Complications Following Elective Major Noncardiac Surgery Among Patients With Prior SARS-CoV-2 Infection.

Importance: There is an urgent need for evidence to inform preoperative risk assessment for the millions of people who have had SARS-CoV-2 infection and are awaiting elective surgery, which is critical to surgical care planning and informed consent. Objective: To assess the association of prior SARS-CoV-2 infection with death, major adverse cardiovascular events, and rehospitalization after elective major noncardiac surgery. Design, Setting, and Participants: This population-based cohort study included adults who had received a polymerase chain reaction test for SARS-CoV-2 infection within 6 months prior to elective major noncardiac surgery in Ontario, Canada, between April 2020 and October 2021, with 30 days follow-up. Exposures: Positive SARS-CoV-2 polymerase chain reaction test result. Main Outcomes and Measures: The main outcome was the composite of death, major adverse cardiovascular events, and all-cause rehospitalization within 30 days after surgery. Results: Of 71 144 patients who underwent elective major noncardiac surgery (median age, 66 years [IQR, 57-73 years]; 59.8% female), 960 had prior SARS-CoV-2 infection (1.3%) and 70 184 had negative test results (98.7%). Prior infection was not associated with the composite risk of death, major adverse cardiovascular events, and rehospitalization within 30 days of elective major noncardiac surgery (5.3% absolute event rate [n = 3770]; 960 patients with a positive test result; adjusted relative risk [aRR], 0.91; 95% CI, 0.68-1.21). There was also no association between prior infection with SARS-CoV-2 and postoperative outcomes when the time between infection and surgery was less than 4 weeks (aRR, 1.15; 95% CI, 0.64-2.09) or less than 7 weeks (aRR, 0.95; 95% CI, 0.56-1.61) and among those who were previously vaccinated (aRR, 0.81; 95% CI, 0.52-1.26). Conclusions and Relevance: In this study, prior infection with SARS-CoV-2 was not associated with death, major adverse cardiovascular events, or rehospitalization following elective major noncardiac surgery, although low event rates and wide 95% CIs do not preclude a potentially meaningful increase in overall risk.

Governing partnerships with technology companies as part of the COVID-19 response in Canada: A qualitative case study.

Cross-sector partnerships are vital for maintaining resilient health systems; however, few studies have sought to empirically assess the barriers and enablers of effective and responsible partnerships during public health emergencies. Through a qualitative, multiple case study, we analyzed 210 documents and conducted 26 interviews with stakeholders in three real-world partnerships between Canadian health organizations and private technology startups during the COVID-19 pandemic. The three partnerships involved: 1) deploying a virtual care platform to care for COVID-19 patients at one hospital, 2) deploying a secure messaging platform for physicians at another hospital, and 3) using data science to support a public health organization. Our results demonstrate that a public health emergency created time and resource pressures throughout a partnership. Given these constraints, early and sustained alignment on the core problem was critical for success. Moreover, governance processes designed for normal operations, such as procurement, were triaged and streamlined. Social learning, or the process of learning from observing others, offset some time and resource pressures. Social learning took many forms ranging from informal conversations between individuals at peer organisations (e.g., hospital chief information officers) to standing meetings at the local university's city-wide COVID-19 response table. We also found that startups' flexibility and understanding of the local context enabled them to play a highly valuable role in emergency response. However, pandemic fueled "hypergrowth" created risks for startups, such as introducing opportunities for deviation away from their core value proposition. Finally, we found each partnership navigated intense workloads, burnout, and personnel turnover through the pandemic. Strong partnerships required healthy, motivated teams. Visibility into and engagement in partnership governance, belief in partnership impact, and strong emotional intelligence in managers promoted team well-being. Taken together, these findings can help to bridge the theory-to-practice gap and guide effective cross-sector partnerships during public health emergencies.

Determinants of Hospital Use and Physician Services Among Adults With a History of Homelessness.

Background: People experiencing homelessness have diverse patterns of healthcare use. This study examined the distribution and determinants of healthcare encounters among adults with a history of homelessness. Methods: Administrative healthcare records were linked with survey data for a general cohort of adults with a history of homelessness and a cohort of homeless adults with mental illness. Binary and count models were used to identify factors associated with hospital admissions, emergency department visits and physician visits for comparison across the 2 cohorts. Results: During the 1-year follow-up period, a higher proportion of people in the cohort with a mental illness used any inpatient (27% vs 14%), emergency (63% vs 53%), or physician services (90% vs 76%) compared to the general homeless cohort. People from racialized groups were less likely use nearly all health services, most notably physician services. Other factors, such as reporting of a regular source of care, poor perceived general health, and diagnosed chronic conditions were associated with higher use of all health services except psychiatric inpatient care. Conclusion: When implementing interventions for patients with the greatest health needs, we must consider the unique factors that contribute to higher healthcare use, as well as the barriers to healthcare access.

Early Impacts of the COVID-19 Pandemic on Public Health Systems and Practice in 3 Canadian Provinces From the Perspective of Public Health Leaders: A Qualitative Study.

CONTEXT: The COVID-19 pandemic has impacted health systems worldwide. Studies to date have largely focused on the health care system with less attention to the impact on public health systems and practice. OBJECTIVE: To describe the early impacts of COVID-19 on public health systems and practice in 3 Canadian provinces from the perspective of public health system leaders and synthesize lessons learned. DESIGN: A qualitative study using semistructured virtual interviews with public health leaders between October 2020 and April 2021. The World Health Organization's essential public health operations framework guided data collection and analysis. SETTING: This study involved the Canadian provinces of Alberta, Ontario, and Québec. These provinces were chosen for their large populations, relatively high COVID-19 burden, and variation in public health systems. PARTICIPANTS: Public health leaders from Alberta (n = 21), Ontario (n = 18), and Québec (n = 19) in organizations with a primary mandate of stewardship and/or administration of essential public health operations (total n = 58). RESULTS: We found that the COVID-19 pandemic led to intensified collaboration in public health systems and a change in workforce capacity to respond to the pandemic. This came with opportunities but also challenges of burnout and disruption of non-COVID-19 services. Information systems and digital technologies were increasingly used and there was greater proximity between public health leaders and other health system leaders. A renewed recognition for public health work was also highlighted. CONCLUSIONS: The COVID-19 pandemic impacted several aspects of public health systems in the provinces studied. Our findings can help public health leaders and policy makers identify areas for further investment (eg, intersectoral collaboration, information systems) and develop plans to address challenges (eg, disrupted services, workforce burnout) that have surfaced.

“We cobble together a storyline of system performance using a diversity of things”: a qualitative study of perspectives on public health performance measurement in Canada

There have been longstanding calls for public health systems transformations in many countries, including Canada. Core to these calls has been strengthening performance measurement. While advancements have been made in performance measurement for certain sectors of the health care system (primarily focused on acute and primary health care), effective use of indicators for measuring public health systems performance are lacking. This study describes the current state, anticipated challenges, and future directions in the development and implementation of a public health performance measurement system for Canada. We conducted a qualitative study using semi-structured interviews with public health leaders (n = 9) between July and August 2021. Public health leaders included researchers, government staff, and former medical officers of health who were purposively selected due to their expertise and experience with performance measurement with relevance to public health systems in Canada. Thematic analysis included both a deductive approach for themes consistent with the conceptual framework and an inductive approach to allow new themes to emerge from the data. Conceptual, methodological, contextual, and infrastructure challenges were highlighted by participants in designing a performance measurement system for public health. Specifically, six major themes evolved that encompass 1) the mission and purpose of public health systems, including challenges inherent in measuring the functions and services of public health;2) the macro context, including the impacts of chronic underinvestment and one-time funding injections on the ability to sustain a measurement system;3) the organizational structure/governance of public health systems including multiple forms across Canada and underdevelopment of information technology systems;4) accountability approaches to performance measurement and management;and 5) timing and unobservability in public health indicators. These challenges require dedicated investment, strong leadership, and political will from the federal and provincial/territorial governments. Unprecedented attention on public health due to the coronavirus disease 2019 pandemic has highlighted opportunities for system improvements, such as addressing the lack of a performance measurement system. This study provides actionable knowledge on conceptual, methodological, contextual, and infrastructure challenges needed to design and build a pan-Canadian performance measurement system for public health.

CoQUAD: a COVID-19 question answering dataset system, facilitating research, benchmarking, and practice.

BACKGROUND: Due to the growing amount of COVID-19 research literature, medical experts, clinical scientists, and researchers frequently struggle to stay up to date on the most recent findings. There is a pressing need to assist researchers and practitioners in mining and responding to COVID-19-related questions on time. METHODS: This paper introduces CoQUAD, a question-answering system that can extract answers related to COVID-19 questions in an efficient manner. There are two datasets provided in this work: a reference-standard dataset built using the CORD-19 and LitCOVID initiatives, and a gold-standard dataset prepared by the experts from a public health domain. The CoQUAD has a Retriever component trained on the BM25 algorithm that searches the reference-standard dataset for relevant documents based on a question related to COVID-19. CoQUAD also has a Reader component that consists of a Transformer-based model, namely MPNet, which is used to read the paragraphs and find the answers related to a question from the retrieved documents. In comparison to previous works, the proposed CoQUAD system can answer questions related to early, mid, and post-COVID-19 topics. RESULTS: Extensive experiments on CoQUAD Retriever and Reader modules show that CoQUAD can provide effective and relevant answers to any COVID-19-related questions posed in natural language, with a higher level of accuracy. When compared to state-of-the-art baselines, CoQUAD outperforms the previous models, achieving an exact match ratio score of 77.50% and an F1 score of 77.10%. CONCLUSION: CoQUAD is a question-answering system that mines COVID-19 literature using natural language processing techniques to help the research community find the most recent findings and answer any related questions.

Prevalence and health care costs of mitochondrial disease in Ontario, Canada: A population-based cohort study.

BACKGROUND: Mitochondrial disease prevalence has been estimated at 1 in 4000 in the United States, and 1 in 5000 worldwide. Prevalence in Canada has not been established, though multi-linked health administrative data resources present a unique opportunity to establish robust population-based estimates in a single-payer health system. This study used administrative data for the Ontario, Canada population between April 1988 and March 2019 to measure mitochondrial disease prevalence and describe patient characteristics and health care costs. RESULTS: 3069 unique individuals were hospitalized with mitochondrial disease in Ontario and eligible for the study cohort, representing a period prevalence of 2.51 per 10,000 or 1 in 3989. First hospitalization was most common between ages 0-9 or 50-69. The mitochondrial disease population experiences a high need for health care and incurred high costs (mean = CAD$24,023 in 12 months before first hospitalization) within the single-payer Ontario health care system. CONCLUSIONS: This study provides needed insight into mitochondrial disease in Canada, and demonstrates the high health burden on patients. The methodology used can be adapted across jurisdictions with similar routine collection of health data, such as in other Canadian provinces. Future work should seek to validate this approach via record linkage of existing disease cohorts in Ontario, and identify specific comorbidities with mitochondrial disease that may contribute to high health resource utilization.

Human factors applications in the design of decision support systems for population health: a scoping review.

INTRODUCTION: Public health professionals engage in complex cognitive tasks, often using evidence-based decision support tools to bolster their decision-making. Human factors methods take a user-centred approach to improve the design of systems, processes, and interfaces to better support planning and decision-making. While human factors methods have been applied to the design of clinical health tools, these methods are limited in the design of tools for population health. The objective of this scoping review is to develop a comprehensive understanding of how human factors techniques have been applied in the design of population health decision support tools. METHODS AND ANALYSIS: The scoping review will follow the methodology and framework proposed by Arksey and O'Malley. We include English-language documents between January 1990 and August 2021 describing the development, validation or application of human factors principles to decision support tools in population health. The search will include Ovid MEDLINE: Epub Ahead of Print, In-Process and Other Non-Indexed Citations, Ovid MEDLINE Daily and Ovid MEDLINE 1946-present; EMBASE, Scopus, PsycINFO, Compendex, IEEE Xplore and Inspec. The results will be integrated into Covidence. First, the abstract of all identified articles will be screened independently by two reviewers with disagreements being resolved by a third reviewer. Next, the full text for articles identified as include or inconclusive will be reviewed by two independent reviewers, leading to a final decision regarding inclusion. Reference lists of included articles will be manually screened to identify additional studies. Data will be extracted by one reviewer, verified by a second, and presented according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for scoping reviews. ETHICS AND DISSEMINATION: Ethics approval is not required for this work as human participants are not involved. The completed review will be published in a peer-reviewed, interdisciplinary journal.

Large-scale implementation of rapid antigen testing system for COVID-19 in workplaces.

The transmission of coronavirus disease 2019 (COVID-19) in workplaces has been a persistent issue throughout the pandemic. In response, a not-for-profit initiative emerged to mitigate COVID-19 workplace transmission in Canada. We report the process for establishing a workplace frequent rapid antigen test (RAT) program. The screening program identified 473 asymptomatic individuals who tested positive on the RAT and confirmed positive by a nasopharyngeal polymerase chain reaction (PCR) diagnostic test. One in 4300 RATs was presumptive positive but later tested PCR negative, and thus, false positives did not meaningfully disrupt workplace operations. Most employers rated the program highly and felt strongly that the program contributed to workplace and community safety. The findings describe a sustained and scalable implementation plan for establishing a frequent workplace testing program. High-frequency testing programs offer the potential to break chains of transmission and act as an extra layer of protection in a comprehensive public health response.

Pivoting data and analytic capacity to support Ontario's COVID-19 response.

Introduction: Health care systems have faced unprecedented challenges due to the COVID-19 pandemic. Access to timely population-based data has been vital to informing public health policy and practice. Methods: We describe how ICES, an independent not-for-profit research and analytic institute in Ontario, Canada, pivoted existing research infrastructure and engaged health system stakeholders to provide near real-time population-based data and analytics to support Ontario's COVID-19 pandemic response. Results: Since April 2020, ICES provided the Ontario COVID-19 Provincial Command Table and public health partners with regular and ad hoc reports on SARS-CoV-2 testing and COVID-19 vaccine coverage. These reports: 1) helped identify congregate care/shared living settings that needed testing and prevention efforts early in the pandemic; 2) provided early indications of inequities in testing and infection in marginalized neighbourhoods, including areas with higher proportions of immigrants and visible minorities; 3) identified areas with high test positivity, which helped Public Health Units target and evaluate prevention efforts; and 4) contributed to altering the province's COVID-19 vaccine roll-out strategy to target high-risk neighbourhoods and helping Public Health Units and community organizations plan local vaccination programs. In addition, ICES is a key component of the Ontario Health Data Platform, which provides scientists with data access to conduct COVID-19 research and analyses. Discussion and Conclusion: ICES was well-positioned to provide rapid analyses for decision-makers to respond to the evolving public health emergency, and continues to contribute to Ontario's pandemic response by providing timely, relevant reports to health system stakeholders and facilitating data access for externally-funded COVID-19 research.

Risk stratification for COVID-19 hospitalization: a multivariable model based on gradient-boosting decision trees.

BACKGROUND: The COVID-19 pandemic has led to an increased demand for health care resources and, in some cases, shortage of medical equipment and staff. Our objective was to develop and validate a multivariable model to predict risk of hospitalization for patients infected with SARS-CoV-2. METHODS: We used routinely collected health records in a patient cohort to develop and validate our prediction model. This cohort included adult patients (age ≥ 18 yr) from Ontario, Canada, who tested positive for SARS-CoV-2 ribonucleic acid by polymerase chain reaction between Feb. 2 and Oct. 5, 2020, and were followed up through Nov. 5, 2020. Patients living in long-term care facilities were excluded, as they were all assumed to be at high risk of hospitalization for COVID-19. Risk of hospitalization within 30 days of diagnosis of SARS-CoV-2 infection was estimated via gradient-boosting decision trees, and variable importance examined via Shapley values. We built a gradient-boosting model using the Extreme Gradient Boosting (XGBoost) algorithm and compared its performance against 4 empirical rules commonly used for risk stratifications based on age and number of comorbidities. RESULTS: The cohort included 36 323 patients with 2583 hospitalizations (7.1%). Hospitalized patients had a higher median age (64 yr v. 43 yr), were more likely to be male (56.3% v. 47.3%) and had a higher median number of comorbidities (3, interquartile range [IQR] 2-6 v. 1, IQR 0-3) than nonhospitalized patients. Patients were split into development (n = 29 058, 80.0%) and held-out validation (n = 7265, 20.0%) cohorts. The gradient-boosting model achieved high discrimination (development cohort: area under the receiver operating characteristic curve across the 5 folds of 0.852; validation cohort: 0.8475) and strong calibration (slope = 1.01, intercept = -0.01). The patients who scored at the top 10% captured 47.4% of hospitalizations, and those who scored at the top 30% captured 80.6%. INTERPRETATION: We developed and validated an accurate risk stratification model using routinely collected health administrative data. We envision that modelling such risk stratification based on routinely collected health data could support management of COVID-19 on a population health level.

Downstream health impacts of employment losses during the COVID-19 pandemic.

OBJECTIVES: The Canadian workforce has experienced significant employment losses during the COVID-19 pandemic, in part as a result of non-pharmaceutical interventions to slow COVID-19 transmission. Health consequences are likely to result from these job losses, but without historical precedent for the current economic shutdown they are challenging to plan for. Our study aimed to use population risk models to quantify potential downstream health impacts of the COVID-19 pandemic and inform public health planning to minimize future health burden. METHODS: The impact of COVID-19 job losses on future premature mortality and high-resource health care utilization (HRU) was estimated using an economic model of Canadian COVID-19 lockdowns and validated population risk models. Five-year excess premature mortality and HRU were estimated by age and sex to describe employment-related health consequences of COVID-19 lockdowns in the Canadian population. RESULTS: With federal income supplementation like the Canadian Emergency Response Benefit, we estimate that each month of economic lockdown will result in 5.6 new high-resource health care system users (HRUs), and 4.1 excess premature deaths, per 100,000, over the next 5 years. These effects were concentrated in ages 45-64, and among males 18-34. Without income supplementation, the health consequences were approximately twice as great in terms of both HRUs and premature deaths. CONCLUSION: Employment losses associated with COVID-19 countermeasures may have downstream implications for health. Public health responses should consider financially vulnerable populations at high risk of downstream health outcomes.

RéSUMé: OBJECTIFS: La population active canadienne a connu d'importantes pertes d'emplois durant la pandémie de COVID-19, en partie en raison des interventions non pharmaceutiques menées pour ralentir la transmission du virus. Ces pertes d'emplois auront probablement des conséquences pour la santé, mais en l'absence d'un précédent historique au ralentissement économique actuel, il est difficile de planifier quoi faire pour atténuer ces conséquences. Notre étude visait à chiffrer les éventuels effets sanitaires de la pandémie de COVID-19 en aval à l'aide de modèles de risque pour la population et à éclairer la planification en santé publique afin de réduire le futur fardeau pour la santé. MéTHODE: Nous avons estimé l'impact des pertes d'emplois dues à la COVID-19 sur les chiffres futurs de mortalité prématurée et d'utilisation élevée des soins de santé (UESS) à l'aide d'un modèle économique des confinements dus à la COVID-19 au Canada et de modèles de risque pour la population validés. Nous avons estimé la surmortalité prématurée et l'UESS par âge et par sexe dans cinq ans afin de décrire les conséquences pour la santé des effets sur l'emploi des confinements dus à la COVID-19 dans la population canadienne. RéSULTATS: Avec les mesures fédérales de supplémentation du revenu comme la Prestation canadienne d'urgence, nous estimons qu'avec chaque mois de confinement économique, il y aura 5,6 nouveaux grands usagers du système de soins de santé (GUSSS) et 4,1 décès prématurés supplémentaires pour 100 000 habitants au cours des cinq prochaines années. Ces effets seront concentrés dans la tranche d'âge des 45 à 64 ans et chez les hommes de 18 à 34 ans. Sans supplémentation du revenu, les conséquences pour la santé seront environ le double, tant pour le nombre de GUSSS que de décès prématurés. CONCLUSION: Les pertes d'emplois associées aux mesures de prévention de la COVID-19 pourraient avoir des conséquences pour la santé en aval. Les interventions de santé publique devraient donc tenir compte des populations financièrement vulnérables à risque élevé de connaître des problèmes de santé en aval.

Déterminants individuels et sociaux du test de dépistage du SRAS-CoV-2 et de l'obtention d'un résultat positif en Ontario, au Canada: une étude populationnelle.

CONTEXTE: Optimiser la réponse de la santé publique pour diminuer le fardeau de la COVID-19 nécessite la caractérisation de l'hétérogénéité du risque posé par la maladie à l'échelle de la population. Cependant, l'hétérogénéité du dépistage du SRAS-CoV-2 peut fausser les estimations selon le modèle d'étude analytique utilisé. Notre objectif était d'explorer les biais collisionneurs dans le cadre d'une vaste étude portant sur les déterminants de la maladie et d'évaluer les déterminants individuels, environnementaux et sociaux du dépistage et du diagnostic du SRAS-CoV-2 parmi les résidents de l'Ontario, au Canada. MÉTHODES: Nous avons exploré la présence potentielle de biais collisionneurs et caractérisé les déterminants individuels, environnementaux et sociaux de l'obtention d'un test de dépistage et d'un résultat positif à la présence de l'infection au SRAS-CoV-2 à l'aide d'analyses transversales parmi les 14,7 millions de personnes vivant dans la collectivité en Ontario, au Canada. Parmi les personnes ayant obtenu un diagnostic, nous avons utilisé des études analytiques distinctes afin de comparer les prédicteurs pour les personnes d'obtenir un résultat de test de dépistage positif plutôt que négatif, pour les personnes symptomatiques d'obtenir un résultat de test de dépistage positif plutôt que négatif et pour les personnes d'obtenir un résultat de test de dépistage positif plutôt que de ne pas obtenir un résultat positif (c.-à-d., obtenir un résultat de test de dépistage négatif ou ne pas obtenir de test de dépistage). Nos analyses comprennent des tests de dépistage réalisés entre le 1er mars et le 20 juin 2020. RÉSULTATS: Sur 14 695 579 personnes, nous avons constaté que 758 691 d'entre elles ont passé un test de dépistage du SRAS-CoV-2, parmi lesquelles 25 030 (3,3 %) ont obtenu un résultat positif. Plus la probabilité d'obtenir un test de dépistage s'éloignait de zéro, plus la variabilité généralement observée dans la probabilité d'un diagnostic était grande parmi les modèles d'études analytiques, particulièrement en ce qui a trait aux facteurs individuels. Nous avons constaté que la variabilité dans l'obtention d'un test de dépistage était moins importante en fonction des déterminants sociaux dans l'ensemble des études analytiques. Les facteurs tels que le fait d'habiter dans une région ayant une plus haute densité des ménages (rapport de cotes corrigé 1,86; intervalle de confiance [IC] à 95 % 1,75­1,98), une plus grande proportion de travailleurs essentiels (rapport de cotes corrigé 1,58; IC à 95 % 1,48­1,69), une population atteignant un plus faible niveau de scolarité (rapport de cotes corrigé 1,33; IC à 95 % 1,26­1,41) et une plus grande proportion d'immigrants récents (rapport de cotes corrigé 1,10; IC à 95 % 1,05­1,15), étaient systématiquement corrélés à une probabilité plus importante d'obtenir un diagnostic de SRAS-CoV-2, peu importe le modèle d'étude analytique employé. INTERPRÉTATION: Lorsque la capacité de dépister est limitée, nos résultats suggèrent que les facteurs de risque peuvent être estimés plus adéquatement en utilisant des comparateurs populationnels plutôt que des comparateurs de résultat négatif au test de dépistage. Optimiser la lutte contre la COVID-19 nécessite des investissements dans des interventions structurelles déployées de façon suffisante et adaptées à l'hétérogénéité des déterminants sociaux du risque, dont le surpeuplement des ménages, l'occupation professionnelle et le racisme structurel.

News media coverage of COVID-19 public health and policy information

During a pandemic, news media play a crucial role in communicating public health and policy information. Traditional newspaper coverage is important amidst increasing disinformation, yet uncertainties make covering health risks and efforts to limit transmission difficult. This study assesses print and online newspaper coverage of the coronavirus disease COVID-19 for March 2020, when the global pandemic was declared, through August 2020 in three countries: Canada (with the lowest per-capita case and death rates during the study timeframe), the United Kingdom (with a pronounced early spike), and the United States (with persistently high rates). Tools previously validated for pandemic-related news records allow measurement of multiple indicators of scientific quality (i.e., reporting that reflects the state of scientific knowledge) and of sensationalism (i.e., strategies rendering news as more extraordinary than it really is). COVID-19 reporting had moderate scientific quality and low sensationalism across 1331 sampled articles in twelve newspapers spanning the political spectrums of the three countries. Newspapers oriented towards the populist-right had the lowest scientific quality in reporting, combined with very low sensationalism in some cases. Against a backdrop of world-leading disease rates, U.S. newspapers on the political left had more exposing coverage, e.g., focused on policy failures or misinformation, and more warning coverage, e.g., focused on the risks of the disease, compared to U.S. newspapers on the political right. Despite the generally assumed benefits of low sensationalism, pandemic-related coverage with low scientific quality that also failed to alert readers to public-health risks, misinformation, or policy failures may have exacerbated the public-health effects of the disease. Such complexities will likely remain central for both pandemic news media reporting and public-health strategies reliant upon it.

Investigating the impact of quarantine on mental health: insights from the COVID-19 international border surveillance study in Canada.

BACKGROUND: Nations throughout the world are imposing mandatory quarantine on those entering the country. Although such measures may be effective in reducing the importation of COVID-19, the mental health implications remain unclear. AIMS: This study sought to assess mental well-being and factors associated with changes in mental health in individuals subject to mandatory quarantine following travel. METHOD: Travellers arriving at a large, urban international airport completed online questionnaires on arrival and days 7 and 14 of mandated quarantine. Questionnaire items, such as travel history, mental health, attitudes toward COVID-19, and protection behaviours, were drawn from the World Health Organization Survey Tool for COVID-19. RESULTS: There was a clinically significant decline in mental health over the course of quarantine among the 10 965 eligible participants. Poor mental health was reported by 5.1% of participants on arrival and 26% on day 7 of quarantine. Factors associated with a greater decline in mental health were younger age, female gender, negative views toward quarantine measures and engaging in fewer COVID-19 prevention behaviours. For instance, travellers who stated that they rarely wore masks had nearly three times higher odds of developing poor mental health. CONCLUSIONS: Although the widespread use of quarantine may be effective in limiting the spread of COVID-19, the mental health implications are profound and have largely been ignored in policy decisions. Psychiatry has a role to play in contributing to the public policy debate to ensure that all aspects of health and well-being are reflected in decisions to isolate people from others.

Caractéristiques et issues des hospitalisations pour les cas de COVID-19 et d'influenza dans la région de Toronto.

CONTEXTE: Les caractéristiques des patients, les soins cliniques, l'utilisation des ressources et les issues cliniques des personnes atteintes de la maladie à coronavirus 2019 (COVID-19) hospitalisées au Canada ne sont pas bien connus. MÉTHODES: Nous avons recueilli des données sur tous les adultes hospitalisés atteints de la COVID-19 ou de l'influenza ayant obtenu leur congé d'unités médicales ou d'unités de soins intensifs médicaux et chirurgicaux entre le 1er novembre 2019 et le 30 juin 2020 dans 7 centres hospitaliers de Toronto et de Mississauga (Ontario). Nous avons comparé les issues cliniques des patients à l'aide de modèles de régression multivariée, en tenant compte des facteurs sociodémographiques et de l'intensité des comorbidités. Nous avons validé le degré d'exactitude de 7 scores de risque mis au point à l'externe pour déterminer leur capacité à prédire le risque de décès chez les patients atteints de la COVID-19. RÉSULTATS: Parmi les hospitalisations retenues, 1027 patients étaient atteints de la COVID-19 (âge médian de 65 ans, 59,1 % d'hommes) et 783 étaient atteints de l'influenza (âge médian de 68 ans, 50,8 % d'hommes). Les patients âgés de moins de 50 ans comptaient pour 21,2 % de toutes les hospitalisations dues à la COVID-19 et 24,0 % des séjours aux soins intensifs. Comparativement aux patients atteints de l'influenza, les patients atteints de la COVID-19 présentaient un taux de mortalité perhospitalière (mortalité non ajustée 19,9 % c. 6,1 %; risque relatif [RR] ajusté 3,46 %, intervalle de confiance [IC] à 95 % 2,56­4,68) et un taux d'utilisation des ressources des unités de soins intensifs (taux non ajusté 26,4 % c. 18,0 %; RR ajusté 1,50, IC à 95 % 1,25­1,80) significativement plus élevés, ainsi qu'une durée d'hospitalisation (durée médiane non ajustée 8,7 jours c. 4,8 jours; rapport des taux d'incidence ajusté 1,45; IC à 95 % 1,25­1,69) significativement plus longue. Le taux de réhospitalisation dans les 30 jours n'était pas significativement différent (taux non ajusté 9,3 % c. 9,6 %; RR ajusté 0,98 %, IC à 95 % 0,70­1,39). Trois scores de risque utilisant un pointage pour prédire la mortalité perhospitalière ont montré une bonne discrimination (aire sous la courbe [ASC] de la fonction d'efficacité du récepteur [ROC] 0,72­0,81) et une bonne calibration. INTERPRÉTATION: Durant la première vague de la pandémie, l'hospitalisation des patients atteints de la COVID-19 était associée à des taux de mortalité et d'utilisation des ressources des unités de soins intensifs et à une durée d'hospitalisation significativement plus importants que les hospitalisations des patients atteints de l'influenza. De simples scores de risque peuvent prédire avec une bonne exactitude le risque de mortalité perhospitalière des patients atteints de la COVID-19.

COVID-19 international border surveillance at Toronto's Pearson Airport: a cohort study.

OBJECTIVES: The primary objective was to estimate the positivity rate of air travellers coming to Toronto, Canada in September and October 2020, on arrival and on day 7 and day 14. The secondary objectives were to estimate the degree of risk based on country of origin and to assess knowledge and attitudes towards COVID-19 control measures and subjective well-being during the quarantine period. DESIGN: Prospective cohort of arriving international travellers. SETTING: Toronto Pearson Airport Terminal 1, Toronto, Canada. PARTICIPANTS: Participants of this study were passengers arriving on international flights. Inclusion criteria were those aged 18 or older who had a final destination within 100 km of the airport, spoke English or French, and provided consent. Excluded were those taking a connecting flight, had no internet access, exhibited symptoms of COVID-19 on arrival or were exempted from quarantine. MAIN OUTCOME MEASURES: Positive for SARS-CoV-2 virus on reverse transcription PCR with self-administered oral-nasal swab and general well-being using the WHO-5 Well-being Index. RESULTS: Of 16 361 passengers enrolled, 248 (1.5%, 95% CI 1.3% to 1.7%) tested positive. Of these, 167 (67%) were identified on arrival, 67 (27%) on day 7, and 14 (6%) on day 14. The positivity rate increased from 1% in September to 2% in October. Average well-being score declined from 19.8 (out of a maximum of 25) to 15.5 between arrival and day 7 (p<0.001). CONCLUSIONS: A single arrival test will pick up two-thirds of individuals who will become positive by day 14, with most of the rest detected on the second test on day 7. These results support strategies identified through mathematical models that a reduced quarantine combined with testing can be as effective as a 14-day quarantine.

Individual and social determinants of SARS-CoV-2 testing and positivity in Ontario, Canada: a population-wide study.

BACKGROUND: Optimizing the public health response to reduce the burden of COVID-19 necessitates characterizing population-level heterogeneity of risks for the disease. However, heterogeneity in SARS-CoV-2 testing may introduce biased estimates depending on analytic design. We aimed to explore the potential for collider bias in a large study of disease determinants, and evaluate individual, environmental and social determinants associated with SARS-CoV-2 testing and diagnosis among residents of Ontario, Canada. METHODS: We explored the potential for collider bias and characterized individual, environmental and social determinants of being tested and testing positive for SARS-CoV-2 infection using cross-sectional analyses among 14.7 million community-dwelling people in Ontario, Canada. Among those with a diagnosis, we used separate analytic designs to compare predictors of people testing positive versus negative; symptomatic people testing positive versus testing negative; and people testing positive versus people not testing positive (i.e., testing negative or not being tested). Our analyses included tests conducted between Mar. 1 and June 20, 2020. RESULTS: Of 14 695 579 people, we found that 758 691 were tested for SARS-CoV-2, of whom 25 030 (3.3%) had a positive test result. The further the odds of testing from the null, the more variability we generally observed in the odds of diagnosis across analytic design, particularly among individual factors. We found that there was less variability in testing by social determinants across analytic designs. Residing in areas with the highest household density (adjusted odds ratio [OR] 1.86, 95% confidence interval [CI] 1.75-1.98), highest proportion of essential workers (adjusted OR 1.58, 95% CI 1.48-1.69), lowest educational attainment (adjusted OR 1.33, 95% CI 1.26-1.41) and highest proportion of recent immigrants (adjusted OR 1.10, 95% CI 1.05-1.15) were consistently related to increased odds of SARS-CoV-2 diagnosis regardless of analytic design. INTERPRETATION: Where testing is limited, our results suggest that risk factors may be better estimated using population comparators rather than test-negative comparators. Optimizing COVID-19 responses necessitates investment in and sufficient coverage of structural interventions tailored to heterogeneity in social determinants of risk, including household crowding, occupation and structural racism.