Abstract
Hybrid work schedules are increasingly popular in post-COVID-19 work culture, and their potential for reducing communicable disease transmission is unknown. Our study objectives were to measure and compare carbon dioxide (CO(2)) concentrations and subsequent infection in an office on "anchor days" vs. "hybrid days." We installed two CO(2) sensors in a breakroom connected to multipole staff areas in a 512 m(2) office. Measured CO(2) and office-reported occupancy data informed a Rudnick & Milton-adapted Wells-Riley model to estimate COVID-19 risks. Four modeling cases examined how uncertainty in infection prevalence and the proportion of symptomatic, in-person workers would impact COVID-19 risks. Air exchange rates (AER) were estimated with CO(2) measures. Linear models were used to assess season-adjusted associations between occupancy, day type, and mean and maximum CO(2). CO(2) concentrations peaked (~1500 ppm) on anchor days in Spring and Winter, with the lowest AERs estimated for these seasons. When assuming the same prevalence of infectious individuals, infection risks on hybrid workdays were 0.06-0.13 less than on anchor days. Behavioral assumptions (i.e., proportions of those who would work in-person even if symptomatic), had a notable impact on infection risk reductions offered by hybrid workdays. Occupancy and day type were associated (p<0.001) with mean and maximum CO(2) concentrations, adjusting for season. We provide initial support that hybrid work schedules may reduce infectious disease transmission. More data are needed to understand how work culture regarding concealed illnesses and preferences for working in person on hybrid days may affect the effectiveness of hybrid workdays in reducing risks.