Identifying people with post-COVID condition using linked, population-based administrative health data from Manitoba, Canada: prevalence and predictors in a cohort of COVID-positive individuals
Jennifer E Enns,
Alan Katz,
Alexander Singer,
Yoav Keynan,
Lisa Lix,
Kendiss Olafson,
Randy Walld,
Nathan C Nickel,
Okechukwu Ekuma,
Sarvesh Logsetty,
Marcelo Urquia,
Diana C Sanchez-Ramirez,
Leona Star,
Rae Spiwak,
Teresa Cavett,
Marina Yogendran,
Jillian Waruk,
Surani Matharaarachichi
Affiliations
Jennifer E Enns
1 Manitoba Centre for Health Policy, Department of Community Health Sciences, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, Manitoba, Canada
Alan Katz
1 Manitoba Centre for Health Policy, Department of Community Health Sciences, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, Manitoba, Canada
Alexander Singer
2 Department of Family Medicine, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, Manitoba, Canada
Yoav Keynan
4 Department of Internal Medicine, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, Manitoba, Canada
Lisa Lix
1 Manitoba Centre for Health Policy, Department of Community Health Sciences, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, Manitoba, Canada
Kendiss Olafson
4 Department of Internal Medicine, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, Manitoba, Canada
Randy Walld
1 Manitoba Centre for Health Policy, Department of Community Health Sciences, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, Manitoba, Canada
Nathan C Nickel
1 Manitoba Centre for Health Policy, Department of Community Health Sciences, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, Manitoba, Canada
Okechukwu Ekuma
1 Manitoba Centre for Health Policy, Department of Community Health Sciences, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, Manitoba, Canada
Sarvesh Logsetty
6 Department of Surgery, University of Manitoba, Winnipeg, Manitoba, Canada
Marcelo Urquia
1 Manitoba Centre for Health Policy, Department of Community Health Sciences, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, Manitoba, Canada
Diana C Sanchez-Ramirez
3 College of Rehabilitation Sciences, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, Manitoba, Canada
Leona Star
5 First Nations Health and Social Secretariat of Manitoba, Winnipeg, Manitoba, Canada
Rae Spiwak
6 Department of Surgery, University of Manitoba, Winnipeg, Manitoba, Canada
Teresa Cavett
2 Department of Family Medicine, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, Manitoba, Canada
Marina Yogendran
1 Manitoba Centre for Health Policy, Department of Community Health Sciences, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, Manitoba, Canada
Jillian Waruk
5 First Nations Health and Social Secretariat of Manitoba, Winnipeg, Manitoba, Canada
Surani Matharaarachichi
7 Department of Statistics, University of Manitoba, Winnipeg, Manitoba, Canada
Objective Many individuals exposed to SARS-CoV-2 experience long-term symptoms as part of a syndrome called post-COVID condition (PCC). Research on PCC is still emerging but is urgently needed to support diagnosis, clinical treatment guidelines and health system resource allocation. In this study, we developed a method to identify PCC cases using administrative health data and report PCC prevalence and predictive factors in Manitoba, Canada.Design Cohort study.Setting Manitoba, Canada.Participants All Manitobans who tested positive for SARS-CoV-2 during population-wide PCR testing from March 2020 to December 2021 (n=66 365) and were subsequently deemed to have PCC based on International Classification of Disease-9/10 diagnostic codes and prescription drug codes (n=11 316). Additional PCC cases were identified using predictive modelling to assess patterns of health service use, including physician visits, emergency department visits and hospitalisation for any reason (n=4155).Outcomes We measured PCC prevalence as % PCC cases among Manitobans with positive tests and identified predictive factors associated with PCC by calculating odds ratios with 95% confidence intervals, adjusted for sociodemographic and clinical characteristics (aOR).Results Among 66 365 Manitobans with positive tests, we identified 15 471 (23%) as having PCC. Being female (aOR 1.64, 95% CI 1.58 to 1.71), being age 60–79 (aOR 1.33, 95% CI 1.25 to 1.41) or age 80+ (aOR 1.62, 95% CI 1.46 to 1.80), being hospitalised within 14 days of COVID-19 infection (aOR 1.95, 95% CI 1.80 to 2.10) and having a Charlson Comorbidity Index of 1+ (aOR 1.95, 95% CI 1.78 to 2.14) were predictive of PCC. Receiving 1+ doses of the COVID-19 vaccine (one dose, aOR 0.80, 95% CI 0.74 to 0.86; two doses, aOR 0.29, 95% CI 0.22 to 0.31) decreased the odds of PCC.Conclusions This data-driven approach expands our understanding of the prevalence and epidemiology of PCC and may be applied in other jurisdictions with population-based data. The study provides additional insights into risk and protective factors for PCC to inform health system planning and service delivery.
