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PurposeClose-contact rates are thought to be a significant driving force behind the dynamics of transmission for many infectious respiratory diseases. Efforts to control such infections typically focus on the practice of strict contact-avoidance measures. Yet, contact rates and their relation to transmission, and the impact of control measures, are seldom quantified. Here, we quantify the response of contact rates, transmission and new cases of COVID-19 to public health contact-restriction orders, and the associations among these three variables, in the Canadian province of British Columbia (BC) and within its two most densely populated regional health authorities: Fraser Health Authority (FHA) and Vancouver Coastal Health Authority (VCHA). MethodsWe obtained time series for self-reported close-contact rates from the BC Mix COVID-19 Survey, new reported cases of COVID-19 from the BC Center for Disease Control, and transmission rates based on dynamic model fits to reported cases. Our study period was from September 13, 2020 to February 19, 2021, during which three public health contact-restriction orders were introduced (October 26, November 7 and November 19, 2020). We used segmented linear regression to quantify impacts of public health orders, Pearson correlation to assess the instantaneous relation between contact rates and transmission, and vector autoregressive modeling to study the lagged relations among the three variables. ResultsOverall, declines in contact rates and transmission occurred concurrently with the announcement of public health orders, whereas declines in new cases showed a reporting delay of roughly two weeks. The impact of the first public health order (October 26, 2020) on contact rates and transmission was more pronounced than that of the other two health orders. Contact rates and transmission on the same day were strongly correlated (correlation coefficients = 0.64, 0.53 and 0.34 for BC, FHA, and VCHA, respectively). Moreover, contact rates were a significant time-series driver of COVID-19 and explained roughly 30% and 18% of the variation in new cases and transmission, respectively. Interestingly, increases in transmission and new cases were followed by reduced rates of contact: overall, average daily cases explained about 10% of the variation in provincial contact rates. ConclusionWe show that close-contact rates were a significant driver of transmission of COVID-19 in British Columbia, Canada and that they varied in response to public health orders. Our results also suggest a possible feedback, by which contact rates respond to recent changes in reported cases. 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.
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BackgroundThis study identified factors associated with hospital admission among people with laboratory-diagnosed COVID-19 cases in British Columbia. MethodsThis study was performed using the BC COVID-19 Cohort, which integrates data on all COVID-19 cases, hospitalizations, medical visits, emergency room visits, prescription drugs, chronic conditions and deaths. The analysis included all laboratory-diagnosed COVID-19 cases in British Columbia as of January 15th, 2021. We evaluated factors associated with hospital admission using multivariable Poisson regression analysis with robust error variance. FindingsFrom 56,874 COVID-19 cases included in the analyses, 2,298 were hospitalized. Models showed significant association of the following factors with increased hospitalization risk: male sex (adjusted risk ratio (aRR)=1.27; 95%CI=1.17-1.37), older age (p-trend <0.0001 across age groups with a graded increase in 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). Among women of reproductive age, in addition to age and comorbidities, pregnancy (aRR=2.69; 95%CI=1.42-5.07) was associated with increased risk of hospital admission. InterpretationOlder age, male sex, substance use, intellectual and developmental disability, chronic comorbidities, and pregnancy increase the risk of COVID-19-related hospitalization. FundingBC Centre for Disease Control, Canadian Institutes of Health Research. Research in contextO_ST_ABSEvidence before this studyC_ST_ABSFactors such as older age, social inequities and chronic health conditions have been associated to severe COVID-19 illness. Most of the evidence comes from studies that dont include all COVID-19 diagnoses in a jurisdiction), focusing on in-hospital mortality. In addition, mental illness and substance use were not evaluated in these studies. This study assessed factors associated with hospital admission among people with laboratory-diagnosed COVID-19 cases in British Columbia. Added value of this studyIn this population-based cohort study that included 56,874 laboratory-confirmed COVID-19 cases, older age, male sex, injection drug use, problematic alcohol use, intellectual and developmental disability, schizophrenia and psychotic disorders, chronic comorbidities and pregnancy were associated with the risk of hospitalization. Insulin-dependent diabetes was associated with higher risk of hospitalization, especially in the subpopulation younger than 40 years. To the best of our knowledge this is the first study reporting this finding, (insulin use and increased risk of COVID-19-related death has been described previously). Implications of all the available evidencePrioritization of vaccination in population groups with the above mentioned risk factors could reduce COVID-19 serious outcomes. The findings indicate the presence of the syndemic of substance use, mental illness and COVID-19, which deserve special public health considerations.