This study identifies trends in abusive discourse towards public health professionals (PHPs) during the COVID-19 pandemic and explores associations between abusive digital content, case numbers, deaths, and major policy announcements. Natural language processing (NLP) and large language model (LLM) techniques were used to develop a computational model to detect abusive content on X (formerly Twitter). This model was applied to abusive posts targeting PHPs during COVID-19 by examining over 1.7 million posts from January 2020 to May 2021. Associations between spikes in abuse and the number of COVID-19 cases, deaths, and government monitoring updates were explored. Pronounced surges in abusive posts coincided with rising case and death counts and the imposition of major federal COVID-19 policies, particularly during the pandemic’s initial emergency response. Digital aggression increased at times of public health statements related to restrictions in social gatherings, testing criteria, vaccinations, and masking. However, during high-case periods, even statements providing case updates, expressing compassion, or urging collective responsibility coincided with higher numbers of abusive posts. This work provides insights into the pressures faced by health officials online and offers implications for designing resilient public communication during future crises.

Objective:To examine differences in mental health-related healthcare utilization for anxiety and depression between individuals who did and did not undergo COVID-19 PCR testing in Ontario. Background: The COVID-19 pandemic has been associated with changes in mental health and healthcare utilization. Methods:We conducted a population-based retrospective cohort study using linked ICES data, including 6,175,114 adults (January 2020-March 2021). Exposure was PCR-positive, PCR-negative, or untested. The outcome was time to first mental health-related healthcare use for anxiety and depression, identified using validated codes. Adjusted hazard ratios (aHRs) were estimated using Cox models with propensity score matching. Results:Individuals who underwent testing had higher mental health-related healthcare utilization than untested individuals. This was observed in PCR-positive (aHR 6.37; 95% CI 6.25-6.50) and PCR-negative groups (aHR 5.91; 95% CI 5.87-5.95). Higher utilization occurred among younger individuals, females, and socioeconomically disadvantaged groups. Results were consistent in matched analyses. Conclusion:Individuals underwent testing had higher mental health service utilization; similar estimates across PCR-positive and PCR-negative groups suggest testing reflects underlying vulnerability and healthcare-seeking behavior rather than a causal effect on mental health outcomes.

This study explores changing patterns of healthcare utilisation for chronic diseases during the COVID-19 pandemic in Ontario, Canada. It compares prepandemic and pandemic morbidity and mortality, focusing on physician and emergency department visits, hospitalisations for anxiety, depression and chronic diseases, as well as all-cause mortality rates. We constructed a cohort of 2 950 384 adults (18+ years), using administrative health databases, who were living in Ontario, Canada, between the period of January 2017 and March 2023 and recorded the number of visits each individual had in the follow-up period related to chronic conditions. The data were then analysed using an interrupted time-series design to observe changes from before compared with during the pandemic in (1) monthly physician or emergency visits and hospitalisations and (2) monthly all-cause deaths. The exposure in this study was the onset of the COVID-19 pandemic in Ontario, Canada. In the prepandemic period, mean monthly PCR-tested visits in Ontario were 364 880, with a steady increase of 1210 visits per month. During the initial phase of the COVID-19 pandemic, there was a decline in physician visits and hospitalisations for chronic diseases. This trend changed, leading to a significant rise in visits that peaked in March 2021, increasing by 1690 visits monthly. From 2022 onwards, visits saw a notable decline, decreasing by 6830 per month (p<0.05), reflecting reduced healthcare utilisation in the later pandemic phases. The COVID-19 pandemic caused significant fluctuations in healthcare utilisation in Ontario. These changes suggest increased risks of missed diagnoses and delayed care, impacting morbidity and mortality. The results emphasise the importance of adaptable healthcare systems and strong pandemic preparedness to maintain care continuity, especially for chronic disease management, during resource-limited periods.

OBJECTIVES:To evaluate whether loneliness was associated with transition rates to and between healthcare settings and death in older adults and to examine whether associations were modified by sex. DESIGN:Retrospective cohort study. SETTING:Ontario, Canada, from December 2008 to February 2020. PARTICIPANTS:Community-dwelling, Ontario respondents (≥65 years) to the 2008/2009 Canadian Community Health Survey-Healthy Aging (CCHS-HA). EXPOSURE:Baseline loneliness was measured with the Three-Item Loneliness Scale in the CCHS-HA. Respondents were classified as not lonely, moderately lonely or severely lonely. PRIMARY OUTCOME MEASURES:Healthcare transitions were assessed over a 12-year period through linkage to health administrative records. Relative rates of transition to and between community, inpatient hospitalisation, home care and long-term care (LTC) settings, as well as death, were estimated using a continuous-time multistate transition framework. Adjusted models were weighted and tested for sex interactions. RESULTS:Of 2671 respondents (weighted n=1 398 180), 20.9% were moderately lonely and 12.0% were severely lonely. Compared with those who were not lonely, moderately lonely respondents transitioned at a faster rate from the community to home care, and severely lonely respondents transitioned at a faster rate from the community to LTC; although, both associations were attenuated with adjustment (RRML 1.37; 95% CI 1.00 to 1.85 and RRSL 1.96; 95% CI 0.99 to 4.12, respectively). Female and male respondents had mostly similar transition patterns. CONCLUSIONS:Our findings suggest that loneliness may hasten transitions from the community to home care and LTC settings in older adults, although these transitions are mostly driven by related health and social factors.

Objectives: There is a need to consider COVID-19 a syndemic; which calls for a comprehensive approach to tackle the associated interconnected challenges. The objective of this study is to investigate the potential syndemic nature of COVID-19, with a specific focus on understanding how viral infection, mental health (such as anxiety and depression), and pre-existing comorbidities interact and influence each other. Study Design: Retrospective population-based cohort study. Methods: We conducted a population-based retrospective cohort study using linked health administrative data from the Institute for Clinical Evaluative Sciences, Ontario. The study included 2,863,423 Ontario residents from January 2020 to March 2021. We analysed healthcare services utilisation (physician visits, emergency visits, and hospitalisations) for chronic conditions among individuals with both COVID-19 and either anxiety or depression, to understand the syndemic impact of COVID-19 and mental health issues among Ontario population. Results: Multiple regression models were used to explore the study's objective. In the final adjusted regression model for the sample, it was found that the individuals who were COVID-19 positive and had either anxiety or depression were more likely to utilise health services for chronic conditions of interest during the pandemic than those who were COVID-19-negative with mental health issues (odds ratio [OR]:, 1.33; 95% confidence interval [CI]: 1.12-1.58). A higher risk of morbidity was observed among males (OR: 1.28; CI: 1.16-1.41), as well as in individuals with diverse ethnic backgrounds and low socioeconomic status. Conclusions: The impact of COVID-19 on mental health, particularly among vulnerable populations with chronic diseases, can be seen as a syndemic. This complex interaction emphasises the need for integrated public health strategies. (c) 2024 The Author(s). Published by Elsevier Ltd on behalf of The Royal Society for Public Health. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4. 0/).

BACKGROUND:There is growing interest in understanding the care needs of lonely people but studies are limited and examine healthcare settings separately. We estimated and compared healthcare trajectories in lonely and not lonely older female and male respondents to a national health survey. METHODS:We conducted a retrospective cohort study of community-dwelling, Ontario respondents (65+ years) to the 2008/2009 Canadian Community Health Survey-Healthy Aging. Respondents were classified at baseline as not lonely, moderately lonely, or severely lonely using the Three-Item Loneliness Scale and then linked with health administrative data to assess healthcare transitions over a 12 -year observation period. Annual risks of moving from the community to inpatient, long-stay home care, long-term care settings-and death-were estimated across loneliness levels using sex-stratified multistate models. RESULTS:Of 2684 respondents (58.8% female sex; mean age 77 years [standard deviation: 8]), 635 (23.7%) experienced moderate loneliness and 420 (15.6%) severe loneliness. Fewer lonely respondents remained in the community with no transitions (not lonely, 20.3%; moderately lonely, 17.5%; and severely lonely, 12.6%). Annual transition risks from the community to home care and long-term care were higher in female respondents and increased with loneliness severity for both sexes (e.g., 2-year home care risk: 6.1% [95% CI 5.5-6.6], 8.4% [95% CI 7.4-9.5] and 9.4% [95% CI 8.2-10.9] in female respondents, and 3.5% [95% CI 3.1-3.9], 5.0% [95% CI 4.0-6.0], and 5.4% [95% CI 4.0-6.8] in male respondents; 5-year long-term care risk: 9.2% [95% CI 8.0-10.8], 11.1% [95% CI 9.3-13.6] and 12.2% [95% CI 9.9-15.3] [female], and 5.3% [95% CI 4.2-6.7], 9.1% [95% CI 6.8-12.5], and 10.9% [95% CI 7.9-16.3] [male]). CONCLUSIONS:Lonely older female and male respondents were more likely to need home care and long-term care, with severely lonely female respondents having the highest probability of moving to these settings.

This qualitative study sought to explore the experiences of public health professionals in Canada who were targets of harassment, abuse, and threatening behavior during the COVID-19 pandemic. Public health professionals from across Canada who held responsibility for public health measures in their respective jurisdictions participated in in-depth interviews. Using constructivist grounded theory and constant comparative analysis a cycle of violence was identified. Results revealed that as infections and deaths due to COVID-19 began to rise across the globe, participants engaged in efforts to educate the public through mainstream media and social media. While education efforts were generally positively received at the onset of the pandemic, as collective frustration with public health restrictions rose and misinformation began to proliferate, social media fueled outrage and polarization, and public anger began to focus on public health officials. Harassment, abuse, and threats on social media were followed by threats delivered through telephone and paper mail, and finally direct physical threats and confrontation-which were then glorified and amplified on social media. As reported by others, harassment and abuse were particularly virulent for public health professionals who were women or visible minority individuals. We conclude that the pattern of abuse identified in this study is reminiscent of the cycle of violence previously identified with respect to those who become radicalized on social media. These findings serve as a poignant example from which to develop guidelines for all professionals and researchers at risk of online abuse both in the health sector and beyond.

Journal Article Cohort Profile: The Ontario Health Study (OHS) Get access Victoria A Kirsh, Victoria A Kirsh Ontario Institute for Cancer Research, Toronto, ON, CanadaDalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada (formerly for N.K.) https://orcid.org/0000-0003-2422-2225 Search for other works by this author on: Oxford Academic PubMed Google Scholar Kimberly Skead, Kimberly Skead Ontario Institute for Cancer Research, Toronto, ON, CanadaDepartment of Molecular Genetics, University of Toronto, Toronto, ON, Canada Search for other works by this author on: Oxford Academic PubMed Google Scholar Kelly McDonald, Kelly McDonald Ontario Institute for Cancer Research, Toronto, ON, Canada Search for other works by this author on: Oxford Academic PubMed Google Scholar Nancy Kreiger, Nancy Kreiger Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada (formerly for N.K.)Prevention and Cancer Control, Ontario Health, Cancer Care Ontario, Toronto, ON, Canada Search for other works by this author on: Oxford Academic PubMed Google Scholar Julian Little, Julian Little Faculty of Medicine, School of Epidemiology and Public Health, University of Ottawa, Ottawa, ON, Canada Search for other works by this author on: Oxford Academic PubMed Google Scholar Karen Menard, Karen Menard Office of Institutional Research and Planning, University of Guelph, Guelph, ON, Canada Search for other works by this author on: Oxford Academic PubMed Google Scholar John McLaughlin, John McLaughlin Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada (formerly for N.K.) Search for other works by this author on: Oxford Academic PubMed Google Scholar Sutapa Mukherjee, Sutapa Mukherjee Adelaide Institute for Sleep Health, Flinders University, Adelaide, South Australia, Australia https://orcid.org/0000-0001-5021-1648 Search for other works by this author on: Oxford Academic PubMed Google Scholar Lyle J Palmer, Lyle J Palmer School of Public Health, University of Adelaide, Adelaide, South Australia, Australia Search for other works by this author on: Oxford Academic PubMed Google Scholar Vivek Goel, Vivek Goel Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada (formerly for N.K.)Office of the President, University of Waterloo, Waterloo, ON, Canada Search for other works by this author on: Oxford Academic PubMed Google Scholar ... Show more Mark P Purdue, Mark P Purdue Occupational and Environmental Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, MD, USA Search for other works by this author on: Oxford Academic PubMed Google Scholar Philip Awadalla Philip Awadalla Ontario Institute for Cancer Research, Toronto, ON, CanadaDalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada (formerly for N.K.)Department of Molecular Genetics, University of Toronto, Toronto, ON, Canada Corresponding author. Ontario Institute for Cancer Research, 661 University Ave, Suite 510, Toronto, ON, M5G 0A3, Canada. E-mail: philip.awadalla@oicr.on.ca https://orcid.org/0000-0001-9946-6393 Search for other works by this author on: Oxford Academic PubMed Google Scholar International Journal of Epidemiology, Volume 52, Issue 2, April 2023, Pages e137–e151, https://doi.org/10.1093/ije/dyac156 Published: 13 August 2022 Article history Received: 22 December 2021 Editorial decision: 01 July 2022 Accepted: 20 July 2022 Published: 13 August 2022

Objectives This study reports the results of a qualitative study involving public health professionals and documents their experiences with cyberviolence, harassment and threats during the COVID-19 pandemic. Method and analysis The research adopted a discovery-oriented qualitative design, using constructivist grounded theory method and long interview style data collection. Twelve public health professionals from across Canada who held responsibility for COVID-19 response and public health measures in their respective jurisdictions participated. Constant comparative analysis was used to generate concepts through inductive processes. Results Data revealed a pattern that began with mainstream media engagement, moved to indirect cyberviolence on social media that fuelled outrage and polarisation of members of the public, followed by direct cyberviolence in the form of email abuse and threats, and finally resulted in physical threats and confrontation—which were then glorified and amplified on social media. The prolonged nature and intensity of harassment and threats led to negative somatic, emotional, professional and social outcomes. Concerns were raised that misinformation and comments undermining the credibility of public health professionals weakened public trust and ultimately the health of the population. Participants provided recommendations for preventing and mitigating the effects of cyber-instigated violence against public health professionals that clustered in three areas: better supports for public health personnel; improved systems for managing communications; and legislative controls on social media including reducing the anonymity of contributors. Conclusion The prolonged and intense harassment, abuse and threats against public health professionals during COVID-19 had significant effects on these professionals, their families, staff and ultimately the safety and health of the public. Addressing this issue is a significant concern that requires the attention of organisations responsible for public health and policy makers.

Objective To investigate the prospective association between life satisfaction and future mental health service use in: (1) hospital/emergency department, and (2) outpatient settings. Design and setting Population-based cohort study of adults from Ontario, Canada. Baseline data were captured through pooled cycles of the Canadian Community Health Survey (CCHS 2005-2014) and linked to health administrative data for up to 5 years of follow-up. Participants 131 809 Ontarians aged 18 years and older. Main outcome measure The number of mental health-related visits in (1) hospitals/emergency department and (2) outpatient settings within 5 years of follow-up. Results Poisson regression models were used to estimate rate ratios in each setting, adjusting for sociodemographic measures, history of mental health-related visits, and health behaviours. In the hospital/emergency setting, compared to those most satisfied with life, those with the poorest satisfaction exhibited a rate ratio of 3.71 (95% CI 2.14 to 6.45) for future visits. In the outpatient setting, this same comparison group exhibited a rate ratio of 1.83 (95% CI 1.42 to 2.37). When the joint effects of household income were considered, compared with the highest income and most satisfied individuals, the least satisfied and lowest income individuals exhibited the highest rate ratio in the hospital/emergency setting at 11.25 (95% CI 5.32 to 23.80) whereas in the outpatient setting, the least satisfied and highest income individuals exhibited the highest rate ratio at 3.33 (95% CI 1.65 to 6.70). Conclusion The findings suggest that life satisfaction is a risk factor for future mental health visits. This study contributes to an evidence base connecting positive well-being with health system outcomes.

Digital technologies have enabled social connection during prolonged periods of physical distancing and travel restrictions throughout the COVID-19 pandemic. These solutions may exclude older adults, who are at higher risk for social isolation, loneliness, and severe outcomes if infected with SARS-CoV-2. This study investigated factors associated with nonuse of social media or video communications to connect with friends and family among older adults during the pandemic’s first wave. A web-based, cross-sectional survey was administered to members of a national retired educators’ organization based in Ontario, Canada, between May 6 and 19, 2020. Respondents (N=4879) were asked about their use of social networking websites or apps to communicate with friends and family, their internet connection and smartphone access, loneliness, and sociodemographic characteristics. Factors associated with nonuse were evaluated using multivariable logistic regression. A thematic analysis was performed on open-ended survey responses that described experiences with technology and virtual connection. Overall, 15.4% (751/4868) of respondents did not use social networking websites or apps. After adjustment, male gender (odds ratio [OR] 1.60, 95% CI 1.33-1.92), advanced age (OR 1.88, 95% CI 1.38-2.55), living alone (OR 1.68, 95% CI 1.39-2.02), poorer health (OR 1.33, 95% CI 1.04-1.71), and lower social support (OR 1.44, 95% CI 1.20-1.71) increased the odds of nonuse. The reliability of internet connection and access to a smartphone also predicted nonuse. Many respondents viewed these technologies as beneficial, especially for maintaining pre–COVID-19 social contacts and routines, despite preferences for in-person connection. Several factors including advanced age, living alone, and low social support increased the odds of nonuse of social media in older adults to communicate with friends and family during COVID-19’s first wave. Our findings identified socially vulnerable subgroups who may benefit from intervention (eg, improved access, digital literacy, and telephone outreach) to improve social connection.

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. 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.

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.

To prevent exponential spread of COVID-19, many governments restricted economic activity through lockdowns. We model these restrictions as shocks to productivity by sector and trace total equilibrium effects across the economy using techniques from production network economics. We combine this economic model with an epidemiological model of income shocks to long-term health. On both long-run health and economic grounds, it is better to keep upstream sectors such as transportation, manufacturing, and wholesale open than consumer-facing sectors such as retail and restaurants.

Objective To determine how machine learning has been applied to prediction applications in population health contexts. Specifically, to describe which outcomes have been studied, the data sources most widely used and whether reporting of machine learning predictive models aligns with established reporting guidelines.Design A scoping review.Data sources MEDLINE, EMBASE, CINAHL, ProQuest, Scopus, Web of Science, Cochrane Library, INSPEC and ACM Digital Library were searched on 18 July 2018.Eligibility criteria We included English articles published between 1980 and 2018 that used machine learning to predict population-health-related outcomes. We excluded studies that only used logistic regression or were restricted to a clinical context.Data extraction and synthesis We summarised findings extracted from published reports, which included general study characteristics, aspects of model development, reporting of results and model discussion items.Results Of 22 618 articles found by our search, 231 were included in the review. The USA (n=71, 30.74%) and China (n=40, 17.32%) produced the most studies. Cardiovascular disease (n=22, 9.52%) was the most studied outcome. The median number of observations was 5414 (IQR=16 543.5) and the median number of features was 17 (IQR=31). Health records (n=126, 54.5%) and investigator-generated data (n=86, 37.2%) were the most common data sources. Many studies did not incorporate recommended guidelines on machine learning and predictive modelling. Predictive discrimination was commonly assessed using area under the receiver operator curve (n=98, 42.42%) and calibration was rarely assessed (n=22, 9.52%).Conclusions Machine learning applications in population health have concentrated on regions and diseases well represented in traditional data sources, infrequently using big data. Important aspects of model development were under-reported. Greater use of big data and reporting guidelines for predictive modelling could improve machine learning applications in population health.Registration number Registered on the Open Science Framework on 17 July 2018 (available at https://osf.io/rnqe6/).

Objective To examine if low life satisfaction is associated with an increased risk of being hospitalised for an ambulatory care sensitive condition (ACSC), in comparison to high life satisfaction Design and setting Population-based cohort study of adults from Ontario, Canada. Baseline data were captured through the Canadian Community Health Survey (CCHS) and linked to health administrative data for follow-up information. Participants 129 467 men and women between the ages 18 and 74. Main outcome measures Time to avoidable hospitalisations defined by ACSCs. Results Life satisfaction was measured at baseline through the CCHS and follow-up information on ACSC hospitalisations were captured by linking participant respondents to hospitalisation records covered under a single payer health system. Within the study time frame (maximum of 14 years), 3037 individuals were hospitalised. Older men in the lowest household income quintile were more likely to be hospitalised with an ACSC. After controlling for age, sex, socioeconomic status (SES) and other behavioural factors, low life satisfaction at baseline had a strong relationship with future hospitalisations for ACSCs (HR 2.71; 95% CI 1.87 to 3.93). The hazards were highest for those who jointly had the lowest levels of life satisfaction and low household income (HR 3.80; 95% CI 2.13 to 6.73). Results did not meaningful change after running a competing risk survival analysis. Conclusions This study demonstrates that poor life satisfaction is associated with hospitalisations for ACSCs after adjustment for several confounders. Furthermore, the magnitude of this relationship was greater for those who were more socioeconomically disadvantaged. This study adds to the existing literature on the impact of life satisfaction on health system outcomes by documenting its impact on avoidable hospitalisations in a universal health system.

Background: Health interventions aimed at facilitating connectedness among seniors have recently gained traction, seeing as social connectedness is increasingly being recognized as an important determinant of health. However, research examining the association between connectedness and health across all age groups is limited, and few studies have focused on community belonging as a tangible aspect of social connectedness. Using a population-based Canadian cohort, this study aims to investigate (1) the associations between community belonging with self-rated general health and self-rated mental health, and (2) how these associations differ across life stages. Methods: Data from six cycles of a national population health survey (Canadian Community Health Survey) from 2003 to 2014 were combined. Multinomial logistic regressions were run for both outcomes on the overall study sample, as well as within three age strata: (1) 18-39, (2) 40-59, and (3) >= 60 years old. Results: Weaker community belonging exhibited an association with both poorer general and mental health, though a stronger association was observed with mental health. These associations were observed across all three age strata. In the fully adjusted model, among those reporting a very weak sense of community belonging, the odds of reporting the poorest versus best level of health were 3.21 (95% CI: 3.11, 3.31) times higher for general health, and 4.95 (95% CI: 4.75, 5.16) times higher for mental health, compared to those reporting a very strong sense of community belonging. The largest effects among those reporting very weak community belonging were observed among those aged between 40 and 59 years old. Conclusion: This study contributed to the evidence base supporting life stage differences in the relationship between community belonging and self-perceived health. This is a starting point to identifying how age-graded differences in unmet social needs relate to population health interventions.

In the event of the current COVID-19 pandemic and in preparation for future pandemics, open science can support mission-oriented research and development, as well as commercialization. Open science shares skills and resources across sectors; avoids duplication and provides the basis for rapid and effective validation due to full transparency. It is a strategy that can adjust quickly to reflect changing incentives and priorities, because it does not rely on any one actor or sector. While eschewing patents, it can ensure high-quality drugs, low pricing, and access through existing regulatory mechanisms. Open science practices and partnerships decrease transaction costs, increase diversity of actors, reduce overall costs, open new, higher-risk/higher-impact approaches to research, and provide entrepreneurs freedom to operate and freedom to innovate. We argue that it is time to re-open science, not only in its now restricted arena of fundamental research, but throughout clinical translation. Our model and attendant recommendations map onto a strategy to accelerate discovery of novel broad-spectrum anti-viral drugs and clinical trials of those drugs, from first-in-human safety-focused trials to late stage trials for efficacy. The goal is to ensure low-cost and rapid access, globally, and to ensure that Canadians do not pay a premium for drugs developed from Canadian science.