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Scand J Public Health ; 50(6): 810-818, 2022 Aug.
Article in English | MEDLINE | ID: covidwho-1874973

ABSTRACT

Background: Not much is known about correlations between country-level characteristics and country-level numbers of COVID-19 cases and mortalities. Methods: Using data from the World Health Organization and other international organisations, we summarised country-level COVID-19 case and mortality counts per 100,000 population, and COVID-19 case fatality rate from January 2020 to August 2021. We conducted adjusted linear regression analysis to assess relationships between these counts/rate and certain country-level characteristics. We reported adjusted regression coefficients, ß and associated 95% confidence intervals. Results: There was a positive correlation between the number of cases and country-level male/female ratio, and positive correlations between the numbers of cases and mortalities and country-level proportion of 60+-year-olds, universal health coverage index of service coverage (UHC) and tourism. Country economic status correlated negatively with the numbers of cases and mortalities. COVID-19 case fatality rate was highest in Peru, South American region (9.2%), and lowest in Singapore, Western Pacific region (0.1%). A negative correlation was observed between case fatality rate and country-level male/female ratio, population density and economic status. These observations remained mostly among mid-/low-income countries, particularly a positive correlation between the number of cases and male/female ratio and proportion of 60+-year-olds. Conclusions: Various country-level characteristics such as male/female ratio, proportion of older adults, country economic status, UHC and tourism appear to be correlated with the country-level number of COVID-19 cases and/or mortalities. Consideration of these characteristics may be necessary when designing country-level COVID-19 epidemiological studies and in comparing COVID-19 data between countries.


Subject(s)
COVID-19 , Aged , COVID-19/epidemiology , Female , Humans , Male , Population Density , Socioeconomic Factors , Universal Health Insurance , World Health Organization
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