064117] [Citation(s) in RCA: 304] [Impact Index Per Article: 76.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022] Open
Abstract
In the wake of community coronavirus disease 2019 (COVID-19) transmission in the United States, there is a growing public health concern regarding the adequacy of resources to treat infected cases. Hospital beds, intensive care units (ICUs), and ventilators are vital for the treatment of patients with severe illness. To project the timing of the outbreak peak and the number of ICU beds required at peak, we simulated a COVID-19 outbreak parameterized with the US population demographics. In scenario analyses, we varied the delay from symptom onset to self-isolation, the proportion of symptomatic individuals practicing self-isolation, and the basic reproduction number R0 Without self-isolation, when R0 = 2.5, treatment of critically ill individuals at the outbreak peak would require 3.8 times more ICU beds than exist in the United States. Self-isolation by 20% of cases 24 h after symptom onset would delay and flatten the outbreak trajectory, reducing the number of ICU beds needed at the peak by 48.4% (interquartile range 46.4-50.3%), although still exceeding existing capacity. When R0 = 2, twice as many ICU beds would be required at the peak of outbreak in the absence of self-isolation. In this scenario, the proportional impact of self-isolation within 24 h on reducing the peak number of ICU beds is substantially higher at 73.5% (interquartile range 71.4-75.3%). Our estimates underscore the inadequacy of critical care capacity to handle the burgeoning outbreak. Policies that encourage self-isolation, such as paid sick leave, may delay the epidemic peak, giving a window of time that could facilitate emergency mobilization to expand hospital capacity.
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Affiliation(s)
- Seyed M Moghadas
- Agent-Based Modelling Laboratory, York University, Toronto, ON M3J 1P3, Canada
| | - Affan Shoukat
- Center for Infectious Disease Modeling and Analysis, Yale School of Public Health, New Haven, CT 06510
| | - Meagan C Fitzpatrick
- Center for Vaccine Development and Global Health, University of Maryland School of Medicine, Baltimore, MD 21201
| | - Chad R Wells
- Center for Infectious Disease Modeling and Analysis, Yale School of Public Health, New Haven, CT 06510
| | - Pratha Sah
- Center for Infectious Disease Modeling and Analysis, Yale School of Public Health, New Haven, CT 06510
| | - Abhishek Pandey
- Center for Infectious Disease Modeling and Analysis, Yale School of Public Health, New Haven, CT 06510
| | - Jeffrey D Sachs
- Center for Sustainable Development at Columbia University, Columbia University, New York, NY 10032
| | - Zheng Wang
- Department of Biostatistics, Yale School of Public Health, New Haven, CT 06510
| | - Lauren A Meyers
- Department of Integrative Biology, The University of Texas at Austin, Austin, TX 78712
| | - Burton H Singer
- Emerging Pathogens Institute, University of Florida, Gainesville, FL 32610
| | - Alison P Galvani
- Center for Infectious Disease Modeling and Analysis, Yale School of Public Health, New Haven, CT 06510
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Shoukat A, Wells CR, Langley JM, Singer BH, Galvani AP, Moghadas SM. Projecting demand for critical care beds during COVID-19 outbreaks in Canada. CMAJ 2020; 192:E489-E496. [PMID: 32269020 DOI: 10.1503/cmaj.200457] [Citation(s) in RCA: 98] [Impact Index Per Article: 24.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 04/02/2020] [Indexed: 12/21/2022] Open
Abstract
BACKGROUND Increasing numbers of coronavirus disease 2019 (COVID-19) cases in Canada may create substantial demand for hospital admission and critical care. We evaluated the extent to which self-isolation of mildly ill people delays the peak of outbreaks and reduces the need for this care in each Canadian province. METHODS We developed a computational model and simulated scenarios for COVID-19 outbreaks within each province. Using estimates of COVID-19 characteristics, we projected the hospital and intensive care unit (ICU) bed requirements without self-isolation, assuming an average number of 2.5 secondary cases, and compared scenarios in which different proportions of mildly ill people practised self-isolation 24 hours after symptom onset. RESULTS Without self-isolation, the peak of outbreaks would occur in the first half of June, and an average of 569 ICU bed days per 10 000 population would be needed. When 20% of cases practised self-isolation, the peak was delayed by 2-4 weeks, and ICU bed requirement was reduced by 23.5% compared with no self-isolation. Increasing self-isolation to 40% reduced ICU use by 53.6% and delayed the peak of infection by an additional 2-4 weeks. Assuming current ICU bed occupancy rates above 80% and self-isolation of 40%, demand would still exceed available (unoccupied) ICU bed capacity. INTERPRETATION At the peak of COVID-19 outbreaks, the need for ICU beds will exceed the total number of ICU beds even with self-isolation at 40%. Our results show the coming challenge for the health care system in Canada and the potential role of self-isolation in reducing demand for hospital-based and ICU care.
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Affiliation(s)
- Affan Shoukat
- Center for Infectious Disease Modeling and Analysis (Shoukat, Wells, Galvani), Yale School of Public Health, New Haven, Conn.; Canadian Center for Vaccinology (Langley), Dalhousie University, IWK Health Centre and Nova Scotia Health Authority (Langley), Halifax, NS; Emerging Pathogens Institute (Singer), University of Florida, Gainesville, Fla.; Agent-Based Modelling Laboratory (Moghadas), York University, Toronto, Ont
| | - Chad R Wells
- Center for Infectious Disease Modeling and Analysis (Shoukat, Wells, Galvani), Yale School of Public Health, New Haven, Conn.; Canadian Center for Vaccinology (Langley), Dalhousie University, IWK Health Centre and Nova Scotia Health Authority (Langley), Halifax, NS; Emerging Pathogens Institute (Singer), University of Florida, Gainesville, Fla.; Agent-Based Modelling Laboratory (Moghadas), York University, Toronto, Ont
| | - Joanne M Langley
- Center for Infectious Disease Modeling and Analysis (Shoukat, Wells, Galvani), Yale School of Public Health, New Haven, Conn.; Canadian Center for Vaccinology (Langley), Dalhousie University, IWK Health Centre and Nova Scotia Health Authority (Langley), Halifax, NS; Emerging Pathogens Institute (Singer), University of Florida, Gainesville, Fla.; Agent-Based Modelling Laboratory (Moghadas), York University, Toronto, Ont.
| | - Burton H Singer
- Center for Infectious Disease Modeling and Analysis (Shoukat, Wells, Galvani), Yale School of Public Health, New Haven, Conn.; Canadian Center for Vaccinology (Langley), Dalhousie University, IWK Health Centre and Nova Scotia Health Authority (Langley), Halifax, NS; Emerging Pathogens Institute (Singer), University of Florida, Gainesville, Fla.; Agent-Based Modelling Laboratory (Moghadas), York University, Toronto, Ont
| | - Alison P Galvani
- Center for Infectious Disease Modeling and Analysis (Shoukat, Wells, Galvani), Yale School of Public Health, New Haven, Conn.; Canadian Center for Vaccinology (Langley), Dalhousie University, IWK Health Centre and Nova Scotia Health Authority (Langley), Halifax, NS; Emerging Pathogens Institute (Singer), University of Florida, Gainesville, Fla.; Agent-Based Modelling Laboratory (Moghadas), York University, Toronto, Ont
| | - Seyed M Moghadas
- Center for Infectious Disease Modeling and Analysis (Shoukat, Wells, Galvani), Yale School of Public Health, New Haven, Conn.; Canadian Center for Vaccinology (Langley), Dalhousie University, IWK Health Centre and Nova Scotia Health Authority (Langley), Halifax, NS; Emerging Pathogens Institute (Singer), University of Florida, Gainesville, Fla.; Agent-Based Modelling Laboratory (Moghadas), York University, Toronto, Ont
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Wells CR, Sah P, Moghadas SM, Pandey A, Shoukat A, Wang Y, Wang Z, Meyers LA, Singer BH, Galvani AP. Impact of international travel and border control measures on the global spread of the novel 2019 coronavirus outbreak. Proc Natl Acad Sci U S A 2020; 117:7504-7509. [PMID: 32170017 PMCID: PMC7132249 DOI: 10.1073/pnas.2002616117] [Citation(s) in RCA: 349] [Impact Index Per Article: 87.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022] Open
Abstract
The novel coronavirus outbreak (COVID-19) in mainland China has rapidly spread across the globe. Within 2 mo since the outbreak was first reported on December 31, 2019, a total of 566 Severe Acute Respiratory Syndrome (SARS CoV-2) cases have been confirmed in 26 other countries. Travel restrictions and border control measures have been enforced in China and other countries to limit the spread of the outbreak. We estimate the impact of these control measures and investigate the role of the airport travel network on the global spread of the COVID-19 outbreak. Our results show that the daily risk of exporting at least a single SARS CoV-2 case from mainland China via international travel exceeded 95% on January 13, 2020. We found that 779 cases (95% CI: 632 to 967) would have been exported by February 15, 2020 without any border or travel restrictions and that the travel lockdowns enforced by the Chinese government averted 70.5% (95% CI: 68.8 to 72.0%) of these cases. In addition, during the first three and a half weeks of implementation, the travel restrictions decreased the daily rate of exportation by 81.3% (95% CI: 80.5 to 82.1%), on average. At this early stage of the epidemic, reduction in the rate of exportation could delay the importation of cases into cities unaffected by the COVID-19 outbreak, buying time to coordinate an appropriate public health response.
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Affiliation(s)
- Chad R Wells
- Center for Infectious Disease Modeling and Analysis, Yale School of Public Health, New Haven, CT 06520
| | - Pratha Sah
- Center for Infectious Disease Modeling and Analysis, Yale School of Public Health, New Haven, CT 06520
| | - Seyed M Moghadas
- Agent-Based Modelling Laboratory, York University, Toronto, ON M3J 1P3, Canada
| | - Abhishek Pandey
- Center for Infectious Disease Modeling and Analysis, Yale School of Public Health, New Haven, CT 06520
| | - Affan Shoukat
- Center for Infectious Disease Modeling and Analysis, Yale School of Public Health, New Haven, CT 06520
| | - Yaning Wang
- State Key Laboratory of Mycology, Institute of Microbiology, Chinese Academy of Sciences, 100101 Beijing, China
| | - Zheng Wang
- Department of Biostatistics, Yale School of Public Health, New Haven, CT 06510
| | - Lauren A Meyers
- Department of Integrative Biology, The University of Texas at Austin, Austin, TX 78712
- Santa Fe Institute, Santa Fe, NM 87501
| | - Burton H Singer
- Emerging Pathogens Institute, University of Florida, Gainesville, FL 32610
| | - Alison P Galvani
- Center for Infectious Disease Modeling and Analysis, Yale School of Public Health, New Haven, CT 06520
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Neurath C, Limeback H, Osmunson B, Connett M, Wells CR. Response to Letter to the Editor: "Dental Fluorosis Trends in US Oral Health Surveys". JDR Clin Trans Res 2019; 5:95. [PMID: 31589556 DOI: 10.1177/2380084419881612] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
Affiliation(s)
- C Neurath
- American Environmental Health Studies Project (AEHSP), Lexington, MA, USA
| | - H Limeback
- University of Toronto Faculty of Dentistry, Preventive Dentistry, McKellar, ON, Canada
| | - B Osmunson
- Smiles of Bellevue, Dental Practice, Bellevue, WA, USA
| | - M Connett
- Waters Kraus & Paul, El Segundo, CA, USA
| | - C R Wells
- University of California Los Angeles (UCLA), Institute of Digital Research and Education (IDRE), Statistical Consulting Group, UCLA Institute for Digital Research and Education, Los Angeles, CA, USA
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Affiliation(s)
- C Neurath
- American Environmental Health Studies Project (AEHSP), Lexington, MA, USA
| | - H Limeback
- University of Toronto Faculty of Dentistry, Preventive Dentistry, McKellar, ON, Canada
| | - B Osmunson
- Smiles of Bellevue, Dental Practice, Bellevue, WA, USA
| | - M Connett
- Waters Kraus & Paul, El Segundo, CA, USA
| | - C R Wells
- University of California Los Angeles (UCLA), Institute of Digital Research and Education (IDRE) Statistical Consulting Group, UCLA Institute for Digital Research and Education, Los Angeles, CA, USA
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Wells CR, Pandey A, Parpia AS, Fitzpatrick MC, Meyers LA, Singer BH, Galvani AP. Ebola vaccination in the Democratic Republic of the Congo. Proc Natl Acad Sci U S A 2019; 116:10178-10183. [PMID: 31036657 PMCID: PMC6525480 DOI: 10.1073/pnas.1817329116] [Citation(s) in RCA: 30] [Impact Index Per Article: 6.0] [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] [Indexed: 11/18/2022] Open
Abstract
Following the April 2018 reemergence of Ebola in a rural region of the Democratic Republic of the Congo (DRC), the virus spread to an urban center by early May. Within 2 wk of the first case confirmation, a vaccination campaign was initiated in which 3,017 doses were administered to contacts of cases and frontline healthcare workers. To evaluate the spatial dynamics of Ebola transmission and quantify the impact of vaccination, we developed a geographically explicit model that incorporates high-resolution data on poverty and population density. We found that while Ebola risk was concentrated around sites initially reporting infections, longer-range dissemination also posed a risk to areas with high population density and poverty. We estimate that the vaccination program contracted the geographical area at risk for Ebola by up to 70.4% and reduced the level of risk within that region by up to 70.1%. The early implementation of vaccination was critical. A delay of even 1 wk would have reduced these effects to 33.3 and 44.8%, respectively. These results underscore the importance of the rapid deployment of Ebola vaccines during emerging outbreaks to containing transmission and preventing global spread. The spatiotemporal framework developed here provides a tool for identifying high-risk regions, in which surveillance can be intensified and preemptive control can be implemented during future outbreaks.
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Affiliation(s)
- Chad R Wells
- Center for Infectious Disease Modeling and Analysis, Yale School of Public Health, New Haven, CT 06520
| | - Abhishek Pandey
- Center for Infectious Disease Modeling and Analysis, Yale School of Public Health, New Haven, CT 06520
| | - Alyssa S Parpia
- Center for Infectious Disease Modeling and Analysis, Yale School of Public Health, New Haven, CT 06520
| | - Meagan C Fitzpatrick
- Center for Infectious Disease Modeling and Analysis, Yale School of Public Health, New Haven, CT 06520
- Center for Vaccine Development and Global Health, University of Maryland School of Medicine, Baltimore, MD 21201
| | - Lauren A Meyers
- Department of Integrative Biology, University of Texas, Austin TX, 78712
| | - Burton H Singer
- Emerging Pathogens Institute, University of Florida, Gainesville, FL 32610
| | - Alison P Galvani
- Center for Infectious Disease Modeling and Analysis, Yale School of Public Health, New Haven, CT 06520
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Wells CR, Galvani AP. Public health impact of disease-behavior dynamics: Comment on "Coupled disease-behavior dynamics on complex networks: A review" by Z. Wang et al. Phys Life Rev 2015; 15:55-6. [PMID: 26514411 PMCID: PMC7128471 DOI: 10.1016/j.plrev.2015.10.013] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2015] [Accepted: 10/14/2015] [Indexed: 11/16/2022]
Affiliation(s)
- Chad R Wells
- Center for Infectious Disease Modeling and Analysis, Yale School of Public Health, New Haven, CT, USA.
| | - Alison P Galvani
- Center for Infectious Disease Modeling and Analysis, Yale School of Public Health, New Haven, CT, USA
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Abstract
Theoretical models of infection spread on networks predict that targeting vaccination at individuals with a very large number of contacts (superspreaders) can reduce infection incidence by a significant margin. These models generally assume that superspreaders will always agree to be vaccinated. Hence, they cannot capture unintended consequences such as policy resistance, where the behavioral response induced by a new vaccine policy tends to reduce the expected benefits of the policy. Here, we couple a model of influenza transmission on an empirically-based contact network with a psychologically structured model of influenza vaccinating behavior, where individual vaccinating decisions depend on social learning and past experiences of perceived infections, vaccine complications and vaccine failures. We find that policy resistance almost completely undermines the effectiveness of superspreader strategies: the most commonly explored approaches that target a randomly chosen neighbor of an individual, or that preferentially choose neighbors with many contacts, provide at best a 2% relative improvement over their non-targeted counterpart as compared to 12% when behavioral feedbacks are ignored. Increased vaccine coverage in super spreaders is offset by decreased coverage in non-superspreaders, and superspreaders also have a higher rate of perceived vaccine failures on account of being infected more often. Including incentives for vaccination provides modest improvements in outcomes. We conclude that the design of influenza vaccine strategies involving widespread incentive use and/or targeting of superspreaders should account for policy resistance, and mitigate it whenever possible.
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Affiliation(s)
- Chad R Wells
- Department of Mathematics and Statistics, University of Guelph, Guelph, Ontario, Canada.
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Wells CR, Tchuenche JM, Meyers LA, Galvani AP, Bauch CT. Impact of imitation processes on the effectiveness of ring vaccination. Bull Math Biol 2011; 73:2748-72. [PMID: 21409511 DOI: 10.1007/s11538-011-9646-4] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/03/2010] [Accepted: 02/18/2011] [Indexed: 11/25/2022]
Abstract
Ring vaccination can be a highly effective control strategy for an emerging disease or in the final phase of disease eradication, as witnessed in the eradication of smallpox. However, the impact of behavioural dynamics on the effectiveness of ring vaccination has not been explored in mathematical models. Here, we analyze a series of stochastic models of voluntary ring vaccination. Contacts of an index case base vaccinating decisions on their own individual payoffs to vaccinate or not vaccinate, and they can also imitate the behaviour of other contacts of the index case. We find that including imitation changes the probability of containment through ring vaccination considerably. Imitation can cause a strong majority of contacts to choose vaccination in some cases, or to choose non-vaccination in other cases-even when the equivalent solution under perfectly rational (non-imitative) behaviour yields mixed choices. Moreover, imitation processes can result in very different outcomes in different stochastic realizations sampled from the same parameter distributions, by magnifying moderate tendencies toward one behaviour or the other: in some realizations, imitation causes a strong majority of contacts not to vaccinate, while in others, imitation promotes vaccination and reduces the number of secondary infections. Hence, the effectiveness of ring vaccination can depend significantly and unpredictably on imitation processes. Therefore, our results suggest that risk communication efforts should be initiated early in an outbreak when ring vaccination is to be applied, especially among subpopulations that are heavily influenced by peer opinions.
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Affiliation(s)
- Chad R Wells
- Department of Mathematics and Statistics, University of Guelph, Guelph, Ontario, Canada.
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Abstract
Aphasia due to simple partial status epilepticus is rare, particularly in the absence of a seizure history. No previous report describes acute aphasia as the sole clinical manifestation of EEG-monitored status epilepticus, with prompt resolution with treatment. We report a 45-year-old man with a left temporal glioblastoma who acutely developed a global aphasia, during which an EEG revealed continual repetitive sharp waves emanating from the left hemisphere. After injection of i.v. diazepam, the EEG seizure activity ceased, and the patient's language output returned to preseizure levels.
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Affiliation(s)
- C R Wells
- Department of Neurology and Neurosciences, New York Hospital-Cornell University Medical Center, New York
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Abstract
We studied a large kindred with a chronic neurodegenerative disorder, affecting at least six male members in three generations. Spastic paraparesis, beginning at about 10 years of age, and hearing deficits were present in all affected members. Additionally, tremor ophthalmologic abnormalities, sensory deficits, short stature, hypogonadism, elevated cerebrospinal fluid protein, and absent or prolonged somatosensory evoked potentials were seen in some relatives. Although clinically similar to adrenomyeloneuropathy, the plasma and fibroblast levels of saturated very long-chain fatty acids were normal. This syndrome probably represents a new type of familial spastic paraparesis.
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Frank AL, Taber LH, Glezen WP, Kasel GL, Wells CR, Paredes A. Breast-feeding and respiratory virus infection. Pediatrics 1982; 70:239-45. [PMID: 7099789] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Grants] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/23/2023] Open
Abstract
Thirty-nine breast-fed and 42 bottle-fed infants were followed up from birth over a four-year period. Virus infection was documented by culture and serologic testing, and history and physical examination were recorded for all episodes of respiratory illness. There were no statistically significant differences in rates or distributions of infection with individual viruses or with all viruses over the first three or six months or during the second six months of life in the two groups, nor were there statistically significant differences in rates or distributions of disease of the upper and lower respiratory tract or total respiratory disease, except for decreased disease of the lower respiratory tract in bottle-fed infants in the second six months. There were trends to decreased morbidity in breast-fed infants in the first three and six months and more episodes of pneumonia and bronchiolitis in bottle-fed infants in the first six months (P less than .05) but similar use of medical care by both groups. High cord blood titers to two viruses were not associated with evidence of breast-feeding protection from infection with those two agents. Breast-fed babies do not have fewer respiratory virus infections or illnesses but may experience less severe illness.
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Abstract
In the Houston Family Study, young children were cultured for virus weekly or biweekly and during acute respiratory illnesses. The interval between the onset of illness and positive culture was examined for 179 infections during 1975-1979. In week 1 after onset, 73%, 73%, and 66% of cultures were positive for influenza A virus, respiratory syncytial virus (RSV), and parainfluenza virus type 3, respectively. Pooled data from influenza B virus infections in 1977 and 1980 showed that 73% of cultures were positive in week 1. Influenza A virus in week 2 or RSV in weeks 2 and 3 was isolated from very few children. However, 37% of cultures were positive for influenza B virus during week 2, and 17% of cultures were still positive for parainfluenza virus type 3 during week 3. Shedding of parainfluenza virus type 3 on days 29-38 was also observed. Parainfluenza virus type 3, RSV, and influenza A virus were isolated up to six days before the onset of illness.
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Friedman S, Wells CR. Prevention of bacterial endocarditis. Pa Med 1976; 79:19. [PMID: 934668] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 12/25/2022]
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Friedman S, Wells CR. Penicillin: multiple applications in rheumatic patients. Pa Med 1975; 78:39. [PMID: 1196645] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 12/26/2022]
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Wells CR. Atherosclerosis as a pediatric problem. Del Med J 1974; 46:457-63. [PMID: 4369794] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 01/10/2023]
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