Study Population

The HEROES-RECOVER network includes prospective cohorts from two studies: HEROES (the Arizona Healthcare, Emergency Response, and Other Essential Workers Surveillance Study) and RECOVER (Research on the Epidemiology of SARS-CoV-2 in Essential Response Personnel). The network was initiated in July 2020 and has a shared protocol, described previously and outlined in the Methods section of the Supplementary Appendix (available with the full text of this article at NEJM.org). Participants were enrolled in six U.S. states: Arizona (Phoenix, Tucson, and other areas), Florida (Miami), Minnesota (Duluth), Oregon (Portland), Texas (Temple), and Utah (Salt Lake City). To minimize potential selection biases, recruitment of participants was stratified according to site, sex, age group, and occupation. The data for this analysis were collected from December 14, 2020, to April 10, 2021. All participants provided written informed consent. The individual protocols for the RECOVER study and the HEROES study were reviewed and approved by the institutional review boards at participating sites or under a reliance agreement.

Participant-Reported Outcome Measures

Sociodemographic and health characteristics were reported by the participants in electronic surveys completed at enrollment. Each month, participants reported their potential exposure to SARS-CoV-2 and their use of face masks and other employer-recommended personal protective equipment (PPE) according to four measures: hours of close contact with (within 3 feet [1 m] of) others at work (coworkers, customers, patients, or the public) in the previous 7 days; the percentage of time using PPE during those hours of close contact at work; hours of close contact with someone suspected or confirmed to have Covid-19 at work, at home, or in the community in the previous 7 days; and the percentage of time using PPE during those hours of close contact with the virus.

Active surveillance for symptoms associated with Covid-19 — defined as fever, chills, cough, shortness of breath, sore throat, diarrhea, muscle aches, or a change in smell or taste — was conducted through weekly text messages, emails, and reports obtained directly from the participant or from medical records. When a Covid-19–like illness was identified, participants completed electronic surveys at the beginning and end of the illness to indicate the date of symptom onset, symptoms, temperatures, the number of days spent sick in bed for at least half the day, the receipt of medical care, and the last day of symptoms. Febrile symptoms associated with Covid-19 were defined as fever, feverishness, chills, or a measured temperature higher than 38°C.

Laboratory Methods

Participants provided a mid-turbinate nasal swab weekly, regardless of whether they had symptoms associated with Covid-19, and provided an additional nasal swab and saliva specimen at the onset of a Covid-19–like illness. Supplies and instructions for participants were standardized across sites. Specimens were shipped on weekdays on cold packs and were tested by means of qualitative reverse-transcriptase–polymerase-chain-reaction (RT-PCR) assay at the Marshfield Clinic Research Institute (Marshfield, WI). Quantitative RT-PCR assays were conducted at the Wisconsin State Laboratory of Hygiene (Madison, WI). SARS-CoV-2 whole-genome sequencing was conducted at the Centers for Disease Control and Prevention, in accordance with previously published protocols,4 for viruses detected in 22 participants who were infected at least 7 days after vaccine dose 1 (through March 3, 2021), as well as for viruses detected in 3 or 4 unvaccinated participants matched to each of those 22 participants in terms of site and testing date, as available (71 total matched participants). Viral lineages were categorized as variants of concern, variants of interest, or other. We compared the percentage of variants of concern (excluding variants of interest) in participants who were at least partially vaccinated (≥14 days after dose 1) with the percentage in participants who were unvaccinated.

Vaccination Status

Covid-19 vaccination status was reported by the participants in electronic and telephone surveys and through direct upload of images of vaccination cards. In addition, data from electronic medical records, occupational health records, or state immunization registries were reviewed at the sites in Minnesota, Oregon, Texas, and Utah. At the time of specimen collection, participants were considered to be fully vaccinated (≥14 days after dose 2), partially vaccinated (≥14 days after dose 1 and <14 days after dose 2), or unvaccinated or to have indeterminate vaccination status (<14 days after dose 1).

Statistical Analysis

The primary outcome was the time to RT-PCR–confirmed SARS-CoV-2 infection in vaccinated participants as compared with unvaccinated participants. Secondary outcomes included the viral RNA load, frequency of febrile symptoms, and duration of illness among participants with SARS-CoV-2 infection.

Table 1. Table 1. Characteristics of the Participants According to SARS-CoV-2 Test Results and Vaccination Status.

The effectiveness of mRNA vaccines was estimated for full vaccination and partial vaccination. Participants with indeterminate vaccination status were excluded from the analysis. Hazard ratios for SARS-CoV-2 infection in vaccinated participants as compared with unvaccinated participants were estimated with the Andersen–Gill extension of the Cox proportional hazards model, which accounted for time-varying vaccination status. Unadjusted vaccine effectiveness was calculated with the following formula: 100%×(1−hazard ratio). An adjusted vaccine effectiveness model accounted for potential confounding in vaccination status with the use of an inverse probability of treatment weighting approach.5 Generalized boosted regression trees were used to estimate individual propensities to be at least partially vaccinated during each study week, on the basis of baseline sociodemographic and health characteristics and the most recent reports of potential virus exposure and PPE use (Table 1 and Table S2 in the Supplementary Appendix).6 Predicted propensities were then used to calculate stabilized weights. Cox proportional hazards models incorporated these stabilized weights, as well as covariates for site, occupation, and a daily indicator of local viral circulation, which was the percentage positive of all SARS-CoV-2 tests performed in the local county (Fig. S1). A sensitivity analysis removed person-days when participants had possible misclassification of vaccination status or infection or when the local viral circulation fell below 3%.

Because there was a relatively small number of breakthrough infections, for the evaluation of possible attenuation effects of vaccination, participants with RT-PCR–confirmed SARS-CoV-2 infection who were partially vaccinated and those who were fully vaccinated were combined into a single vaccinated group, and results for this group were compared with results for participants with SARS-CoV-2 infection who were unvaccinated. Means for the highest viral RNA load measured during infection were compared with the use of a Poisson model adjusted for days from symptom onset to specimen collection and for days with the specimen in transit to the laboratory. Dichotomous outcomes were compared with the use of binary log-logistic regression for the calculation of relative risks. Means for the duration of illness were compared with the use of Student’s t-test under the assumption of unequal variances. All analyses were conducted with SAS software, version 9.4 (SAS Institute), and R software, version 4.0.2 (R Foundation for Statistical Computing).



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Topics #Attenuation #BNT162b2 #COVID19 #mRNA1273 #prevention #Vaccines