Spread of infection and treatment interruption among Japanese workers during the COVID-19 pandemic: a cross-sectional study (preprint)

ABSTRACT

ObjectivesThis study aimed to examine the relationship between regional infection level and treatment interruption for chronic diseases. MethodsA cross-sectional Internet monitoring survey was performed between December 22 and 26, 2020. Data from 9,510 (5,392 males and 4,118 females) participants needing regular treatment or hospital visits were analyzed. We determined the age-sex- and multivariate-adjusted odds ratios (ORs) of treatment interruption associated with various indices of infection level by nesting multilevel logistic models in prefecture of residence. In the multivariate model, sex, age, marital status, job type, equivalent household income, education, self-rated health, and anxiety were adjusted. ResultsThe ORs of treatment interruption for the lowest versus highest levels of infection were 1.32 (95% CI 1.09-1.59) for the overall incidence rate (per 1,000 population), 1.34 (95% CI 1.10-1.63) for the overall number of people infected, 1.28 (95% CI 1.06-1.54) for the monthly incidence rate (per 1,000 population), and 1.38 (95% CI 1.14-1.67) for the number of people infected per month. For each index of infection level, higher infection was linked to more workers experiencing treatment interruption. ConclusionHigher local infection levels were linked to more workers experiencing treatment interruption. Our results suggest that apart from individual characteristics such as socioeconomic and health status, treatment interruptions during the pandemic were also subject to contextual effects related to regional infection levels. Preventing community spread of COVID-19 may thus protect individuals from indirect effects of the pandemic, such as treatment interruption.