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Examining the immediate and ongoing impact of the COVID-19 pandemic on population-based estimates of dementia: a population-based time series analysis in Ontario, Canada.
Jones, Aaron; Bronskill, Susan E; Maclagan, Laura C; Jaakkimainen, Liisa; Kirkwood, David; Mayhew, Alexandra; Costa, Andrew P; Griffith, Lauren E.
  • Jones A; Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, Ontario, Canada jonesa13@mcmaster.ca.
  • Bronskill SE; ICES, Toronto, Ontario, Canada.
  • Maclagan LC; ICES, Toronto, Ontario, Canada.
  • Jaakkimainen L; Institute of Health Policy, Management & Evaluation, University of Toronto, Toronto, Ontario, Canada.
  • Kirkwood D; ICES, Toronto, Ontario, Canada.
  • Mayhew A; ICES, Toronto, Ontario, Canada.
  • Costa AP; Institute of Health Policy, Management & Evaluation, University of Toronto, Toronto, Ontario, Canada.
  • Griffith LE; Department of Family and Community Medicine, University of Toronto, Toronto, Ontario, Canada.
BMJ Open ; 13(1): e067689, 2023 01 13.
Article in English | MEDLINE | ID: covidwho-2193802
ABSTRACT

OBJECTIVES:

Population-based chronic disease surveillance systems were likely disrupted by the COVID-19 pandemic. The objective of this study was to examine the immediate and ongoing impact of the COVID-19 pandemic on the claims-based incidence of dementia.

METHODS:

We conducted a population-based time series analysis from January 2015 to December 2021 in Ontario, Canada. We calculated the monthly claims-based incidence of dementia using a validated case ascertainment algorithm drawing from routinely collected health administrative data. We used autoregressive linear models to compare the claims-based incidence of dementia during the COVID-19 period (2020-2021) to the expected incidence had the pandemic not occurred, controlling for seasonality and secular trends. We examined incidence by source of ascertainment and across strata of sex, age, community size and number of health conditions.

RESULTS:

The monthly claims-based incidence of dementia dropped from a 2019 average of 11.9 per 10 000 to 8.5 per 10 000 in April 2020 (32.6% lower than expected). The incidence returned to expected levels by late 2020. Across the COVID-19 period there were a cumulative 2990 (95% CI 2109 to 3704) fewer cases of dementia observed than expected, equivalent to 1.05 months of new cases. Despite the overall recovery, ascertainment rates continued to be lower than expected among individuals aged 65-74 years and in large urban areas. Ascertainment rates were higher than expected in hospital and among individuals with 11 or more health conditions.

CONCLUSIONS:

The claims-based incidence of dementia recovered to expected levels by late 2020, suggesting minimal long-term changes to population-based dementia surveillance. Continued monitoring of claims-based incidence is necessary to determine whether the lower than expected incidence among individuals aged 65-74 and in large urban areas, and higher than expected incidence among individuals with 11 or more health conditions, is transitory.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: Dementia / COVID-19 Type of study: Experimental Studies / Observational study / Prognostic study Topics: Long Covid Limits: Humans Country/Region as subject: North America Language: English Journal: BMJ Open Year: 2023 Document Type: Article Affiliation country: Bmjopen-2022-067689

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Dementia / COVID-19 Type of study: Experimental Studies / Observational study / Prognostic study Topics: Long Covid Limits: Humans Country/Region as subject: North America Language: English Journal: BMJ Open Year: 2023 Document Type: Article Affiliation country: Bmjopen-2022-067689