Incidence of outbreak-associated COVID-19 cases by industry in Ontario, Canada, April 1, 2020-March 31, 2021 (preprint)

Objectives The objective of our study was to estimate the rate of workplace outbreak-associated cases of COVID-19 by industry in labour market participants aged 15-69 years who reported working the majority of hours outside the home in Ontario, Canada. Methods We conducted a population based cross-sectional study of COVID-19 workplace outbreaks and associated-cases reported in Ontario between April 1, 2020 and March 31, 2021. All outbreaks were manually classified into two digit North American Industry Classification System (NAICS) codes. We obtained denominator data from the Statistics Canada Labour Force Survey in order to estimate the incidence of outbreak-associated cases per 100,000,000 hours amongst individuals who reported the majority of hours were worked outside the home. We performed this analysis across industries and in three distinct time periods. Results Overall, 12% of cases were attributed to workplace outbreaks among working age adults across our study period. While incidence varied across the time periods, the five industries with the highest incidence rates across our study period were agriculture; healthcare and social assistance; food manufacturing; educational services; and, transportation and warehousing. Conclusions Certain industries have consistently increased incidence of COVID-19 over the course of the pandemic. These results may assist in ongoing efforts to reduce transmission of COVID-19, by prioritizing resources, as well as industry-specific guidance, vaccination, and public health messaging.

Neighbourhood-level risk factors of COVID-19 incidence and mortality (preprint)

Background Racialized and low income communities face disproportionally high rates of coronavirus 2019 (COVID-19) infection and death. However, data on inequities in COVID-19 across granular categories of socio-demographic characteristics is more sparse. Methods Neighbourhood-level counts of COVID-19 cases and deaths in Ontario, Canada recorded as of July 28 th , 2020 were extracted from provincial and local reportable infectious disease surveillance systems. Associations between COVID-19 incidence and mortality and 18 neighbourhood-level measures of immigration, race, housing and socio-economic characteristics were estimated with Poisson generalized linear mixed models. Housing characteristic variables were subsequently added to models to explore if housing may have a confounding influence on the relationships between immigration, race, and socio-economic status and COVID-19 incidence. Results There were large inequities in COVID-19 incidence and mortality across the socio-demographic variables examined. Neighbourhoods having a higher proportion immigrants, racialized populations, large households and low socio-economic status were associated with COVID-19 risk. Adjusting for housing characteristics, especially unsuitably crowded housing, attenuated COVID-19 risks. However persistent risk remained for neighbourhoods having high proportions of immigrants, racialized populations, and proportion of Black, Latin American, and South Asian residents. Conclusions Socio-demographic factors account for some of the neighbourhood-level differences in COVID-19 across Ontario. Housing characteristics account for a portion, but not all, of the excess burden of COVID-19 experienced by immigrant, racialized, low income and low education populations.