Écart de mobilité : estimation des seuils de mobilité requis pour maîtriser le SRAS-CoV-2 au Canada.

CONTEXTE: Les interventions non pharmacologiques demeurent le principal moyen de maîtriser le coronavirus du syndrome respiratoire aigu sévère 2 (SRAS-CoV-2) d'ici à ce que la couverture vaccinale soit suffisante pour donner lieu à une immunité collective. Nous avons utilisé des données de mobilité anonymisées de téléphones intelligents afin de quantifier le niveau de mobilité requis pour maîtriser le SRAS-CoV-2 (c.-à-d., seuil de mobilité), et la différence par rapport au niveau de mobilité observé (c.-à-d., écart de mobilité). MÉTHODES: Nous avons procédé à une analyse de séries chronologiques sur l'incidence hebdomadaire du SRAS-CoV-2 au Canada entre le 15 mars 2020 et le 6 mars 2021. Le paramètre mesuré était le taux de croissance hebdomadaire, défini comme le rapport entre les cas d'une semaine donnée et ceux de la semaine précédente. Nous avons mesuré les effets du temps moyen passé hors domicile au cours des 3 semaines précédentes à l'aide d'un modèle de régression log-normal, en tenant compte de la province, de la semaine et de la température moyenne. Nous avons calculé le seuil de mobilité et l'écart de mobilité pour le SRAS-CoV-2. RÉSULTATS: Au cours des 51 semaines de l'étude, en tout, 888 751 personnes ont contracté le SRAS-CoV-2. Chaque augmentation de 10 % de l'écart de mobilité a été associée à une augmentation de 25 % du taux de croissance des cas hebdomadaires de SRAS-CoV-2 (rapport 1,25, intervalle de confiance à 95 % 1,20­1,29). Comparativement à la mobilité prépandémique de référence de 100 %, le seuil de mobilité a été plus élevé au cours de l'été (69 %, écart interquartile [EI] 67 %­70 %), et a chuté à 54 % pendant l'hiver 2021 (EI 52 %­55 %); un écart de mobilité a été observé au Canada entre juillet 2020 et la dernière semaine de décembre 2020. INTERPRÉTATION: La mobilité permet de prédire avec fiabilité et constance la croissance des cas hebdomadaires et il faut maintenir des niveaux faibles de mobilité pour maîtriser le SRAS-CoV-2 jusqu'à la fin du printemps 2021. Les données de mobilité anonymisées des téléphones intelligents peuvent servir à guider le relâchement ou le resserrement des mesures de distanciation physique provinciales et régionales.

A sub-national real-time epidemiological and vaccination database for the COVID-19 pandemic in Canada.

The COVID-19 pandemic has demonstrated the need for real-time, open-access epidemiological information to inform public health decision-making and outbreak control efforts. In Canada, authority for healthcare delivery primarily lies at the provincial and territorial level; however, at the outset of the pandemic no definitive pan-Canadian COVID-19 datasets were available. The COVID-19 Canada Open Data Working Group was created to fill this crucial data gap. As a team of volunteer contributors, we collect daily COVID-19 data from a variety of governmental and non-governmental sources and curate a line-list of cases and mortality for all provinces and territories of Canada, including information on location, age, sex, travel history, and exposure, where available. We also curate time series of COVID-19 recoveries, testing, and vaccine doses administered and distributed. Data are recorded systematically at a fine sub-national scale, which can be used to support robust understanding of COVID-19 hotspots. We continue to maintain this dataset, and an accompanying online dashboard, to provide a reliable pan-Canadian COVID-19 resource to researchers, journalists, and the general public.

The uneven impacts of avoiding public transit on riders' access to healthcare during COVID-19.

Background: During the COVID-19 pandemic, many urban residents stopped riding public transit despite their reliance on it to reach essential services like healthcare. Few studies have examined the implications of public transit reliance on riders' ability to reach healthcare when transit is disrupted. To understand how shocks to transportation systems impact healthcare access, this study measures the impact of avoiding public transit on the ability of riders to access healthcare and pharmacy services during lockdowns. Methods: We deployed a cross-sectional survey of residents of Toronto and Vancouver in May 2020 through Facebook advertisements and community list-serves. Eligibility criteria included riding transit at least weekly prior to the pandemic and subsequent cessation of transit use during the pandemic. We applied multivariable modified Poisson models to identify socio-demographic, transportation, health-related, and neighborhood predictors of experiencing increased difficulty accessing healthcare and getting prescriptions while avoiding public transit. We also predicted which respondents reported deferring medical care until they felt comfortable riding transit again. Results: A total of 4367 former transit riders were included (64.2% female, 56.1% Toronto residents). Several factors were associated with deferring medical care including: being non-White (Toronto, APR, 1.14; 95% CI, 1.00-1.29; Vancouver, APR, 1.52; 95% CI, 1.26-1.84), having a physical disability (Toronto, APR, 1.20; 95% CI, 1.00-1.45; Vancouver, APR, 1.42; 95% CI, 1.08-1.87), having no vehicle access (Toronto, APR, 1.74; 95% CI, 1.51-2.00; Vancouver, APR, 2.74; 95% CI, 2.20-3.42), and having low income (Toronto, APR, 1.77; 95% CI, 1.44-2.17; Vancouver, APR, 1.51; 95% CI, 1.06-2.14). Discussion: During COVID-19 in two major Canadian cities, former transit riders from marginalized groups were more likely to defer medical care than other former riders. COVID-19 related transit disruptions may have imposed a disproportionate burden on the health access of marginalized individuals. Policymakers should consider prioritizing healthcare access for vulnerable residents during crises.

The association of estimated cardiorespiratory fitness with COVID-19 incidence and mortality: A cohort study.

BACKGROUND: It has been suggested that cardiorespiratory fitness (CRF) may be used to identify those at greatest risk for severe COVID-19 illness. However, no study to date has examined the association between CRF and COVID-19. The objectives of this study were to determine whether CRF is independently associated with testing positive with or dying from COVID-19. METHODS: This is a prospective cohort study of 2,690 adults from the UK Biobank Study that were followed from March 16th, 2020 to July 26th, 2020. Participants who were tested for COVID-19 and had undergone CRF assessment were examined. CRF was estimated (eCRF) and categorized as low (<20th percentile), moderate (20th to 80th percentile) and high (≥80th percentile) within sex and ten-year age groups (e.g. 50-60 years). Participants were classified as having COVID-19 if they tested positive (primarily PCR tests) at an in-patient or out-patient setting as of July 26, 2020. Participants were classified as having died from COVID-19 if the primary or underlying cause of death was listed ICD-10 codes U071 or U072 by June 30th, 2020. Adjusted risk ratios (aRR) and 95% confidence intervals (CI) were estimated and a forward model building approach used to identify covariates. FINDINGS: There was no significant association between eCRF and testing positive for COVID-19. Conversely, individuals with moderate (aRR = 0.43, 95% CI: 0.25, 0.75) and high fitness (aRR = 0.37, 95% CI: 0.16, 0.85) had a significantly lower risk of dying from COVID-19 than those with low fitness. CONCLUSIONS: While eCRF was not significantly associated with testing positive for COVID-19, we observed a significant dose-response between having higher eCRF and a decreased risk of dying from COVID-19. This suggests that prior gains in CRF could be protective against dying from COVID-19 should someone develop the virus.

The mobility gap: estimating mobility thresholds required to control SARS-CoV-2 in Canada.

BACKGROUND: Nonpharmaceutical interventions remain the primary means of controlling severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) until vaccination coverage is sufficient to achieve herd immunity. We used anonymized smartphone mobility measures to quantify the mobility level needed to control SARS-CoV-2 (i.e., mobility threshold), and the difference relative to the observed mobility level (i.e., mobility gap). METHODS: We conducted a time-series study of the weekly incidence of SARS-CoV-2 in Canada from Mar. 15, 2020, to Mar. 6, 2021. The outcome was weekly growth rate, defined as the ratio of cases in a given week versus the previous week. We evaluated the effects of average time spent outside the home in the previous 3 weeks using a log-normal regression model, accounting for province, week and mean temperature. We calculated the SARS-CoV-2 mobility threshold and gap. RESULTS: Across the 51-week study period, a total of 888 751 people were infected with SARS-CoV-2. Each 10% increase in the mobility gap was associated with a 25% increase in the SARS-CoV-2 weekly case growth rate (ratio 1.25, 95% confidence interval 1.20-1.29). Compared to the prepandemic baseline mobility of 100%, the mobility threshold was highest in the summer (69%; interquartile range [IQR] 67%-70%), and dropped to 54% in winter 2021 (IQR 52%-55%); a mobility gap was present in Canada from July 2020 until the last week of December 2020. INTERPRETATION: Mobility strongly and consistently predicts weekly case growth, and low levels of mobility are needed to control SARS-CoV-2 through spring 2021. Mobility measures from anonymized smartphone data can be used to guide provincial and regional loosening and tightening of physical distancing measures.

Has public health messaging during the COVID-19 pandemic reflected local risks to health?: A content analysis of tweeting practices across Canadian geographies.

During the COVID-19 pandemic, public health agencies and decision-makers have used social media to disseminate information, encourage changes to behaviour and promote community supports and resources. Their communications have served to educate the public on risks and initiate the widespread adoption of public health measures to 'flatten the curve'. We conducted a content analysis of COVID-19 Tweets by Canadian public health accounts during the first 6 months of the pandemic to explore differences in Tweeting practices by geography and identify opportunities to improve risk communication. We found that Canadian public health accounts in particular geographic settings did not always apply best practices for health communication. Tweeting practices differed considerably between jurisdictions with varying burdens of COVID-19. Going forward, Tweets authored by public health accounts that promote behaviour change and community-building ought to be utilized whenever risks to health are high to reflect an increase in disease transmission requiring intervention. Our study highlights the need for public health communicators to deliver messaging that is relevant for the levels of risk that their audiences are encountering in a given geographic context.

Examining Tweet Content and Engagement of Canadian Public Health Agencies and Decision Makers During COVID-19: Mixed Methods Analysis.

BACKGROUND: Effective communication during a health crisis can ease public concerns and promote the adoption of important risk-mitigating behaviors. Public health agencies and leaders have served as the primary communicators of information related to COVID-19, and a key part of their public outreach has taken place on social media platforms. OBJECTIVE: This study examined the content and engagement of COVID-19 tweets authored by Canadian public health agencies and decision makers. We propose ways for public health accounts to adjust their tweeting practices during public health crises to improve risk communication and maximize engagement. METHODS: We retrieved data from tweets by Canadian public health agencies and decision makers from January 1, 2020, to June 30, 2020. The Twitter accounts were categorized as belonging to either a public health agency, regional or local health department, provincial health authority, medical health officer, or minister of health. We analyzed trends in COVID-19 tweet engagement and conducted a content analysis on a stratified random sample of 485 tweets to examine the message functions and risk communication strategies used by each account type. RESULTS: We analyzed 32,737 tweets authored by 118 Canadian public health Twitter accounts, of which 6982 tweets were related to COVID-19. Medical health officers authored the largest percentage of COVID-19-related tweets (n=1337, 35%) relative to their total number of tweets and averaged the highest number of retweets per COVID-19 tweet (112 retweets per tweet). Public health agencies had the highest frequency of daily tweets about COVID-19 throughout the study period. Compared to tweets containing media and user mentions, hashtags and URLs were used in tweets more frequently by all account types, appearing in 69% (n=4798 tweets) and 68% (n=4781 tweets) of COVID-19-related tweets, respectively. Tweets containing hashtags also received the highest average retweets (47 retweets per tweet). Our content analysis revealed that of the three tweet message functions analyzed (information, action, community), tweets providing information were the most commonly used across most account types, constituting 39% (n=181) of all tweets; however, tweets promoting actions from users received higher than average retweets (55 retweets per tweet). When examining tweets that received one or more retweet (n=359), the difference between mean retweets across the message functions was statistically significant (P<.001). The risk communication strategies that we examined were not widely used by any account type, appearing in only 262 out of 485 tweets. However, when these strategies were used, these tweets received more retweets compared to tweets that did not use any risk communication strategies (P<.001) (61 retweets versus 13 retweets on average). CONCLUSIONS: Public health agencies and decision makers should examine what messaging best meets the needs of their Twitter audiences to maximize sharing of their communications. Public health accounts that do not currently employ risk communication strategies in their tweets may be missing an important opportunity to engage with users about the mitigation of health risks related to COVID-19.

Measures of Adiposity and Risk of Testing Positive for SARS-CoV-2 in the UK Biobank Study.

Objective: To assess if body mass index (BMI) and high waist circumference (HWC) are associated with testing positive for the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Methods: 9,386 UK Biobank study participants tested for SARS-CoV-2 from March 16th 2020 to June 29th 2020 were analyzed. A forward model building approach was used to estimate adjusted risk ratios (RR) and 95% confidence intervals (95% CI). Analyses were stratified by age due to a significant first-order interaction between age and HWC. Results: Approximately 17% (n = 1,577) of participants tested positive for SARS-CoV-2. BMI category had a linear association with testing positive for SARS-CoV-2 among participants <65 years (RR = 1.09, 95% CI 1.02-1.17). For participants ≥65 years, only obesity class II (RR = 1.38, 95% CI 1.10-1.74) had a significantly greater risk of testing positive for SARS-CoV-2 than those who were underweight/normal weight. While HWC was not associated with testing positive for SARS-CoV-2 in those <65 years, having an HWC was associated with an increased risk of testing positive for SARS-CoV-2 in participants ≥65 years (RR = 1.12, 95% CI 1.00-1.27). Conclusion: The associations of BMI and HWC with testing positive for SARS-CoV-2 differed by age. Notably, HWC was associated with testing positive in those ≥65 years, but not those who were younger, independent of BMI. This suggests that measures of adiposity in addition to BMI may be used to identify older individuals at greater risk of testing positive for SARS-CoV-2.

Open government data, uncertainty and coronavirus: An infodemiological case study.

Governments around the world have made data on COVID-19 testing, case numbers, hospitalizations and deaths openly available, and a breadth of researchers, media sources and data scientists have curated and used these data to inform the public about the state of the coronavirus pandemic. However, it is unclear if all data being released convey anything useful beyond the reputational benefits of governments wishing to appear open and transparent. In this analysis we use Ontario, Canada as a case study to assess the value of publicly available SARS-CoV-2 positive case numbers. Using a combination of real data and simulations, we find that daily publicly available test results probably contain considerable error about individual risk (measured as proportion of tests that are positive, population based incidence and prevalence of active cases) and that short term variations are very unlikely to provide useful information for any plausible decision making on the part of individual citizens. Open government data can increase the transparency and accountability of government, however it is essential that all publication, use and re-use of these data highlight their weaknesses to ensure that the public is properly informed about the uncertainty associated with SARS-CoV-2 information.