Canadian Medical Association Journal

ObjectivesEstimates of health system costs due to COVID-19, especially for long-term disability (post COVID-19 condition [PCC]) are key to health system planning, but attributable cost data remain scarce. We characterized COVID-19-attributable costs from the health system perspective. MethodsPopulation-based matched cohort study in Ontario, Canada, using health administrative data. To assign attribution to COVID-19, individuals, defined as exposed (positive SARS-CoV-2 PCR test, 01/2020-12/2020) were matched 1:1 to an unexposed individuals (01/2016-12/2018). Historical matching was used to reduce biases due to overall reductions in healthcare during the pandemic and contamination bias. The index date was defined as the first occurrence of positive SARS-CoV-2 PCR test. We used phase-of-care costing to calculate mean attributable per-person costs (2023 CAD), standardized to 10 days, during four phases of illness: pre-index date, acute care, post-acute care (suggestive of PCC), and terminal phase (stratified by early and late deaths). Finally, we estimated total costs at 360 days by combining costs with survival estimates. ResultsOf 165,838 exposed individuals, 159,817 were matched (mean age 40{+/-}20 years, 51% female). Mean (95%CI) attributable 10-day costs per person were $1 ($-4, $6) pre-index, $240 ($231, $249) during acute care, and $18 ($14, $21) during post-acute phases. During the terminal phase, mean attributable costs were $3,928 ($3,471, $4,384) for early deaths and $1,781 ($1,182, $2,380) for late deaths. Hospitalizations accounted for 42% to 100% of total costs. Compared to males, costs among females were lower during the acute care phase, but higher during the post-acute care phase. Mean cumulative per-person cost at 360 days was $2,553 ($2,348, $2,756); females had lower costs ($2,194 [$1,945, $2,446]) than males ($2,921 [$2,602, $3,241]). ConclusionsSARS-CoV-2 infection is associated with substantial long-term healthcare costs, consistent with our understanding of the PCC. Understanding phase-specific costs can inform health sector budget planning, future economic evaluations, and pandemic planning.

BackgroundHaving temporary immigration status affords limited rights, workplace protections, and access to services. There is not yet research data on impacts of the COVID-19 pandemic for people with temporary immigration status in Canada. MethodsWe use linked administrative data to describe SARS-CoV-2 testing, positive tests, and COVID-19 primary care service use in British Columbia from January 1, 2020, to July 31, 2021, stratified by immigration status (Citizen, Permanent Resident, Temporary Resident). We plot the rate of people tested and the rate of people confirmed positive for COVID-19 by week from April 19, 2020, to July 31, 2021, across immigration groups. Results4.9% of people with temporary immigration status had a positive test for SARS-CoV-2 over this period, compared to 4.0% among people with permanent residency and 2.1% among people who hold Canadian citizenship. This pattern is persistent by sex/gender, age group, neighborhood income quintile, health authority, and in both metropolitan and small urban settings. At the same time we observe lower access to testing and COVID-19 related primary care among people with temporary status. InterpretationPeople with temporary immigration status in BC experience higher SARS-CoV-2 test positivity; alarmingly, this was coupled with lower access to testing and primary care. Interwoven immigration, health and occupational policies place people with temporary status in circumstances of precarity and higher health risk. Extending permanent residency status to all immigrants residing in Canada and decoupling access to health care from immigration status could reduce precarity due to temporary immigration status.

BackgroundThe burden of COVID-19 in Canada is unequally distributed geographically, with the largest number of cases and fatalities recorded in Quebec and Ontario while other provinces experienced limited outbreaks. To date, however, no study has assessed how provincial epidemics have unfolded in a comparative perspective. This is essential to calibrate projections of the future course of the epidemic and plan health care resources for the second wave of infections. MethodsUsing newly released individual-level data collected by the Public Health Agency of Canada, we assess COVID-19-related morbidity and mortality across age and gender groups at the provincial level through a combination of demographic and survival analyses. ResultsQuebec has the highest absolute and per capita number of COVID-19 confirmed positive cases, hospitalizations and fatalities in all age groups. In each province, a higher number of women than men test positive for the disease, especially above age 80. Yet consistently across age groups, infected men are more likely to be hospitalized and enter intensive care than women do. These gender differences in hospitalisation rates account for the higher case fatality risk due to COVID-19 among men compared to women. InterpretationAlthough health care capacity across provinces has been sufficient to treat severe cases, we find that the main factor accounting for gender differences in COVID-19-related mortality is the need for hospitalization and intensive care, especially above age 80. This suggests a selection effect of severe cases requiring to be treated in a hospital setting that needs to be further investigated.

SARS-CoV-2 strained Ontarios health system, with social determinants of health (SDH) underexplored in cost analyses. We examined COVID-19 attributable healthcare resource use and costs from the Ontario health system perspective using health administrative data. We conducted a cohort study, matching 162,633 SARS-CoV-2-exposed individuals 1:1 to unexposed individuals. We calculated 10-day per-person mean attributable costs (2023 CAD) across care phases (pre-diagnosis, acute, post-acute, terminal), stratified by individual and area-level SDH. Among exposed individuals (mean age 40.4 years, 50.7% female), 6% were hospitalized, 1.3% admitted to critical care, and 2% died within 360 days. Mean (SD) person acute phase cost was $244 ($235-$253) and higher among males, recent immigrants, individuals living in low-income neighbourhoods and neighbourhoods with a higher proportion of crowded households. Extrapolating to the population level of 166,801 exposed individuals, the mean total survival-adjusted 360-day cost was $436 million. COVID-19 increased healthcare costs, disproportionately burdening marginalized communities.

IntroductionNational responses to the SARS-CoV-2 pandemic have been highly variable, which may explain some of the heterogeneity in the pandemics health and economic impacts across the world. We sought to explore the effectiveness of the Canadian pandemic response relative to responses in four peer countries with similar political, economic and health systems, and with close historical and cultural ties to Canada (the United States, United Kingdom, France, and Australia) from March 2020 to May 2022. MethodsWe used reported age-specific mortality data to generate estimates of pandemic mortality standardized to the Canadian population. Age-specific case fatality, hospitalization, and intensive care admission probabilities for the Canadian province of Ontario were applied to estimated deaths in order to calculate hospitalizations and intensive care admissions averted by the Canadian response. The monetary value of averted hospitalizations was estimated using cost estimates from the Canadian Institute for Health Information. Age-specific quality-adjusted life-years (QALY) lost due to fatality were estimated using published estimates. QALY were monetized using a net expected benefit approach. ResultsRelative to the United States, United Kingdom, and France, the Canadian pandemic response was estimated to have averted 94,492, 64,306 and 13,641 deaths respectively, with more than 480,000 hospitalizations averted, and 1 million QALY saved, relative to the United States. A United States pandemic response applied to Canada would have resulted in more than $40 billion in economic losses due to healthcare expenditures and lost QALY; losses relative to the United Kingdom and France would have been $21 billion and $5 billion respectively. By contrast, an Australian pandemic response would have averted over 28,000 additional deaths and averted nearly $9 billion in costs in Canada. ConclusionsCanada outperformed peer countries that aimed for mitigation, rather than elimination, of SARS-CoV-2 in the first two years of the pandemic, likely because of a more stringent public health response to disease transmission. This resulted in substantial numbers of lives saved and economic costs averted. However, comparison with Australia demonstrates that an elimination focus would have allowed Canada to save tens of thousands of lives, and would have saved substantial economic costs.

BackgroundThe requirement for critical care in even a modest fraction of SARS-CoV-2 infected individuals made ICU resources an important societal chokepoint during the recent pandemic. We developed a simple regression-based point score in 2020 based on an objective of forecasting critical care occupancy in the Canadian province of Ontario based on mean age of cases, case numbers, and testing volume. Evolution of the pandemic (variants of concern, vaccination) led us to re-assess and re-calibrate our earlier work, with inclusion of information vaccination which became widespread in 2021. MethodsWe obtained complete provincial SARS-CoV-2 case, testing, and vaccination data for the period from March 2020 to September 2022, with data subdivided into 6 major "waves", following the approach applied by other Canadian investigators. Our initial model was fit only using the first two "wild type" SARS-CoV-2 waves; an updated model included wave 3 (N501Y+ variants). Our model was validated by comparing model projections to waves not used for model fitting; validation model fits were evaluated with Spearmans rho; counterfactuals without vaccination were modeled to impute fraction of critical care admissions prevented with vaccination. Costing was based on published economic estimates. ResultsOur initial model (fit to waves 1 and 2) was well calibrated (rho 0.85) but predictive validity was modest (rho 0.46). Predictive validity improved in models fit to the first 3 pandemic waves without vaccination (rho 0.60) or with vaccination (rho 0.68) (P for inclusion of vaccination 0.013 by Likelihood Ratio Test). Prevented fraction of ICU admissions attributable to vaccination was 144% (22017 admissions expected vs. 9020 observed); based on published estimates of ICU admission cost for SARS-CoV-2 the 12977 admissions averted $2.9 (CDN) billion in economic costs, in contrast to the $3 billion total cost of the vaccination program. ConclusionsSimple time series regression incorporating case and testing characteristics continues to be useful as a tool for forecasting critical care occupancy due to SARS-CoV-2 but early pandemic models need to be updated to capture the preventive effects of widespread vaccination. The economic benefit of vaccination for prevention of critical care resource consumption during the pandemic is substantial, achieving near cost neutrality with the provinces entire vaccination program.

BackgroundThe goal of this study was to project the number of COVID-19 cases and demand for acute hospital resources for Fall of 2021 in a representative mid-sized community in southwestern Ontario. We sought to evaluate whether current levels of vaccine coverage and contact reduction could mitigate a potential 4th wave fueled by the Delta variant, or whether the reinstitution of more intense public health measures will be required. MethodsWe developed an age-stratified dynamic transmission model of COVID-19 in a mid-sized city (population 500,000) currently experiencing a relatively low, but increasing, infection rate in Step 3 of Ontarios Wave 3 recovery. We parameterized the model using the medical literature, grey literature, and government reports. We estimated the current level of contact reduction by model calibration to cases and hospitalizations. We projected the number of infections, number of hospitalizations, and the time to re-instate high intensity public health measures over the fall of 2021 under different levels of vaccine coverage and contact reduction. ResultsMaintaining contact reductions at the current level, estimated to be a 17% reduction compared to pre-pandemic contact levels, results in COVID-related admissions exceeding 20% of pre-pandemic critical care capacity by late October, leading to cancellation of elective surgeries and other non-COVID health services. At high levels of vaccination and relatively high levels of mask wearing, a moderate additional effort to reduce contacts (30% reduction compared to pre-pandemic contact levels), is necessary to avoid re-instating intensive public health measures. Compared to prior waves, the age distribution of both cases and hospitalizations shifts younger and the estimated number of pediatric critical care hospitalizations may substantially exceed 20% of capacity. DiscussionHigh rates of vaccination coverage in people over the age of 12 and mask wearing in public settings will not be sufficient to prevent an overwhelming resurgence of COVID-19 in the Fall of 2021. Our analysis indicates that immediate moderate public health measures can prevent the necessity for more intense and disruptive measures later.

BackgroundThe global spread of coronavirus disease 2019 (COVID-19) continues in several jurisdictions, causing significant strain to healthcare systems. The purpose of our study is to predict the impact of the COVID-19 pandemic on patient outcomes and the healthcare system in Ontario, Canada. MethodsWe developed an individual-level simulation to model the flow of COVID-19 patients through the Ontario healthcare system. We simulated different combined scenarios of epidemic trajectory and healthcare capacity. Outcomes include numbers of patients needing admission to the ward, Intensive Care Unit (ICU), and requiring ventilation; days to resource depletion; and numbers of patients awaiting resources and deaths associated with limited access to resources. FindingsWe demonstrate that with effective early public health measures system resources need not be depleted. For scenarios considering late or ineffective implementation of physical distancing, health system resources would be depleted within 14-26 days. Resource depletion was also avoided or delayed with aggressive measures to rapidly increase ICU, ventilator, and acute care hospital capacity. InterpretationWe found that without aggressive physical distancing measures the Ontario healthcare system would have been inadequately equipped to manage the expected number of patients with COVID-19, despite the rapid capacity increase. This overall lack of resources would have led to an increase in mortality. By slowing the spread of the disease via ongoing public health measures and having increased healthcare capacity, Ontario may have avoided catastrophic stresses to its health care system.

BackgroundIn 2024, the National Advisory Committee on Immunization recommended universal RSV immunization across Canada, prioritizing infants in remote communities. However, in the absence of population-based data, programs may not effectively narrow health gaps in remote communities. MethodsRetrospective cohort study of all births in British Columbia (BC) from April 2013 to March 2024, followed for 1 year, using health administrative data. Main outcomes were hospitalizations for all-cause and RSV-lower respiratory tract infection (LRTI). Secondary outcomes were tertiary Pediatric Intensive Care Unit (PICU) admissions, length of stay, and air transport. Main exposures were community remoteness and social determinants of health. Incidence rates and incidence rate ratios (IRR) adjusted for sex, prematurity, and chronic conditions were estimated using Poisson generalized estimating equations. ResultsAmong 472,623 infants, those living in remote communities (N=3636) had higher hospitalization risk for all-cause (IRR: 2.91, 95%CI 2.02-3.65) and RSV-LRTIs (IRR: 1.60, 95%CI 1.17-2.19) compared to metropolitan areas. Length of stay and PICU admission rates were similar by region. Almost half (48.8%) of children from remote areas hospitalized for all-cause LRTIs required air evacuation. Infants from remote communities remained at higher risk for all-cause (aIRR 2.84, 95% CI 2.22-3.63) and RSV-LRTI (aIRR 1.56, 95% CI 1.15-2.12) hospitalizations after adjusting for covariates. InterpretationInfants in remote communities experienced a disproportionately high RSV-LRTI burden, supporting prioritized RSV interventions in these regions. The residual risk after accounting for known factors highlights the need to investigate additional drivers of vulnerability in remote areas.

Background: The SARS-CoV-2 disease 2019 (COVID-19) pandemic has spread across the world with varying impact on health systems and outcomes. We assessed how the type and timing of public-health interventions impacted the course of the outbreak in Alberta and the other Canadian provinces. Methods: We used publicly-available data to summarize rates of laboratory data and mortality in relation to measures implemented to contain the outbreak and testing strategy. We estimated the transmission potential of SARS-CoV-2 before the state of emergency declaration for each province (R0) and at the study end date (Rt). Results: The first cases were confirmed in Ontario (January 25) and British Columbia (January 28). All provinces implemented the same health-policy measures between March 12 and March 30. Alberta had a higher percentage of the population tested (3.8%) and a lower mortality rate (3/100,000) than Ontario (2.6%; 11/100,000) or Quebec (3.1%; 31/100,000). British Columbia tested fewer people (1.7%) and had similar mortality as Alberta. Data on provincial testing strategies were insufficient to inform further analyses. Mortality rates increased with increasing rates of lab-confirmed cases in Ontario and Quebec, but not in Alberta. Ro was similar across all provinces, but varied widely from 2.6 (95% confidence intervals 1.9-3.4) to 6.4 (4.3-8.5), depending on the assumed time interval between onset of symptoms in a primary and a secondary case (serial interval). The outbreak is currently under control in Alberta, British Columbia and Nova Scotia (Rt <1). Interpretation: COVID-19-related health outcomes varied by province despite rapid implementation of similar health-policy interventions across Canada. Insufficient information about provincial testing strategies and a lack of primary data on serial interval are major limitations of existing data on the Canadian COVID-19 outbreak.

This study combined public data and geospatial analysis to examine physicians language abilities and locations in Alberta, Canada, and produced an interactive map to allow patients and policymakers to view the data. We identified n=11,370 active physicians in the province of Alberta, of whom we further identified n=194 (1.7%) as University of Ottawa (uOttawa) graduates, n=955 (8.4%) as French-speaking, and n=4,965 (43.7%) as community-based family physicians. French-speaking physicians were concentrated in Census Division 6 (n=464, 48.6%) surrounding Calgary and Census Division 11 (n=356, 37.3%) surrounding Edmonton. Overall reported French-language ability was low, with just 955 (8.4%) of all active physicians reporting competency in French. uOttawa graduates (n=70, 36.1%) were much more likely to report French ability than graduates of other schools (n=885, 7.9%), women (n=457, 9.6%) were slightly more likely than men (n=497, 7.6%), and specialists (n=666, 10.4%) were more likely than family physicians (n=289, 5.8%).

BackgroundUnderstanding resource use for COVID-19 is critical. We conducted a population-based cohort study using public health data to describe COVID-19 associated age- and sex-specific acute care use, length of stay (LOS), and mortality. MethodsWe used Ontarios Case and Contact Management (CCM) Plus database of individuals who tested positive for COVID-19 in Ontario from March 1 to September 30, 2020 to determine age- and sex-specific hospitalizations, intensive care unit (ICU) admissions, invasive mechanical ventilation (IMV) use, LOS, and mortality. We stratified analyses by month of infection to study temporal trends and conducted subgroup analyses by long-term care residency. ResultsDuring the observation period, 56,476 COVID-19 cases were reported (72% < 60 years, 52% female). The proportion of cases shifted from older populations (> 60 years) to younger populations (10-39 years) over time. Overall, 10% of individuals were hospitalized, of those 22% were admitted to ICU, and 60% of those used IMV. Mean LOS for individuals in the ward, ICU without IMV, and ICU with IMV was 12.8, 8.5, 20.5 days, respectively. Mortality for individuals receiving care in the ward, ICU without IMV, and ICU with IMV was 24%, 30%, and 45%, respectively. All outcomes varied by age and decreased over time, overall and within age groups. InterpretationThis descriptive study shows acute care use and mortality varying by age, and decreasing between March and September in Ontario. Improvements in clinical practice and changing risk distributions among those infected may contribute to fewer severe outcomes among those infected with COVID-19.

ImportancePrevention-focused health policy requires analytic frameworks capable of detecting changes in population health and associated costs within policy-relevant time horizons, particularly in managed care systems where premiums reflect actuarial risk rather than realized medical expenditures. ObjectiveTo evaluate a healthstate-based analytic framework (CareMaps) for measuring population health dynamics, disease progression, and associated costs using longitudinal Medicaid managed care claims data. Design, Setting, and ParticipantsRetrospective longitudinal analysis of deidentified Medicaid managed care claims in New Mexico from 2011 through 2014. The study included individuals aged 0 to 64 years enrolled in managed care plans. ExposuresChronic disease burden categorized into mutually exclusive, ordered healthstates based on the number of chronic conditions. Main Outcomes and MeasuresCounty- and managed care organization (MCO) level prevalence of healthstates, transition rates between healthstates, and healthstate-specific cost estimates derived from capitation premiums and medical loss ratio defined medical expenditures. ResultsThe CareMaps framework identified specific geographic and MCO level variation in chronic disease prevalence, healthstate transition rates, and per-member spending patterns that were not fully explained by actuarial risk adjustment. Transitions from nonchronic to chronic healthstates varied markedly across counties, indicating heterogeneity in disease progression and prevention related outcomes. Conclusions and RelevanceA healthstate based analytic framework applied to longitudinal Medicaid managed care data enables standardized measurement of population health dynamics and associated costs within policy relevant time horizons. Such approaches may support evaluation of preventive care performance, inform risk adjustment, and enhance public-sector oversight of managed care programs.

The pandemic caused by SARS-CoV-2 has proven challenging clinically, and at the population level, due to heterogeneity in both transmissibility and severity. Recent case incidence in Ontario, Canada (autumn 2020) has outstripped incidence in seen during the first (spring) pandemic wave; but has been associated with a lower incidence of intensive care unit (ICU) admissions and deaths. We hypothesized that differential ICU burden might be explained by increased testing volumes, as well as the shift in mean case age from older to younger. We constructed a negative binomial regression model using only three covariates, at a 2-week lag: log10(weekly cases); log10(weekly deaths); and mean weekly case age. This model reproduced observed ICU admission volumes, and demonstrated good preliminary predictive validity. Furthermore, when admissions were used in combination with ICU length of stay, our modeled estimates demonstrated excellent convergent validity with ICU occupancy data reported by the Canadian Institute for Health Information. Our approach needs external validation in other settings and at larger and smaller geographic scales, but appears to be a useful short-term forecasting tool for ICU resource demand; we also demonstrate that the virulence of SARS-CoV-2 infection has not meaningfully changed in Ontario between the first and second waves, but the demographics of those infected, and the fraction of cases identified, have.

BackgroundThe COVID-19 pandemic placed immense strain on Canadas healthcare system and disproportionately affected individuals with poorer baseline health. Healthcare-associated infections (HAIs) increase risk for both patients and healthcare workers and are often more severe due to advanced age and comorbidities. While efforts have aimed to reduce in-hospital transmission, the individual- and community-level consequences of HAIs require further study. We aimed to assess whether healthcare-associated COVID-19 cases had higher odds of death compared to hospitalized community-acquired cases, and to evaluate the directionality of transmission between hospitals and the community. MethodsWe analyzed COVID-19 surveillance data from Ontarios Case Contact and Management System and the COVaxON vaccine registry (March 17, 2020, to September 4, 2022). Latent class analysis was used to classify hospitalized cases by likelihood of healthcare-associated infection. Mortality odds by category were estimated using binomial logistic regression. Directionality between hospital outbreaks and community cases was assessed using a modified Granger causality approach. FindingsCompared to patients with low likelihood of healthcare-associated infection, those moderately likely to have acquired COVID-19 in hospital had elevated odds of death (OR: 1.26, 95% CI: 1.14-1.40); no significant increase was seen in the high-likelihood group (OR: 1.05, 95% CI: 0.96-1.15). Community cases did not predict hospital outbreaks (p=0.5749), but hospital outbreaks predicted community case growth (p<0.0001). InterpretationHospital-acquired COVID-19 is associated with excess mortality and may drive community transmission. Preventing in-hospital transmission is critical to protecting patients and controlling broader epidemic spread. FundingSupported by a Canadian Institutes for Health Research project grant, #518192.

BackgroundNunavut is a northern Canadian territory in Inuit Nunangat (Inuit homeland in Canada). Approximately 85% of the population identifies as Inuit. A high proportion of infants in Nunavut are admitted to hospital with acute respiratory tract infection (ARI) but previous studies have been limited in regional and/or short duration of coverage. This study aimed to estimate the incidence rate, microbiology and outcomes of ARI hospitalizations in Nunavut infants. MethodsWe conducted chart reviews with a retrospective cohort of infants aged <1 year from Nunavut at six Canadian hospitals, including two regional and four tertiary pediatric hospitals January 1, 2010, to June 30, 2020. Descriptive statistics and multivariable logistic regression were performed. ResultsWe identified 1189 ARI admissions of infants during the study period, with an incidence rate of 133.9 per 1000 infants per year (95% confidence interval (CI): 126.8, 141.3). Of these admissions, 56.0% (n=666) were to regional hospitals alone, 72.3% (n=860) involved hospitalization outside of Nunavut, 15.6% (n=185) were admitted into intensive care, and 9.2% (n=109) underwent mechanical ventilation. Of the 730 admissions with a pathogen identified, 45.8% had respiratory syncytial virus (RSV; n=334), for a yearly incidence rate of 37.8 hospitalizations per 1000 infants (95% CI: 33.9, 42.1). Among RSV hospitalizations, 41.1% (n=138) were infants 0-2 months of age and 32.1% (n=108) were > 6months. InterpretationUnderstanding the high burden of ARI among Nunavut infants can inform health policy and serve as a baseline for assessing the impact of any new interventions targeting infant ARIs.

Introduction - Worldwide, nursing home residents have experienced disproportionately high COVID-19 mortality due to the intersection of congregate living, multimorbidity, and advanced age. Among 12 OECD countries, Canada has had the highest proportion of COVID-19 deaths in nursing home residents (78%), raising concerns about a skewed pandemic response that averted much transmission and mortality in community-dwelling residents, but did not adequately protect those in nursing homes. To investigate this, we measured temporal variations in hospitalizations among community and nursing home-dwelling decedents with COVID-19 during the first and second waves of the pandemic. Methods - We conducted a population-based cohort study of residents of Ontario, Canada with COVID-19 who died between March 11, 2020 (first COVID-19 death in Ontario) and October 28, 2020. We examined hospitalization prior to death as a function of 4 factors: community (defined as all non-nursing home residents) vs. nursing home residence, age in years (<70, 70-79, 80-89, [&ge;]90), gender, and month of death (1st wave: March-April [peak], May, June-July 2020 [nadir], 2nd wave: August-October 2020). Results - A total of 3,114 people with confirmed COVID-19 died in Ontario from March to October, 2020 (Table 1), of whom 1,354 (43.5%) were hospitalized prior to death (median: 9 days before death, interquartile range: 4-19). Among nursing home decedents (N=2000), 22.4% were admitted to hospital prior to death, but this varied substantially from a low of 15.5% in March-April (peak of wave 1) to a high of 41.2% in June-July (nadir of wave 1). Among community-dwelling decedents (N=1,114), admission to acute care was higher (81.4%) and remained relatively stable throughout the first and second waves. Similar temporal trends for nursing home versus community decedents were apparent in age-stratified analyses (Figure 1). Women who died were less likely to have been hospitalized compared to men in both community (80% women vs 84% men) and nursing home (21% women vs 24% men) settings. Discussion - Only a minority of Ontario nursing home residents who died of COVID-19 were hospitalized prior to death, and that there were substantial temporal variations, with hospitalizations reaching their lowest point when overall COVID-19 incidence peaked in mid-April, 2020. While many nursing home residents had pre-pandemic advance directives precluding hospitalization, the low admission rate observed in March-April 2020 (15.5%) was inconsistent with both higher admission rates in subsequent months (>30%), and comparatively stable rates among community-dwelling adults. Our findings substantiate reports suggesting that hospitalizations for nursing home residents with COVID-19 were low during the peak of the pandemics first wave in Canada, which may have contributed to the particularly high concentration of COVID-19 mortality in Ontarios nursing homes.

ImportanceResident crowding in nursing homes is associated with larger SARS-CoV-2 outbreaks. However, this association has not been previously documented for non-SARS-CoV-2 respiratory infections. ObjectiveWe sought to measure the association between nursing home crowding and respiratory infections in Ontario nursing homes prior to the COVID-19 pandemic. Design, Setting, and ParticipantsWe conducted a retrospective cohort study of nursing home residents in Ontario, Canada over a five-year period prior to the COVID-19 pandemic, between September 2014 and August 2019. ExposureUsing administrative data, we estimated the crowding index equal to the mean number of residents per bedroom and bathroom (residents / [0.5*bedrooms+0.5*bathrooms]). OutcomesThe incidence of outbreak-associated infections and mortality per 100 nursing home residents per year. We also examined infection and mortality outcomes for outbreaks due to 7 specific pathogens: coronaviruses (OC43, 229E, NL63, HKU1), influenza A, influenza B, human metapneumovirus, parainfluenza virus, respiratory syncytial virus, rhinovirus/enterovirus. ResultsThere was one or more respiratory outbreak in 93.9% (588/626) nursing homes in Ontario. There were 4,921 outbreaks involving 64,829 cases of respiratory infection, and 1,969 deaths. Outbreaks attributable to a single identified pathogen were principally caused by influenza A (29%), rhinovirus (11.7%), influenza B (8.1%), and respiratory syncytial virus (6.1%). Among homes, 42.7% (251/588) homes had a high crowding index ([&ge;] 2.0). After adjustment, more crowded homes had higher outbreak-associated respiratory infection incidence (aRR 1.89; 95% 1.64-2.18) and mortality incidence (aRR 2.28; 95% 1.84-2.84). More crowded homes had higher adjusted estimates of the incidence of infection and mortality for each of the 7 respiratory pathogens examined. Conclusions and RelevanceResidents of crowded nursing homes experienced more respiratory-outbreak infections and mortality due to influenza and other non-SARS-CoV-2 respiratory pathogens. Decreasing crowding in nursing homes is an important patient safety target beyond the COVID-19 pandemic.

BackgroundSocioeconomic disparities in COVID-19 outcomes have been widely documented, but evidence regarding inequities in SARS-CoV-2 transmission remains mixed. In Canada, infection-induced seroprevalence appeared to converge across socioeconomic strata by late 2022, raising questions about whether transmission inequities diminished during the Omicron period. AimTo assess whether apparent convergence in SARS-CoV-2 seroprevalence reflects true equity in transmission or masks persistent socioeconomic disparities in force of infection. MethodsWe analysed serial cross-sectional SARS-CoV-2 seroprevalence data (anti-nucleocapsid antibodies) from Canadian Blood Services donors collected between April 2021 and April 2023 and stratified by area-level material deprivation quintile. We fitted a dynamic susceptible-infected model with sero-reversion to the full seroprevalence time series, estimating quintile-specific forces of infection before and after the emergence of the Omicron variant (January 2022). Models allowing differential Omicron-related amplification by socioeconomic status were compared using likelihood-based criteria. ResultsDuring the pre-Omicron period, force of infection increased monotonically with material deprivation; the most deprived quintile experienced a 71% higher force of infection than the least deprived (incidence rate ratio (IRR): 1.71; 95% CI: 1.60-1.83). Following Omicron emergence, force of infection increased markedly in all quintiles but by differing magnitudes. Relative increases were largest in the least deprived quintile (48.5-fold) and smallest in the most deprived quintile (31.8-fold), resulting in compression of the socioeconomic gradient (Q5 vs Q1 IRR: 1.12; 95% CI: 1.11-1.14). Despite this compression, materially deprived populations continued to experience elevated transmission risk. ConclusionConvergence in SARS-CoV-2 seroprevalence across socioeconomic strata masked persistent inequalities in force of infection. Dynamic modelling demonstrates that apparent equity arose from differential amplification of transmission during the Omicron period rather than from elimination of underlying socioeconomic disparities.

ImportanceProtecting healthcare workers (HCWs) from COVID-19 is a priority to maintain a safe and functioning healthcare system. The risk of transmitting COVID-19 to family members is a source of stress for many. ObjectiveTo describe and compare HCW and non-HCW COVID-19 cases in Ontario, Canada, as well as the frequency of COVID-19 among HCWs household members. Design, Setting, and ParticipantsUsing reportable disease data at Public Health Ontario which captures all COVID-19 cases in Ontario, Canada, we conducted a population-based cross-sectional study comparing demographic, exposure, and clinical variables between HCWs and non-HCWs with COVID-19 as of 14 May 2020. We calculated rates of infections over time and determined the frequency of within household transmissions using natural language processing based on residential address. Exposures and OutcomesWe contrasted age, gender, comorbidities, clinical presentation (including asymptomatic and presymptomatic), exposure histories including nosocomial transmission, and clinical outcomes between HCWs and non-HCWs with confirmed COVID-19. ResultsThere were 4,230 (17.5%) HCW COVID-19 cases in Ontario, of whom 20.2% were nurses, 2.3% were physicians, and the remaining 77.4% other specialties. HCWs were more likely to be between 30-60 years of age and female. HCWs were more likely to present asymptomatically (8.1% versus 7.0%, p=0.010) or with atypical symptoms (17.8% versus 10.5%, p<0.001). The mortality among HCWs was 0.2% compared to 10.5% of non-HCWs. HCWs commonly had exposures to a confirmed case or outbreak (74.1%), however only 3.1% were confirmed to be nosocomial. The rate of new infections was 5.5 times higher in HCWs than non-HCWs, but mirrored the epidemic curve. We identified 391 (9.8%) probable secondary household transmissions and 143 (3.6%) acquisitions. Children < 19 years comprised 14.6% of secondary cases compared to only 4.2% of the primary cases. Conclusions and RelevanceHCWs represent a disproportionate number of COVID-19 cases in Ontario but with low confirmed numbers of nosocomial transmission. The data support substantial testing bias and under-ascertainment of general population cases. Protecting HCWs through appropriate personal protective equipment and physical distancing from colleagues is paramount. Key PointsO_ST_ABSQuestionC_ST_ABSWhat are the differences between healthcare workers and non-healthcare workers with COVID-19? FindingsIn this population-based cross-sectional study there were 4,230 healthcare workers comprising 17.5% of COVID-19 cases. Healthcare workers were diagnosed with COVID-19 at a rate 5.5 times higher than the general population with 0.8% of all healthcare workers, compared to 0.1% of non-healthcare workers. MeaningHigh healthcare worker COVID-19 burden highlights the importance of physical distancing from colleagues, appropriate personal protective equipment, as well as likely substantial testing bias and under-ascertainment of COVID-19 in the general population.