Public transit mobility as a leading indicator of COVID-19 transmission in 40 cities during the first wave of the pandemic.

Background: The rapid global emergence of the COVID-19 pandemic in early 2020 created urgent demand for leading indicators to track the spread of the virus and assess the consequences of public health measures designed to limit transmission. Public transit mobility, which has been shown to be responsive to previous societal disruptions such as disease outbreaks and terrorist attacks, emerged as an early candidate. Methods: We conducted a longitudinal ecological study of the association between public transit mobility reductions and COVID-19 transmission using publicly available data from a public transit app in 40 global cities from March 16 to April 12, 2020. Multilevel linear regression models were used to estimate the association between COVID-19 transmission and the value of the mobility index 2 weeks prior using two different outcome measures: weekly case ratio and effective reproduction number. Results: Over the course of March 2020, median public transit mobility, measured by the volume of trips planned in the app, dropped from 100% (first quartile (Q1)-third quartile (Q3) = 94-108%) of typical usage to 10% (Q1-Q3 = 6-15%). Mobility was strongly associated with COVID-19 transmission 2 weeks later: a 10% decline in mobility was associated with a 12.3% decrease in the weekly case ratio (exp(ß) = 0.877; 95% confidence interval (CI): [0.859-0.896]) and a decrease in the effective reproduction number (ß = -0.058; 95% CI: [-0.068 to -0.048]). The mobility-only models explained nearly 60% of variance in the data for both outcomes. The adjustment for epidemic timing attenuated the associations between mobility and subsequent COVID-19 transmission but only slightly increased the variance explained by the models. Discussion: Our analysis demonstrated the value of public transit mobility as a leading indicator of COVID-19 transmission during the first wave of the pandemic in 40 global cities, at a time when few such indicators were available. Factors such as persistently depressed demand for public transit since the onset of the pandemic limit the ongoing utility of a mobility index based on public transit usage. This study illustrates an innovative use of "big data" from industry to inform the response to a global pandemic, providing support for future collaborations aimed at important public health challenges.

Development of a ParticipACTION App-Based Intervention for Improving Postsecondary Students' 24-Hour Movement Guideline Behaviors: Protocol for the Application of Intervention Mapping.

BACKGROUND: The Canadian 24-Hour Movement Guidelines for adults provide specific recommendations for levels of physical activity, sedentary behavior, and sleep (ie, the movement behaviors) required for optimal health. Performance of the movement behaviors is associated with improved mental well-being. However, most postsecondary students do not meet the movement behavior recommendations within the Canadian 24-Hour Movement Guidelines and experience increased stress and declining well-being, suggesting the need for an intervention targeting students' movement behaviors. OBJECTIVE: We aimed to develop and implement a theory-informed intervention intended to improve the movement behaviors and mental well-being of first-year postsecondary students. METHODS: The Intervention Mapping protocol was applied in the development and implementation of the intervention. Intervention Mapping entailed performing a needs assessment, determining the intervention outcomes, selecting theory- and evidence-based change methods and applications, preparing and producing intervention plans and materials, developing the implementation plan, and finally developing an evaluation plan. The Theoretical Domains Framework and the Behavior Change Wheel were also used in conjunction with the Intervention Mapping protocol to ensure a solid theoretical basis for the intervention. This protocol led to the development and implementation of a 6-week, theory-informed ParticipACTION app-based intervention aimed at helping first-year postsecondary students improve their movement behaviors and mental well-being. The developed app content provided students with information on each of the movement behaviors and behavioral strategies (ie, goal setting, action planning, monitoring, and coping planning). The use of Intervention Mapping allowed for the continuous involvement of various multidisciplinary partners and end users, ensuring that the intervention design and implementation was appropriate for the target audience. The feasibility, acceptability, and potential impact of the intervention will be examined in a subsequent proof-of-concept study at 2 Canadian university campuses. RESULTS: Participant recruitment occurred during September 2021, and the intervention was conducted from October to December 2021. The deadline for completion of the postintervention questionnaire by participants was mid-December 2021. The analysis of data examining the feasibility, acceptability, and potential impact of the intervention began in January 2022, with the publication of the proof-of-concept evaluation expected in 2023. CONCLUSIONS: Intervention Mapping with the Theoretical Domains Framework and Behavior Change Wheel was a useful approach to combine evidence and theoretical concepts to guide the design and implementation of a ParticipACTION app-based intervention targeting postsecondary students' movement behaviors and mental well-being. This process may serve as an example for other researchers developing multiple behavior change app-based interventions. Should the forthcoming evaluation demonstrate the intervention's acceptability, feasibility, and potential impact, the intervention may provide a scalable method of improving postsecondary students' movement behaviors and mental well-being. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR1-10.2196/39977.

Wearable Device Validity in Measuring Steps, Energy Expenditure, and Heart Rate Across Age, Gender, and Body Mass Index: Data Analysis From a Systematic Review.

BACKGROUND: This paper examined whether the criterion validity of step count (SC), energy expenditure (EE), and heart rate (HR) varied across studies depending on the average age, body mass index (BMI), and predominant gender of participants. METHODS: Data from 1536 studies examining the validity of various wearable devices were used. Separate multilevel regression models examined the associations among age, gender, and BMI with device criterion validity assessed using mean absolute percent error (MAPE) at the study level. RESULTS: MAPE values were reported in 970 studies for SC, 328 for EE, and 238 for HR, respectively. There were several significant differences in MAPE between age, gender, and BMI categories for SC, EE, and HR. SC MAPE was significantly different for older adults compared with adults. Compared with studies among normal-weight populations, MAPE was greater among studies with overweight samples for SC, HR, and EE. Comparing studies with more women than men, MAPE was significantly greater for EE and HR. CONCLUSIONS: There are important differences in the criterion validity of commercial wearable devices across studies of varying ages, BMIs, and genders. Few studies have examined differences in error between different age groups, particularly for EE and HR.

The availability and distribution of vaping retailers across Ontario neighbourhoods, 2016-2019.

OBJECTIVES: To characterize the distribution of vaping retailers and examine the association between neighbourhood income and vaping retailer availability in Ontario prior to and after regulatory changes to the vaping market in 2018. METHODS: We quantified vaping access by number of vaping retailers for 19,964 dissemination areas (DAs) in Ontario and percentage of schools near a vaping retailer. We used mixed-effects regression models to examine the associations between vaping access and neighbourhood income in 2018 and 2019. RESULTS: Between 2016 and 2019, the number of vaping retailers in Ontario increased by 22.6% (5999 to 7355), despite a mild drop from 2016 to 2018. In 2019, 59.7% of urban neighbourhoods had one or more vaping retailers within 1000 m of their geographic centre, and 79.4% of elementary, 82.8% of secondary, and 84.2% of post-secondary schools had at least one within 1000 m. Neighbourhood income was associated with access to vaping retailers, with a greater number in low-income regions. In 2019, neighbourhoods in the lowest income quintile had over twice the number of vaping retailers per capita within 1000 m compared to the highest income quintile (adjusted incidence rate ratio 2.40; 95% CI 2.24-2.58). Increases over time in access to vaping retailers did not differ by geographic region, neighbourhood income quintile, or school type. CONCLUSION: We observed a substantial increase in access to vaping retailers in Ontario including proximity to elementary and secondary schools following the 2018 provincial marketing regulations and federal nicotine regulations. Access to vaping was greatest in low-income neighbourhoods and may contribute to established inequities in vaping-related adverse events.

RéSUMé: OBJECTIFS: Caractériser la répartition des détaillants de vapotage et examiner l'association entre le revenu du quartier et la disponibilité des détaillants de vapotage en Ontario avant et après les modifications réglementaires du marché du vapotage en 2018. MéTHODES: Nous avons quantifié l'accès au vapotage selon le nombre de détaillants de vapotage pour 19 964 aires de diffusion (DA) en Ontario et le pourcentage d'écoles à proximité d'un détaillant de vapotage. Nous avons utilisé des modèles de régression à effets mixtes pour examiner les associations entre l'accès au vapotage et le revenu du quartier en 2018 et 2019. RéSULTATS: Entre 2016 et 2019, le nombre de détaillants de vapotage en Ontario a augmenté de 22,6 % (5 999 à 7 355), malgré une légère baisse de 2016 à 2018. En 2019, 59,7 % des quartiers urbains avaient un ou plusieurs détaillants de vapotage à moins de 1 000 m de leur centre géographique, et 79,4 % des écoles élémentaires, 82,8 % des écoles secondaires et 84,2 % des écoles postsecondaires en avaient au moins un détaillant à moins de 1 000 m. Le revenu du quartier était associé à l'accès aux détaillants, avec plus de détaillants dans les régions à faible revenu. En 2019, les quartiers du quintile de revenu le plus bas comptaient plus de deux fois plus de détaillants de vapotage par habitant dans un rayon de 1 000 m par rapport au quintile le plus élevé (rapport de taux d'incidence ajusté 2,40; IC à 95 % 2,24-2,58). Les augmentations au fil du temps de l'accès aux détaillants de vapotage ne différaient pas selon la région géographique, le quintile de revenu du quartier ou le type d'école. CONCLUSION: Nous avons observé une augmentation significative de l'accès aux détaillants de vapotage en Ontario, y compris la proximité des écoles primaires et secondaires à la suite des nouvelles réglementations provinciales sur le marketing et de la réglementation fédérale sur la nicotine en 2018. L'accès au vapotage était le plus élevé dans les quartiers à faible revenu et pourrait contribuer aux inégalités par rapport aux événements indésirables lié au vapotage et tabac.

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 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.

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.

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.

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.

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.

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.