Decreasing immunity after BNT162b2 vaccine in Israel
The data source
Data on all residents of Israel who had been fully vaccinated before June 1, 2021 and who had not been infected before the study period was pulled from the Israeli Ministry of Health database on September 2. 2021. which has passed 7 days or more since receiving the second dose of BNT162b2 vaccine. We used the official Ministry of Health database which contains all information regarding Covid-19 (see Additional Methods 1 in the Additional Annex, available with the full text of this article on NEJM.org). We extracted information from the database on all documented SARS-CoV-2 infections (i.e. a positive PCR result) and the severity of the disease after infection. We focused on infections that had been documented during the period July 11-31, 2021 (study period), removing from data all confirmed cases that had been documented prior to this period. The start date was chosen as a time when the virus had already spread across the country and across sectors of the population. The end date was right after Israel launched a campaign for the use of a booster vaccine (third dose). The study period coincided with the summer school holidays.
We omitted from all analyzes children and adolescents under 16 years of age (most of whom were not vaccinated or had recently been vaccinated). Only people 40 years of age or older were included in the analysis for critical illness because severe illness was rare in the younger population. Critical illness was defined as a resting respiratory rate of more than 30 breaths per minute, an oxygen saturation of less than 94% while the person was breathing room air, or a partial pressure ratio of arterial oxygen to the fraction of inspired oxygen of less than 300.14 People who died from Covid-19 during the follow-up period were included in the study and classified as having had serious illness.
During the study period, around 10% of infections detected were among residents of Israel returning from abroad. Most residents who traveled abroad had been vaccinated and had been exposed to different populations, so their risk of infection differed from that of the rest of the study population. We therefore removed from the analysis all residents who returned from abroad in July.
The official vaccination schedule in Israel involved the administration of the second dose 3 weeks after the first dose. All residents 60 years of age or older were eligible for vaccination as of December 20, 2020, becoming fully vaccinated as of mid-January 2021. At that time, younger people were eligible for vaccination only if they belonged designated groups (eg, healthcare professionals and severely immunocompromised adults). The age of eligibility was reduced to 55 on January 12, 2021 and to 40 on January 19, 2021. On February 4, 2021, all persons 16 years of age or older became eligible for vaccination. So, if they were not in a designated group, people 40 to 59 received the second dose from mid-February and those 16 to 39 received the second dose from early March. Based on these dates, we have defined our interest periods in half-months starting January 16; vaccination times for individual people were determined based on when they became fully vaccinated (i.e. 1 week after receiving the second dose). All analyzes were stratified by vaccination period and age group (16 to 39 years, 40 to 59 years and ≥60 years).
The association between the rate of confirmed infections and the period of vaccination provides a measure of the decline in immunity. Without weakened immunity, one would not expect to see any difference in infection rates among people vaccinated at different times. To examine the effect of decreased immunity during the period when the delta variant was predominant, we compared the rate of confirmed infections (per 1,000 people) during the study period (July 11-31, 2021) among people who have been fully immunized during different time periods. . The 95% confidence intervals for the rates were calculated by multiplying the standard confidence intervals for the proportions by 1000. A similar analysis was performed to compare the association between the rate of severe Covid-19 and the vaccination period. , but for this result we used periods of whole months because there were fewer cases of severe illness.
To account for possible confounding factors, we fitted Poisson regressions. The outcome variable was the number of documented SARS-CoV-2 infections or severe Covid-19 cases during the study period. The vaccination period, which was defined as 7 days after receiving the second dose of the Covid-19 vaccine, was the main exposure of interest. The models compared rates per 1,000 people between different vaccination periods, in which the baseline period for each age group was set based on when all people in that group first became eligible for the vaccine. vaccination. A differential effect of the vaccination period for each age group was allowed by the inclusion of an interaction term between age and vaccination period. Additional potential confounding factors were added as covariates, as described below, and the natural logarithm of the number of people was added as a lag. For each vaccination period and age group, an adjusted rate was calculated as the expected number of weekly events per 100,000 people if all people in that age group had been vaccinated during that period. All the analyzes were carried out using the glm function of statistical software R.17
In addition to age and sex, the regression analysis included the following confounding factors as covariates. First, because event rates increased rapidly over the study period (Figure 1), we have included the week in which the event was recorded. Second, although PCR testing is free in Israel for all residents, adherence to PCR testing recommendations varies and is a possible source of detection bias. To take this into account in part, we stratified people according to the number of PCR tests that had been performed during the period from March 1 to November 31, 2020, that is, before the start of the vaccination campaign. . We have defined three levels of use: zero, one and two or more PCR tests. Finally, the three main population groups in Israel (general Jew, Arab, and ultra-Orthodox Jew) have varying risk factors for infection. The proportion of people vaccinated, as well as the level of exposure to the virus, differed between these groups.18 Although we limited the study to the dates when the virus was found nationwide, we included the population sector as a covariate to control for any residual confounding effects.
We performed several secondary analyzes to test the robustness of the results, including calculating the rate of confirmed infection in a later 10-year age group and an analysis limited to the general Jewish population (in which the epidemic of delta started), which includes the majority of people in Israel. In addition, a model including a measure of socioeconomic status as a covariate was fitted to the data, as this was an important risk factor in a previous study.18 Since socioeconomic status was unknown for 5% of people in our study and the lack of data appeared to be informative, and also because of concerns about non-differential misclassification (people of unknown socioeconomic status may have had different rates of vaccination, infection, and severe), we did not include socioeconomic status in the primary analysis. Finally, we compared the association between the number of PCR tests that had been performed before the vaccination campaign (i.e. before December 2020) with the number that were performed during the study period in order to ” assess the possible magnitude of detection bias in our analysis. . A good correlation between past behavior regarding PCR tests and behavior over the study period would reassure that including past behavior as a covariate in the model would, at least in part, control detection bias.