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Xia Y, Flores Anato JL, Colijn C, Janjua N, Irvine M, Williamson T, Varughese MB, Li M, Osgood N, Earn DJD, Sander B, Cipriano LE, Murty K, Xiu F, Godin A, Buckeridge D, Hurford A, Mishra S, Maheu-Giroux M. Canada's provincial COVID-19 pandemic modelling efforts: A review of mathematical models and their impacts on the responses. CANADIAN JOURNAL OF PUBLIC HEALTH = REVUE CANADIENNE DE SANTE PUBLIQUE 2024; 115:541-557. [PMID: 39060710 DOI: 10.17269/s41997-024-00910-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/01/2023] [Accepted: 05/31/2024] [Indexed: 07/28/2024]
Abstract
SETTING Mathematical modelling played an important role in the public health response to COVID-19 in Canada. Variability in epidemic trajectories, modelling approaches, and data infrastructure across provinces provides a unique opportunity to understand the factors that shaped modelling strategies. INTERVENTION Provinces implemented stringent pandemic interventions to mitigate SARS-CoV-2 transmission, considering evidence from epidemic models. This study aimed to summarize provincial COVID-19 modelling efforts. We identified modelling teams working with provincial decision-makers, through referrals and membership in Canadian modelling networks. Information on models, data sources, and knowledge translation were abstracted using standardized instruments. OUTCOMES We obtained information from six provinces. For provinces with sustained community transmission, initial modelling efforts focused on projecting epidemic trajectories and healthcare demands, and evaluating impacts of proposed interventions. In provinces with low community transmission, models emphasized quantifying importation risks. Most of the models were compartmental and deterministic, with projection horizons of a few weeks. Models were updated regularly or replaced by new ones, adapting to changing local epidemic dynamics, pathogen characteristics, vaccines, and requests from public health. Surveillance datasets for cases, hospitalizations and deaths, and serological studies were the main data sources for model calibration. Access to data for modelling and the structure for knowledge translation differed markedly between provinces. IMPLICATION Provincial modelling efforts during the COVID-19 pandemic were tailored to local contexts and modulated by available resources. Strengthening Canadian modelling capacity, developing and sustaining collaborations between modellers and governments, and ensuring earlier access to linked and timely surveillance data could help improve pandemic preparedness.
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Affiliation(s)
- Yiqing Xia
- Department of Epidemiology and Biostatistics, School of Population and Global Health, McGill University, Montréal, QC, Canada
| | - Jorge Luis Flores Anato
- Department of Epidemiology and Biostatistics, School of Population and Global Health, McGill University, Montréal, QC, Canada
| | - Caroline Colijn
- Department of Mathematics, Faculty of Science, Simon Fraser University, Burnaby, BC, Canada
| | - Naveed Janjua
- School of Population and Public Health, University of British Columbia, Vancouver, BC, Canada
- British Columbia Centre for Disease Control (BCCDC), Vancouver, BC, Canada
| | - Mike Irvine
- British Columbia Centre for Disease Control (BCCDC), Vancouver, BC, Canada
| | - Tyler Williamson
- Department of Community Health Sciences, University of Calgary, Calgary, AB, Canada
- Centre for Health Informatics, University of Calgary, Calgary, AB, Canada
| | - Marie B Varughese
- Analytics and Performance Reporting Branch, Alberta Health, Edmonton, AB, Canada
- Department of Mathematical and Statistical Sciences, University of Alberta, Edmonton, AB, Canada
| | - Michael Li
- Department of Mathematical and Statistical Sciences, University of Alberta, Edmonton, AB, Canada
| | - Nathaniel Osgood
- Department of Computer Science, University of Saskatchewan, Saskatoon, SK, Canada
| | - David J D Earn
- Department of Mathematics & Statistics, McMaster University, Hamilton, ON, Canada
- M. G. DeGroote Institute for Infectious Disease Research, McMaster University, Hamilton, ON, Canada
| | - Beate Sander
- Institute of Health Policy, Management and Evaluation (IHPME), Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada
- Toronto General Hospital Research Institute, University Health Network, Toronto, ON, Canada
- Public Health Ontario, Toronto, ON, Canada
- ICES, Toronto, ON, Canada
| | - Lauren E Cipriano
- Ivey Business School, University of Western Ontario, London, ON, Canada
- Departments of Epidemiology & Biostatistics and Medicine, Schulich School of Medicine & Dentistry, University of Western Ontario, London, ON, Canada
| | - Kumar Murty
- Department of Mathematics, University of Toronto, Toronto, ON, Canada
| | - Fanyu Xiu
- Department of Epidemiology and Biostatistics, School of Population and Global Health, McGill University, Montréal, QC, Canada
| | - Arnaud Godin
- Department of Medicine, Faculty of Medicine and Health Science, McGill University, Montréal, QC, Canada
| | - David Buckeridge
- Department of Epidemiology and Biostatistics, School of Population and Global Health, McGill University, Montréal, QC, Canada
| | - Amy Hurford
- Department of Biology and Department of Mathematics and Statistics, Faculty of Science, Memorial University of Newfoundland and Labrador, St. John's, NL, Canada
| | - Sharmistha Mishra
- Institute of Health Policy, Management and Evaluation (IHPME), Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada
- Division of Infectious Diseases, Department of Medicine, University of Toronto, Toronto, ON, Canada
- MAP Centre for Urban Health Solutions, St. Michael's Hospital, Unity Health Toronto, Toronto, ON, Canada
- Institute of Medical Sciences, University of Toronto, Toronto, ON, Canada
| | - Mathieu Maheu-Giroux
- Department of Epidemiology and Biostatistics, School of Population and Global Health, McGill University, Montréal, QC, Canada.
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2
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Waddell CJ, Saldana CS, Schoonveld MM, Meehan AA, Lin CK, Butler JC, Mosites E. Infectious Diseases Among People Experiencing Homelessness: A Systematic Review of the Literature in the United States and Canada, 2003-2022. Public Health Rep 2024:333549241228525. [PMID: 38379269 DOI: 10.1177/00333549241228525] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/22/2024] Open
Abstract
Homelessness increases the risk of acquiring an infectious disease. We conducted a systematic review of the literature to identify quantitative data related to infectious diseases and homelessness. We searched Google Scholar, PubMed, and SCOPUS for quantitative literature published from January 2003 through December 2022 in English from the United States and Canada. We excluded literature on vaccine-preventable diseases and HIV because these diseases were recently reviewed. Of the 250 articles that met inclusion criteria, more than half were on hepatitis C virus or Mycobacterium tuberculosis. Other articles were on COVID-19, respiratory syncytial virus, Staphylococcus aureus, group A Streptococcus, mpox (formerly monkeypox), 5 sexually transmitted infections, and gastrointestinal or vectorborne pathogens. Most studies showed higher prevalence, incidence, or measures of risk for infectious diseases among people experiencing homelessness as compared with people who are housed or the general population. Although having increased published data that quantify the infectious disease risks of homelessness is encouraging, many pathogens that are known to affect people globally who are not housed have not been evaluated in the United States or Canada. Future studies should focus on additional pathogens and factors leading to a disproportionately high incidence and prevalence of infectious diseases among people experiencing homelessness.
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Affiliation(s)
- Caroline J Waddell
- Office of Readiness and Response, Centers for Disease Control and Prevention, Atlanta, GA, USA
- Epidemic Intelligence Service, Centers for Disease Control and Prevention, Atlanta, GA, USA
| | - Carlos S Saldana
- Division of Infectious Disease, School of Medicine, Emory University, Atlanta, GA, USA
| | - Megan M Schoonveld
- Office of Readiness and Response, Centers for Disease Control and Prevention, Atlanta, GA, USA
- Oak Ridge Institute for Science and Education, US Department of Energy, Oak Ridge, TN, USA
| | - Ashley A Meehan
- Office of Readiness and Response, Centers for Disease Control and Prevention, Atlanta, GA, USA
| | - Christina K Lin
- Department of Medicine, School of Medicine, Emory University, Atlanta, GA, USA
| | - Jay C Butler
- Office of Readiness and Response, Centers for Disease Control and Prevention, Atlanta, GA, USA
- Division of Infectious Disease, School of Medicine, Emory University, Atlanta, GA, USA
| | - Emily Mosites
- Office of Readiness and Response, Centers for Disease Control and Prevention, Atlanta, GA, USA
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Shibata T, Okano S, Onozuka D, Ohta E, Kutsuna S. Analysis of Concentrated COVID-19 Outbreaks in Elderly Facilities in Suita City, Osaka Prefecture, Japan. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2023; 20:6926. [PMID: 37887664 PMCID: PMC10606492 DOI: 10.3390/ijerph20206926] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/16/2023] [Revised: 09/28/2023] [Accepted: 10/13/2023] [Indexed: 10/28/2023]
Abstract
There are several types of facilities for elderly individuals in Japan. Infection control efforts, such as care provision and medical care access, differ according to the type of facility. Elderly individuals at these facilities who were infected with coronavirus disease 2019 (COVID-19) experienced severe illness and mortality. This study aimed to determine the characteristics of concentrated COVID-19 outbreaks that occurred in nursing homes and care facilities in Suita City. During this study, twenty-five elderly facilities in Suita City with a capacity of 40 or more individuals where an outbreak occurred during the sixth or seventh wave of infection were included. We investigated whether there was a difference in the COVID-19 incidence and the percentage of positive cases according to the type of facility. We also investigated the relationship between the facility capacity and positive case rate and that between the number of positive cases and outbreak duration. The incidence rate of COVID-19 was significantly different according to the facility type (p < 0.001). No association was found between the facility capacity and positive case rate. The outbreak duration increased as the number of positive cases increased (p = 0.004).
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Affiliation(s)
| | - Sawa Okano
- Suita City Public Health Center, Suita 564-0072, Japan
| | - Daisuke Onozuka
- Department of Infection Prevention and Control, Osaka University Hospital, Suita 565-0871, Japan
| | - Etsuko Ohta
- Department of Infection Prevention and Control, Osaka University Hospital, Suita 565-0871, Japan
| | - Satoshi Kutsuna
- Department of Infection Prevention and Control, Osaka University Hospital, Suita 565-0871, Japan
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4
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Liang Y, Sun Q, Liu Q, Pang Y, Tang S. SARS-CoV-2 incidence, seroprevalence, and COVID-19 vaccination coverage in the homeless population: a systematic review and meta-analysis. Front Public Health 2023; 11:1044788. [PMID: 37900041 PMCID: PMC10600393 DOI: 10.3389/fpubh.2023.1044788] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2022] [Accepted: 09/25/2023] [Indexed: 10/31/2023] Open
Abstract
Objectives SARS-CoV-2 infection and COVID-19 vaccination of homeless people are a serious public health concern during COVID-19 pandemic. We aimed to systematically assess SARS-CoV-2 incidence, seroprevalence, and COVID-19 vaccination coverage in homeless people, which are important to inform resource allocation and policy adjustment for the prevention and control of COVID-19. Methods We searched PubMed, Web of Science, and the World Health Organization COVID-19 database for the studies of SARS-CoV-2 incidence, seroprevalence, and COVID-19 vaccination coverage in the homeless population. Subgroup analyses were conducted to pool SARS-CoV-2 incidence and seroprevalence in sheltered homeless, unsheltered homeless, and mixed population, respectively. Potential sources of heterogeneity in the estimates were explored by meta-regression analysis. Results Forty-nine eligible studies with a total of 75,402 homeless individuals and 5,000 shelter staff were included in the meta-analysis. The pooled incidence of SARS-CoV-2 infection was 10% (95% CI: 7 to 12%) in the homeless population and 8% (5 to 12%) for shelter staff. In addition, the overall estimated SARS-CoV-2 specific seroprevalence was 19% (8 to 33%) for homeless populations and 22% (3 to 52%) for shelter staff, respectively. Moreover, for the homeless subjects, the pooled incidence was 10% (4 to 23%) for asymptomatic SARS-CoV-2 infections, 6% (1 to 12%) for symptomatic SARS-CoV-2 infections, 3% (1 to 4%) for hospitalization for COVID-19, and 1% (0 to 2%) for severe COVID-19 cases, respectively while no COVID-19-related death was reported. Furthermore, the data derived from 12 included studies involving 225,448 homeless individuals revealed that the pooled proportion of one dose COVID-19 vaccination was 41% (35 to 47%), which was significantly lower than those in the general population. Conclusion Our study results indicate that the homeless people remain highly susceptible to SARS-CoV-2 infection, but COVID-19 vaccination coverage was lower than the general population, underscoring the need for prioritizing vaccine deployment and implementing enhanced preventive measures targeting this vulnerable group.
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Affiliation(s)
| | | | | | | | - Shixing Tang
- Guangdong Provincial Key Laboratory of Tropical Disease Research, Department of Epidemiology, School of Public Health, Southern Medical University, Guangzhou, China
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O'Donnell C, Brownlee K, Martin E, Suyama J, Albert S, Anderson S, Bhatte S, Bonner K, Burton C, Corn M, Eng H, Flage B, Frerotte J, Balasubramani GK, Haggerty C, Haight J, Harrison LH, Hartman A, Hitter T, King WC, Ledger K, Marsh JW, McDonald MC, Miga B, Moses K, Newman A, Ringler M, Roberts M, Sax T, Shekhar A, Sterne M, Tenney T, Vanek M, Wells A, Wenzel S, Williams J. SARS-CoV-2 control on a large urban college campus without mass testing. JOURNAL OF AMERICAN COLLEGE HEALTH : J OF ACH 2023:1-9. [PMID: 36595575 DOI: 10.1080/07448481.2022.2153600] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/15/2021] [Revised: 06/22/2022] [Accepted: 09/19/2022] [Indexed: 06/17/2023]
Abstract
OBJECTIVE A small percentage of universities and colleges conducted mass SARS-CoV-2 testing. However, universal testing is resource-intensive, strains national testing capacity, and false negative tests can encourage unsafe behaviors. PARTICIPANTS A large urban university campus. METHODS Virus control centered on three pillars: mitigation, containment, and communication, with testing of symptomatic and a random subset of asymptomatic students. RESULTS Random surveillance testing demonstrated a prevalence among asymptomatic students of 0.4% throughout the term. There were two surges in cases that were contained by enhanced mitigation and communication combined with targeted testing. Cumulative cases totaled 445 for the term, most resulting from unsafe undergraduate student behavior and among students living off-campus. A case rate of 232/10,000 undergraduates equaled or surpassed several peer institutions that conducted mass testing. CONCLUSIONS An emphasis on behavioral mitigation and communication can control virus transmission on a large urban campus combined with a limited and targeted testing strategy.
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Affiliation(s)
- Christopher O'Donnell
- Department of Medicine, University of Pittsburgh School of Medicine (UPSOM), Pittsburgh, Pennsylvania, USA
| | | | - Elise Martin
- Department of Medicine, University of Pittsburgh School of Medicine (UPSOM), Pittsburgh, Pennsylvania, USA
| | - Joe Suyama
- Department of Emergency Medicine, UPSOM, Pittsburgh, Pennsylvania, USA
| | - Steve Albert
- Department of Behavioral and Community Health Sciences, University of Pittsburgh Graduate School of Public Health (GSPH), Pittsburgh, Pennsylvania, USA
| | - Steven Anderson
- Office of the Dean, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Sai Bhatte
- Kenneth P. Dietrich School of Arts & Sciences, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Kenyon Bonner
- Office of the Dean, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Chad Burton
- University of Pittsburgh Information Technology, Pittsburgh, Pennsylvania, USA
| | - Micaela Corn
- Office of University Communications & Marketing, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Heather Eng
- Department of Epidemiology, GSPH, Pittsburgh, Pennsylvania, USA
| | - Bethany Flage
- Department of Infectious Disease and Microbiology, GSPH, Pittsburgh, Pennsylvania, USA
| | - Jay Frerotte
- Environmental Health and Safety, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | | | | | - Joel Haight
- Swanson School of Engineering, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Lee H Harrison
- Department of Medicine, University of Pittsburgh School of Medicine (UPSOM), Pittsburgh, Pennsylvania, USA
| | - Amy Hartman
- Department of Infectious Disease and Microbiology, GSPH, Pittsburgh, Pennsylvania, USA
| | - Thomas Hitter
- Office of Policy Development and Management, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Wendy C King
- Department of Epidemiology, GSPH, Pittsburgh, Pennsylvania, USA
| | - Kate Ledger
- Office of University Communications & Marketing, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Jane W Marsh
- Department of Medicine, University of Pittsburgh School of Medicine (UPSOM), Pittsburgh, Pennsylvania, USA
| | | | - Bethany Miga
- Office of the Chancellor, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Kimberly Moses
- Office of University Counsel, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Anne Newman
- Department of Epidemiology, GSPH, Pittsburgh, Pennsylvania, USA
| | - Meg Ringler
- Office of University Communications & Marketing, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Mark Roberts
- Department of Health Policy and Management, GSPH, Pittsburgh, Pennsylvania, USA
| | - Theresa Sax
- Department of Epidemiology, GSPH, Pittsburgh, Pennsylvania, USA
| | | | - Matthew Sterne
- Office of Business and Auxiliary Services, GSPH, Pittsburgh, Pennsylvania, USA
| | - Tyler Tenney
- Office of Policy Development and Management, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Marian Vanek
- Office of the Dean, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Alan Wells
- Department of Pathology, UPSOM, Pittsburgh, Pennsylvania, USA
| | - Sally Wenzel
- Department of Environmental and Occupational Health, GSPH, Pittsburgh, Pennsylvania, USA
| | - John Williams
- Department of Pediatrics, UPSOM, Pittsburgh, Pennsylvania, USA
- Institute for Infection, Inflammation, and Immunity in Children, Pittsburgh, Pennsylvania, USA
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6
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Zhu A, Bruketa E, Svoboda T, Patel J, Elmi N, El-Khechen Richandi G, Baral S, Orkin AM. Respiratory infectious disease outbreaks among people experiencing homelessness: a systematic review of prevention and mitigation strategies. Ann Epidemiol 2023; 77:127-135. [PMID: 35342013 DOI: 10.1016/j.annepidem.2022.03.004] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2021] [Revised: 02/16/2022] [Accepted: 03/05/2022] [Indexed: 01/04/2023]
Abstract
PURPOSE People experiencing homelessness (PEH) are at increased risk of respiratory infections and associated morbidity and mortality. To characterize optimal intervention strategies, we completed a systematic review of mitigation strategies for PEH to minimize the spread and impact of respiratory infectious disease outbreaks, including COVID-19. METHODS The study protocol was registered in PROSPERO (#2020 CRD42020208964) and was consistent with the preferred reporting in systematic reviews and meta-analyses guidelines. A search algorithm containing keywords that were synonymous to the terms "Homeless" and "Respiratory Illness" was applied to the six databases. The search concluded on September 22, 2020. Quality assessment was performed at the study level. Steps were conducted by two independent team members. RESULTS A total of 4468 unique titles were retrieved with 21 meeting criteria for inclusion. Interventions included testing, tracking, screening, infection prevention and control, isolation support, and education. Historically, there has been limited study of intervention strategies specifically for PEH across the world. CONCLUSIONS Staff and organizations providing services for people experiencing homelessness face specific challenges in adhering to public health guidelines such as physical distancing, isolation, and routine hygiene practices. There is a discrepancy between the burden of infectious diseases among PEH and specific research characterizing optimal intervention strategies to mitigate transmission in the context of shelters. Improving health for people experiencing homelessness necessitates investment in programs scaling existing interventions and research to study new approaches.
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Affiliation(s)
- Alice Zhu
- Population Health Service, Inner City Health Associates. Toronto, ON, Canada; Department of Family and Community Medicine, University of Toronto, ON, Canada; Department of General Surgery, University of Toronto, Toronto, ON, Canada
| | - Eva Bruketa
- Population Health Service, Inner City Health Associates. Toronto, ON, Canada; Queen's University, School of Medicine, Kingston, ON, Canada
| | - Tomislav Svoboda
- Population Health Service, Inner City Health Associates. Toronto, ON, Canada; Department of Family and Community Medicine, University of Toronto, ON, Canada
| | - Jamie Patel
- Population Health Service, Inner City Health Associates. Toronto, ON, Canada; Ryerson University, Daphne Cockwell School of Nursing, Toronto, ON, Canada
| | - Nika Elmi
- Population Health Service, Inner City Health Associates. Toronto, ON, Canada; Johns Hopkins School of Public Health, Baltimore, MD, USA
| | | | - Stefan Baral
- Population Health Service, Inner City Health Associates. Toronto, ON, Canada; Johns Hopkins School of Public Health, Baltimore, MD, USA
| | - Aaron M Orkin
- Population Health Service, Inner City Health Associates. Toronto, ON, Canada; Department of Family and Community Medicine, University of Toronto, ON, Canada; Dalla Lana School of Public Health, University of Toronto, ON, Canada.
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7
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Ma H, Yiu KCY, Baral SD, Fahim C, Moloney G, Darvin D, Landsman D, Chan AK, Straus S, Mishra S. COVID-19 Cases Among Congregate Care Facility Staff by Neighborhood of Residence and Social and Structural Determinants: Observational Study. JMIR Public Health Surveill 2022; 8:e34927. [PMID: 35867901 PMCID: PMC9534317 DOI: 10.2196/34927] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2021] [Revised: 07/20/2022] [Accepted: 07/21/2022] [Indexed: 11/13/2022] Open
Abstract
Background Disproportionate risks of COVID-19 in congregate care facilities 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 is limited information on how COVID-19 among facility staff reflects urban neighborhood disparities, particularly when stratified by the social and structural determinants of community-level transmission. Objective This study aimed to compare the concentration of cumulative cases by geography and social and structural determinants across 3 mutually exclusive subgroups in the Greater Toronto Area (population: 7.1 million): community, facility staff, and health care workers (HCWs) 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 rollout). We derived neighborhood-level social and structural determinants from census data and generated Lorenz curves, Gini coefficients, and the Hoover index to visualize and quantify inequalities in cases. Results The hardest-hit neighborhoods (comprising 20% of the population) accounted for 53.87% (44,937/83,419) of community cases, 48.59% (2356/4849) of facility staff cases, and 42.34% (1669/3942) of other HCW cases. Compared with other HCWs, cases among facility staff reflected the distribution of community cases more closely. Cases among facility staff reflected greater social and structural inequalities (larger Gini coefficients) than those of other HCWs across all determinants. Facility staff cases were also more likely than community cases to be concentrated in lower-income neighborhoods (Gini 0.24, 95% CI 0.15-0.38 vs 0.14, 95% CI 0.08-0.21) with a higher household density (Gini 0.23, 95% CI 0.17-0.29 vs 0.17, 95% CI 0.12-0.22) and with a greater proportion working in other essential services (Gini 0.29, 95% CI 0.21-0.40 vs 0.22, 95% CI 0.17-0.28). Conclusions COVID-19 cases among facility staff largely reflect neighborhood-level heterogeneity and disparities, even more so than cases among other HCWs. The findings signal the importance of interventions prioritized and tailored to the home geographies of facility staff in addition to workplace measures, including prioritization and reach of vaccination at home (neighborhood level) and at work.
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Affiliation(s)
- Huiting Ma
- St Michael's Hospital, Unity Health Toronto, Toronto, ON, Canada
| | - Kristy C Y Yiu
- St Michael's Hospital, Unity Health Toronto, Toronto, ON, Canada
| | - Stefan D Baral
- Department of Epidemiology, Johns Hopkins School of Public Health, Baltimore, MD, United States
| | - Christine Fahim
- St Michael's Hospital, Unity Health Toronto, Toronto, ON, Canada
| | - Gary Moloney
- St Michael's Hospital, Unity Health Toronto, Toronto, ON, Canada
| | - Dariya Darvin
- St Michael's Hospital, Unity Health Toronto, Toronto, ON, Canada
| | - David Landsman
- St Michael's Hospital, Unity Health Toronto, Toronto, ON, Canada
| | - Adrienne K Chan
- Division of Infectious Diseases, Department of Medicine, University of Toronto, Toronto, ON, Canada.,Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada.,Division of Infectious Diseases, Sunnybrook Health Sciences, University of Toronto, Toronto, ON, Canada.,Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, ON, Canada
| | - Sharon Straus
- St Michael's Hospital, Unity Health Toronto, Toronto, ON, Canada.,Department of Medicine, University of Toronto, Toronto, ON, Canada
| | - Sharmistha Mishra
- St Michael's Hospital, Unity Health Toronto, Toronto, ON, Canada.,Division of Infectious Diseases, Department of Medicine, University of Toronto, Toronto, ON, Canada.,Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada.,Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, ON, Canada
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8
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Eder L, Croxford R, Drucker AM, Mendel A, Kuriya B, Touma Z, Johnson SR, Cook R, Bernatsky S, Haroon N, Widdifield J. Understanding COVID-19 Risk in Patients With Immune-Mediated Inflammatory Diseases: A Population-Based Analysis of SARS-CoV-2 Testing. Arthritis Care Res (Hoboken) 2022; 75:317-325. [PMID: 34486829 PMCID: PMC8653048 DOI: 10.1002/acr.24781] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2021] [Revised: 08/06/2021] [Accepted: 09/02/2021] [Indexed: 12/04/2022]
Abstract
OBJECTIVE To investigate the incidence of and factors associated with SARS-CoV-2 testing and infection in immune-mediated inflammatory disease (IMID) patients versus matched non-IMID comparators from the general population. METHODS We conducted a population-based, matched cohort study among adult residents from Ontario, Canada, from January 2020 to December 2020. We created cohorts for the following IMIDs: rheumatoid arthritis (RA), psoriasis, psoriatic arthritis, ankylosing spondylitis, systemic autoimmune rheumatic diseases, multiple sclerosis (MS), iritis, inflammatory bowel disease (IBD), polymyalgia rheumatica, and vasculitis. Each patient was matched with 5 patients without IMIDs based on sociodemographic factors. We estimated the incidence of SARS-CoV-2 testing and infection in IMID patients and non-IMID patients. Multivariable logistic regressions assessed odds of SARS-CoV-2 infection. RESULTS We studied 493,499 patients with IMIDs and 2,466,946 patients without IMIDs. Patients with IMIDs were more likely to have at least 1 SARS-CoV-2 test versus patients without IMIDs (27.4% versus 22.7%), but the proportion testing positive for SARS-CoV-2 was identical (0.9% in both groups). Overall, IMID patients had 20% higher odds of being tested for SARS-CoV-2 (odds ratio 1.20 [95% confidence interval 1.19-1.21]). The odds of SARS-CoV-2 infection varied across IMID groups but was not significantly elevated for most IMID groups compared with non-IMID comparators. The odds of SARS-CoV-2 infection was lower in IBD and MS and marginally higher in RA and iritis. CONCLUSION Patients across all IMIDs were more likely to be tested for SARS-CoV-2 versus those without IMIDs. The risk of SARS-CoV-2 infection varied across disease subgroups.
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Affiliation(s)
- Lihi Eder
- University of TorontoTorontoOntarioCanada
| | | | | | | | - Bindee Kuriya
- Sinai Health System, University of TorontoTorontoOntarioCanada
| | - Zahi Touma
- Toronto Western Hospital, University of TorontoTorontoOntarioCanada
| | - Sindhu R. Johnson
- Toronto Western Hospital, Mount Sinai Hospital, University of TorontoTorontoOntarioCanada
| | | | | | - Nigil Haroon
- Schroeder Arthritis Institute, Krembil Research Institute, University Health Network, Toronto Western Hospital, University of TorontoTorontoOntarioCanada
| | - Jessica Widdifield
- Sunnybrook Research Institute, ICES, University of TorontoTorontoOntarioCanada
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9
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Verbiest MEA, Stoop A, Scheffelaar A, Janssen MM, van Boekel LC, Luijkx KG. Health impact of the first and second wave of COVID-19 and related restrictive measures among nursing home residents: a scoping review. BMC Health Serv Res 2022; 22:921. [PMID: 35841028 PMCID: PMC9286708 DOI: 10.1186/s12913-022-08186-w] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2021] [Accepted: 06/10/2022] [Indexed: 11/22/2022] Open
Abstract
Background and objectives COVID-19 disproportionally affects older adults living in nursing homes. The purpose of this review was to explore and map the scientific literature on the health impact of COVID-19 and related restrictive measures during the first and second wave among nursing home residents. A specific focus was placed on health data collected among nursing home residents themselves. Research design and methods In this study, best practices for scoping reviews were followed. Five databases were systematically searched for peer-reviewed empirical studies published up until December 2020 in which data were collected among nursing home residents. Articles were categorized according to the type of health impact (physical, social and/or psychological) and study focus (impact of COVID-19 virus or related restrictive measures). Findings were presented using a narrative style. Results Of 60 included studies, 57 examined the physical impact of COVID-19. All of these focused on the direct impact of the COVID-19 virus. These studies often used an observational design and quantitative data collection methods, such as swab testing or reviewing health records. Only three studies examined the psychological impact of COVID-19 of which one study focused on the impact of COVID-19-related restrictive measures. Findings were contradictory; both decreased and improved psychological wellbeing was found during the pandemic compared with before. No studies were found that examined the impact on social wellbeing and one study examined other health-related outcomes, including preference changes of nursing home residents in Advanced Care planning following the pandemic. Discussion and implications Studies into the impact of the first and second wave of the COVID-19 pandemic among nursing home residents predominantly focused on the physical impact. Future studies into the psychological and social impact that collect data among residents themselves will provide more insight into their perspectives, such as lived experiences, wishes, needs and possibilities during later phases of the pandemic. These insights can inform policy makers and healthcare professionals in providing person-centered care during the remaining COVID-19 pandemic and in future crisis periods.
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Affiliation(s)
- Marjolein E A Verbiest
- Academic Collaborative Centre Older Adults, Tranzo Scientific Centre for Care and Wellbeing, Tilburg School of Social and Behavioral Sciences, Tilburg University, PO Box 90153, 5000 LE, Tilburg, the Netherlands.
| | - Annerieke Stoop
- Academic Collaborative Centre Older Adults, Tranzo Scientific Centre for Care and Wellbeing, Tilburg School of Social and Behavioral Sciences, Tilburg University, PO Box 90153, 5000 LE, Tilburg, the Netherlands
| | - Aukelien Scheffelaar
- Academic Collaborative Centre Older Adults, Tranzo Scientific Centre for Care and Wellbeing, Tilburg School of Social and Behavioral Sciences, Tilburg University, PO Box 90153, 5000 LE, Tilburg, the Netherlands
| | - Meriam M Janssen
- Academic Collaborative Centre Older Adults, Tranzo Scientific Centre for Care and Wellbeing, Tilburg School of Social and Behavioral Sciences, Tilburg University, PO Box 90153, 5000 LE, Tilburg, the Netherlands
| | - Leonieke C van Boekel
- Academic Collaborative Centre Older Adults, Tranzo Scientific Centre for Care and Wellbeing, Tilburg School of Social and Behavioral Sciences, Tilburg University, PO Box 90153, 5000 LE, Tilburg, the Netherlands
| | - Katrien G Luijkx
- Academic Collaborative Centre Older Adults, Tranzo Scientific Centre for Care and Wellbeing, Tilburg School of Social and Behavioral Sciences, Tilburg University, PO Box 90153, 5000 LE, Tilburg, the Netherlands
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Corey J, Lyons J, O’Carroll A, Stafford R, Ivers JH. A Scoping Review of the Health Impact of the COVID-19 Pandemic on Persons Experiencing Homelessness in North America and Europe. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2022; 19:ijerph19063219. [PMID: 35328907 PMCID: PMC8954292 DOI: 10.3390/ijerph19063219] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/04/2022] [Revised: 03/02/2022] [Accepted: 03/04/2022] [Indexed: 02/04/2023]
Abstract
Persons experiencing homelessness (PEH) are at heightened risk for infection, morbidity, and mortality from COVID-19. However, health consequences of the pandemic extend far beyond those directly caused by the virus. This scoping review aimed to explore the impacts of the COVID-19 pandemic on the health and well-being of PEH in North America and Europe. A systematic search of academic and grey literature was conducted in September 2021. To be included, studies had to include primary data related to the impact of the pandemic on health or well-being of PEH and be written in English. All potentially relevant references were independently screened by two reviewers, and minor conflicts were settled with input of a third reviewer. A total of 96 articles met criteria for inclusion. Data extraction was completed for all included studies, and findings synthesised and presented thematically. Numerous health impacts of the pandemic on PEH were identified, including SARS-CoV-2 infection, morbidity, mortality, and hospitalisation, fear of infection, access to housing, hygiene, PPE, food, as well as mental health, substance use, other health-related outcomes and treatment services. Gaps in the literature relating to persons using alcohol, access to mental health support, and violence were also identified. Implications for future research are discussed.
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Affiliation(s)
- Julia Corey
- Department of Public Health & Primary Care, School of Medicine, Trinity College Dublin, D24H74 Dublin, Ireland; (J.C.); (J.L.)
| | - James Lyons
- Department of Public Health & Primary Care, School of Medicine, Trinity College Dublin, D24H74 Dublin, Ireland; (J.C.); (J.L.)
| | | | - Richie Stafford
- HSE Community Healthcare Organisation Dublin North City & County, D09C8P5 Dublin, Ireland;
| | - Jo-Hanna Ivers
- Department of Public Health & Primary Care, School of Medicine, Trinity College Dublin, D24H74 Dublin, Ireland; (J.C.); (J.L.)
- Correspondence:
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11
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Xia Y, Ma H, Moloney G, Velásquez García HA, Sirski M, Janjua NZ, Vickers D, Williamson T, Katz A, Yiu K, Kustra R, Buckeridge DL, Brisson M, Baral SD, Mishra S, Maheu-Giroux M. Geographic concentration of SARS-CoV-2 cases by social determinants of health in metropolitan areas in Canada: a cross-sectional study. CMAJ 2022; 194:E195-E204. [PMID: 35165131 PMCID: PMC8900797 DOI: 10.1503/cmaj.211249] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 01/07/2022] [Indexed: 12/27/2022] Open
Abstract
Background: Understanding inequalities in SARS-CoV-2 transmission associated with the social determinants of health could help the development of effective mitigation strategies that are responsive to local transmission dynamics. This study aims to quantify social determinants of geographic concentration of SARS-CoV-2 cases across 16 census metropolitan areas (hereafter, cities) in 4 Canadian provinces, British Columbia, Manitoba, Ontario and Quebec. Methods: We used surveillance data on confirmed SARS-CoV-2 cases and census data for social determinants at the level of the dissemination area (DA). We calculated Gini coefficients to determine the overall geographic heterogeneity of confirmed cases of SARS-CoV-2 in each city, and calculated Gini covariance coefficients to determine each city’s heterogeneity by each social determinant (income, education, housing density and proportions of visible minorities, recent immigrants and essential workers). We visualized heterogeneity using Lorenz (concentration) curves. Results: We observed geographic concentration of SARS-CoV-2 cases in cities, as half of the cumulative cases were concentrated in DAs containing 21%–35% of their population, with the greatest geographic heterogeneity in Ontario cities (Gini coefficients 0.32–0.47), followed by British Columbia (0.23–0.36), Manitoba (0.32) and Quebec (0.28–0.37). Cases were disproportionately concentrated in areas with lower income and educational attainment, and in areas with a higher proportion of visible minorities, recent immigrants, high-density housing and essential workers. Although a consistent feature across cities was concentration by the proportion of visible minorities, the magnitude of concentration by social determinant varied across cities. Interpretation: Geographic concentration of SARS-CoV-2 cases was observed in all of the included cities, but the pattern by social determinants varied. Geographically prioritized allocation of resources and services should be tailored to the local drivers of inequalities in transmission in response to the resurgence of SARS-CoV-2.
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Affiliation(s)
- Yiqing Xia
- Department of Epidemiology and Biostatistics (Xia, Buckeridge, Maheu-Giroux), School of Population and Global Health, McGill University, Montréal, Que.; MAP Centre for Urban Health Solutions (Xia, Ma, Moloney, Yiu, Mishra), St. Michael's Hospital, Unity Health Toronto, Toronto, Ont.; School of Population and Public Health (Velásquez García, Janjua), University of British Columbia; British Columbia Centre for Disease Control (Velásquez García, Janjua), Vancouver, BC; Departments of Community Health Sciences and Family Medicine (Sirski, Katz), Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, Man.; Department of Community Health Sciences (Vickers, Williamson) and Centre for Health Informatics (Williamson), University of Calgary, Calgary, Alta.; Dalla Lana School of Public Health (Kustra), University of Toronto, Toronto, Ont.; Département de médecine sociale et préventive (Brisson), Faculté de médecine, Université Laval, Québec, Que.; Department of Epidemiology (Baral), Johns Hopkins School of Public Health, Baltimore, Md.; Division of Infectious Diseases (Mishra), Department of Medicine, University of Toronto, Toronto, Ont
| | - Huiting Ma
- Department of Epidemiology and Biostatistics (Xia, Buckeridge, Maheu-Giroux), School of Population and Global Health, McGill University, Montréal, Que.; MAP Centre for Urban Health Solutions (Xia, Ma, Moloney, Yiu, Mishra), St. Michael's Hospital, Unity Health Toronto, Toronto, Ont.; School of Population and Public Health (Velásquez García, Janjua), University of British Columbia; British Columbia Centre for Disease Control (Velásquez García, Janjua), Vancouver, BC; Departments of Community Health Sciences and Family Medicine (Sirski, Katz), Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, Man.; Department of Community Health Sciences (Vickers, Williamson) and Centre for Health Informatics (Williamson), University of Calgary, Calgary, Alta.; Dalla Lana School of Public Health (Kustra), University of Toronto, Toronto, Ont.; Département de médecine sociale et préventive (Brisson), Faculté de médecine, Université Laval, Québec, Que.; Department of Epidemiology (Baral), Johns Hopkins School of Public Health, Baltimore, Md.; Division of Infectious Diseases (Mishra), Department of Medicine, University of Toronto, Toronto, Ont
| | - Gary Moloney
- Department of Epidemiology and Biostatistics (Xia, Buckeridge, Maheu-Giroux), School of Population and Global Health, McGill University, Montréal, Que.; MAP Centre for Urban Health Solutions (Xia, Ma, Moloney, Yiu, Mishra), St. Michael's Hospital, Unity Health Toronto, Toronto, Ont.; School of Population and Public Health (Velásquez García, Janjua), University of British Columbia; British Columbia Centre for Disease Control (Velásquez García, Janjua), Vancouver, BC; Departments of Community Health Sciences and Family Medicine (Sirski, Katz), Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, Man.; Department of Community Health Sciences (Vickers, Williamson) and Centre for Health Informatics (Williamson), University of Calgary, Calgary, Alta.; Dalla Lana School of Public Health (Kustra), University of Toronto, Toronto, Ont.; Département de médecine sociale et préventive (Brisson), Faculté de médecine, Université Laval, Québec, Que.; Department of Epidemiology (Baral), Johns Hopkins School of Public Health, Baltimore, Md.; Division of Infectious Diseases (Mishra), Department of Medicine, University of Toronto, Toronto, Ont
| | - Héctor A Velásquez García
- Department of Epidemiology and Biostatistics (Xia, Buckeridge, Maheu-Giroux), School of Population and Global Health, McGill University, Montréal, Que.; MAP Centre for Urban Health Solutions (Xia, Ma, Moloney, Yiu, Mishra), St. Michael's Hospital, Unity Health Toronto, Toronto, Ont.; School of Population and Public Health (Velásquez García, Janjua), University of British Columbia; British Columbia Centre for Disease Control (Velásquez García, Janjua), Vancouver, BC; Departments of Community Health Sciences and Family Medicine (Sirski, Katz), Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, Man.; Department of Community Health Sciences (Vickers, Williamson) and Centre for Health Informatics (Williamson), University of Calgary, Calgary, Alta.; Dalla Lana School of Public Health (Kustra), University of Toronto, Toronto, Ont.; Département de médecine sociale et préventive (Brisson), Faculté de médecine, Université Laval, Québec, Que.; Department of Epidemiology (Baral), Johns Hopkins School of Public Health, Baltimore, Md.; Division of Infectious Diseases (Mishra), Department of Medicine, University of Toronto, Toronto, Ont
| | - Monica Sirski
- Department of Epidemiology and Biostatistics (Xia, Buckeridge, Maheu-Giroux), School of Population and Global Health, McGill University, Montréal, Que.; MAP Centre for Urban Health Solutions (Xia, Ma, Moloney, Yiu, Mishra), St. Michael's Hospital, Unity Health Toronto, Toronto, Ont.; School of Population and Public Health (Velásquez García, Janjua), University of British Columbia; British Columbia Centre for Disease Control (Velásquez García, Janjua), Vancouver, BC; Departments of Community Health Sciences and Family Medicine (Sirski, Katz), Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, Man.; Department of Community Health Sciences (Vickers, Williamson) and Centre for Health Informatics (Williamson), University of Calgary, Calgary, Alta.; Dalla Lana School of Public Health (Kustra), University of Toronto, Toronto, Ont.; Département de médecine sociale et préventive (Brisson), Faculté de médecine, Université Laval, Québec, Que.; Department of Epidemiology (Baral), Johns Hopkins School of Public Health, Baltimore, Md.; Division of Infectious Diseases (Mishra), Department of Medicine, University of Toronto, Toronto, Ont
| | - Naveed Z Janjua
- Department of Epidemiology and Biostatistics (Xia, Buckeridge, Maheu-Giroux), School of Population and Global Health, McGill University, Montréal, Que.; MAP Centre for Urban Health Solutions (Xia, Ma, Moloney, Yiu, Mishra), St. Michael's Hospital, Unity Health Toronto, Toronto, Ont.; School of Population and Public Health (Velásquez García, Janjua), University of British Columbia; British Columbia Centre for Disease Control (Velásquez García, Janjua), Vancouver, BC; Departments of Community Health Sciences and Family Medicine (Sirski, Katz), Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, Man.; Department of Community Health Sciences (Vickers, Williamson) and Centre for Health Informatics (Williamson), University of Calgary, Calgary, Alta.; Dalla Lana School of Public Health (Kustra), University of Toronto, Toronto, Ont.; Département de médecine sociale et préventive (Brisson), Faculté de médecine, Université Laval, Québec, Que.; Department of Epidemiology (Baral), Johns Hopkins School of Public Health, Baltimore, Md.; Division of Infectious Diseases (Mishra), Department of Medicine, University of Toronto, Toronto, Ont
| | - David Vickers
- Department of Epidemiology and Biostatistics (Xia, Buckeridge, Maheu-Giroux), School of Population and Global Health, McGill University, Montréal, Que.; MAP Centre for Urban Health Solutions (Xia, Ma, Moloney, Yiu, Mishra), St. Michael's Hospital, Unity Health Toronto, Toronto, Ont.; School of Population and Public Health (Velásquez García, Janjua), University of British Columbia; British Columbia Centre for Disease Control (Velásquez García, Janjua), Vancouver, BC; Departments of Community Health Sciences and Family Medicine (Sirski, Katz), Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, Man.; Department of Community Health Sciences (Vickers, Williamson) and Centre for Health Informatics (Williamson), University of Calgary, Calgary, Alta.; Dalla Lana School of Public Health (Kustra), University of Toronto, Toronto, Ont.; Département de médecine sociale et préventive (Brisson), Faculté de médecine, Université Laval, Québec, Que.; Department of Epidemiology (Baral), Johns Hopkins School of Public Health, Baltimore, Md.; Division of Infectious Diseases (Mishra), Department of Medicine, University of Toronto, Toronto, Ont
| | - Tyler Williamson
- Department of Epidemiology and Biostatistics (Xia, Buckeridge, Maheu-Giroux), School of Population and Global Health, McGill University, Montréal, Que.; MAP Centre for Urban Health Solutions (Xia, Ma, Moloney, Yiu, Mishra), St. Michael's Hospital, Unity Health Toronto, Toronto, Ont.; School of Population and Public Health (Velásquez García, Janjua), University of British Columbia; British Columbia Centre for Disease Control (Velásquez García, Janjua), Vancouver, BC; Departments of Community Health Sciences and Family Medicine (Sirski, Katz), Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, Man.; Department of Community Health Sciences (Vickers, Williamson) and Centre for Health Informatics (Williamson), University of Calgary, Calgary, Alta.; Dalla Lana School of Public Health (Kustra), University of Toronto, Toronto, Ont.; Département de médecine sociale et préventive (Brisson), Faculté de médecine, Université Laval, Québec, Que.; Department of Epidemiology (Baral), Johns Hopkins School of Public Health, Baltimore, Md.; Division of Infectious Diseases (Mishra), Department of Medicine, University of Toronto, Toronto, Ont
| | - Alan Katz
- Department of Epidemiology and Biostatistics (Xia, Buckeridge, Maheu-Giroux), School of Population and Global Health, McGill University, Montréal, Que.; MAP Centre for Urban Health Solutions (Xia, Ma, Moloney, Yiu, Mishra), St. Michael's Hospital, Unity Health Toronto, Toronto, Ont.; School of Population and Public Health (Velásquez García, Janjua), University of British Columbia; British Columbia Centre for Disease Control (Velásquez García, Janjua), Vancouver, BC; Departments of Community Health Sciences and Family Medicine (Sirski, Katz), Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, Man.; Department of Community Health Sciences (Vickers, Williamson) and Centre for Health Informatics (Williamson), University of Calgary, Calgary, Alta.; Dalla Lana School of Public Health (Kustra), University of Toronto, Toronto, Ont.; Département de médecine sociale et préventive (Brisson), Faculté de médecine, Université Laval, Québec, Que.; Department of Epidemiology (Baral), Johns Hopkins School of Public Health, Baltimore, Md.; Division of Infectious Diseases (Mishra), Department of Medicine, University of Toronto, Toronto, Ont
| | - Kristy Yiu
- Department of Epidemiology and Biostatistics (Xia, Buckeridge, Maheu-Giroux), School of Population and Global Health, McGill University, Montréal, Que.; MAP Centre for Urban Health Solutions (Xia, Ma, Moloney, Yiu, Mishra), St. Michael's Hospital, Unity Health Toronto, Toronto, Ont.; School of Population and Public Health (Velásquez García, Janjua), University of British Columbia; British Columbia Centre for Disease Control (Velásquez García, Janjua), Vancouver, BC; Departments of Community Health Sciences and Family Medicine (Sirski, Katz), Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, Man.; Department of Community Health Sciences (Vickers, Williamson) and Centre for Health Informatics (Williamson), University of Calgary, Calgary, Alta.; Dalla Lana School of Public Health (Kustra), University of Toronto, Toronto, Ont.; Département de médecine sociale et préventive (Brisson), Faculté de médecine, Université Laval, Québec, Que.; Department of Epidemiology (Baral), Johns Hopkins School of Public Health, Baltimore, Md.; Division of Infectious Diseases (Mishra), Department of Medicine, University of Toronto, Toronto, Ont
| | - Rafal Kustra
- Department of Epidemiology and Biostatistics (Xia, Buckeridge, Maheu-Giroux), School of Population and Global Health, McGill University, Montréal, Que.; MAP Centre for Urban Health Solutions (Xia, Ma, Moloney, Yiu, Mishra), St. Michael's Hospital, Unity Health Toronto, Toronto, Ont.; School of Population and Public Health (Velásquez García, Janjua), University of British Columbia; British Columbia Centre for Disease Control (Velásquez García, Janjua), Vancouver, BC; Departments of Community Health Sciences and Family Medicine (Sirski, Katz), Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, Man.; Department of Community Health Sciences (Vickers, Williamson) and Centre for Health Informatics (Williamson), University of Calgary, Calgary, Alta.; Dalla Lana School of Public Health (Kustra), University of Toronto, Toronto, Ont.; Département de médecine sociale et préventive (Brisson), Faculté de médecine, Université Laval, Québec, Que.; Department of Epidemiology (Baral), Johns Hopkins School of Public Health, Baltimore, Md.; Division of Infectious Diseases (Mishra), Department of Medicine, University of Toronto, Toronto, Ont
| | - David L Buckeridge
- Department of Epidemiology and Biostatistics (Xia, Buckeridge, Maheu-Giroux), School of Population and Global Health, McGill University, Montréal, Que.; MAP Centre for Urban Health Solutions (Xia, Ma, Moloney, Yiu, Mishra), St. Michael's Hospital, Unity Health Toronto, Toronto, Ont.; School of Population and Public Health (Velásquez García, Janjua), University of British Columbia; British Columbia Centre for Disease Control (Velásquez García, Janjua), Vancouver, BC; Departments of Community Health Sciences and Family Medicine (Sirski, Katz), Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, Man.; Department of Community Health Sciences (Vickers, Williamson) and Centre for Health Informatics (Williamson), University of Calgary, Calgary, Alta.; Dalla Lana School of Public Health (Kustra), University of Toronto, Toronto, Ont.; Département de médecine sociale et préventive (Brisson), Faculté de médecine, Université Laval, Québec, Que.; Department of Epidemiology (Baral), Johns Hopkins School of Public Health, Baltimore, Md.; Division of Infectious Diseases (Mishra), Department of Medicine, University of Toronto, Toronto, Ont
| | - Marc Brisson
- Department of Epidemiology and Biostatistics (Xia, Buckeridge, Maheu-Giroux), School of Population and Global Health, McGill University, Montréal, Que.; MAP Centre for Urban Health Solutions (Xia, Ma, Moloney, Yiu, Mishra), St. Michael's Hospital, Unity Health Toronto, Toronto, Ont.; School of Population and Public Health (Velásquez García, Janjua), University of British Columbia; British Columbia Centre for Disease Control (Velásquez García, Janjua), Vancouver, BC; Departments of Community Health Sciences and Family Medicine (Sirski, Katz), Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, Man.; Department of Community Health Sciences (Vickers, Williamson) and Centre for Health Informatics (Williamson), University of Calgary, Calgary, Alta.; Dalla Lana School of Public Health (Kustra), University of Toronto, Toronto, Ont.; Département de médecine sociale et préventive (Brisson), Faculté de médecine, Université Laval, Québec, Que.; Department of Epidemiology (Baral), Johns Hopkins School of Public Health, Baltimore, Md.; Division of Infectious Diseases (Mishra), Department of Medicine, University of Toronto, Toronto, Ont
| | - Stefan D Baral
- Department of Epidemiology and Biostatistics (Xia, Buckeridge, Maheu-Giroux), School of Population and Global Health, McGill University, Montréal, Que.; MAP Centre for Urban Health Solutions (Xia, Ma, Moloney, Yiu, Mishra), St. Michael's Hospital, Unity Health Toronto, Toronto, Ont.; School of Population and Public Health (Velásquez García, Janjua), University of British Columbia; British Columbia Centre for Disease Control (Velásquez García, Janjua), Vancouver, BC; Departments of Community Health Sciences and Family Medicine (Sirski, Katz), Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, Man.; Department of Community Health Sciences (Vickers, Williamson) and Centre for Health Informatics (Williamson), University of Calgary, Calgary, Alta.; Dalla Lana School of Public Health (Kustra), University of Toronto, Toronto, Ont.; Département de médecine sociale et préventive (Brisson), Faculté de médecine, Université Laval, Québec, Que.; Department of Epidemiology (Baral), Johns Hopkins School of Public Health, Baltimore, Md.; Division of Infectious Diseases (Mishra), Department of Medicine, University of Toronto, Toronto, Ont
| | - Sharmistha Mishra
- Department of Epidemiology and Biostatistics (Xia, Buckeridge, Maheu-Giroux), School of Population and Global Health, McGill University, Montréal, Que.; MAP Centre for Urban Health Solutions (Xia, Ma, Moloney, Yiu, Mishra), St. Michael's Hospital, Unity Health Toronto, Toronto, Ont.; School of Population and Public Health (Velásquez García, Janjua), University of British Columbia; British Columbia Centre for Disease Control (Velásquez García, Janjua), Vancouver, BC; Departments of Community Health Sciences and Family Medicine (Sirski, Katz), Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, Man.; Department of Community Health Sciences (Vickers, Williamson) and Centre for Health Informatics (Williamson), University of Calgary, Calgary, Alta.; Dalla Lana School of Public Health (Kustra), University of Toronto, Toronto, Ont.; Département de médecine sociale et préventive (Brisson), Faculté de médecine, Université Laval, Québec, Que.; Department of Epidemiology (Baral), Johns Hopkins School of Public Health, Baltimore, Md.; Division of Infectious Diseases (Mishra), Department of Medicine, University of Toronto, Toronto, Ont.
| | - Mathieu Maheu-Giroux
- Department of Epidemiology and Biostatistics (Xia, Buckeridge, Maheu-Giroux), School of Population and Global Health, McGill University, Montréal, Que.; MAP Centre for Urban Health Solutions (Xia, Ma, Moloney, Yiu, Mishra), St. Michael's Hospital, Unity Health Toronto, Toronto, Ont.; School of Population and Public Health (Velásquez García, Janjua), University of British Columbia; British Columbia Centre for Disease Control (Velásquez García, Janjua), Vancouver, BC; Departments of Community Health Sciences and Family Medicine (Sirski, Katz), Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, Man.; Department of Community Health Sciences (Vickers, Williamson) and Centre for Health Informatics (Williamson), University of Calgary, Calgary, Alta.; Dalla Lana School of Public Health (Kustra), University of Toronto, Toronto, Ont.; Département de médecine sociale et préventive (Brisson), Faculté de médecine, Université Laval, Québec, Que.; Department of Epidemiology (Baral), Johns Hopkins School of Public Health, Baltimore, Md.; Division of Infectious Diseases (Mishra), Department of Medicine, University of Toronto, Toronto, Ont
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12
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Mishra S, Ma H, Moloney G, Yiu KCY, Darvin D, Landsman D, Kwong JC, Calzavara A, Straus S, Chan AK, Gournis E, Rilkoff H, Xia Y, Katz A, Williamson T, Malikov K, Kustra R, Maheu-Giroux M, Sander B, Baral SD. Increasing concentration of COVID-19 by socioeconomic determinants and geography in Toronto, Canada: an observational study. Ann Epidemiol 2022; 65:84-92. [PMID: 34320380 DOI: 10.1101/2021.04.01.21254585] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2021] [Revised: 07/15/2021] [Accepted: 07/18/2021] [Indexed: 05/20/2023]
Abstract
BACKGROUND Inequities in the burden of COVID-19 were observed early in Canada and around the world, suggesting economically marginalized communities faced disproportionate risks. However, there has been limited systematic assessment of how heterogeneity in risks has evolved in large urban centers over time. PURPOSE To address this gap, we quantified the magnitude of risk heterogeneity in Toronto, Ontario from January to November 2020 using a retrospective, population-based observational study using surveillance data. METHODS We generated epidemic curves by social determinants of health (SDOH) and crude Lorenz curves by neighbourhoods to visualize inequities in the distribution of COVID-19 and estimated Gini coefficients. We examined the correlation between SDOH using Pearson-correlation coefficients. RESULTS Gini coefficient of cumulative cases by population size was 0.41 (95% confidence interval [CI]:0.36-0.47) and 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); multigenerational households (0.19, 95%CI:0.15-0.23); and essential workers (0.28, 95%CI:0.23-0.34). CONCLUSIONS There was rapid epidemiologic transition from higher- to lower-income neighborhoods with Lorenz curve transitioning from below to above the line of equality across SDOH. Moving forward necessitates integrating programs and policies addressing socioeconomic inequities and structural racism into COVID-19 prevention and vaccination programs.
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Affiliation(s)
- Sharmistha Mishra
- St. Michael's Hospital, Unity Health Toronto, Toronto, Canada; Division of Infectious Diseases, Department of Medicine, University of Toronto, Toronto, Canada.
| | - Huiting Ma
- St. Michael's Hospital, Unity Health Toronto, Toronto, Canada
| | - Gary Moloney
- St. Michael's Hospital, Unity Health Toronto, Toronto, Canada
| | - Kristy C Y Yiu
- St. Michael's Hospital, Unity Health Toronto, Toronto, Canada
| | - Dariya Darvin
- St. Michael's Hospital, Unity Health Toronto, Toronto, Canada
| | - David Landsman
- St. Michael's Hospital, Unity Health Toronto, Toronto, Canada
| | - Jeffrey C Kwong
- ICES, Toronto, Canada; Public Health Ontario, Toronto, Canada; Department of Family and Community Medicine, Faculty of Medicine, University of Toronto, Toronto, Canada; Dalla Lana School of Public Health, University of Toronto, Toronto, Canada; University Health Network, Toronto, Canada
| | | | - Sharon Straus
- Department of Medicine, St. Michael's Hospital, University of Toronto, Toronto, Canada
| | - Adrienne K Chan
- Division of Infectious Diseases, Department of Medicine, University of Toronto, Toronto, Canada; Dalla Lana School of Public Health, University of Toronto, Toronto, Canada; Department of Medicine, St. Michael's Hospital, University of Toronto, Toronto, Canada; Division of Infectious Diseases, Sunnybrook Health Sciences, University of Toronto, Toronto, Canada
| | - Effie Gournis
- Dalla Lana School of Public Health, University of Toronto, Toronto, Canada; Toronto Public Health, City of Toronto, Toronto, Canada
| | | | - Yiqing Xia
- St. Michael's Hospital, Unity Health Toronto, Toronto, Canada; Department of Epidemiology, Biostatistics and Occupational Health, School of Population and Global Health, McGill University, Montréal, Canada
| | - Alan Katz
- Departments of Community Health Sciences and Family Medicine, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, Canada
| | - Tyler Williamson
- Department of Community Health Sciences, University of Calgary, Calgary, Canada; Centre for Health Informatics, University of Calgary, Calgary, Canada
| | - Kamil Malikov
- Capacity Planning and Analytics Division, Ontario Ministry of Health, Toronto, Canada
| | - Rafal Kustra
- Dalla Lana School of Public Health, University of Toronto, Toronto, Canada
| | - Mathieu Maheu-Giroux
- Department of Epidemiology, Biostatistics and Occupational Health, School of Population and Global Health, McGill University, Montréal, Canada
| | - Beate Sander
- ICES, Toronto, Canada; Public Health Ontario, Toronto, Canada; Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, Canada
| | - Stefan D Baral
- Department of Epidemiology, Johns Hopkins School of Public Health, Baltimore, United States
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13
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Luong L, Beder M, Nisenbaum R, Orkin A, Wong J, Damba C, Emond R, Lena S, Wright V, Loutfy M, Bruce-Barrett C, Cheung W, Cheung YK, Williams V, Vanmeurs M, Boozary A, Manning H, Hester J, Hwang SW. Prevalence of SARS-CoV-2 infection among people experiencing homelessness in Toronto during the first wave of the COVID-19 pandemic. Canadian Journal of Public Health 2021; 113:117-125. [PMID: 34919211 PMCID: PMC8678973 DOI: 10.17269/s41997-021-00591-8] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/04/2021] [Accepted: 10/25/2021] [Indexed: 12/19/2022]
Abstract
OBJECTIVES People experiencing homelessness are at increased risk of SARS-CoV-2 infection. This study reports the point prevalence of SARS-CoV-2 infection during testing conducted at sites serving people experiencing homelessness in Toronto during the first wave of the COVID-19 pandemic. We also explored the association between site characteristics and prevalence rates. METHODS The study included individuals who were staying at shelters, encampments, COVID-19 physical distancing sites, and drop-in and respite sites and completed outreach-based testing for SARS-CoV-2 during the period April 17 to July 31, 2020. We examined test positivity rates over time and compared them to rates in the general population of Toronto. Negative binomial regression was used to examine the relationship between each shelter-level characteristic and SARS-CoV-2 positivity rates. We also compared the rates across 3 time periods (T1: April 17-April 25; T2: April 26-May 23; T3: May 24-June 25). RESULTS The overall prevalence of SARS-CoV-2 infection was 8.5% (394/4657). Site-specific rates showed great heterogeneity with infection rates ranging from 0% to 70.6%. Compared to T1, positivity rates were 0.21 times lower (95% CI: 0.06-0.75) during T2 and 0.14 times lower (95% CI: 0.04-0.44) during T3. Most cases were detected during outbreak testing (384/394 [97.5%]) rather than active case finding. CONCLUSION During the first wave of the pandemic, rates of SARS-CoV-2 infection at sites for people experiencing homelessness in Toronto varied significantly over time. The observation of lower rates at certain sites may be attributable to overall time trends, expansion of outreach-based testing to include sites without known outbreaks, and/or individual site characteristics.
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Affiliation(s)
- Linh Luong
- MAP Centre for Urban Health Solutions, Li Ka Shing Knowledge Institute, St Michael's Hospital, Unity Health Toronto, 30 Bond Street, Toronto, ON, M5B 1W8, Canada
| | - Michaela Beder
- Department of Psychiatry, University of Toronto, Toronto, ON, Canada
| | - Rosane Nisenbaum
- MAP Centre for Urban Health Solutions, Li Ka Shing Knowledge Institute, St Michael's Hospital, Unity Health Toronto, 30 Bond Street, Toronto, ON, M5B 1W8, Canada.,Division of Biostatistics, Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada
| | - Aaron Orkin
- Department of Family and Community Medicine, University of Toronto, Toronto, ON, Canada
| | | | - Cynthia Damba
- Central Local Health Integration Network, Ontario Health Toronto, Toronto, ON, Canada
| | - Ryan Emond
- Central Local Health Integration Network, Ontario Health Toronto, Toronto, ON, Canada
| | - Suvendrini Lena
- Department of Medicine, Women's College Hospital, Toronto, ON, Canada.,The Centre for Addiction and Mental Health, Toronto, ON, Canada
| | - Vanessa Wright
- Department of Family and Community Medicine, Women's College Hospital, Toronto, ON, Canada
| | - Mona Loutfy
- Women's College Research Institute, Women's College Hospital, University of Toronto & Maple Leaf Medical Clinic, Toronto, ON, Canada
| | | | - Wilfred Cheung
- Central Local Health Integration Network, Ontario Health Toronto, Toronto, ON, Canada
| | - Yick Kan Cheung
- Central Local Health Integration Network, Ontario Health Toronto, Toronto, ON, Canada
| | - Victoria Williams
- Central Local Health Integration Network, Ontario Health Toronto, Toronto, ON, Canada
| | - Miriam Vanmeurs
- Central Local Health Integration Network, Ontario Health Toronto, Toronto, ON, Canada
| | | | | | - Joe Hester
- Anishnawbe Health Toronto, Toronto, ON, Canada
| | - Stephen W Hwang
- MAP Centre for Urban Health Solutions, Li Ka Shing Knowledge Institute, St Michael's Hospital, Unity Health Toronto, 30 Bond Street, Toronto, ON, M5B 1W8, Canada.
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14
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Schultes O, Clarke V, Paltiel AD, Cartter M, Sosa L, Crawford FW. COVID-19 Testing and Case Rates and Social Contact Among Residential College Students in Connecticut During the 2020-2021 Academic Year. JAMA Netw Open 2021; 4:e2140602. [PMID: 34940864 PMCID: PMC8703252 DOI: 10.1001/jamanetworkopen.2021.40602] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/06/2021] [Accepted: 10/30/2021] [Indexed: 01/24/2023] Open
Abstract
Importance During the 2020-2021 academic year, many institutions of higher education reopened to residential students while pursuing strategies to mitigate the risk of SARS-CoV-2 transmission on campus. Reopening guidance emphasized polymerase chain reaction or antigen testing for residential students and social distancing measures to reduce the frequency of close interpersonal contact, and Connecticut colleges and universities used a variety of approaches to reopen campuses to residential students. Objective To characterize institutional reopening strategies and COVID-19 outcomes in 18 residential college and university campuses across Connecticut. Design, Setting, and Participants This retrospective cohort study used data on COVID-19 testing and cases and social contact from 18 college and university campuses in Connecticut that had residential students during the 2020-2021 academic year. Exposures Tests for COVID-19 performed per week per residential student. Main Outcomes and Measures Cases per week per residential student and mean (95% CI) social contact per week per residential student. Results Between 235 and 4603 residential students attended the fall semester across each of 18 institutions of higher education in Connecticut, with fewer residential students at most institutions during the spring semester. In census block groups containing residence halls, the fall student move-in resulted in a 475% (95% CI, 373%-606%) increase in mean contact, and the spring move-in resulted in a 561% (95% CI, 441%-713%) increase in mean contact compared with the 7 weeks prior to move-in. The association between test frequency and case rate per residential student was complex; institutions that tested students infrequently detected few cases but failed to blunt transmission, whereas institutions that tested students more frequently detected more cases and prevented further spread. In fall 2020, each additional test per student per week was associated with a decrease of 0.0014 cases per student per week (95% CI, -0.0028 to -0.00001). Conclusions and Relevance The findings of this cohort study suggest that, in the era of available vaccinations and highly transmissible SARS-CoV-2 variants, colleges and universities should continue to test residential students and use mitigation strategies to control on-campus COVID-19 cases.
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Affiliation(s)
| | | | | | | | - Lynn Sosa
- Connecticut Department of Public Health, Hartford
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15
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Smith TE, Rodgers IT, Silverman DJ, Dreslin SR, Olfson M, Dixon LB, Wall MM. COVID-19 Case Rates After Surveillance and Vaccinations in a Statewide Psychiatric Hospital System. Am J Public Health 2021; 111:1780-1783. [PMID: 34529451 PMCID: PMC8561174 DOI: 10.2105/ajph.2021.306444] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 06/01/2021] [Indexed: 11/04/2022]
Abstract
Individuals with serious mental illness are particularly vulnerable to COVID-19. The New York State (NYS) Office of Mental Health implemented patient and staff rapid testing, quarantining, and vaccination to limit COVID-19 spread in 23 state-operated psychiatric hospitals between November 2020 and February 2021. COVID-19 infection rates in inpatients and staff decreased by 96% and 71%, respectively, and the NYS population case rate decreased by 6%. Repeated COVID-19 testing and vaccination should be priority interventions for state-operated psychiatric hospitals. (Am J Public Health. 2021;111(10):1780-1783. https://doi.org/10.2105/AJPH.2021.306444).
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Affiliation(s)
- Thomas E Smith
- Thomas E. Smith, Ian T. Rodgers, Mark Olfson, Lisa B. Dixon, and Melanie M. Wall are with the New York State Psychiatric Institute, New York, NY. Daniel J. Silverman and Sally R. Dreslin are with the New York State Office of Mental Health, Albany, NY
| | - Ian T Rodgers
- Thomas E. Smith, Ian T. Rodgers, Mark Olfson, Lisa B. Dixon, and Melanie M. Wall are with the New York State Psychiatric Institute, New York, NY. Daniel J. Silverman and Sally R. Dreslin are with the New York State Office of Mental Health, Albany, NY
| | - Daniel J Silverman
- Thomas E. Smith, Ian T. Rodgers, Mark Olfson, Lisa B. Dixon, and Melanie M. Wall are with the New York State Psychiatric Institute, New York, NY. Daniel J. Silverman and Sally R. Dreslin are with the New York State Office of Mental Health, Albany, NY
| | - Sally R Dreslin
- Thomas E. Smith, Ian T. Rodgers, Mark Olfson, Lisa B. Dixon, and Melanie M. Wall are with the New York State Psychiatric Institute, New York, NY. Daniel J. Silverman and Sally R. Dreslin are with the New York State Office of Mental Health, Albany, NY
| | - Mark Olfson
- Thomas E. Smith, Ian T. Rodgers, Mark Olfson, Lisa B. Dixon, and Melanie M. Wall are with the New York State Psychiatric Institute, New York, NY. Daniel J. Silverman and Sally R. Dreslin are with the New York State Office of Mental Health, Albany, NY
| | - Lisa B Dixon
- Thomas E. Smith, Ian T. Rodgers, Mark Olfson, Lisa B. Dixon, and Melanie M. Wall are with the New York State Psychiatric Institute, New York, NY. Daniel J. Silverman and Sally R. Dreslin are with the New York State Office of Mental Health, Albany, NY
| | - Melanie M Wall
- Thomas E. Smith, Ian T. Rodgers, Mark Olfson, Lisa B. Dixon, and Melanie M. Wall are with the New York State Psychiatric Institute, New York, NY. Daniel J. Silverman and Sally R. Dreslin are with the New York State Office of Mental Health, Albany, NY
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16
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Righolt CH, Zhang G, Sever E, Wilkinson K, Mahmud SM. Patterns and descriptors of COVID-19 testing and lab-confirmed COVID-19 incidence in Manitoba, Canada, March 2020-May 2021: A population-based study. ACTA ACUST UNITED AC 2021; 2:100038. [PMID: 34409400 PMCID: PMC8360706 DOI: 10.1016/j.lana.2021.100038] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2021] [Revised: 07/27/2021] [Accepted: 07/27/2021] [Indexed: 11/20/2022]
Abstract
Background We studied lab-confirmed COVID-19 infection (LCCI) testing, incidence, and severity. Methods We included all Manitoba residents and limited our severity analysis to LCCI patients. We calculated testing, incidence and vaccination rates between March 8, 2020 and June 1, 2021. We estimated the association between patient characteristics and testing (rate ratio [RR]; Poisson regression), including the reason for testing (screening, symptomatic, contact/outbreak asymptomatic), incidence (hazard ratio [HR]; Cox regression), and severity (prevalence ratio [PR], Cox regression). Findings The overall testing rate during the second/third wave was 570/1,000 person-years, with an LCCI rate of 50/1,000 person-years. The secondary attack rate during the second/third wave was 16%. Across regions, young children (<10) had the lowest positivity for symptomatic testing, the highest positivity for asymptomatic testing, and the highest risk of LCCI as asymptomatic contact. People in the lowest income quintile had the highest risk of LCCI, 1.3-6x the hazard of those in the highest income quintile. Long-term care (LTC) residents were particularly affected in the second wave with HRs>10 for asymptomatic residents. Interpretation Although the severity of LCCI in children was low, they have a high risk of asymptomatic positivity. The groups most vulnerable to LCCI, who should remain a focus of public health, were residents of Manitoba's North, LTC facilities, and low-income neighbourhoods. Funding Canada Research Chair Program
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Affiliation(s)
| | | | | | | | - Salaheddin M. Mahmud
- Correspondence Author: Dr. Salaheddin Mahmud, MD PhD FRCPC, Professor and Director, Vaccine and Drug Evaluation Centre, Department of Community Health Sciences, University of Manitoba, 337 - 750 McDermot Avenue, Winnipeg, Manitoba, R3E 0T5 Canada
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17
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Sundaram ME, Calzavara A, Mishra S, Kustra R, Chan AK, Hamilton MA, Djebli M, Rosella LC, Watson T, Chen H, Chen B, Baral SD, Kwong JC. Déterminants individuels et sociaux du test de dépistage du SRAS-CoV-2 et de l’obtention d’un résultat positif en Ontario, au Canada: une étude populationnelle. CMAJ 2021; 193:E1261-E1276. [PMID: 34400488 PMCID: PMC8386493 DOI: 10.1503/cmaj.202608-f] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 04/06/2021] [Indexed: 11/08/2022] Open
Abstract
Contexte: Optimiser la réponse de la santé publique pour diminuer le fardeau de la COVID-19 nécessite la caractérisation de l’hétérogénéité du risque posé par la maladie à l’échelle de la population. Cependant, l’hétérogénéité du dépistage du SRAS-CoV-2 peut fausser les estimations selon le modèle d’étude analytique utilisé. Notre objectif était d’explorer les biais collisionneurs dans le cadre d’une vaste étude portant sur les déterminants de la maladie et d’évaluer les déterminants individuels, environnementaux et sociaux du dépistage et du diagnostic du SRAS-CoV-2 parmi les résidents de l’Ontario, au Canada. Méthodes: Nous avons exploré la présence potentielle de biais collisionneurs et caractérisé les déterminants individuels, environnementaux et sociaux de l’obtention d’un test de dépistage et d’un résultat positif à la présence de l’infection au SRAS-CoV-2 à l’aide d’analyses transversales parmi les 14,7 millions de personnes vivant dans la collectivité en Ontario, au Canada. Parmi les personnes ayant obtenu un diagnostic, nous avons utilisé des études analytiques distinctes afin de comparer les prédicteurs pour les personnes d’obtenir un résultat de test de dépistage positif plutôt que négatif, pour les personnes symptomatiques d’obtenir un résultat de test de dépistage positif plutôt que négatif et pour les personnes d’obtenir un résultat de test de dépistage positif plutôt que de ne pas obtenir un résultat positif (c.-à-d., obtenir un résultat de test de dépistage négatif ou ne pas obtenir de test de dépistage). Nos analyses comprennent des tests de dépistage réalisés entre le 1er mars et le 20 juin 2020. Résultats: Sur 14 695 579 personnes, nous avons constaté que 758 691 d’entre elles ont passé un test de dépistage du SRAS-CoV-2, parmi lesquelles 25 030 (3,3 %) ont obtenu un résultat positif. Plus la probabilité d’obtenir un test de dépistage s’éloignait de zéro, plus la variabilité généralement observée dans la probabilité d’un diagnostic était grande parmi les modèles d’études analytiques, particulièrement en ce qui a trait aux facteurs individuels. Nous avons constaté que la variabilité dans l’obtention d’un test de dépistage était moins importante en fonction des déterminants sociaux dans l’ensemble des études analytiques. Les facteurs tels que le fait d’habiter dans une région ayant une plus haute densité des ménages (rapport de cotes corrigé 1,86; intervalle de confiance [IC] à 95 % 1,75–1,98), une plus grande proportion de travailleurs essentiels (rapport de cotes corrigé 1,58; IC à 95 % 1,48–1,69), une population atteignant un plus faible niveau de scolarité (rapport de cotes corrigé 1,33; IC à 95 % 1,26–1,41) et une plus grande proportion d’immigrants récents (rapport de cotes corrigé 1,10; IC à 95 % 1,05–1,15), étaient systématiquement corrélés à une probabilité plus importante d’obtenir un diagnostic de SRAS-CoV-2, peu importe le modèle d’étude analytique employé. Interprétation: Lorsque la capacité de dépister est limitée, nos résultats suggèrent que les facteurs de risque peuvent être estimés plus adéquatement en utilisant des comparateurs populationnels plutôt que des comparateurs de résultat négatif au test de dépistage. Optimiser la lutte contre la COVID-19 nécessite des investissements dans des interventions structurelles déployées de façon suffisante et adaptées à l’hétérogénéité des déterminants sociaux du risque, dont le surpeuplement des ménages, l’occupation professionnelle et le racisme structurel.
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Affiliation(s)
- Maria E Sundaram
- ICES Central (Sundaram, Calzavara, Hamilton, Djebli, Rosella, Watson, H. Chen, B. Chen, Kwong); Département de médecine (Mishra, Chan); Institut de gestion, d'évaluation et de politiques de santé (Mishra, Chan); Institut des sciences médicales (Mishra); École de santé publique Dalla Lana (Kustra, Chan, Hamilton, Djebli, Rosella, Watson, H. Chen, Kwong); Département des sciences statistiques (Kustra); Département de médecine familiale et communautaire (Kwong), Université de Toronto; MAP Centre for Urban Health Solutions (Mishra), Institut du savoir Li Ka Shing, Hôpital St. Michael, Unity Health Toronto; Centre des sciences de la santé Sunnybrook (Chan); Santé publique Ontario (Kwong, H. Chen); Toronto, Ont.; Département d'épidémiologie (Baral), École de santé publique Bloomberg de l'Université Johns Hopkins, Baltimore, Md
| | - Andrew Calzavara
- ICES Central (Sundaram, Calzavara, Hamilton, Djebli, Rosella, Watson, H. Chen, B. Chen, Kwong); Département de médecine (Mishra, Chan); Institut de gestion, d'évaluation et de politiques de santé (Mishra, Chan); Institut des sciences médicales (Mishra); École de santé publique Dalla Lana (Kustra, Chan, Hamilton, Djebli, Rosella, Watson, H. Chen, Kwong); Département des sciences statistiques (Kustra); Département de médecine familiale et communautaire (Kwong), Université de Toronto; MAP Centre for Urban Health Solutions (Mishra), Institut du savoir Li Ka Shing, Hôpital St. Michael, Unity Health Toronto; Centre des sciences de la santé Sunnybrook (Chan); Santé publique Ontario (Kwong, H. Chen); Toronto, Ont.; Département d'épidémiologie (Baral), École de santé publique Bloomberg de l'Université Johns Hopkins, Baltimore, Md
| | - Sharmistha Mishra
- ICES Central (Sundaram, Calzavara, Hamilton, Djebli, Rosella, Watson, H. Chen, B. Chen, Kwong); Département de médecine (Mishra, Chan); Institut de gestion, d'évaluation et de politiques de santé (Mishra, Chan); Institut des sciences médicales (Mishra); École de santé publique Dalla Lana (Kustra, Chan, Hamilton, Djebli, Rosella, Watson, H. Chen, Kwong); Département des sciences statistiques (Kustra); Département de médecine familiale et communautaire (Kwong), Université de Toronto; MAP Centre for Urban Health Solutions (Mishra), Institut du savoir Li Ka Shing, Hôpital St. Michael, Unity Health Toronto; Centre des sciences de la santé Sunnybrook (Chan); Santé publique Ontario (Kwong, H. Chen); Toronto, Ont.; Département d'épidémiologie (Baral), École de santé publique Bloomberg de l'Université Johns Hopkins, Baltimore, Md
| | - Rafal Kustra
- ICES Central (Sundaram, Calzavara, Hamilton, Djebli, Rosella, Watson, H. Chen, B. Chen, Kwong); Département de médecine (Mishra, Chan); Institut de gestion, d'évaluation et de politiques de santé (Mishra, Chan); Institut des sciences médicales (Mishra); École de santé publique Dalla Lana (Kustra, Chan, Hamilton, Djebli, Rosella, Watson, H. Chen, Kwong); Département des sciences statistiques (Kustra); Département de médecine familiale et communautaire (Kwong), Université de Toronto; MAP Centre for Urban Health Solutions (Mishra), Institut du savoir Li Ka Shing, Hôpital St. Michael, Unity Health Toronto; Centre des sciences de la santé Sunnybrook (Chan); Santé publique Ontario (Kwong, H. Chen); Toronto, Ont.; Département d'épidémiologie (Baral), École de santé publique Bloomberg de l'Université Johns Hopkins, Baltimore, Md
| | - Adrienne K Chan
- ICES Central (Sundaram, Calzavara, Hamilton, Djebli, Rosella, Watson, H. Chen, B. Chen, Kwong); Département de médecine (Mishra, Chan); Institut de gestion, d'évaluation et de politiques de santé (Mishra, Chan); Institut des sciences médicales (Mishra); École de santé publique Dalla Lana (Kustra, Chan, Hamilton, Djebli, Rosella, Watson, H. Chen, Kwong); Département des sciences statistiques (Kustra); Département de médecine familiale et communautaire (Kwong), Université de Toronto; MAP Centre for Urban Health Solutions (Mishra), Institut du savoir Li Ka Shing, Hôpital St. Michael, Unity Health Toronto; Centre des sciences de la santé Sunnybrook (Chan); Santé publique Ontario (Kwong, H. Chen); Toronto, Ont.; Département d'épidémiologie (Baral), École de santé publique Bloomberg de l'Université Johns Hopkins, Baltimore, Md
| | - Mackenzie A Hamilton
- ICES Central (Sundaram, Calzavara, Hamilton, Djebli, Rosella, Watson, H. Chen, B. Chen, Kwong); Département de médecine (Mishra, Chan); Institut de gestion, d'évaluation et de politiques de santé (Mishra, Chan); Institut des sciences médicales (Mishra); École de santé publique Dalla Lana (Kustra, Chan, Hamilton, Djebli, Rosella, Watson, H. Chen, Kwong); Département des sciences statistiques (Kustra); Département de médecine familiale et communautaire (Kwong), Université de Toronto; MAP Centre for Urban Health Solutions (Mishra), Institut du savoir Li Ka Shing, Hôpital St. Michael, Unity Health Toronto; Centre des sciences de la santé Sunnybrook (Chan); Santé publique Ontario (Kwong, H. Chen); Toronto, Ont.; Département d'épidémiologie (Baral), École de santé publique Bloomberg de l'Université Johns Hopkins, Baltimore, Md
| | - Mohamed Djebli
- ICES Central (Sundaram, Calzavara, Hamilton, Djebli, Rosella, Watson, H. Chen, B. Chen, Kwong); Département de médecine (Mishra, Chan); Institut de gestion, d'évaluation et de politiques de santé (Mishra, Chan); Institut des sciences médicales (Mishra); École de santé publique Dalla Lana (Kustra, Chan, Hamilton, Djebli, Rosella, Watson, H. Chen, Kwong); Département des sciences statistiques (Kustra); Département de médecine familiale et communautaire (Kwong), Université de Toronto; MAP Centre for Urban Health Solutions (Mishra), Institut du savoir Li Ka Shing, Hôpital St. Michael, Unity Health Toronto; Centre des sciences de la santé Sunnybrook (Chan); Santé publique Ontario (Kwong, H. Chen); Toronto, Ont.; Département d'épidémiologie (Baral), École de santé publique Bloomberg de l'Université Johns Hopkins, Baltimore, Md
| | - Laura C Rosella
- ICES Central (Sundaram, Calzavara, Hamilton, Djebli, Rosella, Watson, H. Chen, B. Chen, Kwong); Département de médecine (Mishra, Chan); Institut de gestion, d'évaluation et de politiques de santé (Mishra, Chan); Institut des sciences médicales (Mishra); École de santé publique Dalla Lana (Kustra, Chan, Hamilton, Djebli, Rosella, Watson, H. Chen, Kwong); Département des sciences statistiques (Kustra); Département de médecine familiale et communautaire (Kwong), Université de Toronto; MAP Centre for Urban Health Solutions (Mishra), Institut du savoir Li Ka Shing, Hôpital St. Michael, Unity Health Toronto; Centre des sciences de la santé Sunnybrook (Chan); Santé publique Ontario (Kwong, H. Chen); Toronto, Ont.; Département d'épidémiologie (Baral), École de santé publique Bloomberg de l'Université Johns Hopkins, Baltimore, Md
| | - Tristan Watson
- ICES Central (Sundaram, Calzavara, Hamilton, Djebli, Rosella, Watson, H. Chen, B. Chen, Kwong); Département de médecine (Mishra, Chan); Institut de gestion, d'évaluation et de politiques de santé (Mishra, Chan); Institut des sciences médicales (Mishra); École de santé publique Dalla Lana (Kustra, Chan, Hamilton, Djebli, Rosella, Watson, H. Chen, Kwong); Département des sciences statistiques (Kustra); Département de médecine familiale et communautaire (Kwong), Université de Toronto; MAP Centre for Urban Health Solutions (Mishra), Institut du savoir Li Ka Shing, Hôpital St. Michael, Unity Health Toronto; Centre des sciences de la santé Sunnybrook (Chan); Santé publique Ontario (Kwong, H. Chen); Toronto, Ont.; Département d'épidémiologie (Baral), École de santé publique Bloomberg de l'Université Johns Hopkins, Baltimore, Md
| | - Hong Chen
- ICES Central (Sundaram, Calzavara, Hamilton, Djebli, Rosella, Watson, H. Chen, B. Chen, Kwong); Département de médecine (Mishra, Chan); Institut de gestion, d'évaluation et de politiques de santé (Mishra, Chan); Institut des sciences médicales (Mishra); École de santé publique Dalla Lana (Kustra, Chan, Hamilton, Djebli, Rosella, Watson, H. Chen, Kwong); Département des sciences statistiques (Kustra); Département de médecine familiale et communautaire (Kwong), Université de Toronto; MAP Centre for Urban Health Solutions (Mishra), Institut du savoir Li Ka Shing, Hôpital St. Michael, Unity Health Toronto; Centre des sciences de la santé Sunnybrook (Chan); Santé publique Ontario (Kwong, H. Chen); Toronto, Ont.; Département d'épidémiologie (Baral), École de santé publique Bloomberg de l'Université Johns Hopkins, Baltimore, Md
| | - Branson Chen
- ICES Central (Sundaram, Calzavara, Hamilton, Djebli, Rosella, Watson, H. Chen, B. Chen, Kwong); Département de médecine (Mishra, Chan); Institut de gestion, d'évaluation et de politiques de santé (Mishra, Chan); Institut des sciences médicales (Mishra); École de santé publique Dalla Lana (Kustra, Chan, Hamilton, Djebli, Rosella, Watson, H. Chen, Kwong); Département des sciences statistiques (Kustra); Département de médecine familiale et communautaire (Kwong), Université de Toronto; MAP Centre for Urban Health Solutions (Mishra), Institut du savoir Li Ka Shing, Hôpital St. Michael, Unity Health Toronto; Centre des sciences de la santé Sunnybrook (Chan); Santé publique Ontario (Kwong, H. Chen); Toronto, Ont.; Département d'épidémiologie (Baral), École de santé publique Bloomberg de l'Université Johns Hopkins, Baltimore, Md
| | - Stefan D Baral
- ICES Central (Sundaram, Calzavara, Hamilton, Djebli, Rosella, Watson, H. Chen, B. Chen, Kwong); Département de médecine (Mishra, Chan); Institut de gestion, d'évaluation et de politiques de santé (Mishra, Chan); Institut des sciences médicales (Mishra); École de santé publique Dalla Lana (Kustra, Chan, Hamilton, Djebli, Rosella, Watson, H. Chen, Kwong); Département des sciences statistiques (Kustra); Département de médecine familiale et communautaire (Kwong), Université de Toronto; MAP Centre for Urban Health Solutions (Mishra), Institut du savoir Li Ka Shing, Hôpital St. Michael, Unity Health Toronto; Centre des sciences de la santé Sunnybrook (Chan); Santé publique Ontario (Kwong, H. Chen); Toronto, Ont.; Département d'épidémiologie (Baral), École de santé publique Bloomberg de l'Université Johns Hopkins, Baltimore, Md
| | - Jeffrey C Kwong
- ICES Central (Sundaram, Calzavara, Hamilton, Djebli, Rosella, Watson, H. Chen, B. Chen, Kwong); Département de médecine (Mishra, Chan); Institut de gestion, d'évaluation et de politiques de santé (Mishra, Chan); Institut des sciences médicales (Mishra); École de santé publique Dalla Lana (Kustra, Chan, Hamilton, Djebli, Rosella, Watson, H. Chen, Kwong); Département des sciences statistiques (Kustra); Département de médecine familiale et communautaire (Kwong), Université de Toronto; MAP Centre for Urban Health Solutions (Mishra), Institut du savoir Li Ka Shing, Hôpital St. Michael, Unity Health Toronto; Centre des sciences de la santé Sunnybrook (Chan); Santé publique Ontario (Kwong, H. Chen); Toronto, Ont.; Département d'épidémiologie (Baral), École de santé publique Bloomberg de l'Université Johns Hopkins, Baltimore, Md.
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Mohsenpour A, Bozorgmehr K, Rohleder S, Stratil J, Costa D. SARS-Cov-2 prevalence, transmission, health-related outcomes and control strategies in homeless shelters: Systematic review and meta-analysis. EClinicalMedicine 2021; 38:101032. [PMID: 34316550 PMCID: PMC8298932 DOI: 10.1016/j.eclinm.2021.101032] [Citation(s) in RCA: 37] [Impact Index Per Article: 12.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/08/2021] [Revised: 07/02/2021] [Accepted: 07/02/2021] [Indexed: 01/07/2023] Open
Abstract
BACKGROUND People experiencing homelessness (PEH) may be at risk for COVID19. We synthesised evidence on SARS-Cov-2 infection, transmission, outcomes of disease, effects of non-pharmaceutical interventions (NPI), and the effectiveness of strategies for infection prevention and control (IPC). METHODS Systematic review of articles, indexed in electronic databases (EMBASE, WHO-Covid19, Web of Science), institutional websites and the Norwegian Institute of Public Health's live map of COVID-19 evidence, and published from December 1st, 2019, to March 3rd, 2021. Empirical papers of any study design addressing Covid-19 and health(-related) outcomes in PEH or shelters' staff were included. (PROSPERO-2020-CRD42020187033). FINDINGS Of 536 publications, 37 studies were included (two modelling, 31 observational, four qualitative studies). Random-effect meta-analysis yields a baseline SARS-Cov-2 prevalence of 2•32% (95% Confidence-Interval, 95%CI=1•30-3•34) in PEH and 1•55% (95%CI=0•79-2•31) in staff. In outbreaks, the pooled prevalence increases to 31•59% (95%CI=20•48-42•71) in PEH and 14•80% (95%CI=10•73-18•87) in staff. Main IPC strategies were universal rapid testing, expansion of non-congregate housing, and in-shelter measures (bed spacing, limited staff rotation, reduction in number of residents). INTERPRETATION 32% of PEH and 15% staff are infected during outbreaks of SARS-Cov-2 in homeless shelters. Most studies were conducted in the USA. No studies were found quantifying health-related outcomes of NPI. Overview and evaluation of IPC strategies for PEH, a better understanding of disease transmission, and reliable data on PEH within Covid-19 notification systems are needed. Qualitative studies may serve to voice PEH and shelter staff experiences, and guide future evaluations and IPC strategies. FUNDING None.
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Affiliation(s)
- Amir Mohsenpour
- Department of Population Medicine and Health Services Research, School of Public Health, Bielefeld University, P.O. Box: 10 01 31, 33501 Bielefeld, Germany
- Section for Health Equity Studies and Migration, Department of General Practice and Health Services Research, Heidelberg University Hospital, Germany
- Corresponding author at: Department of Population Medicine and Health Services Research, School of Public Health, Bielefeld University, P.O. Box: 10 01 31, 33501 Bielefeld, Germany.
| | - Kayvan Bozorgmehr
- Department of Population Medicine and Health Services Research, School of Public Health, Bielefeld University, P.O. Box: 10 01 31, 33501 Bielefeld, Germany
- Section for Health Equity Studies and Migration, Department of General Practice and Health Services Research, Heidelberg University Hospital, Germany
| | - Sven Rohleder
- Department of Population Medicine and Health Services Research, School of Public Health, Bielefeld University, P.O. Box: 10 01 31, 33501 Bielefeld, Germany
- Section for Health Equity Studies and Migration, Department of General Practice and Health Services Research, Heidelberg University Hospital, Germany
| | - Jan Stratil
- Institute for Medical Informatics, Biometry and Epidemiology, Ludwig-Maximilians-University Munich, Germany
| | - Diogo Costa
- Department of Population Medicine and Health Services Research, School of Public Health, Bielefeld University, P.O. Box: 10 01 31, 33501 Bielefeld, Germany
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Mishra S, Ma H, Moloney G, Yiu KC, Darvin D, Landsman D, Kwong JC, Calzavara A, Straus S, Chan AK, Gournis E, Rilkoff H, Xia Y, Katz A, Williamson T, Malikov K, Kustra R, Maheu-Giroux M, Sander B, Baral SD. Increasing concentration of COVID-19 by socioeconomic determinants and geography in Toronto, Canada: an observational study. Ann Epidemiol 2021; 65:84-92. [PMID: 34320380 PMCID: PMC8730782 DOI: 10.1016/j.annepidem.2021.07.007] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2021] [Revised: 07/15/2021] [Accepted: 07/18/2021] [Indexed: 12/31/2022]
Abstract
BACKGROUND Inequities in the burden of COVID-19 were observed early in Canada and around the world suggesting economically marginalized communities faced disproportionate risks. However, there has been limited systematic assessment of how heterogeneity in risks has evolved in large urban centers over time. PURPOSE To address this gap, we quantified the magnitude of risk heterogeneity in Toronto, Ontario from January-November, 2020 using a retrospective, population-based observational study using surveillance data. METHODS We generated epidemic curves by social determinants of health (SDOH) and crude Lorenz curves by neighbourhoods to visualize inequities in the distribution of COVID-19 and estimated Gini coefficients. We examined the correlation between SDOH using Pearson-correlation coefficients. RESULTS Gini coefficient of cumulative cases by population size was 0.41 (95% confidence interval [CI]:0.36-0.47) and 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). CONCLUSIONS There was rapid epidemiologic transition from higher to lower income neighbourhoods with Lorenz curve transitioning from below to above the line of equality across SDOH. Moving forward necessitates integrating programs and policies addressing socioeconomic inequities and structural racism into COVID-19 prevention and vaccination programs.
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Affiliation(s)
- Sharmistha Mishra
- St. Michael's Hospital, Unity Health Toronto, Toronto, Canada; Division of Infectious Diseases, Department of Medicine, University of Toronto, Toronto, Canada.
| | - Huiting Ma
- St. Michael's Hospital, Unity Health Toronto, Toronto, Canada.
| | - Gary Moloney
- St. Michael's Hospital, Unity Health Toronto, Toronto, Canada.
| | - Kristy Cy Yiu
- St. Michael's Hospital, Unity Health Toronto, Toronto, Canada.
| | - Dariya Darvin
- St. Michael's Hospital, Unity Health Toronto, Toronto, Canada.
| | - David Landsman
- St. Michael's Hospital, Unity Health Toronto, Toronto, Canada.
| | - Jeffrey C Kwong
- ICES, Toronto, Canada; Public Health Ontario, Toronto, Canada; Department of Family and Community Medicine, Faculty of Medicine, University of Toronto, Toronto, Canada; Dalla Lana School of Public Health, University of Toronto, Toronto, Canada.
| | | | - Sharon Straus
- Department of Medicine, St. Michael's Hospital, University of Toronto, Toronto, Canada.
| | - Adrienne K Chan
- Division of Infectious Diseases, Department of Medicine, University of Toronto, Toronto, Canada; Dalla Lana School of Public Health, University of Toronto, Toronto, Canada; Division of Infectious Diseases, Sunnybrook Health Sciences, University of Toronto, Toronto, Canada; Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, Canada.
| | - Effie Gournis
- Dalla Lana School of Public Health, University of Toronto, Toronto, Canada; Toronto Public Health, City of Toronto, Toronto, Canada.
| | | | - Yiqing Xia
- St. Michael's Hospital, Unity Health Toronto, Toronto, Canada; Department of Epidemiology, Biostatistics and Occupational Health, School of Population and Global Health, McGill University, Montréal, Canada.
| | - Alan Katz
- Departments of Community Health Sciences and Family Medicine, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, Canada.
| | - Tyler Williamson
- Department of Community Health Sciences, University of Calgary, Calgary, Canada; Centre for Health Informatics, University of Calgary, Calgary, Canada.
| | - Kamil Malikov
- Capacity Planning and Analytics Division, Ontario Ministry of Health, Toronto, Canada.
| | - Rafal Kustra
- Dalla Lana School of Public Health, University of Toronto, Toronto, Canada.
| | - Mathieu Maheu-Giroux
- Department of Epidemiology, Biostatistics and Occupational Health, School of Population and Global Health, McGill University, Montréal, Canada.
| | - Beate Sander
- ICES, Toronto, Canada; Public Health Ontario, Toronto, Canada; Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, Canada.
| | - Stefan D Baral
- Department of Epidemiology, Johns Hopkins School of Public Health, Baltimore, United States.
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- St. Michael's Hospital, Unity Health Toronto, Toronto, Canada; Division of Infectious Diseases, Department of Medicine, University of Toronto, Toronto, Canada; ICES, Toronto, Canada; Public Health Ontario, Toronto, Canada; Department of Family and Community Medicine, Faculty of Medicine, University of Toronto, Toronto, Canada; Dalla Lana School of Public Health, University of Toronto, Toronto, Canada; Department of Medicine, St. Michael's Hospital, University of Toronto, Toronto, Canada; Division of Infectious Diseases, Sunnybrook Health Sciences, University of Toronto, Toronto, Canada; Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, Canada; Toronto Public Health, City of Toronto, Toronto, Canada; Department of Epidemiology, Biostatistics and Occupational Health, School of Population and Global Health, McGill University, Montréal, Canada; Departments of Community Health Sciences and Family Medicine, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, Canada; Department of Community Health Sciences, University of Calgary, Calgary, Canada; Centre for Health Informatics, University of Calgary, Calgary, Canada; Capacity Planning and Analytics Division, Ontario Ministry of Health, Toronto, Canada; Department of Epidemiology, Johns Hopkins School of Public Health, Baltimore, United States
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Sundaram ME, Calzavara A, Mishra S, Kustra R, Chan AK, Hamilton MA, Djebli M, Rosella LC, Watson T, Chen H, Chen B, Baral SD, Kwong JC. Individual and social determinants of SARS-CoV-2 testing and positivity in Ontario, Canada: a population-wide study. CMAJ 2021; 193:E723-E734. [PMID: 33906966 PMCID: PMC8177943 DOI: 10.1503/cmaj.202608] [Citation(s) in RCA: 53] [Impact Index Per Article: 17.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 04/06/2021] [Indexed: 12/16/2022] Open
Abstract
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.
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Affiliation(s)
- Maria E Sundaram
- ICES Central (Sundaram, Calzavara, Hamilton, Djebli, Rosella, Watson, H. Chen, B. Chen, Kwong); Department of Medicine (Mishra, Chan); Institute of Health Policy, Management and Evaluation (Mishra, Chan); Institute of Medical Science (Mishra); Dalla Lana School of Public Health (Kustra, Chan, Hamilton, Djebli, Rosella, Watson, H. Chen, Kwong); Department of Statistical Sciences (Kustra); and Department of Family and Community Medicine (Kwong), University of Toronto; MAP Centre for Urban Health Solutions (Mishra), Li Ka Shing Knowledge Institute, St. Michael's Hospital, Unity Health Toronto; Sunnybrook Health Sciences Centre (Chan); Public Health Ontario (Kwong, H. Chen); University Health Network (Kwong), Toronto, Ont.; Department of Epidemiology (Baral), Johns Hopkins Bloomberg School of Public Health, Baltimore, Md
| | - Andrew Calzavara
- ICES Central (Sundaram, Calzavara, Hamilton, Djebli, Rosella, Watson, H. Chen, B. Chen, Kwong); Department of Medicine (Mishra, Chan); Institute of Health Policy, Management and Evaluation (Mishra, Chan); Institute of Medical Science (Mishra); Dalla Lana School of Public Health (Kustra, Chan, Hamilton, Djebli, Rosella, Watson, H. Chen, Kwong); Department of Statistical Sciences (Kustra); and Department of Family and Community Medicine (Kwong), University of Toronto; MAP Centre for Urban Health Solutions (Mishra), Li Ka Shing Knowledge Institute, St. Michael's Hospital, Unity Health Toronto; Sunnybrook Health Sciences Centre (Chan); Public Health Ontario (Kwong, H. Chen); University Health Network (Kwong), Toronto, Ont.; Department of Epidemiology (Baral), Johns Hopkins Bloomberg School of Public Health, Baltimore, Md
| | - Sharmistha Mishra
- ICES Central (Sundaram, Calzavara, Hamilton, Djebli, Rosella, Watson, H. Chen, B. Chen, Kwong); Department of Medicine (Mishra, Chan); Institute of Health Policy, Management and Evaluation (Mishra, Chan); Institute of Medical Science (Mishra); Dalla Lana School of Public Health (Kustra, Chan, Hamilton, Djebli, Rosella, Watson, H. Chen, Kwong); Department of Statistical Sciences (Kustra); and Department of Family and Community Medicine (Kwong), University of Toronto; MAP Centre for Urban Health Solutions (Mishra), Li Ka Shing Knowledge Institute, St. Michael's Hospital, Unity Health Toronto; Sunnybrook Health Sciences Centre (Chan); Public Health Ontario (Kwong, H. Chen); University Health Network (Kwong), Toronto, Ont.; Department of Epidemiology (Baral), Johns Hopkins Bloomberg School of Public Health, Baltimore, Md
| | - Rafal Kustra
- ICES Central (Sundaram, Calzavara, Hamilton, Djebli, Rosella, Watson, H. Chen, B. Chen, Kwong); Department of Medicine (Mishra, Chan); Institute of Health Policy, Management and Evaluation (Mishra, Chan); Institute of Medical Science (Mishra); Dalla Lana School of Public Health (Kustra, Chan, Hamilton, Djebli, Rosella, Watson, H. Chen, Kwong); Department of Statistical Sciences (Kustra); and Department of Family and Community Medicine (Kwong), University of Toronto; MAP Centre for Urban Health Solutions (Mishra), Li Ka Shing Knowledge Institute, St. Michael's Hospital, Unity Health Toronto; Sunnybrook Health Sciences Centre (Chan); Public Health Ontario (Kwong, H. Chen); University Health Network (Kwong), Toronto, Ont.; Department of Epidemiology (Baral), Johns Hopkins Bloomberg School of Public Health, Baltimore, Md
| | - Adrienne K Chan
- ICES Central (Sundaram, Calzavara, Hamilton, Djebli, Rosella, Watson, H. Chen, B. Chen, Kwong); Department of Medicine (Mishra, Chan); Institute of Health Policy, Management and Evaluation (Mishra, Chan); Institute of Medical Science (Mishra); Dalla Lana School of Public Health (Kustra, Chan, Hamilton, Djebli, Rosella, Watson, H. Chen, Kwong); Department of Statistical Sciences (Kustra); and Department of Family and Community Medicine (Kwong), University of Toronto; MAP Centre for Urban Health Solutions (Mishra), Li Ka Shing Knowledge Institute, St. Michael's Hospital, Unity Health Toronto; Sunnybrook Health Sciences Centre (Chan); Public Health Ontario (Kwong, H. Chen); University Health Network (Kwong), Toronto, Ont.; Department of Epidemiology (Baral), Johns Hopkins Bloomberg School of Public Health, Baltimore, Md
| | - Mackenzie A Hamilton
- ICES Central (Sundaram, Calzavara, Hamilton, Djebli, Rosella, Watson, H. Chen, B. Chen, Kwong); Department of Medicine (Mishra, Chan); Institute of Health Policy, Management and Evaluation (Mishra, Chan); Institute of Medical Science (Mishra); Dalla Lana School of Public Health (Kustra, Chan, Hamilton, Djebli, Rosella, Watson, H. Chen, Kwong); Department of Statistical Sciences (Kustra); and Department of Family and Community Medicine (Kwong), University of Toronto; MAP Centre for Urban Health Solutions (Mishra), Li Ka Shing Knowledge Institute, St. Michael's Hospital, Unity Health Toronto; Sunnybrook Health Sciences Centre (Chan); Public Health Ontario (Kwong, H. Chen); University Health Network (Kwong), Toronto, Ont.; Department of Epidemiology (Baral), Johns Hopkins Bloomberg School of Public Health, Baltimore, Md
| | - Mohamed Djebli
- ICES Central (Sundaram, Calzavara, Hamilton, Djebli, Rosella, Watson, H. Chen, B. Chen, Kwong); Department of Medicine (Mishra, Chan); Institute of Health Policy, Management and Evaluation (Mishra, Chan); Institute of Medical Science (Mishra); Dalla Lana School of Public Health (Kustra, Chan, Hamilton, Djebli, Rosella, Watson, H. Chen, Kwong); Department of Statistical Sciences (Kustra); and Department of Family and Community Medicine (Kwong), University of Toronto; MAP Centre for Urban Health Solutions (Mishra), Li Ka Shing Knowledge Institute, St. Michael's Hospital, Unity Health Toronto; Sunnybrook Health Sciences Centre (Chan); Public Health Ontario (Kwong, H. Chen); University Health Network (Kwong), Toronto, Ont.; Department of Epidemiology (Baral), Johns Hopkins Bloomberg School of Public Health, Baltimore, Md
| | - Laura C Rosella
- ICES Central (Sundaram, Calzavara, Hamilton, Djebli, Rosella, Watson, H. Chen, B. Chen, Kwong); Department of Medicine (Mishra, Chan); Institute of Health Policy, Management and Evaluation (Mishra, Chan); Institute of Medical Science (Mishra); Dalla Lana School of Public Health (Kustra, Chan, Hamilton, Djebli, Rosella, Watson, H. Chen, Kwong); Department of Statistical Sciences (Kustra); and Department of Family and Community Medicine (Kwong), University of Toronto; MAP Centre for Urban Health Solutions (Mishra), Li Ka Shing Knowledge Institute, St. Michael's Hospital, Unity Health Toronto; Sunnybrook Health Sciences Centre (Chan); Public Health Ontario (Kwong, H. Chen); University Health Network (Kwong), Toronto, Ont.; Department of Epidemiology (Baral), Johns Hopkins Bloomberg School of Public Health, Baltimore, Md
| | - Tristan Watson
- ICES Central (Sundaram, Calzavara, Hamilton, Djebli, Rosella, Watson, H. Chen, B. Chen, Kwong); Department of Medicine (Mishra, Chan); Institute of Health Policy, Management and Evaluation (Mishra, Chan); Institute of Medical Science (Mishra); Dalla Lana School of Public Health (Kustra, Chan, Hamilton, Djebli, Rosella, Watson, H. Chen, Kwong); Department of Statistical Sciences (Kustra); and Department of Family and Community Medicine (Kwong), University of Toronto; MAP Centre for Urban Health Solutions (Mishra), Li Ka Shing Knowledge Institute, St. Michael's Hospital, Unity Health Toronto; Sunnybrook Health Sciences Centre (Chan); Public Health Ontario (Kwong, H. Chen); University Health Network (Kwong), Toronto, Ont.; Department of Epidemiology (Baral), Johns Hopkins Bloomberg School of Public Health, Baltimore, Md
| | - Hong Chen
- ICES Central (Sundaram, Calzavara, Hamilton, Djebli, Rosella, Watson, H. Chen, B. Chen, Kwong); Department of Medicine (Mishra, Chan); Institute of Health Policy, Management and Evaluation (Mishra, Chan); Institute of Medical Science (Mishra); Dalla Lana School of Public Health (Kustra, Chan, Hamilton, Djebli, Rosella, Watson, H. Chen, Kwong); Department of Statistical Sciences (Kustra); and Department of Family and Community Medicine (Kwong), University of Toronto; MAP Centre for Urban Health Solutions (Mishra), Li Ka Shing Knowledge Institute, St. Michael's Hospital, Unity Health Toronto; Sunnybrook Health Sciences Centre (Chan); Public Health Ontario (Kwong, H. Chen); University Health Network (Kwong), Toronto, Ont.; Department of Epidemiology (Baral), Johns Hopkins Bloomberg School of Public Health, Baltimore, Md
| | - Branson Chen
- ICES Central (Sundaram, Calzavara, Hamilton, Djebli, Rosella, Watson, H. Chen, B. Chen, Kwong); Department of Medicine (Mishra, Chan); Institute of Health Policy, Management and Evaluation (Mishra, Chan); Institute of Medical Science (Mishra); Dalla Lana School of Public Health (Kustra, Chan, Hamilton, Djebli, Rosella, Watson, H. Chen, Kwong); Department of Statistical Sciences (Kustra); and Department of Family and Community Medicine (Kwong), University of Toronto; MAP Centre for Urban Health Solutions (Mishra), Li Ka Shing Knowledge Institute, St. Michael's Hospital, Unity Health Toronto; Sunnybrook Health Sciences Centre (Chan); Public Health Ontario (Kwong, H. Chen); University Health Network (Kwong), Toronto, Ont.; Department of Epidemiology (Baral), Johns Hopkins Bloomberg School of Public Health, Baltimore, Md
| | - Stefan D Baral
- ICES Central (Sundaram, Calzavara, Hamilton, Djebli, Rosella, Watson, H. Chen, B. Chen, Kwong); Department of Medicine (Mishra, Chan); Institute of Health Policy, Management and Evaluation (Mishra, Chan); Institute of Medical Science (Mishra); Dalla Lana School of Public Health (Kustra, Chan, Hamilton, Djebli, Rosella, Watson, H. Chen, Kwong); Department of Statistical Sciences (Kustra); and Department of Family and Community Medicine (Kwong), University of Toronto; MAP Centre for Urban Health Solutions (Mishra), Li Ka Shing Knowledge Institute, St. Michael's Hospital, Unity Health Toronto; Sunnybrook Health Sciences Centre (Chan); Public Health Ontario (Kwong, H. Chen); University Health Network (Kwong), Toronto, Ont.; Department of Epidemiology (Baral), Johns Hopkins Bloomberg School of Public Health, Baltimore, Md
| | - Jeffrey C Kwong
- ICES Central (Sundaram, Calzavara, Hamilton, Djebli, Rosella, Watson, H. Chen, B. Chen, Kwong); Department of Medicine (Mishra, Chan); Institute of Health Policy, Management and Evaluation (Mishra, Chan); Institute of Medical Science (Mishra); Dalla Lana School of Public Health (Kustra, Chan, Hamilton, Djebli, Rosella, Watson, H. Chen, Kwong); Department of Statistical Sciences (Kustra); and Department of Family and Community Medicine (Kwong), University of Toronto; MAP Centre for Urban Health Solutions (Mishra), Li Ka Shing Knowledge Institute, St. Michael's Hospital, Unity Health Toronto; Sunnybrook Health Sciences Centre (Chan); Public Health Ontario (Kwong, H. Chen); University Health Network (Kwong), Toronto, Ont.; Department of Epidemiology (Baral), Johns Hopkins Bloomberg School of Public Health, Baltimore, Md
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Sundaram ME, Calzavara A, Mishra S, Kustra R, Chan AK, Hamilton MA, Djebli M, Rosella LC, Watson T, Chen H, Chen B, Baral SD, Kwong JC. Individual and social determinants of SARS-CoV-2 testing and positivity in Ontario, Canada: a population-wide study. CMAJ 2021. [PMID: 33906966 DOI: 10.1101/2020.11.09.20223792] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/14/2023] Open
Abstract
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.
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Affiliation(s)
- Maria E Sundaram
- ICES Central (Sundaram, Calzavara, Hamilton, Djebli, Rosella, Watson, H. Chen, B. Chen, Kwong); Department of Medicine (Mishra, Chan); Institute of Health Policy, Management and Evaluation (Mishra, Chan); Institute of Medical Science (Mishra); Dalla Lana School of Public Health (Kustra, Chan, Hamilton, Djebli, Rosella, Watson, H. Chen, Kwong); Department of Statistical Sciences (Kustra); and Department of Family and Community Medicine (Kwong), University of Toronto; MAP Centre for Urban Health Solutions (Mishra), Li Ka Shing Knowledge Institute, St. Michael's Hospital, Unity Health Toronto; Sunnybrook Health Sciences Centre (Chan); Public Health Ontario (Kwong, H. Chen); University Health Network (Kwong), Toronto, Ont.; Department of Epidemiology (Baral), Johns Hopkins Bloomberg School of Public Health, Baltimore, Md
| | - Andrew Calzavara
- ICES Central (Sundaram, Calzavara, Hamilton, Djebli, Rosella, Watson, H. Chen, B. Chen, Kwong); Department of Medicine (Mishra, Chan); Institute of Health Policy, Management and Evaluation (Mishra, Chan); Institute of Medical Science (Mishra); Dalla Lana School of Public Health (Kustra, Chan, Hamilton, Djebli, Rosella, Watson, H. Chen, Kwong); Department of Statistical Sciences (Kustra); and Department of Family and Community Medicine (Kwong), University of Toronto; MAP Centre for Urban Health Solutions (Mishra), Li Ka Shing Knowledge Institute, St. Michael's Hospital, Unity Health Toronto; Sunnybrook Health Sciences Centre (Chan); Public Health Ontario (Kwong, H. Chen); University Health Network (Kwong), Toronto, Ont.; Department of Epidemiology (Baral), Johns Hopkins Bloomberg School of Public Health, Baltimore, Md
| | - Sharmistha Mishra
- ICES Central (Sundaram, Calzavara, Hamilton, Djebli, Rosella, Watson, H. Chen, B. Chen, Kwong); Department of Medicine (Mishra, Chan); Institute of Health Policy, Management and Evaluation (Mishra, Chan); Institute of Medical Science (Mishra); Dalla Lana School of Public Health (Kustra, Chan, Hamilton, Djebli, Rosella, Watson, H. Chen, Kwong); Department of Statistical Sciences (Kustra); and Department of Family and Community Medicine (Kwong), University of Toronto; MAP Centre for Urban Health Solutions (Mishra), Li Ka Shing Knowledge Institute, St. Michael's Hospital, Unity Health Toronto; Sunnybrook Health Sciences Centre (Chan); Public Health Ontario (Kwong, H. Chen); University Health Network (Kwong), Toronto, Ont.; Department of Epidemiology (Baral), Johns Hopkins Bloomberg School of Public Health, Baltimore, Md
| | - Rafal Kustra
- ICES Central (Sundaram, Calzavara, Hamilton, Djebli, Rosella, Watson, H. Chen, B. Chen, Kwong); Department of Medicine (Mishra, Chan); Institute of Health Policy, Management and Evaluation (Mishra, Chan); Institute of Medical Science (Mishra); Dalla Lana School of Public Health (Kustra, Chan, Hamilton, Djebli, Rosella, Watson, H. Chen, Kwong); Department of Statistical Sciences (Kustra); and Department of Family and Community Medicine (Kwong), University of Toronto; MAP Centre for Urban Health Solutions (Mishra), Li Ka Shing Knowledge Institute, St. Michael's Hospital, Unity Health Toronto; Sunnybrook Health Sciences Centre (Chan); Public Health Ontario (Kwong, H. Chen); University Health Network (Kwong), Toronto, Ont.; Department of Epidemiology (Baral), Johns Hopkins Bloomberg School of Public Health, Baltimore, Md
| | - Adrienne K Chan
- ICES Central (Sundaram, Calzavara, Hamilton, Djebli, Rosella, Watson, H. Chen, B. Chen, Kwong); Department of Medicine (Mishra, Chan); Institute of Health Policy, Management and Evaluation (Mishra, Chan); Institute of Medical Science (Mishra); Dalla Lana School of Public Health (Kustra, Chan, Hamilton, Djebli, Rosella, Watson, H. Chen, Kwong); Department of Statistical Sciences (Kustra); and Department of Family and Community Medicine (Kwong), University of Toronto; MAP Centre for Urban Health Solutions (Mishra), Li Ka Shing Knowledge Institute, St. Michael's Hospital, Unity Health Toronto; Sunnybrook Health Sciences Centre (Chan); Public Health Ontario (Kwong, H. Chen); University Health Network (Kwong), Toronto, Ont.; Department of Epidemiology (Baral), Johns Hopkins Bloomberg School of Public Health, Baltimore, Md
| | - Mackenzie A Hamilton
- ICES Central (Sundaram, Calzavara, Hamilton, Djebli, Rosella, Watson, H. Chen, B. Chen, Kwong); Department of Medicine (Mishra, Chan); Institute of Health Policy, Management and Evaluation (Mishra, Chan); Institute of Medical Science (Mishra); Dalla Lana School of Public Health (Kustra, Chan, Hamilton, Djebli, Rosella, Watson, H. Chen, Kwong); Department of Statistical Sciences (Kustra); and Department of Family and Community Medicine (Kwong), University of Toronto; MAP Centre for Urban Health Solutions (Mishra), Li Ka Shing Knowledge Institute, St. Michael's Hospital, Unity Health Toronto; Sunnybrook Health Sciences Centre (Chan); Public Health Ontario (Kwong, H. Chen); University Health Network (Kwong), Toronto, Ont.; Department of Epidemiology (Baral), Johns Hopkins Bloomberg School of Public Health, Baltimore, Md
| | - Mohamed Djebli
- ICES Central (Sundaram, Calzavara, Hamilton, Djebli, Rosella, Watson, H. Chen, B. Chen, Kwong); Department of Medicine (Mishra, Chan); Institute of Health Policy, Management and Evaluation (Mishra, Chan); Institute of Medical Science (Mishra); Dalla Lana School of Public Health (Kustra, Chan, Hamilton, Djebli, Rosella, Watson, H. Chen, Kwong); Department of Statistical Sciences (Kustra); and Department of Family and Community Medicine (Kwong), University of Toronto; MAP Centre for Urban Health Solutions (Mishra), Li Ka Shing Knowledge Institute, St. Michael's Hospital, Unity Health Toronto; Sunnybrook Health Sciences Centre (Chan); Public Health Ontario (Kwong, H. Chen); University Health Network (Kwong), Toronto, Ont.; Department of Epidemiology (Baral), Johns Hopkins Bloomberg School of Public Health, Baltimore, Md
| | - Laura C Rosella
- ICES Central (Sundaram, Calzavara, Hamilton, Djebli, Rosella, Watson, H. Chen, B. Chen, Kwong); Department of Medicine (Mishra, Chan); Institute of Health Policy, Management and Evaluation (Mishra, Chan); Institute of Medical Science (Mishra); Dalla Lana School of Public Health (Kustra, Chan, Hamilton, Djebli, Rosella, Watson, H. Chen, Kwong); Department of Statistical Sciences (Kustra); and Department of Family and Community Medicine (Kwong), University of Toronto; MAP Centre for Urban Health Solutions (Mishra), Li Ka Shing Knowledge Institute, St. Michael's Hospital, Unity Health Toronto; Sunnybrook Health Sciences Centre (Chan); Public Health Ontario (Kwong, H. Chen); University Health Network (Kwong), Toronto, Ont.; Department of Epidemiology (Baral), Johns Hopkins Bloomberg School of Public Health, Baltimore, Md
| | - Tristan Watson
- ICES Central (Sundaram, Calzavara, Hamilton, Djebli, Rosella, Watson, H. Chen, B. Chen, Kwong); Department of Medicine (Mishra, Chan); Institute of Health Policy, Management and Evaluation (Mishra, Chan); Institute of Medical Science (Mishra); Dalla Lana School of Public Health (Kustra, Chan, Hamilton, Djebli, Rosella, Watson, H. Chen, Kwong); Department of Statistical Sciences (Kustra); and Department of Family and Community Medicine (Kwong), University of Toronto; MAP Centre for Urban Health Solutions (Mishra), Li Ka Shing Knowledge Institute, St. Michael's Hospital, Unity Health Toronto; Sunnybrook Health Sciences Centre (Chan); Public Health Ontario (Kwong, H. Chen); University Health Network (Kwong), Toronto, Ont.; Department of Epidemiology (Baral), Johns Hopkins Bloomberg School of Public Health, Baltimore, Md
| | - Hong Chen
- ICES Central (Sundaram, Calzavara, Hamilton, Djebli, Rosella, Watson, H. Chen, B. Chen, Kwong); Department of Medicine (Mishra, Chan); Institute of Health Policy, Management and Evaluation (Mishra, Chan); Institute of Medical Science (Mishra); Dalla Lana School of Public Health (Kustra, Chan, Hamilton, Djebli, Rosella, Watson, H. Chen, Kwong); Department of Statistical Sciences (Kustra); and Department of Family and Community Medicine (Kwong), University of Toronto; MAP Centre for Urban Health Solutions (Mishra), Li Ka Shing Knowledge Institute, St. Michael's Hospital, Unity Health Toronto; Sunnybrook Health Sciences Centre (Chan); Public Health Ontario (Kwong, H. Chen); University Health Network (Kwong), Toronto, Ont.; Department of Epidemiology (Baral), Johns Hopkins Bloomberg School of Public Health, Baltimore, Md
| | - Branson Chen
- ICES Central (Sundaram, Calzavara, Hamilton, Djebli, Rosella, Watson, H. Chen, B. Chen, Kwong); Department of Medicine (Mishra, Chan); Institute of Health Policy, Management and Evaluation (Mishra, Chan); Institute of Medical Science (Mishra); Dalla Lana School of Public Health (Kustra, Chan, Hamilton, Djebli, Rosella, Watson, H. Chen, Kwong); Department of Statistical Sciences (Kustra); and Department of Family and Community Medicine (Kwong), University of Toronto; MAP Centre for Urban Health Solutions (Mishra), Li Ka Shing Knowledge Institute, St. Michael's Hospital, Unity Health Toronto; Sunnybrook Health Sciences Centre (Chan); Public Health Ontario (Kwong, H. Chen); University Health Network (Kwong), Toronto, Ont.; Department of Epidemiology (Baral), Johns Hopkins Bloomberg School of Public Health, Baltimore, Md
| | - Stefan D Baral
- ICES Central (Sundaram, Calzavara, Hamilton, Djebli, Rosella, Watson, H. Chen, B. Chen, Kwong); Department of Medicine (Mishra, Chan); Institute of Health Policy, Management and Evaluation (Mishra, Chan); Institute of Medical Science (Mishra); Dalla Lana School of Public Health (Kustra, Chan, Hamilton, Djebli, Rosella, Watson, H. Chen, Kwong); Department of Statistical Sciences (Kustra); and Department of Family and Community Medicine (Kwong), University of Toronto; MAP Centre for Urban Health Solutions (Mishra), Li Ka Shing Knowledge Institute, St. Michael's Hospital, Unity Health Toronto; Sunnybrook Health Sciences Centre (Chan); Public Health Ontario (Kwong, H. Chen); University Health Network (Kwong), Toronto, Ont.; Department of Epidemiology (Baral), Johns Hopkins Bloomberg School of Public Health, Baltimore, Md
| | - Jeffrey C Kwong
- ICES Central (Sundaram, Calzavara, Hamilton, Djebli, Rosella, Watson, H. Chen, B. Chen, Kwong); Department of Medicine (Mishra, Chan); Institute of Health Policy, Management and Evaluation (Mishra, Chan); Institute of Medical Science (Mishra); Dalla Lana School of Public Health (Kustra, Chan, Hamilton, Djebli, Rosella, Watson, H. Chen, Kwong); Department of Statistical Sciences (Kustra); and Department of Family and Community Medicine (Kwong), University of Toronto; MAP Centre for Urban Health Solutions (Mishra), Li Ka Shing Knowledge Institute, St. Michael's Hospital, Unity Health Toronto; Sunnybrook Health Sciences Centre (Chan); Public Health Ontario (Kwong, H. Chen); University Health Network (Kwong), Toronto, Ont.; Department of Epidemiology (Baral), Johns Hopkins Bloomberg School of Public Health, Baltimore, Md
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22
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Affiliation(s)
- Muge Cevik
- Division of Infection and Global Health Research, School of Medicine, University of St Andrews, St Andrews, UK
| | - Stefan D Baral
- Department of Epidemiology, Johns Hopkins School of Public Health, Baltimore, MD, USA
| | - Alex Crozier
- Division of Biosciences, University College London, London, UK
| | - Jackie A Cassell
- Department of Primary Care and Public Health, Brighton and Sussex Medical School, Brighton, UK
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23
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Baral S, Bond A, Boozary A, Bruketa E, Elmi N, Freiheit D, Ghosh SM, Goyer ME, Orkin AM, Patel J, Richter T, Robertson A, Sutherland C, Svoboda T, Turnbull J, Wong A, Zhu A. Seeking shelter: homelessness and COVID-19. Facets (Ott) 2021. [DOI: 10.1139/facets-2021-0004] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022] Open
Abstract
Those experiencing homelessness in Canada are impacted inequitably by COVID-19 due to their increased exposure, vulnerability of environment and medical comorbidities, and their lack of access to preventive care and treatment in the context of the pandemic. In shelter environments one is unable to effectively physically distance, maintain hygiene, obtain a test, or isolate. As a result, unique strategies are required for this population to protect them and those who serve them. Recommendations are provided to reduce or prevent further negative consequences from the COVID-19 pandemic for people experiencing homelessness. These recommendations were informed by a systematic review of the literature, as well as a jurisdictional scan. Where evidence did not exist, expert consensus from key providers and those experiencing homelessness throughout Canada was included. These recommendations recognize the need for short-term interventions to mitigate the immediate risk to this community, including coordination of response, appropriate precautions and protective equipment, reducing congestion, cohorting, testing, case and contact management strategies, dealing with outbreaks, isolation centres, and immunization. Longer-term recommendations are also provided with a view to ending homelessness by addressing the root causes of homelessness and by the provision of adequate subsidized and supportive housing through a Housing First strategy. It is imperative that meaningful changes take place now in how we serve those experiencing homelessness and how we mitigate specific vulnerabilities. These recommendations call for intersectoral, collaborative engagement to work for solutions targeted towards protecting the most vulnerable within our community through both immediate actions and long-term planning to eliminate homelessness.
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Affiliation(s)
- Stefan Baral
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205, USA
- Inner City Health Associates, Toronto, ON M5C 1K6, Canada
| | - Andrew Bond
- Inner City Health Associates, Toronto, ON M5C 1K6, Canada
- Department of Family and Community Medicine, University of Toronto, Toronto, ON M5G 1V7, Canada
| | - Andrew Boozary
- Population Health and Social Medicine, University Health Network, Toronto, ON M5G 2C4, Canada
- University of Toronto, Toronto, ON M5S 1A8, Canada
- Columbia University, New York, NY 10032, USA
| | - Eva Bruketa
- Queen’s University, Kingston, ON K7L 3N6, Canada
| | - Nika Elmi
- Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205, USA
| | | | - S. Monty Ghosh
- Department of General Internal Medicine & Neurology, University of Alberta, Edmonton, AB T6G 2G3, Canada
- Department of Medicine & Psychiatry, University of Calgary, Calgary, AB T2N 1N4, Canada
| | - Marie Eve Goyer
- Family Medicine and Emergency Department, University of Montréal, Montréal, QC H3T 1J4, Canada
| | - Aaron M. Orkin
- Inner City Health Associates, Toronto, ON M5C 1K6, Canada
- Department of Family and Community Medicine, University of Toronto, Toronto, ON M5G 1V7, Canada
- Department of Emergency Medicine, St. Joseph’s Health Centre, Toronto, ON M6R 1B5, Canada
- Department of Emergency Medicine, Humber River Hospital, Toronto, ON M3M 0B2, Canada
| | - Jamie Patel
- Faculty of Community Services, Ryerson University, Toronto, ON M5B 2K3, Canada
| | - Tim Richter
- Canadian Alliance to End Homelessness, Calgary, AB T3H 0N8, Canada
| | - Angela Robertson
- Parkdale Queen West Community Health Centre, Toronto, ON M6K 1L2, Canada
| | - Christy Sutherland
- PHS Community Services Society, Vancouver, BC V6A 1M9, Canada
- Department of Family Medicine, University of British Columbia, Vancouver, BC V6T 1Z3, Canada
| | - Tomislav Svoboda
- Department of Family and Community Medicine, University of Toronto, Toronto, ON M5G 1V7, Canada
| | - Jeffrey Turnbull
- University of Ottawa, Ottawa, ON K1N 6N5, Canada
- Ottawa Inner City Health, Ottawa, ON K1N 5N7, Canada
| | - Alexander Wong
- Department of Medicine, University of Saskatchewan, Regina, SK S4T 0H8, Canada
| | - Alice Zhu
- University of Toronto, Toronto, ON M5S 1A8, Canada
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