ArticlePloS one2024
Spectrum of COVID-19 cases in Arkhangelsk, Northwest Russia: Findings from a population-based study linking serosurvey, registry data, and self-reports of symptoms.
Article in PloS one, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
introductionThe spectrum of COVID-19 manifestations makes it challenging to estimate the exact proportion of people who had the infection in a population, with the proportion of asymptomatic cases likely being underestimated. We aimed to assess and describe the spectrum of COVID-19 cases in a sample of adult population aged 40-74 years in Arkhangelsk, Northwest Russia, a year after the start of the pandemic. MATERIALS AND
methodsA population-based survey conducted between February 24, 2021 and June 30, 2021 with an unvaccinated sample aged 40-74 years (N = 1089) combined a serological survey data, national COVID-19 case registry, and self-reported data on COVID-19 experience and symptoms. Based on the agreement between these sources, we classified the study participants as non-infected and previously infected (asymptomatic, non-hospitalized and hospitalized symptomatic) cases, and compared these groups regarding demographics, lifestyle and health characteristics.
resultsAfter a year of the pandemic in Arkhangelsk, 59.7% 95% confidence intervals (CI) (56.7; 62.6) of the surveyed population had had COVID-19. Among those who had been infected, symptomatic cases comprised 47.1% 95% CI (43.2; 51.0), with 8.6% 95% CI (6.6; 11.1) of them having been hospitalized. Of the asymptomatic cases, 96.2% were not captured by the healthcare system. Older age was positively associated, while smoking showed a negative association with symptomatic COVID-19. Individuals older than 65 years, and those with poor self-rated health were more likely to be hospitalized.
conclusionMore than half of the infected individuals were not captured by the healthcare-based registry, mainly those with asymptomatic infections. COVID-19 severity was positively associated with older age and poor self-rated health, and inversely associated with smoking. Combining different sources of surveillance data could reduce the number of unidentified asymptomatic cases and enhance surveillance for emerging infections.
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