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Trade-offs abound in healthcare yet depending on where one stands relative to the stages of a pandemic, choice making may be more or less constrained. During the early stages of COVID-19 when there was much uncertainty, healthcare systems faced greater constraints and focused on the singular criterion of “flattening the curve.” As COVID-19 progressed and the first wave diminished (relatively speaking depending on the jurisdiction), more opportunities presented for making explicit choices between COVID and non-COVID patients. Then, as the second wave surged, again decision makers were more constrained even as more information and greater understanding developed. Moving out of the pandemic to recovery, choice making becomes paramount as there are no set rules to lean back into historical patterns of resource allocation. In fact, the opportunity at hand, when using explicit tools...

A mathematical model of COVID-19 is presented where the decision to increase or decrease social distancing is modelled dynamically as a function of the measured active and total cases as well as the perceived cost of isolating. Along with the cost of isolation, we define an overburden healthcare cost and a total cost. We explore these costs by adjusting parameters that could change with policy decisions. We observe that two disease prevention practices, namely increasing isolation activity and increasing incentive to isolate do not always lead to optimal health outcomes. We demonstrate that this is due to the fatigue and cost of isolation. We further demonstrate that an increase in the number of lock-downs, each of shorter duration can lead to minimal costs. Our results are compared with case data in Ontario, Canada from March to August 2020 and details of expanding the results to...

Abstract OBJECTIVE We implement a model-based approach to identify the optimal allocation of a COVID-19 vaccine in the province of Alberta, Canada. METHODS We develop an epidemiologic model to evaluate allocation strategies defined by age and risk target groups, coverage, effectiveness, and cost of vaccine. The model simulates hypothetical immunization scenarios within a dynamic context, capturing concurrent public health strategies and population behaviour changes. RESULTS In a scenario with 80% vaccine effectiveness, 40% population coverage, and prioritisation of those over the age of 60 at high-risk of poor outcomes, active cases are reduced by 17% and net monetary benefit increased by $263 million dollars, relative to no vaccine. Concurrent implementation of policies such as school closure and senior contact reductions have similar impacts on incremental net monetary benefit...

Abstract The promise of efficacious vaccines against SARS-CoV-2 is fulfilled and vaccination campaigns have started worldwide. However, the fight against the pandemic is far from over. Here, we propose an age-structured compartmental model to study the interplay of disease transmission, vaccines rollout, and behavioural dynamics. We investigate, via in-silico simulations, individual and societal behavioural changes, possibly induced by the start of the vaccination campaigns, and manifested as a relaxation in the adoption of non-pharmaceutical interventions. We explore different vaccine efficacy, vaccination rollout speeds, prioritization strategies, as well as multiple behavioural responses. We apply our model to six countries worldwide (Egypt, Peru, Serbia, Ukraine, Canada, and Italy) selected to sample diverse socio-demographic and socio-economic contexts. To isolate the...

Background Racialized and low income communities face disproportionally high rates of coronavirus 2019 (COVID-19) infection and death. However, data on inequities in COVID-19 across granular categories of socio-demographic characteristics is more sparse. Methods Neighbourhood-level counts of COVID-19 cases and deaths in Ontario, Canada recorded as of July 28th, 2020 were extracted from provincial and local reportable infectious disease surveillance systems. Associations between COVID-19 incidence and mortality and 18 neighbourhood-level measures of immigration, race, housing and socio-economic characteristics were estimated with Poisson generalized linear mixed models. Housing characteristic variables were subsequently added to models to explore if housing may have a confounding influence on the relationships between immigration, race, and socio-economic status and COVID-19...

The COVID-19 pandemic exhibits stark social inequities in infection and mortality outcomes. We investigated neighborhood-level inequities across cities in the US and Canada for COVID-19 cumulative case rates (46 cities), death rates (12 cities), testing rates and test positivity (12 cities), using measures that characterize social gradients by race/ethnicity, socioeconomic composition, or both jointly. We found consistent evidence of social gradients for case, death and positivity rates, with the most privileged neighborhoods having the lowest rates, but no meaningful variation in the magnitude of inequities between cities. Gradients were not apparent in testing rates, suggesting inadequate testing in the most deprived neighborhoods. Health agencies should monitor and compare inequities as part of their COVID-19 reporting practices and to guide pandemic response efforts. HIGHLIGHTS

Coronavirus disease 2019 (COVID-19) is a severe, novel virus that has spread globally. The implementation of a combination of public health interventions is required to reduce viral spread and avoid overwhelming acute care systems. Once available, an effective vaccination will further mitigate the impact of the COVID-19 pandemic. However, decision makers will initially need to prioritise access to limited vaccine stockpiles as these will be insufficient to vaccine the whole population. The aim of this study is to identify optimal vaccine allocation strategies defined by age and risk target groups, coverage, effectiveness, and cost of vaccine, within a dynamic context where other public health responses and population behaviour change. In this study we use an epidemiological model of COVID-19 that has been enhanced to produce expected costs and Quality Adjusted Life Year results as...

The COVID-19 pandemic has profoundly disrupted daily life in Canada. This study assesses changes in health behaviours during the early stages of the pandemic and examines socio-demographic disparities associated with these changes. We analyze data on adults age 25 and older (N = 4383) from the public-use Canadian Perspectives Survey Series 1: Impacts of COVID-19 (CPSS-COVID). Multinomial regression models assess the association between demographic and socio-economic characteristics with increases or decreases in six health behaviours: alcohol, tobacco, and cannabis use, junk food consumption, and TV and internet screen time. While findings varied across the six behaviours, overall, there was an increase in negative health behaviours: 14% of Canadian adults reported increasing their alcohol use (95% CI = 0.12, 0.15), 25% increased their junk food consumption (95% CI = 0.23, 0.27), and...

Testing for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is largely passive, which impedes epidemic control. We defined active testing strategies for SARS-CoV-2 using reverse transcription polymerase chain reaction (RT-PCR) for groups at increased risk of acquiring SARS-CoV-2 in all Canadian provinces. We identified 5 groups who should be prioritized for active RT-PCR testing: contacts of people who are positive for SARS-CoV-2, and 4 at-risk populations – hospital employees, community health care workers and people in long-term care facilities, essential business employees, and schoolchildren and staff. We estimated costs, human resources and laboratory capacity required to test people in each group or to perform surveillance testing in random samples. During July 8-17, 2020, across all provinces in Canada, an average of 41 751 RT-PCR tests were performed daily; we...

This study examined the emerging impact of COVID-19 on gambling during the first 6 weeks of emergency measures in Ontario, Canada. A cross-sectional online survey of 2005 gamblers, including a sub-sample of 1081 online gamblers (age 18 years and older), was administered to assess risky gambling behaviours and motivations, financial impacts from COVID-19, the influence of COVID-19 on online gambling, mental health concerns and substance use. A series of odds ratio comparisons and measures of association were carried out. Results show significant likelihood of online gambling among those classified as high-risk gamblers (according to the Problem Gambling Severity Index) and those with past experience of online gambling, though migration from land-based gambling was apparent. Among high-risk online gamblers, the most predictive risk factors included moderate and severe anxiety and...