Ido Somekh
Quantifying the Population-Level Effect of the COVID-19 Mass Vaccination Campaign in Israel: A Modeling Study
Somekh, Ido; Khudabukhsh, Wasiur R.; Root, Elisabeth Dowling; Boker, Lital Keinan; Rempala, Grzegorz; Simões, Eric A.F.; Somekh, Eli
Authors
Dr. WASIUR RAHMAN KHUDA BUKHSH WASIUR.KHUDABUKHSH@NOTTINGHAM.AC.UK
Assistant Professor
Elisabeth Dowling Root
Lital Keinan Boker
Grzegorz Rempala
Eric A.F. Simões
Eli Somekh
Abstract
Background: Estimating real-world vaccine effectiveness is challenging as a variety of population factors can impact vaccine effectiveness. We aimed to assess the population-level reduction in cumulative severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) cases, hospitalizations, and mortality due to the BNT162b2 mRNA coronavirus disease 2019 (COVID-19) vaccination campaign in Israel during January-February 2021. Methods: A susceptible-infected-recovered/removed (SIR) model and a Dynamic Survival Analysis (DSA) statistical approach were used. Daily counts of individuals who tested positive and of vaccine doses administered, obtained from the Israeli Ministry of Health, were used to calibrate the model. The model was parameterized using values derived from a previous phase of the pandemic during which similar lockdown and other preventive measures were implemented in order to take into account the effect of these prevention measures on COVID-19 spread. Results: Our model predicted for the total population a reduction of 648 585 SARS-CoV-2 cases (75% confidence interval [CI], 25 877-1 396 963) during the first 2 months of the vaccination campaign. The number of averted hospitalizations for moderate to severe conditions was 16 101 (75% CI, 2010-33 035), and reduction of death was estimated at 5123 (75% CI, 388-10 815) fatalities. Among children aged 0-19 years, we estimated a reduction of 163 436 (75% CI, 0-433 233) SARS-CoV-2 cases, which we consider to be an indirect effect of the vaccine. Conclusions: Our results suggest that the rapid vaccination campaign prevented hundreds of thousands of new cases as well as thousands of hospitalizations and fatalities and has probably averted a major health care crisis.
Citation
Somekh, I., Khudabukhsh, W. R., Root, E. D., Boker, L. K., Rempala, G., Simões, E. A., & Somekh, E. (2022). Quantifying the Population-Level Effect of the COVID-19 Mass Vaccination Campaign in Israel: A Modeling Study. Open Forum Infectious Diseases, 9(5), Article ofac087. https://doi.org/10.1093/ofid/ofac087
Journal Article Type | Article |
---|---|
Acceptance Date | Feb 7, 2022 |
Online Publication Date | Feb 18, 2022 |
Publication Date | May 1, 2022 |
Deposit Date | Apr 9, 2022 |
Publicly Available Date | Apr 11, 2022 |
Journal | Open Forum Infectious Diseases |
Print ISSN | 2328-8957 |
Electronic ISSN | 2328-8957 |
Publisher | Oxford University Press |
Peer Reviewed | Peer Reviewed |
Volume | 9 |
Issue | 5 |
Article Number | ofac087 |
DOI | https://doi.org/10.1093/ofid/ofac087 |
Keywords | Infectious Diseases |
Public URL | https://nottingham-repository.worktribe.com/output/7684179 |
Publisher URL | https://academic.oup.com/ofid/advance-article/doi/10.1093/ofid/ofac087/6530634?login=false |
Files
Quantifying the Population-level Effect of the COVID-19 Mass Vaccination
(548 Kb)
PDF
Publisher Licence URL
https://creativecommons.org/licenses/by-nc-nd/4.0/
You might also like
Incorporating age and delay into models for biophysical systems
(2020)
Journal Article
Quasi-Steady-State Approximations Derived from the Stochastic Model of Enzyme Kinetics
(2019)
Journal Article
Generalized Cost-Based Job Scheduling in Very Large Heterogeneous Cluster Systems
(2020)
Journal Article
Downloadable Citations
About Repository@Nottingham
Administrator e-mail: discovery-access-systems@nottingham.ac.uk
This application uses the following open-source libraries:
SheetJS Community Edition
Apache License Version 2.0 (http://www.apache.org/licenses/)
PDF.js
Apache License Version 2.0 (http://www.apache.org/licenses/)
Font Awesome
SIL OFL 1.1 (http://scripts.sil.org/OFL)
MIT License (http://opensource.org/licenses/mit-license.html)
CC BY 3.0 ( http://creativecommons.org/licenses/by/3.0/)
Powered by Worktribe © 2024
Advanced Search