Protection and decline of natural and hybrid immunity to SARS-CoV-2

Study population

Our analysis, which was based on data from the Israeli Ministry of Health’s national database, focused on infections that were confirmed during the study period, from August 1 to September 30, 2021. During this period, Israel was in the midst of a fourth wave of pandemic that was dominated by the B.1.617.2 (delta) variant.17 Israel had already campaigned to offer two doses of the BNT162b2 vaccine and had launched a campaign with third and fourth booster doses (see Supplementary Methods 1 section in the Supplementary Appendix, available with the full text of this article on NEJM. org). In addition, as of March 2021, unvaccinated individuals who had recovered from the 2019 coronavirus disease (Covid-19) at least 3 months earlier were eligible for a single dose of BNT162b2 vaccine.

In this study, SARS-CoV-2 reinfection was defined as a positive polymerase chain reaction (PCR) test in a subject who tested positive from a sample obtained at least 90 days prior to the study day.18 The definition of severe Covid-19 was consistent with that of the National Institutes of Health19 – that is, 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 inhaled oxygen of less than 300. Israel Ministry of Health includes, for all residents who have received a Covid-19 vaccine, have been tested for Covid-19 or previously infected with SARS-CoV-2, basic demographic information such as gender, age, place of residence and population sector, as well as complete data on vaccinations and confirmed infections.

Study Population.

Eligible subjects in the study did not have a documented positive polymerase chain reaction assay between July 1, 2021 and July 30, 2021, had received at most one vaccine dose before recovery or after recovery from coronavirus disease 2019 (Covid-19), and had no vaccine before August 1, 2021. received a Covid-19 vaccine other than BNT162b2. Age groups from January 1, 2021 are shown. SARS-CoV-2 stands for severe acute respiratory syndrome coronavirus 2.

Using these data at the individual resident level, we studied confirmed infections in individuals 16 years of age or older who tested positive for SARS-CoV-2 infection before July 1, 2021, or who received at least two doses of BNT162b2 vaccine. had received at least 7 days before the end of the study period. We excluded the following from the analysis: those whose data does not include age or gender information; those who tested positive for SARS-CoV-2 between July 1 and July 31, 2021; those who recovered from PCR-confirmed SARS-CoV-2 infection and subsequently received more than one dose of BNT162b2 vaccine (a small group with limited follow-up data); those who received more than one dose of BNT162b2 vaccine and subsequently recovered from PCR-confirmed SARS-CoV-2 infection (a small group); those who have spent the entire study period abroad; and those who had received a vaccine other than BNT162b2 before August 1, 2021 (Figure 1

Study design and supervision

We compared the incidences of confirmed infection over the study period among cohorts of individuals with different histories of immunizing events (ie, infection or vaccination). The recovered, unvaccinated cohort included subjects who had a confirmed infection 90 days or more prior to the study day. There were two “hybrid” cohorts (ie, cohorts with participants who had both natural and vaccination immunity); the recovered single-dose cohort consisted of individuals who had recovered from Covid-19 and who later received a single dose of vaccine at least 7 days prior to study day, and the single-dose cohort recovered those who had received a single dose of vaccine, followed by a confirmed infection at least 90 days before the study day. The two-dose cohort was composed of subjects who had not been infected before the start of the study and who had received the second dose of vaccine at least 7 days before the study day, and the three-dose cohort was composed of those who had not been infected before the start of the study. were infected in the study and who had received the third (booster) dose of the vaccine at least 12 days before the study day.

These cohorts were subdivided into subcohorts based on the time elapsed since the last immunizing event. We used 2 months as the base time interval to define the subcohorts, but we combined 12 to 18 months for the recovered unvaccinated cohort and omitted the 8 to less than 10 month period for the vaccinated and hybrid cohorts due to the small number of individuals in those cohorts.

A person can contribute follow-up days to different subcohorts and can also move from one cohort to another according to the following rules. A person who had recovered from Covid-19 and who had received a first dose of BNT162b2 vaccine during the study period, left the recovered unvaccinated cohort on the day of vaccination and entered the recovered single-dose cohort 7 days later. A person who recovered from Covid-19 who had received a first vaccine dose but then received a second dose during the study period left the recovered cohort with one dose at the time of the second vaccination. One subject in the two-dose cohort who received a third (booster) dose during the study period left the two-dose cohort on the day of the booster dose and entered the three-dose cohort 12 days later.20 An individual who tested positive for SARS-CoV-2 infection between May 1 and June 30, 2021, and who also received a single dose of BNT162b2 vaccine, entered the recovered single-dose cohort or the single-dose recovered cohort (already or unconfirmed infection before vaccination) 90 days after the positive test. A person who received a vaccine other than BNT162b2 left the study on the day of that vaccination.

Studies often compare infection rates among recovered or vaccinated individuals with those among unvaccinated individuals who have not been previously infected. However, due to the high vaccination coverage in Israel, this latter cohort is small and not representative of the total population. In addition, the Israeli Ministry of Health database does not contain complete information on such individuals. Therefore, we included unvaccinated, previously uninfected individuals in our analysis.

The study was approved by the Institutional Review Board of Sheba Medical Center. Israel’s Ministry of Health and Pfizer have a data-sharing agreement, but only the final results of this study were shared.

Static analysis

To analyze the data, we used methods similar to those in our previous studies.8,20,21 We assumed that the risk of infection in each cohort would be independent of the dwell time in previous cohorts (i.e., time spent in the cohort before a confirmed infection), and we focused on the relationship between the proportional hazard survival model and the Poisson- regression model22 (see Additional Methods section 2). Specifically, for each subcohort, the number of confirmed infections and the number of person days at risk during the study period were counted.

A Poisson regression model was applied, adjusting for age group as of January 1, 2021 (16 to 39 years, 40 to 59 years or ≥60 years), gender, population sector (generally Jewish, Arab or ultra-Orthodox Jewish), calendar week and an exposure risk measure. The latter was calculated for each subject on each follow-up day based on the number of new confirmed infections during the previous 7 days in the subject’s area of ​​residence; this continuous measure was then classified into 10 risk groups according to deciles.20 Average exposure risk was attributed to individuals with missing residency data. To ensure that the effect of missing data was small, a descriptive comparison of subjects who had missing data with those who had no missing data, as well as a multiple attribution analysis were performed (see Supplementary Analysis section 1). Goodness of fit of the model was checked by examining Pearson residuals across the categories.

In a complementary analysis, we equipped a model with an interaction between age group and subcohort to estimate the age-specific incidence in each subcohort. Each case of infection contributed an event to the respective subcohort. Based on the estimated parameters of the fitted regression model, the incidence in each subcohort, adjusted for the confounders, was estimated as the expected number of events per 100,000 days if all person days at risk were included in that subcohort (see Supplementary Methods section 3). The 95% confidence intervals were calculated using a bootstrap-like simulation approach23 without adjustment for multiples. We repeated the analysis of subcohorts at 1-month intervals (instead of 2-month intervals) to better distinguish between individuals who chose to be vaccinated earlier and those who chose to be vaccinated later (or between those who were previously infected and those who were infected later).

To investigate the effect of misclassification of individuals into cohorts due to undocumented infections, we performed a sensitivity analysis assuming that 50% or 70% of true infections were undocumented. There were too few cases for an in-depth comparison of the incidence of serious diseases within and between the cohorts with natural immunity and those with hybrid immunity; thus, only a descriptive analysis was performed. The results of a comparison of the incidence of severe Covid-19 between individuals who received two doses of BNT162b2 vaccine and those who received a third (booster) dose are reported elsewhere.21

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