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

Protection and decline of natural and hybrid immunity to SARS-CoV-2 |  NEJM
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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, August 1 to September 30, 2021. During this period, Israel was in the midst of a fourth pandemic wave dominated by the B.1.617.2 (delta) variant.17 Israel had previously conducted a campaign offering two doses of the BNT162b2 vaccine and launched a campaign offering third and fourth booster doses (see Supplementary Methods section 1 in the Supplementary Appendix, available with the full text of this article on NEJM.org ). Additionally, as of March 2021, unvaccinated individuals who had recovered from coronavirus disease 2019 (Covid-19) at least 3 months previously were eligible to receive a single dose of BNT162b2 vaccine.

In this study, reinfection with SARS-CoV-2 was defined as a positive polymerase chain reaction (PCR) test in a person who had tested positive from a specimen obtained at least 90 days before the day of the study.18 The definition of severe Covid-19 was consistent with that of the National Institutes of Health19 — i.e. a resting respiratory rate greater than 30 breaths per minute, an oxygen saturation of less than 94% while the person was breathing room air, or a ratio of arterial oxygen partial pressure to fraction of inspired oxygen less than 300 Israeli Ministry of Health database includes, for all residents who received a Covid-19 vaccine, were tested for Covid-19, or were previously infected with SARS-CoV -2, basic demographic information such as sex, age, place of residence and sector of the population, as well as complete records of vaccinations and confirmed infections.

Study population.

Those eligible for the study did not have a documented positive polymerase chain reaction test between July 1 and July 30, 2021, had received at most one dose of vaccine before recovery or after recovery from the disease at coronavirus 2019 (Covid-19), and had not received a Covid-19 vaccine other than BNT162b2 before August 1, 2021. Age groups as of January 1, 2021 are shown. SARS-CoV-2 refers to severe acute respiratory syndrome coronavirus 2.

Using these individual resident-level data, we studied confirmed infections among people 16 years of age or older who had tested positive for SARS-CoV-2 infection before July 1, 2021 or who had received at least two doses of BNT162b2 vaccine at least 7 days before the end of the study period. We excluded the following people from the analysis: those whose data did not include information on age or sex; those who had tested positive for SARS-CoV-2 between July 1 and July 31, 2021; those who had 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 then recovered from PCR-confirmed SARS-CoV-2 infection (a small group); those who have spent the entire period of study 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 people with varying histories of immune-conferring events (i.e., infection or vaccination). The recovered, unvaccinated cohort involved people who had had a confirmed infection 90 days or more before the day of the study. There were two “hybrid” cohorts (ie, cohorts with participants who had both natural immunity and immunity from vaccination); the recovered one-dose cohort consisted of people who had recovered from Covid-19 and subsequently received a single dose of vaccine at least 7 days before the day of the study, and the recovered one-dose cohort involved those who had received a single dose of vaccine, followed by a confirmed infection at least 90 days before the day of the study. The two-dose cohort consisted of people 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 day of the study, and the three-dose cohort was composed of those who had not been infected before the start of the study and who had received the third dose (booster) of vaccine at least 12 days before the day of the study.

These cohorts were divided into sub-cohorts based on the time elapsed since the last immunity conferring event. We used 2 months as the base time interval to define the subcohorts, but we combined months 12 to 18 for the unvaccinated recovered cohort and omitted the period from 8 to less than 10 months for the vaccinated and hybrid cohorts. due to the small number of people in these cohorts.

A person could contribute follow-up days to different sub-cohorts and could also move from one cohort to another according to the following rules. One person who had recovered from Covid-19 and received a first dose of BNT162b2 vaccine during the study period left the recovered and unvaccinated cohort on the day of vaccination and entered the recovered cohort at one dose 7 days later. One person who had recovered from Covid-19 and received a first dose of vaccine but then received a second dose during the study period left the cohort at a dose recovered at the time of the second vaccination. One person 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 A person 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 either the one-dose recovered cohort or the cohort recovered at one dose (depending on whether confirmed infection pre-vaccination or not) 90 days after positive test. One person who received a vaccine other than BNT162b2 left the study on the day of this vaccination.

Studies often compare infection rates in recovered or vaccinated people with those in unvaccinated people who have not been infected before. However, due to the high vaccination rate in Israel, this latest cohort is small and not representative of the general population. Furthermore, the Israeli Ministry of Health database does not contain complete information on these individuals. Therefore, we did not include unvaccinated and previously uninfected people in our analysis.

The study was approved by the Sheba Medical Center Institutional Review Board. 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

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

A Poisson regression model was fitted, adjusting for age group as of January 1, 2021 (16–39, 40–59, or ≥60), gender, sector of the population (General Jewish, Arab or ultra-Orthodox Jew). ), the calendar week and a measure of the risk of exposure. The latter was calculated for each person on each follow-up day based on the rate of new infections confirmed during the previous 7 days in the person’s area of ​​residence; this continuous measure was then categorized into 10 risk groups according to deciles.20 A medium exposure risk was assigned to those with missing residency data. To ensure that the effect of missing data was small, a descriptive comparison of people who had missing data with those who did not have missing data, as well as a multiple imputation analysis, was performed (see the Additional Analysis section 1) . The goodness of fit of the model was checked by examining the Pearson residuals in the categories.

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

To examine the effect of misclassifying people 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 a thorough comparison of the incidences of severe disease within and between cohorts with natural immunity and those with hybrid immunity; thus, only a descriptive analysis was performed. The results of a comparison of the incidences of severe Covid-19 between people who received two doses of BNT162b2 vaccine and those who received a third (booster) dose are reported elsewhere.21

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