Quantifying the Population-Level Effect of the COVID-19 Mass Vaccination Campaign in Israel: A Modeling Study

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.

Keywords: COVID-19; effect; modeling; real-life; vaccination.

Figure 1.

Daily case counts of SARS-CoV-2-positive tests. Daily numbers of SARS-CoV-2-positive samples tested during March 2020–February 2021 are shown. The “epidemic waves” of COVID-19 in Israel are depicted; major time points, including lockdown periods, social restrictions, and the start of vaccinations, are noted. Abbreviations: COVID-19, coronavirus disease 2019; SARS-CoV-2, severe acute respiratory syndrome coronavirus 2.

Figure 2.

SARS-CoV-2 infections, hospitalizations, fatalities, and vaccinations by date. A, Daily counts of positive SARS-CoV-2 tests. B, Time series and counts of the BNT162b2-mRNA COVID-19 vaccine first dose administered. Vaccinations began on December 19, 2020. C, Daily counts of COVID-19 moderately to severely ill hospitalizations. In order to account for potential changes in the definition of moderate, severe, and critical cases, we have combined the counts. D, Daily counts of COVID-19 fatalities. Abbreviations: COVID-19, coronavirus disease 2019; SARS-CoV-2, severe acute respiratory syndrome coronavirus 2.

Figure 3.

Actual cumulative numbers, and calculated numbers under the no vaccination scenario, of SARS-CoV-2 infections, hospitalizations, and fatalities. Weekly numbers of SARS-CoV-2 infections, hospitalizations, and deaths are shown during January–February 2021, including the actual numbers and the calculated numbers of the no vaccination scenario utilizing the 2 different approaches. A, The actual and calculated numbers of the no vaccination scenario of SARS-CoV-2 weekly positive tests are shown for the whole population. B, The actual and calculated numbers of the no vaccination scenario of weekly SARS-CoV-2-positive tests are shown for children aged 0–19 years, demonstrating the indirect effect of vaccination on the young population (<20 years of age). C, The actual and calculated numbers of the no vaccination scenario of weekly SARS-CoV-2 hospitalizations are shown, demonstrating the effect of vaccination on hospitalizations for moderate to severe conditions. D, The actual and calculated numbers of the no vaccination scenario of weekly SARS-CoV-2 deaths are shown, demonstrating the effect of vaccination on cumulative fatality. The solid red curve corresponds to actual case counts. The purple dotted line (and blue shaded regions indicating 75% confidence bounds) shows the no intervention scenario modeled under Approach 1. The black dashed line (and gray shaded region indicating 75% confidence bounds) corresponds to the no vaccination scenario modeled under Approach 2. Abbreviations: COVID-19, coronavirus disease 2019; SARS-CoV-2, severe acute respiratory syndrome coronavirus 2.

Figure 4.

Comparison of actual SARS-CoV-2 infections and simulated counts during January 8–January 28, 2021. Comparison of simulated cumulative counts of positive counts and daily counts of positive tests with true counts is shown. As of January 8, 2021, the cumulative count of positive tests was 480 338. As demonstrated in the figure, the simulated trajectories lie close to the true counts of cumulative positive tests. The solid red line shows the actual trajectories. The means of the simulated trajectories are shown as a broken line in purple. The shaded blue regions indicate 75% confidence around the mean trajectory. A, Comparison of the cumulative counts of positive counts against the true counts. B, Comparison of the fitted daily counts of positive tests against true counts of daily positive tests. The dips in the counts are due to weakened effects. Even though the true trajectory of daily counts of positive tests is unsmooth, the simulated counts of daily positive tests are generally close to it. In particular, the true trajectory lies entirely within the 75% confidence bounds, indicating a good fit of the model to the data. Abbreviations: COVID-19, coronavirus disease 2019; SARS-CoV-2, severe acute respiratory syndrome coronavirus 2.