December 3, 2023

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Protection of BNT162b2 Vaccine Booster against Covid-19 in Israel

Study Population

Study Population.

The participants in the study included persons who were 60 years of age or older and who had been fully vaccinated before March 1, 2021, had available data regarding sex, had no documented positive result on polymerase-chain-reaction assay for SARS-CoV-2 before July 30, 2021, and had not returned from travel abroad in August 2021. The number of confirmed infections in each population is shown in parentheses.

Our analysis was based on medical data from the Ministry of Health database that were extracted on September 2, 2021. At that time, a total of 1,186,779 Israeli residents who were 60 years of age or older had been fully vaccinated (i.e., received two doses of BNT162b2) at least 5 months earlier (i.e., before March 1, 2021) and were alive on July 30, 2021. We excluded from the analysis participants who had missing data regarding sex; were abroad in August 2021; had received a diagnosis of PCR-positive Covid-19 before July 30, 2021; had received a booster dose before July 30, 2021; or had been fully vaccinated before January 16, 2021. A total of 1,137,804 participants met the inclusion criteria for the analysis (Figure 1).

The data included vaccination dates (first, second, and third doses); information regarding PCR testing (sampling dates and results); the date of any Covid-19 hospitalization (if relevant); demographic variables, such as age, sex, and demographic group (general Jewish, Arab, or ultra-Orthodox Jewish population), as determined by the participant’s statistical area of residence (similar to a census block)8; and clinical status (mild or severe disease). Severe disease was defined as a resting respiratory rate of more than 30 breaths per minute, an oxygen saturation of less than 94% while breathing ambient air, or a ratio of partial pressure of arterial oxygen to fraction of inspired oxygen of less than 300.9

Study Design

Our study period started at the beginning of the booster vaccination campaign on July 30, 2021. The end dates were chosen as August 31, 2021, for confirmed infection and August 26, 2021, for severe illness. The selection of dates was designed to minimize the effects of missing outcome data owing to delays in the reporting of test results and to the development of severe illness. The protection gained by the booster shot was not expected to reach its maximal capacity immediately after vaccination but rather to build up during the subsequent week.10,11 At the same time, during the first days after vaccination, substantial behavioral changes in the booster-vaccinated population are possible (Fig. S1 in the Supplementary Appendix, available with the full text of this article at One such potential change is increased avoidance of exposure to excess risk until the booster dose becomes effective. Another potential change is a reduced incidence of testing for Covid-19 around the time of receipt of the booster (Fig. S2). Thus, it is preferable to assess the effect of the booster only after a sufficient period has passed since its administration.

We considered 12 days as the interval between the administration of a booster dose and its likely effect on the observed number of confirmed infections. The choice of the interval of at least 12 days after booster vaccination as the cutoff was scientifically justified from an immunologic perspective, since studies have shown that after the booster dose, neutralization levels increase only after several days.6 In addition, when confirmed infection (i.e., positivity on PCR assay) is used as an outcome, a delay occurs between the date of infection and the date of PCR testing. For symptomatic cases, it is likely that infection occurs on average 5 to 6 days before testing, similar to the incubation period for Covid-19.12,13 Thus, our chosen interval of 12 days included 7 days until an effective buildup of antibodies after vaccination plus 5 days of delay in the detection of infection.

To estimate the reduction in the rates of confirmed infection and severe disease among booster recipients, we analyzed data on the rate of confirmed infection and on the rate of severe illness among fully vaccinated participants who had received the booster dose (booster group) and those who had received only two vaccine doses (nonbooster group). The membership in these groups was dynamic, since participants who were initially included in the nonbooster group left it after receipt of the booster dose and subsequently were included in the booster group 12 days later, provided that they did not have confirmed infection during the interim period (Fig. S3).

In each group, we calculated the rate of both confirmed infection and severe illness per person-days at risk. In the booster group, we considered that days at risk started 12 days after receipt of the third dose and ended either at the time of the occurrence of a study outcome or at the end of the study period. In the nonbooster group, days at risk started 12 days after the beginning of the study period (August 10, 2021) and ended at time of the occurrence of a study outcome, at the end of the study period, or at the time of receipt of a booster dose. The time of onset of severe Covid-19 was considered to be the date of the confirmed infection. In order to minimize the problem of censoring, the rate of severe illness was calculated on the basis of cases that had been confirmed on or before August 26, 2021. This schedule was adopted to allow for a week of follow-up (until the date when we extracted the data) for determining whether severe illness had developed. The study protocol is available at


The study was approved by the institutional review board of the Sheba Medical Center. All the authors contributed to the writing and critical review of the manuscript, approved the final version, and made the decision to submit the manuscript for publication. The Israeli Ministry of Health and Pfizer have a data-sharing agreement, but only the final results of this study were shared.

Statistical Analysis

We performed Poisson regression to estimate the rate of a specific outcome, using the function for fitting generalized linear models (glm) in R statistical software.14 These analyses were adjusted for the following covariates: age (60 to 69 years, 70 to 79 years, and ≥80 years), sex, demographic group (general Jewish, Arab, or ultra-Orthodox Jewish population),8 and the date of the second vaccine dose (in half-month intervals). We included the date of the second dose as a covariate to account for the waning effect of the earlier vaccination and for the likely early administration of vaccine in high-risk groups.2 Since the overall rate of both confirmed infection and severe illness increased exponentially during the study period, days at the beginning of the study period had lower exposure risk than days at the end. To account for growing exposure risk, we included the calendar date as an additional covariate. After accounting for these covariates, we used the study group (booster or nonbooster) as a factor in the regression model and estimated its effect on rate. We estimated the rate ratio comparing the nonbooster group with the booster group, a measure that is similar to relative risk. For reporting uncertainty around our estimate, we took the exponent of the 95% confidence interval for the regression coefficient without adjustment for multiplicity. We also used the results of the model to calculate the average between-group difference in the rates of confirmed infection and severe illness.15

In a secondary analysis, we compared infection rates before and after the booster dose became effective. Specifically, we repeated the Poisson regression analysis described above but compared the rate of confirmed infection between 4 and 6 days after the booster dose with the rate at least 12 days after the booster dose. Our hypothesis was that the booster dose was not yet effective during the former period.10 This analysis compares different periods after booster vaccination among persons who received the booster dose and may reduce selection bias. However, booster recipients might have undergone less frequent PCR testing and behaved more cautiously with regard to virus exposure soon after receiving the booster dose (Fig. S2). Thus, we hypothesize that the rate ratio could be underestimated in this analysis.

To further examine the reduction in the rate of confirmed infection as a function of the interval since receipt of the booster, we fitted a Poisson regression that includes days 1 to 32 after the booster dose as separate factors in the model. The period before receipt of the booster dose was used as the reference category. This analysis was similar to the Poisson modeling described above and produced rates for different days after the booster vaccination.

To test for different possible biases, we performed several sensitivity analyses. First, we analyzed the data using alternative statistical methods relying on matching and weighting. These analyses are described in detail in the Methods section in the Supplementary Appendix. Second, we tested the effect of a specific study period by splitting the data into different study periods and performing the same analysis on each. Third, we performed the same analyses using data only from the general Jewish population, since the participants in that cohort dominated the booster-vaccinated population.