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Background Social determinants of health (SDOH) have been associated with coronavirus disease 2019 (COVID-19) outcomes. We examined patterns in COVID-19–related mortality by SDOH and compared these patterns to those for non–COVID-19 mortality. Methods Residents of Ontario, Canada, aged ≥20 years were followed from 1 March 2020 to 2 March 2021. COVID-19–related death was defined as death within 30 days following or 7 days prior to a positive COVID-19 test. Area-level SDOH from the 2016 census included median household income; proportion with diploma or higher educational attainment; proportion essential workers, racially minoritized groups, recent immigrants, apartment buildings, and high-density housing; and average household size. We examined associations between SDOH and COVID-19–related mortality, and non-COVID-19 mortality using cause-specific hazard models. Results Of 11 810 255 individuals, we observed 3880 COVID-19–related deaths and 88 107 non–COVID-19 deaths. After accounting for demographics, baseline health, and other area-level SDOH, the following were associated with increased hazards of COVID-19–related death (hazard ratio [95% confidence interval]: lower income (1.30 [1.04–1.62]), lower educational attainment (1.27 [1.07–1.52]), higher proportions essential workers (1.28 [1.05–1.57]), racially minoritized groups (1.42 [1.08–1.87]), apartment buildings (1.25 [1.07–1.46]), and large vs medium household size (1.30 [1.12–1.50]). Areas with higher proportion racially minoritized groups were associated with a lower hazard of non–COVID-19 mortality (0.88 [0.84–0.92]). Conclusions Area-level SDOH are associated with COVID-19–related mortality after accounting for demographic and clinical factors. COVID-19 has reversed patterns of lower non–COVID-19 mortality among racially minoritized groups. Pandemic responses should include strategies to address disproportionate risks and inequitable coverage of preventive interventions associated with SDOH.

Economically marginalized communities have faced disproportionately higher risks for infection and death from COVID-19 across Canada. It was anticipated that health disparities would dissipate over time and during subsequent waves. We used person-level surveillance and neighbourhood-level income data to explore, using Lorenz curves and Gini coefficients, magnitude of inequalities in COVID-19 hospitalizations and deaths over five waves of COVID-19 in Ontario, Canada (population 14 million) between February 26, 2020 and February 28, 2022. We found that despite attempts at equity-informed policies alongside fluctuating levels of public health measures, inequalities in hospitalizations and deaths by income remained at levels observed during the first wave - prior to vaccination, discussion or implementation of equity-informed policies - and despite rising levels of hybrid immunity. There was no change in the magnitude of inequalities across all waves evaluated. Our findings indicate that interventions did not sufficiently address differential exposure risks amplified at the intersections of household crowding and size, workplace exposures, and systemic barriers to prevention and care (including access to therapeutics). Equity and effectiveness of programs are inherently linked and ongoing evaluation of both is central to inform the public health response to future waves of COVID-19 and other rapidly emergent pandemics.

In March 2020, COVID-19 assessment centres were launched across the province of Ontario to facilitate COVID-19 testing outside of emergency departments. We aimed to study the degree to which assessment centres provide education and follow-up care for patients with suspected COVID-19.We conducted an online survey of Ontario COVID-19 assessment centre directors between September 15 and October 15, 2020. The primary outcomes studied were the types of educational modalities employed and information conveyed, methods and frequency of test result communication, and any follow-up care that was offered. Survey respondents were also asked to provide descriptions of barriers to patient education and test communication.A total of 56 directors (representing 73 assessment centres) completed the survey. The most frequent educational modalities employed were educational handouts (92%), direct in-person counselling (89%), and referral to website (72%). Seventy-one percent of respondents indicated patients with positive test results would be notified, and 61% of respondents indicated that follow-up care would be offered. The most frequently reported barriers to patient education were insufficient time and high volume of tests, while the most frequently reported barriers to communication of test results were difficulty accessing online health portals and high volume of tests.The ability of many assessment centres to provide patient education is limited by both individual patient and system-level factors. Assessment centres may benefit from standardization of educational materials, improved accessibility to test results for patients in marginalized groups, and virtual pathways to facilitate additional counselling and care for individuals who test positive.En mars 2020, des centres d’évaluation de la COVID-19 ont été lancés dans la province de l’Ontario afin de favoriser le dépistage de la COVID-19 hors des services d’urgence. Les chercheurs visaient à étudier dans quelle mesure ces centres transmettent de l’information et des soins de suivi aux patients chez qui on présume une COVID-19.Les chercheurs ont réalisé un sondage en ligne auprès des directeurs des centres d’évaluation de la COVID-19 de l’Ontario entre le 15 septembre et le 15 octobre 2020. Le type de modalités pédagogiques utilisé et d’information transmise, les modes et la fréquence de communication des résultats des tests et les soins de suivi offerts étaient les résultats cliniques primaires à l’étude. Les répondants au sondage ont également été invités à décrire les obstacles à la transmission d’information aux patients et à la communication des résultats.Au total, 56 directeurs (représentant 73 centres d’évaluation) ont rempli le sondage. Les principales modalités pédagogiques étaient la remise de document d’information (92 %), des conseils individuels directs (89 %) et l’orientation vers un site Web (72 %). Ainsi, 71 % des répondants ont indiqué que les patients obtenant un résultat positif en étaient avisés, et 61 %, que des soins de suivi seraient offerts. Les principaux obstacles à la transmission d’information aux patients étaient le manque de temps et le volume élevé de tests, tandis que les principaux obstacles à la transmission des résultats étaient la difficulté d’accès aux portails santé en ligne et le volume élevé de tests.La capacité de nombreux centres d’évaluation à transmettre de l’information aux patients est limitée à la fois par des facteurs liés aux patients eux-mêmes et par des facteurs systémiques. Les centres d’évaluation pourraient tirer profit de la standardisation des documents pédagogiques, d’un meilleur accès aux résultats des tests pour les patients de groupes marginalisés et de trajectoires virtuelles pour favoriser la transmission de conseils et de soins supplémentaires aux personnes dont les résultats sont positifs.

The pandemic has affected hundreds of millions of people; early reports suggesting high rates of prolonged symptoms may be prone to selection bias.In a program caring for all SARS-CoV-2 positive inpatients and outpatients between March to October 2020, and offering universal 90-day follow-up, we compared those who died prior to 90 days, not responding to follow-up, declining, or accepting follow-up. Among those seen or declining follow-up, we determined the prevalence and predictors of persistent symptoms.Among 993 patients, 21 (2.1%) died prior to 90 days, 506 (50.9%) did not respond, 260 (26.1%) declined follow-up because they were well, and 206 (20.7%) were fully assessed. Of 466 who responded to follow-up inquiry, 133 (28.5%) reported ≥1 persistent symptom, including constitutional (15.5%), psychiatric (14.2%), rheumatologic (13.1%), neurologic (13.1%), cardiorespiratory (12.0%), and gastrointestinal (1.7%). Predictors differed for each symptom type. Any persistent symptom was more common in older patients (adjusted odds ratio [aOR] 1.11, 95% CI 1.04 to 1.18/5 years), those diagnosed in hospital (aOR 2.03, 95% CI 1.24 to 3.33) and those with initial constitutional and rheumatologic symptoms. Patients not responding to follow-up were younger and healthier at baseline.Persistent symptoms are common and diverse 3 months post-COVID-19 but are likely over-estimated by most reports.La pandémie touche des centaines de millions de gens. Les rapports précoces laissant croire à des symptômes prolongés pourraient être assujettis à un biais de sélection.Dans un programme de soins auprès de tous les patients ambulatoires et hospitalisés ayant reçu un résultat positif au SRAS-CoV-2 entre mars et octobre 2020, assorti d’un suivi universel de 90 jours, les chercheurs ont comparé les personnes qui ont succombé avant 90 jours, n’ont pas répondu au suivi ou ont décliné ou accepté le suivi. Chez celles qui ont été vues ou ont décliné le suivi, ils ont déterminé la prévalence et les prédicteurs de symptômes persistants.Chez les 993 patients, 21 (2,1 %) sont décédés avant les 90 jours, 506 (50,9 %) n’ont pas répondu, 260 (26,1 %) ont décliné le suivi parce qu’ils se sentaient bien et 206 (20,7 %) se sont soumis à une évaluation complète. Des 466 qui ont répondu à l’offre de suivi, 133 (28,5 %) ont signalé ressentir au moins un symptôme persistant, y compris d’ordre constitutionnel (15,5 %), psychiatrique (14,2 %), rhumatologique (13,1 %), neurologique (13,1 %), cardiorespiratoire (12,0 %) et gastro-intestinal (1,7 %). Les prédicteurs différaient en fonction de chaque type de symptômes. Les symptômes persistants étaient courants chez les personnes âgées (rapport de cotes corrigé [RCc] 1,11, IC à 95 %, 1,04 à 1,18/cinq ans), les personnes diagnostiquées à l’hôpital (RCc 2,03, IC à 95 %, 1,24 à 3,33) et celles dont les manifestations initiales comportaient des symptômes constitutionnels et rhumatologiques. Les patients qui ne répondaient pas au suivi étaient plus jeunes et en meilleure santé au départ.Les symptômes persistants sont courants et diversifiés trois mois après la COVID-19, mais sont probablement surestimés dans la plupart des rapports.

There is growing evidence of the potential for cardiac involvement in patients who have been infected with COVID-19. In this case study, we present a patient with no history of cardiovascular disease, who was hospitalized for COVID-19 pneumonia and subsequently recovered. Despite normal serum troponin levels and left ventricular structure and function, multi-parametric cardiac magnetic resonance imaging revealed a classic myocarditis-like pattern of injury approximately 6 months after his convalescence. Physicians should be aware of the possibility of late myocardial injury/inflammation in patients with recovered COVID-19, even in the absence of elevated troponin levels and/or left ventricular dysfunction.

In a multi-facility prospective cohort study, we identified 116 acute care, 26 long-term care, and 67 rehabilitation patients who received direct care from a universally masked healthcare worker while communicable with COVID-19. Among 133(64%) patients with at least 14-day follow-up, three (2.3%, 95% CI, 0.77-6.4) became positive for SARS-CoV-2. Universal masking, embedded with other infection control practices, is associated with low risk of transmission of SARS-CoV-2 from healthcare workers to patients and residents.

BackgroundPost-exposure prophylaxis (PEP) is a well-established strategy for the prevention of infectious diseases, in which recently exposed people take a short course of medication to prevent infection. The primary objective of the COVID-19 Ring-based Prevention Trial with lopinavir/ritonavir (CORIPREV-LR) is to evaluate the efficacy of a 14-day course of oral lopinavir/ritonavir as PEP against COVID-19 among individuals with a high-risk exposure to a confirmed case.MethodsThis is an open-label, multicenter, 1:1 cluster-randomized trial of LPV/r 800/200 mg twice daily for 14 days (intervention arm) versus no intervention (control arm), using an adaptive approach to sample size calculation. Participants will be individuals aged > 6 months with a high-risk exposure to a confirmed COVID-19 case within the past 7 days. A combination of remote and in-person study visits at days 1, 7, 14, 35, and 90 includes comprehensive epidemiological, clinical, microbiologic, and serologic sampling. The primary outcome is microbiologically confirmed COVID-19 infection within 14 days after exposure, defined as a positive respiratory tract specimen for SARS-CoV-2 by polymerase chain reaction. Secondary outcomes include safety, symptomatic COVID-19, seropositivity, hospitalization, respiratory failure requiring ventilator support, mortality, psychological impact, and health-related quality of life. Additional analyses will examine the impact of LPV/r on these outcomes in the subset of participants who test positive for SARS-CoV-2 at baseline. To detect a relative risk reduction of 40% with 80% power atα = 0.05, assuming the secondary attack rate in ring members (p0) = 15%, 5 contacts per case and intra-class correlation coefficient (ICC) = 0.05, we require 110 clusters per arm, or 220 clusters overall and approximately 1220 enrollees after accounting for 10% loss-to-follow-up. We will modify the sample size target after 60 clusters, based on preliminary estimates ofp0, ICC, and cluster size and consider switching to an alternative drug after interim analyses and as new data emerges. The primary analysis will be a generalized linear mixed model with logit link to estimate the effect of LPV/r on the probability of infection. Participants who test positive at baseline will be excluded from the primary analysis but will be maintained for additional analyses to examine the impact of LPV/r on early treatment.DiscussionHarnessing safe, existing drugs such as LPV/r as PEP could provide an important tool for control of the COVID-19 pandemic. Novel aspects of our design include the ring-based prevention approach, and the incorporation of remote strategies for conducting study visits and biospecimen collection.Trial registrationThis trial was registered atwww.ClinicalTrials.gov(NCT04321174) on March 25, 2020.

Contexte: Optimiser la reponse de la sante publique pour diminuer le fardeau de la COVID-19 necessite la caracterisation de l’heterogeneite du risque pose par la maladie a l’echelle de la population. Cependant, l’heterogeneite du depistage du SRAS-CoV-2 peut fausser les estimations selon le modele d’etude analytique utilise. Notre objectif etait d’explorer les biais collisionneurs dans le cadre d’une vaste etude portant sur les determinants de la maladie et d’evaluer les determinants individuels, environnementaux et sociaux du depistage et du diagnostic du SRAS-CoV-2 parmi les residents de l’Ontario, au Canada. Methodes: Nous avons explore la presence potentielle de biais collisionneurs et caracterise les determinants individuels, environnementaux et sociaux de l’obtention d’un test de depistage et d’un resultat positif a la presence de l’infection au SRAS-CoV-2 a l’aide d’analyses transversales parmi les 14,7 millions de personnes vivant dans la collectivite en Ontario, au Canada. Parmi les personnes ayant obtenu un diagnostic, nous avons utilise des etudes analytiques distinctes afin de comparer les predicteurs pour les personnes d’obtenir un resultat de test de depistage positif plutot que negatif, pour les personnes symptomatiques d’obtenir un resultat de test de depistage positif plutot que negatif et pour les personnes d’obtenir un resultat de test de depistage positif plutot que de ne pas obtenir un resultat positif (c.-a-d., obtenir un resultat de test de depistage negatif ou ne pas obtenir de test de depistage). Nos analyses comprennent des tests de depistage realises entre le 1er mars et le 20 juin 2020. Resultats: Sur 14 695 579 personnes, nous avons constate que 758 691 d’entre elles ont passe un test de depistage du SRAS-CoV-2, parmi lesquelles 25 030 (3,3 %) ont obtenu un resultat positif. Plus la probabilite d’obtenir un test de depistage s’eloignait de zero, plus la variabilite generalement observee dans la probabilite d’un diagnostic etait grande parmi les modeles d’etudes analytiques, particulierement en ce qui a trait aux facteurs individuels. Nous avons constate que la variabilite dans l’obtention d’un test de depistage etait moins importante en fonction des determinants sociaux dans l’ensemble des etudes analytiques. Les facteurs tels que le fait d’habiter dans une region ayant une plus haute densite des menages (rapport de cotes corrige 1,86; intervalle de confiance [IC] a 95 % 1,75–1,98), une plus grande proportion de travailleurs essentiels (rapport de cotes corrige 1,58; IC a 95 % 1,48–1,69), une population atteignant un plus faible niveau de scolarite (rapport de cotes corrige 1,33; IC a 95 % 1,26–1,41) et une plus grande proportion d’immigrants recents (rapport de cotes corrige 1,10; IC a 95 % 1,05–1,15), etaient systematiquement correles a une probabilite plus importante d’obtenir un diagnostic de SRAS-CoV-2, peu importe le modele d’etude analytique employe. Interpretation: Lorsque la capacite de depister est limitee, nos resultats suggerent que les facteurs de risque peuvent etre estimes plus adequatement en utilisant des comparateurs populationnels plutot que des comparateurs de resultat negatif au test de depistage. Optimiser la lutte contre la COVID-19 necessite des investissements dans des interventions structurelles deployees de facon suffisante et adaptees a l’heterogeneite des determinants sociaux du risque, dont le surpeuplement des menages, l’occupation professionnelle et le racisme structurel.

BACKGROUND: In pandemics, local hospitals need to anticipate a surge in health care needs. We examined the modelled surge because of the coronavirus disease 2019 (COVID-19) pandemic that was used to inform the early hospital-level response against cases as they transpired. METHODS: To estimate hospital-level surge in March and April 2020, we simulated a range of scenarios of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spread in the Greater Toronto Area (GTA), Canada, using the best available data at the time. We applied outputs to hospital-specific data to estimate surge over 6 weeks at 2 hospitals (St. Michael’s Hospital and St. Joseph’s Health Centre). We examined multiple scenarios, wherein the default (R(0) = 2.4) resembled the early trajectory (to Mar. 25, 2020), and compared the default model projections with observed COVID-19 admissions in each hospital from Mar. 25 to May 6, 2020. RESULTS: For the hospitals to remain below non-ICU bed capacity, the default pessimistic scenario required a reduction in non-COVID-19 inpatient care by 38% and 28%, respectively, with St. Michael’s Hospital requiring 40 new ICU beds and St. Joseph’s Health Centre reducing its ICU beds for non-COVID-19 care by 6%. The absolute difference between default-projected and observed census of inpatients with COVID-19 at each hospital was less than 20 from Mar. 25 to Apr. 11; projected and observed cases diverged widely thereafter. Uncertainty in local epidemiological features was more influential than uncertainty in clinical severity. INTERPRETATION: Scenario-based analyses were reliable in estimating short-term cases, but would require frequent re-analyses. Distribution of the city’s surge was expected to vary across hospitals, and community-level strategies were key to mitigating each hospital’s surge.

Outpatient parenteral antimicrobial therapy (OPAT) is a safe and effective alternative to hospitalization for many patients with infectious disease. The objective of this study was to describe the experience with a newly established formal OPAT program at a Canadian academic centre.We conducted a retrospective cohort study including all patients referred to the OPAT clinic between July 2016 and June 2017 and a contemporary cohort of patients who received home parenteral therapy without clinic referral. A quasi-experimental design was used to assess the impact of the clinic on patient outcomes compared with a pre-intervention cohort of patients from 2012 to 2013.Between July 2016 and June 2017, 334 patients were referred to the OPAT clinic; 33% of the patients visited the emergency department (ED), and 21% required readmission within 60 days. Compared with the clinic patients, urinary tract infection diagnoses were more common among the 39 contemporary patients who were treated with home parenteral antibiotics without OPAT clinic referral (51% versus 4%, respectively;The OPAT clinic served a high volume of patients in its first year of operation and may be helpful in reducing unfavourable patient outcomes.L’antibiothérapie parentérale ambulatoire (APA) remplace l’hospitalisation de manière sécuritaire et efficace pour bien des patients atteints d’une maladie infectieuse. La présente étude visait à décrire l’expérience d’un nouveau programme officiel d’APA dans un centre universitaire canadien.Les auteurs ont procédé à une étude de cohorte rétrospective incluant tous les patients orientés vers une clinique d’APA entre juillet 2016 et juin 2017 et une cohorte de patients qui, pendant la même période, ont reçu un traitement parentéral à domicile sans être orientés en clinique. Ils ont utilisé une méthodologie quasi-expérimentale pour évaluer les répercussions du suivi en clinique sur les patients par rapport à une cohorte de patients avant l’intervention, entre 2012 et 2013.Entre juillet 2016 et juin 2017, 334 patients ont été orientés vers la clinique d’APA; 33 % ont consulté à l’urgence et 21 % ont dû être réhospitalisés dans les 60 jours. Les diagnostics d’infection urinaire étaient plus courants chez les 39 patients recevant une antibiothérapie parentérale à domicile sans être dirigés vers une clinique d’APA que dans la cohorte suivie en clinique (51 % par rapport à 4 %, respectivement;La clinique d’APA a accueilli un fort volume de patients pendant sa première année de fonctionnement et peut contribuer à réduire les résultats cliniques défavorables chez les patients.

Social determinants of health (SDOH) have been associated with COVID-19 outcomes. We examined differential patterns in COVID-19-related mortality by SDOH accounting for confounders and compared these patterns to those for non-COVID-19 mortality.Residents of Ontario, Canada aged ≥20 years were followed from March-01-2020 to March-02-2021. COVID-19-related death was defined as death within [-7,30] days of a positive COVID-19 test. Area-level SDOH from 2016 Census included: median household income; proportion with diploma or higher educational-attainment; proportion essential workers, racially-minoritised groups, recent immigrants, apartment buildings, and high-density housing; and average household size. We examined associations between SDOH and COVID-19-related mortality using cause-specific hazard models, treating non-COVID-19 mortality as competing risks, and vice-versa.Of 11,810,255 individuals, we observed 3,880(0.03%) COVID-19-related deaths and 88,107(0.75%) non-COVID-19 deaths. After accounting for individual-level demographics, baseline health, and other area-level SDOH, the following area-level SDOH were associated with increased hazards of COVID-19-related death (hazard ratios[95% confidence intervals]: lower income (1.30[1.04-1.62]), lower educational-attainment (1.27[1.07-1.52]), higher proportions essential workers (1.28[1.05-1.57]), racially-minoritised groups (1.42[1.08-1.87]), apartment buildings (1.25[1.07-1.46]), and large vs. medium household size (1.30[1.12-1.50]). In comparison, areas with higher proportion racially-minoritised groups were associated with a lower hazard of non-COVID-19 mortality (0.88[0.84-0.92]).Area-level SDOH are associated with COVID-19-related mortality after accounting for demographic and clinical factors. COVID-19 has reversed patterns of lower non-COVID-19 mortality among racially-minoritised groups vs. their counterparts. Pandemic responses should include strategies (e.g., 'hotspot' and risk-group tailored vaccination) to address disproportionate risks and inequitable reach of, and access to, preventive interventions associated with SDOH.

ImportanceSocial determinants of health (SDOH) play an important role in COVID-19 outcomes. More research is needed to quantify this relationship and understand the underlying mechanisms.ObjectivesTo examine differential patterns in COVID-19-related mortality by area-level SDOH accounting for confounders; and to compare these patterns to those for non-COVID-19 mortality, and COVID-19 case fatality (COVID-19-related death among those diagnosed).Design, setting, and participantsPopulation-based retrospective cohort study including all community living individuals aged 20 years or older residing in Ontario, Canada, as of March 1, 2020 who were followed through to March 2, 2021.ExposureSDOH variables derived from the 2016 Canada Census at the dissemination area-level including: median household income; educational attainment; proportion of essential workers, racialized groups, recent immigrants, apartment buildings, and high-density housing; and average household size.Main outcomes and measuresCOVID-19-related death was defined as death within 30 days following, or 7 days prior to a positive SARS-CoV-2 test. Cause-specific hazard models were employed to examine the associations between SDOH and COVID-19-related mortality, treating non-COVID-19 mortality as a competing risk.ResultsOf 11,810,255 individuals included, 3,880 (0.03%) died related to COVID-19 and 88,107 (0.75%) died without a positive test. After accounting for demographics, baseline health, and other SDOH, the following SDOH were associated with increased hazard of COVID-19-related death (hazard ratios [95% confidence intervals]) comparing the most to least vulnerable group): lower income (1.30[1.09-1.54]), lower educational attainment (1.27[1.10-1.47]), higher proportion essential workers (1.28[1.10-1.50]), higher proportion racialized groups (1.42[1.16-1.73]), higher proportion apartment buildings (1.25[1.11-1.41]), and larger vs. medium household size (1.30[1.13-1.48]). In comparison, areas with higher proportion racialized groups were associated with a lower hazard of non-COVID-19 mortality (0.88[0.85-0.92]). With the exception of income, SDOH were not independently associated with COVID-19 case fatality.Conclusions and relevanceArea-level social and structural inequalities determine COVID-19-related mortality after accounting for individual demographic and clinical factors. COVID-19 has reversed the pattern of lower non-COVID-19 mortality by racialized groups. Pandemic responses should include prioritized and community-tailored intervention strategies to address SDOH that mechanistically underpin disproportionate acquisition and transmission risks and shape barriers to the reach of, and access to prevention interventions.Key pointsQuestionAre area-level social determinants of health factors independently associated with coronavirus disease 2019 (COVID-19)-related mortality after accounting for demographics and clinical factors?FindingsIn this population-based cohort study including 11.8 million adults residing in Ontario, Canada and 3,880 COVID-19-related death occurred between Mar 1, 2020 and Mar 2, 2021, we found that areas characterized by lower SES (including lower income, lower educational attainment, and higher proportion essential workers), greater ethnic diversity, more apartment buildings, and larger vs. medium household size were associated with increased hazard of COVID-19-related mortality compared to their counterparts, even after accounting for individual-level demographics, baseline health, and other area-level SDOH.MeaningPandemic responses should include prioritized and community-tailored intervention strategies to address SDOH that mechanistically underpin inequalities in acquisition and transmission risks, and in the reach of, and access to prevention interventions.

Most individuals with coronavirus disease 2019 (COVID-19) experience mild symptoms and are managed in the outpatient setting. The aim of this study was to determine whether self-reported symptoms at the time of diagnosis can identify patients at risk of clinical deterioration.This was a retrospective cohort study of 671 outpatients with laboratory-confirmed COVID-19 diagnosed in Toronto between March 1 and October 16, 2020. We examined the association between patients' baseline characteristics and self-reported symptoms at the time of diagnosis and the risk of subsequent hospitalization.Of 671 participants, 26 (3.9%) required hospitalization. Individuals aged 65 years or older were more likely to require hospitalization (odds ratio [OR] 5.29, 95% CI 2.19 to 12.77), whereas those without medical comorbidities were unlikely to be hospitalized (OR 0.02, 95% CI 0.00 to 0.17). After adjusting for age and presence of comorbidities, sputum production (adjusted OR [aOR] 5.01, 95% CI 1.97 to 12.75), arthralgias (aOR 4.82, 95% CI 1.85 to 12.53), diarrhea (aOR 4.56, 95% CI 1.82 to 11.42), fever (aOR 3.64, 95% CI 1.50 to 8.82), chills (aOR 3.62, 95% CI 1.54 to 8.50), and fatigue (aOR 2.59, 95% CI 1.04 to 6.47) were associated with subsequent hospitalization.Early assessment of symptoms among outpatients with COVID-19 can help identify individuals at risk of clinical deterioration. Additional studies are needed to determine whether more intense follow-up and early intervention among high-risk individuals can alter the clinical trajectory of and outcomes among outpatients with COVID-19.La plupart des personnes atteintes de la maladie à coronavirus 2019 (COVID-19) éprouvent des symptômes légers et sont prises en charge en milieu ambulatoire. La présente étude visait à déterminer si les symptômes autodéclarés au moment du diagnostic permettent de dépister les patients à risque de détérioration clinique.Les chercheurs ont réalisé la présente étude de cohorte rétrospective auprès de 671 patients ambulatoires atteints d’une COVID-19 diagnostiquée à Toronto et confirmée en laboratoire entre le 1er mars et le 16 octobre 2020. Ils ont examiné l’association entre les caractéristiques de référence et les symptômes autodéclarés des patients au moment du diagnostic, d’une part, et le risque d’hospitalisation, d’admission en soins intensifs ou de décès par la suite, d’autre part.Des 671 participants, 26 (3,9 %) ont dû être hospitalisés, sept (1,0 %) ont été admis en soins intensifs et trois (0,4 %) sont décédés dans les 30 jours suivant le diagnostic. Les personnes de 65 ans ou plus étaient plus susceptibles de devoir être hospitalisées (RC 5,29, IC à 95 % 2,19 à 12,77) et celles qui n’avaient pas d’autres problèmes de santé l’étaient moins (RC 0,02, IC à 95 % 0,00 à 0,17). Après redressement pour tenir compte de l’âge et de la présence d’autres problèmes de santé, la production de mucus (RC ajusté [RCa] 5,01, IC à 95 % 2,11 à 13,66), les arthralgies (RCa 4,82, IC à 95 % 1,85 à 12,53), la diarrhée (RCa 4,56, IC à 95 % 1,82 à 11,42), la fièvre (RCa 3,64, IC à 95 % 1,50 à 8,82), les frissons (RCa 3,62, IC à 95 % 1,54 à 8,50) et la fatigue (RCa 2,59, IC à 95 % 1,04 à 6,47) étaient associés à des hospitalisations.L’évaluation précoce des symptômes des patients ambulatoires atteints de la COVID-19 peut contribuer à dépister les personnes vulnérables à une détérioration clinique. Lorsque ce facteur s’ajoute à l’âge et à l’histoire de problèmes de santé, la symptomatologie fournit plus d’information pronostique aux cliniciens qui prennent en charge les patients atteints de COVID-19 en milieu ambulatoire. D’autres études s’imposent pour déterminer si un suivi plus intense et une intervention précoce auprès des personnes très vulnérables peuvent modifier la trajectoire clinique et le pronostic des patients ambulatoires atteints de la COVID-19.

BACKGROUND Disproportionate risks of COVID-19 in congregate settings including long-term care homes, retirement homes, and shelters both affect and are affected by SARS-CoV-2 infections among facility-staff. In cities across Canada, there has been a consistent trend of geographic clustering of COVID-19 cases. However, there remain limited data on how COVID-19 among facility-staff reflect urban neighbourhood disparities, particularly stratified by the social and structural determinants of community-level transmission. OBJECTIVE To compare the concentration of cumulative cases by geography and social/structural determinants across three mutually exclusive subgroups in the Greater Toronto Area (population 7.1 million): community, facility-staff, and healthcare workers (HCW) in other settings. METHODS We conducted a retrospective, observational study using surveillance data on laboratory-confirmed COVID-19 cases (January 23 to December 13, 2020; prior to vaccination roll-out). We derived neighbourhood-level social/structural determinants from census data, and generated Lorenz curves and Gini coefficients to visualize and quantify inequalities in cases. RESULTS The hardest-hit neighbourhoods (comprising 20% of the population) accounted for 53.4% of community cases, 48.6% of facility-staff cases, and 42.3% of other HCW cases. Compared with other HCW, cases in facility-staff more closely reflected the distribution of community cases. Cases in facility-staff reflected greater social and structural inequalities (larger Gini coefficients) than other HCW across all determinants. Facility-staff cases were also more likely than community cases to be concentrated in lower income neighbourhoods (Gini 0.24[0.15-0.38] vs 0.14[0.08-0.21] with lower household density (Gini 0.23[0.17-0.29] vs 0.17[0.12-0.22]) and with a greater proportion working in other essential services (Gini 0.29 [0.21-0.40], 0.22[0.17-0.28]). CONCLUSIONS COVID-19 cases among facility-staff largely reflects neighbourhood-level heterogeneity and disparities; even more so than cases in other HCW. Findings signal the importance of interventions prioritized and tailored to home geographies of facility-staff in addition to workplace measures, including prioritization and reach of vaccination at home (neighbourhood-level) and at work.

Background An increasing proportion of patients with HIV-associated cryptococcal meningitis have received antiretroviral therapy (ART) before presentation. There is some evidence suggesting an increased 2-week mortality in those receiving ART for 14 days. However, presentation and outcomes for cryptococcal meningitis patients who have recently initiated ART, and those with virologic failure and/or nonadherence, are not well described. Methods Six hundred seventy-eight adults with a first episode of cryptococcal meningitis recruited into a randomized, noninferiority, multicenter phase 3 trial in 4 Sub-Saharan countries were analyzed to compare clinical presentation and 2- and 10-week mortality outcomes between ART-naïve and -experienced patients and between patients receiving ART for varying durations before presentation. Results Over half (56%; 381/678) the study participants diagnosed with a first episode of cryptococcal meningitis were ART-experienced. All-cause mortality was similar at 2 weeks (17% vs 20%; hazard ratio [HR], 0.85; 95% CI, 0.6–1.2; P = .35) and 10 weeks (38% vs 36%; HR, 1.03; 95% CI, 0.8–1.32; P = .82) for ART-experienced and ART-naïve patients. Among ART-experienced patients, using different cutoff points for ART duration, there were no significant differences in 2- and 10-week mortality based on duration of ART. Conclusions In this study, there were no significant differences in mortality at 2 and 10 weeks between ART-naïve and -experienced patients and between ART-experienced patients according to duration on ART.

POINTS CLES La reponse initiale du Canada a la maladie a coronavirus 2019 (COVID-19) a principalement repose sur des strategies universelles telles que le confinement et l’isolement des personnes infectees par le coronavirus du syndrome respiratoire aigu severe 2 (SRAS-CoV-2) ou y ayant

Despite being highly vulnerable to acquiring HIV, no effective evidence-based interventions (EBI) exist for street-connected young people (SCY) in low- and middle-income countries (LMICs). Therefore, this paper describes the research process of adapting an existing EBI in Eldoret, Kenya using a modified ADAPT-ITT model with a young key population. From May to August 2018 we adapted the combined Stepping Stones and Creating Futures interventions. We used community-based participatory methods, focus group discussions, and working groups with four Peer Facilitators and 24 SCY aged 16-24 years. At the inception of this project, a matched-savings programme was integrated into the intervention to further address structural drivers of HIV. Numerous adaptations came forth through the participatory process. Engaging SCY in the adaptation process ensured the programme was responsive to their needs, relevant to the street context, and respected their right to participate in the research process.

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.

BackgroundInequities in the burden of COVID-19 observed across Canada suggest heterogeneity within community transmission.ObjectivesTo quantify the magnitude of heterogeneity in the wider community (outside of long-term care homes) in Toronto, Canada and assess how the magnitude in concentration evolved over time (January 21 to November 21, 2020).DesignRetrospective, population-based observational study using surveillance data from Ontario’s Case and Contact Management system.SettingToronto, Canada.ParticipantsLaboratory-confirmed cases of COVID-19 (N=33,992).MeasurementsWe generated epidemic curves by SDOH and crude Lorenz curves by neighbourhoods to visualize inequities in the distribution of COVID-19 cases by social determinants of health (SDOH) and estimated the crude Gini coefficient. We examined the correlation between SDOH using Pearson correlation coefficients.ResultsThe Gini coefficient of cumulative cases by population size was 0.41 (95% CI: 0.36-0.47) and were estimated for: household income (0.20, 95%CI: 0.14-0.28); visible minority (0.21, 95%CI: 0.16-0.28); recent immigration (0.12, 95%CI: 0.09-0.16); suitable housing (0.21, 95%CI: 0.14-0.30); multi-generational households (0.19, 95%CI: 0.15-0.23); and essential workers (0.28, 95% CI: 0.23-0.34). Most SDOH were highly correlated.Locally acquired cases were concentrated in higher income neighbourhoods in the early phase of the epidemic, and then concentrated in lower income neighbourhoods. Mirroring the trajectory of epidemic curves by income, the Lorenz curve shifted over time from below to above the line of equality with a similar pattern across SDOH.LimitationsStudy relied on area-based measures of the SDOH and individual case counts of COVID-19. We cannot infer concentration of cases by specific occupational exposures given limitation to broad occupational categories.ConclusionCOVID-19 is increasingly concentrated by SDOH given socioeconomic inequities and structural racism.Primary Funding SourceCanadian Institutes of Health Research.

Among 472 patients with human immunodeficiency virus-associated cryptococcal meningitis, 16% had severe visual loss at presentation, and 46% of these were 4-week survivors and remained severely impaired. Baseline cerebrospinal fluid opening pressure ≥40 cmH2O (adjusted odds ratio [aOR], 2.56; 95% confidence interval [CI], 1.36–4.83; P = .02) and fungal burden >6.0 log10 colonies/mL (aOR, 3.01; 95% CI, 1.58–5.7; P = .003) were independently associated with severe visual loss.

ImportanceNursing home residents have been disproportionately impacted by the COVID-19 epidemic. Prevention recommendations have emphasized frequent testing of healthcare personnel and residents, but additional strategies are needed to protect nursing home residents.ObjectiveWe developed a reproducible index of nursing home crowding and determined whether crowding was associated with incidence of COVID-19 in the first months of the COVID-19 epidemic.Design, Setting, and ParticipantsPopulation-based retrospective cohort study of over 78,000 residents of 618 distinct nursing homes in Ontario, Canada from March 29 to May 20, 2020.ExposureThe nursing home crowding index equalled the average number of residents per bedroom and bathroom.OutcomesPrimary outcomes included the cumulative incidence of COVID-19 infection and mortality, per 100 residents; introduction of COVID-19 into a home (≥1 resident case) was a negative tracer.ResultsOf 623 homes in Ontario, we obtained complete information on 618 homes (99%) housing 78,607 residents. A total of 5,218 residents (6.6%) developed COVID-19 infection, and 1,452 (1.8%) died with COVID-19 infection as of May 20, 2020. COVID-19 infection was distributed unevenly across nursing homes: 4,496 (86%) of infections occurred in just 63 (10%) of homes. The crowding index ranged across homes from 1.3 (mainly single-occupancy rooms) to 4.0 (exclusively quadruple occupancy rooms); 308 (50%) homes had high crowding index (≥2). Incidence in high crowding index homes was 9.7%, versus 4.5% in low crowding index homes (pConclusions and RelevanceCrowding was associated with higher incidence of COVID-19 infection and mortality. Reducing crowding in nursing homes could prevent future COVID-19 mortality.

Background With the global shortage of skilled health workers estimated at 7.2 million, outpatient tuberculosis (TB) care is commonly task-shifted to lay health workers (LHWs) in many low- and middle-income countries where the shortages are greatest. While shown to improve access to care and some health outcomes including TB treatment outcomes, lack of training and supervision limit the effectiveness of LHW programs. Our objective was to refine and evaluate an intervention designed to address common causes of non-adherence to TB treatment and LHW knowledge and skills training needs. Methods We employed a pragmatic cluster randomized controlled trial. Participants included 103 health centres (HCs) providing TB care in four districts in Malawi, randomized 1:1 stratified by district and HC funding (Ministry of Health, non-Ministry funded). At intervention HCs, a TB treatment adherence intervention was implemented using educational outreach, a point-of-care reminder tool, and a peer support network. Clusters in the control arm provided usual care. The primary outcome was the proportion of patients with successful TB treatment (i.e., cure or treatment completion). We used a generalized linear mixed model, with district as a fixed effect and HC as a random effect, to compare proportions of patients with treatment success, among the trial arms, with adjustment for baseline differences. Results We randomized 51 HCs to the intervention group and 52 HCs to the control group. Four intervention and six control HCs accrued no eligible patients, and 371 of 1169 patients had missing outcome, HC, or demographic data, which left 74 HCs and 798 patients for analysis. Randomization group was not related to missing outcome, however, district, age, and TB type were significantly related and included in the primary analysis model. Among the 1153 patients with HC and demographic data, 297/605 (49%) and 348/548 (64%) in the intervention and control arms, respectively, had treatment success. The intervention had no significant effect on treatment success (adjusted odds ratio 1.35 [95% confidence interval 0.93–1.98]). Conclusion We found no significant effect of the intervention on TB treatment outcomes with high variability in implementation quality, highlighting important challenges to both scale-up and sustainability. Trial registration ClinicalTrials.gov NCT02533089. Registered August 20, 2015.

There is a pressing need for an in-depth understanding of immunity to SARS-CoV-2. In this study, we investigated human T cell recall responses to fully glycosylated spike trimer, recombinant N protein, as well as to S, N, M, and E peptide pools in the early convalescent phase and compared them with influenza-specific memory responses from the same donors. All subjects showed SARS-CoV-2–specific T cell responses to at least one Ag. Both SARS-CoV-2–specific and influenza-specific CD4+ T cell responses were predominantly of the central memory phenotype; however SARS-CoV-2–specific CD4+ T cells exhibited a lower IFN-γ to TNF ratio compared with influenza-specific memory responses from the same donors, independent of disease severity. SARS-CoV-2–specific T cells were less multifunctional than influenza-specific T cells, particularly in severe cases, potentially suggesting exhaustion. Most SARS-CoV-2–convalescent subjects also produced IFN-γ in response to seasonal OC43 S protein. We observed granzyme B+/IFN-γ+, CD4+, and CD8+ proliferative responses to peptide pools in most individuals, with CD4+ T cell responses predominating over CD8+ T cell responses. Peripheral T follicular helper (pTfh) responses to S or N strongly correlated with serum neutralization assays as well as receptor binding domain–specific IgA; however, the frequency of pTfh responses to SARS-CoV-2 was lower than the frequency of pTfh responses to influenza virus. Overall, T cell responses to SARS-CoV-2 are robust; however, CD4+ Th1 responses predominate over CD8+ T cell responses, have a more inflammatory profile, and have a weaker pTfh response than the response to influenza virus within the same donors, potentially contributing to COVID-19 disease.

Importance Optimizing the public health response to reduce coronavirus disease 2019 (COVID-19) burden necessitates characterizing population-level heterogeneity of COVID-19 risks. However, heterogeneity in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) testing may introduce biased estimates depending on analytic design. Objective Characterizing individual, environmental, and social determinants of SARS-CoV-2 testing and COVID-19 diagnosis. Design We conducted cross-sectional analyses among 14.7 million people comparing individual, environmental, and social determinants among individuals who were tested versus not yet tested. Among those diagnosed, we used three analytic designs to compare predictors of: 1) individuals testing positive versus negative; 2) symptomatic individuals testing positive versus negative; and 3) individuals testing positive versus individuals not testing positive (i.e. testing negative or not being tested). Analyses included tests conducted between March 1 and June 20, 2020. Setting Ontario, Canada. Participants All individuals with ≥1 healthcare system contact since March 2012, excluding individuals deceased before, or born after, March 1, 2020, or residing in a long-term care facility. Exposures Individual-level characteristics (age, sex, underlying health conditions, prior healthcare use), area-based environmental (air pollution) exposures, and area-based social determinants of health (income, education, housing, marital status, race/ethnicity, and recent immigration). Main Outcomes and Measures Odds of SARS-CoV-2 test, and of COVID-19 diagnosis. Results Of a total of 14,695,579 individuals, 758,691 had been tested, of whom 25,030 (3.3%) tested positive. The further the odds of testing from the null, the more variability observed in the odds of diagnosis across analytic design, particularly among individual factors. There was less variability in testing by social determinants across analytic design. Residing in areas with highest household density (adjusted odds ratio: 2.08; 95%CI: 1.95-1.21), lowest educational attainment (adjusted odds ratio: 1.52; 95%CI: 1.44-1.60), and highest proportion of recent immigrants (adjusted odds ratio: 1.12; 95%CI: 1.07-1.16) were consistently related to increased odds of COVID-19 across analytic designs. Conclusions and Relevance Where testing is limited, risk factors may be better estimated using population comparators rather than test-negative comparators. Optimizing COVID-19 responses necessitates investment and sufficient coverage of structural interventions tailored to heterogeneity in social determinants of risk, including household crowding and systemic racism. Key Points Question What are the social determinants of health that contextualize individual-level risks for coronavirus disease 2019 (COVID-19), and how do selection biases affect our understanding of these risks? Findings In this province-wide observational study of 14.7 million Canadians, social determinants related to housing, education, and recent immigration were associated with increased COVID-19 risks, with little evidence of selection bias. Individual factors, such as underlying health conditions, were more prone to selection bias using certain analytic approaches. Meaning Social determinants of health appear to drive COVID-19 incidence in Ontario, Canada. Interventions aiming to prevent COVID-19 transmission should address these empiric structural risks.