A cross-sectional study nested within the VACCICO-VAO prospective cohort study was performed. The characteristics of the VACCICO-VAO cohort have been described previously [
21]. In summary, the Hospital Universitario Rio Hortega (HURH) in Valladolid, Spain, vaccinated all HCWs between January and March 2021. The HCWs were invited to participate in a prospective cohort study. As a part of the cohort follow-up, from October to December 2022 (coinciding with the administration of the fourth dose of SARS-CoV‑2 vaccine), all participants were invited to complete a survey on the risk factors for SARS-CoV‑2 infection during the pandemic period. The cohort study was approved by the Ethics Committee for Drug Research (CEIm) of the HURH (protocol number: CEIC 21-E0031).
Participants and recruitment
All HCWs who were vaccinated against SARS-CoV-2 at the beginning of 2021 and were enrolled in the VACCICO-VAO cohort were identified. In October 2022, all participants in the VACCICO-VAO cohort were invited to participate in the survey. Two methods were used for survey recruitment: a) All participants in the VACCICO-VAO cohort were invited by email, and b) participants were reminded when they were vaccinated at the Occupational Risk Prevention Service.
Measures
The survey contained two sections to measure occupational and nonoccupational risk factors. For the occupational risk factors, respondents were asked to identify their grade of exposure to SARS-CoV‑2 during the workday, which was classified into three categories: (i) very high: HCWs working in intensive care units, COVID wards or emergency wards; (ii) high: HCWs working in non-COVID hospital wards and operating rooms or performing complementary tests with air or digestive exposure (bronchoscopy, endoscopy, ear nose and throat and maxillofacial examinations) and (iii) intermediate: HCWs working in consultations, laboratories, administrative staff, pharmacies, dining rooms, and cafeterias or performing other complementary tests. The responders were also asked whether they worked directly and for long periods of time in rooms or spaces in which high-flow oxygen therapy or nebulization was administered, and whether they worked on night shifts or as 24-hour on-site guards.
For the nonoccupational risk factors, respondents were asked about their home characteristics and household members (number of people living in the home, number of people with direct exposure to SARS-CoV‑2, number of students), shared spaces at home, such as elevators or stairs, and location (rural, urban, peri-urban, and others). They were asked about their means of transportation (What is your most common means of transportation to the hospital?), and lifestyle (exposure to the virus outside the workplace). To collect data on social distancing, the participants were invited to answer two questions in this section: (1) how do you define yourself from the perspective of social contact outside the workplace? with three options: (i) little social contact, (ii) regular social contact but maintaining social distance or (iii) regular social contact with little or no social distance and (2) number of times per week that they attended social events, such as dinners, lunches, going out for snacks, theaters, concerts and gyms. For all questions, participants were asked to describe their actions over the previous year.
The demographic information included age, sex, ethnicity, job title, professional category, and comorbidities at the start of the study period. Data on vaccination status, SARS-CoV‑2 infections, and reinfections were prospectively collected during the cohort follow-up. Data on infection and reinfection were collected in the survey and double checked in the registry of the Occupational Risk Prevention Service. Data on vaccinations for other diseases (measles, tuberculosis, and influenza) were also included in the survey.
Statistical analysis
Participants were grouped into three age groups (under 35 years, 35–49 years, and 50 years or older) to analyze the role of different risk factors according to age.
We compared the different risk factors for having a SARS-CoV‑2 infection at least once using simple logistic regression and the mean number of COVID-19 episodes using simple linear regression. Factors with statistically significant associations in the unadjusted model were included in the multivariable analysis. To assess the evolution of risk factors during the pandemic, we performed a Cox survival analysis. We use IBM SPSS Statistics for Windows, Version 26.0 (IBM Corp., Armonk, NY, USA) for the analysis.