Social Contacts and Transmission of COVID-19 in British Columbia, Canada.

Background: Close-contact rates are thought to be a driving force behind the transmission of many infectious respiratory diseases. Yet, contact rates and their relation to transmission and the impact of control measures, are seldom quantified. We quantify the response of contact rates, reported cases and transmission of COVID-19, to public health contact-restriction orders, and examine the associations among these three variables in the province of British Columbia, Canada. Methods: We derived time series data for contact rates, daily cases and transmission of COVID-19 from a social contacts survey, reported case counts and by fitting a transmission model to reported cases, respectively. We used segmented regression to investigate impacts of public health orders; Pearson correlation to determine associations between contact rates and transmission; and vector autoregressive modeling to quantify lagged associations between contacts rates, daily cases, and transmission. Results: Declines in contact rates and transmission occurred concurrently with the announcement of public health orders, whereas declines in cases showed a reporting delay of about 2 weeks. Contact rates were a significant driver of COVID-19 and explained roughly 19 and 20% of the variation in new cases and transmission, respectively. Interestingly, increases in COVID-19 transmission and cases were followed by reduced contact rates: overall, daily cases explained about 10% of the variation in subsequent contact rates. Conclusion: We showed that close-contact rates were a significant time-series driver of transmission and ultimately of reported cases of COVID-19 in British Columbia, Canada and that they varied in response to public health orders. Our results also suggest possible behavioral feedback, by which increased reported cases lead to reduced subsequent contact rates. Our findings help to explain and validate the commonly assumed, but rarely measured, response of close contact rates to public health guidelines and their impact on the dynamics of infectious diseases.

Mental Health and Substance Use Associated with Hospitalization among People with COVID-19: A Population-Based Cohort Study.

This study identified factors associated with hospital admission among people with laboratory-diagnosed COVID-19 cases in British Columbia. The study used data from the BC COVID-19 Cohort, which integrates data on all COVID-19 cases with data on hospitalizations, medical visits, emergency room visits, prescription drugs, chronic conditions and deaths. The analysis included all laboratory-diagnosed COVID-19 cases in British Columbia to 15 January 2021. We evaluated factors associated with hospital admission using multivariable Poisson regression analysis with robust error variance. Of the 56,874 COVID-19 cases included in the analysis, 2298 were hospitalized. Factors associated with increased hospitalization risk were as follows: male sex (adjusted risk ratio (aRR) = 1.27; 95% CI = 1.17-1.37), older age (p-trend < 0.0001 across age groups increasing hospitalization risk with increasing age [aRR 30-39 years = 3.06; 95% CI = 2.32-4.03, to aRR 80+ years = 43.68; 95% CI = 33.41-57.10 compared to 20-29 years-old]), asthma (aRR = 1.15; 95% CI = 1.04-1.26), cancer (aRR = 1.19; 95% CI = 1.09-1.29), chronic kidney disease (aRR = 1.32; 95% CI = 1.19-1.47), diabetes (treated without insulin aRR = 1.13; 95% CI = 1.03-1.25, requiring insulin aRR = 5.05; 95% CI = 4.43-5.76), hypertension (aRR = 1.19; 95% CI = 1.08-1.31), injection drug use (aRR = 2.51; 95% CI = 2.14-2.95), intellectual and developmental disabilities (aRR = 1.67; 95% CI = 1.05-2.66), problematic alcohol use (aRR = 1.63; 95% CI = 1.43-1.85), immunosuppression (aRR = 1.29; 95% CI = 1.09-1.53), and schizophrenia and psychotic disorders (aRR = 1.49; 95% CI = 1.23-1.82). In an analysis restricted to women of reproductive age, pregnancy (aRR = 2.69; 95% CI = 1.42-5.07) was associated with increased risk of hospital admission. Older age, male sex, substance use, intellectual and developmental disability, chronic comorbidities, and pregnancy increase the risk of COVID-19-related hospitalization.