Risk Factors for COVID-19: Community Exposure and Mask-Wearing

Importance: Many studies have focused on characteristics of symptomatic COVID-19 patients and clinical risk factors. This study reports prevalence of COVID-19 in the general population and identifies factors that affect exposure to the virus. Objective: To measure the prevalence of COVID-19 in a hospital service area and identify factors that may increase or decrease the risk of infection and exposure. Design: This cohort study collected survey information relating to work and living situations, income, behavior, socio-demographic characteristics and pre-pandemic health characteristics. This data was combined with polymerase chain reaction (PCR) testing and two different serologic assays. Setting and Participants: Our sampling frame was the primary care population of a Level 1 medical center in the Northeast U.S.. A random sample was drawn, stratified by age and gender. About 20 percent opted in and 1,694 completed the survey. Participants were invited to receive PCR and serologic testing. A total of 454 individuals provided samples between June 25th and June 28th, 2020. Research Methods: Survey data was collected via Redcap. PCR testing was conducted at a community testing site using nasopharyngeal swabs. Serologic testing was done using two different methods to ensure the reliability of the results. Main Outcomes: Positivity rate was used to calculate approximate prevalence, hospitalization rate and infection fatality rate (IFR). Survey data was used to analyze risk factors, including the number of contacts reported by study participants. Results: We found a positivity rate of 2.2 percent, a hospitalization rate of 1.2 percent and an adjusted IFR of 0.55 percent. The number of contacts with adults and seniors increases the probability of becoming infected. Occupation, living in apartment versus a house, and wearing a facial mask outside work increased probability of COVID-19 infection. Conclusions and Relevance: Based on the IFR and the number of deaths, estimations about the total number of infections in similar demographic areas with different infection rates can be made. Comparing this number with the number of officially reported infections leads to an estimate of unreported cases. Occupational, living-situation, and behavioral data may aid in the identification of non-clinical factors affecting SARS-CoV-2 exposure and infection.