Home Scholarly articles Protection of the BNT162b2 vaccine booster against Covid-19 in Israel

Protection of the BNT162b2 vaccine booster against Covid-19 in Israel

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Study population

Study population.

Study participants included people aged 60 or older who had been fully vaccinated before March 1, 2021, had data regarding gender, had no documented positive results on the polymerase chain reaction test 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’s database that was retrieved on September 2, 2021. At that time, a total of 1,186,779 Israeli residents aged 60 or older had been fully immunized ( that is, they had received two doses of BNT162b2) at least 5 months earlier (ie before March 1, 2021) and were alive on July 30, 2021. We excluded from analysis of participants who had missing data regarding gender; were abroad in August 2021; had been diagnosed with Covid-19 PCR positive before July 30, 2021; had received a booster dose before July 30, 2021; or had been fully vaccinated by January 16, 2021. A total of 1,137,804 participants met the inclusion criteria for analysis (Figure 1).

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

Study design

Our study period began at the start of the booster vaccination campaign on July 30, 2021. End dates were chosen as August 31, 2021, for confirmed infection, and August 26, 2021, for severe illness. The date selection was designed to minimize the effects of missing data on results due to delays in reporting test results and the development of serious illness. The protection obtained by the booster should not reach its maximum capacity immediately after vaccination, but rather build up over the following 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 Annex, available with the full text of this article on NEJM.org) . One of these potential changes is the increased avoidance of exposure to excessive risk until the booster dose becomes effective. Another potential change is a reduced incidence of testing for Covid-19 upon receipt of the booster (Fig. S2). Thus, it is preferable to evaluate the effect of the booster only after a sufficient period has elapsed since its administration.

We considered 12 days as the interval between 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 the booster vaccination as the threshold was scientifically justified from an immunological point of view, since studies have shown that after the booster dose, neutralization levels do not increase. only after several days.6 Additionally, when confirmed infection (i.e., PCR test positivity) is used as the result, there is a delay between the date of infection and the date of the PCR test. For symptomatic cases, the infection is likely to occur on average 5 to 6 days before the test, similar to the incubation period for Covid-19.12.13 Thus, our chosen 12 day interval included 7 days until effective accumulation of antibodies after vaccination plus 5 days delay in detection of infection.

To estimate the reduction in confirmed infection and severe disease rates in booster recipients, we analyzed data on confirmed infection rate and severe disease rate in fully immunized participants who received the dose of booster (booster group) and those who had received only two doses of vaccine (non-booster group). Membership in these groups was dynamic, as participants who were initially included in the non-booster group left after receiving the booster dose and were then included in the booster group 12 days later, provided that they did not confirm the infection during the intervening period. (Fig. S3).

In each group, we calculated the rate of confirmed infection and severe illness per person-day at risk. In the booster group, we considered that the risk days began 12 days after receiving the third dose and ended either when a study result appeared or at the end of the period. ‘study. In the non-booster group, at-risk days began 12 days after the start of the study period (August 10, 2021) and ended when a study result occurred, at the end of the study period. during the study period, or upon receipt of a booster dose. The time of onset of severe Covid-19 was considered the date of confirmed infection. In order to minimize the censorship problem, the critical illness rate has been calculated based on cases confirmed by August 26, 2021. This schedule has been adopted to allow for one week of follow-up (until the date when we have extracts data) to determine if serious illness has developed. The study protocol is available on NEJM.org.

Monitoring

The study was approved by the Institutional Review Board of Sheba Medical Center. All 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 have been shared.

Statistical analyzes

We performed Poisson regression to estimate the rate of a specific outcome, using the generalized linear models (glm) fit function in R statistical software.14 These analyzes 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 dose of vaccine (at half-month intervals). We included the date of the second dose as a covariate to account for the decreasing effect of previous vaccination and the likely early administration of the vaccine in high risk groups.2 Since the overall rate of confirmed infection and severe illness increased exponentially over the study period, the days at the start of the study period had a lower risk of exposure than the days at the start of the study period. the end. To account for the risk of increasing exposure, we have included the calendar date as an additional covariate. After taking these covariates into account, we used the study group (booster or nonbooster) as a factor in the regression model and estimated its effect on the rate. We estimated the rate ratio by comparing the non-booster group with the booster group, a measure that is similar to relative risk. To account for the uncertainty around our estimate, we took the exponent of the 95% confidence interval for the regression coefficient without adjustment for the multiplicity. We also used the model results to calculate the mean difference between groups in the rates of confirmed infection and severe disease.15

In a secondary analysis, we compared the infection rates before and after the effectiveness of the booster dose. 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 first period.ten This analysis compares different time periods after the booster vaccination in those who received the booster dose and may reduce selection bias. However, booster recipients may 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 might be underestimated in this analysis.

To further examine the reduction in the rate of confirmed infection as a function of time since receiving 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 receiving the booster dose was used as a reference category. This analysis was similar to the Poisson modeling described above and produced rates for different days after the booster vaccination.

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


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