Risk factors associated with severe Covid-19 outcomes in Jamaica
A cross-sectional study of national surveillance data
Bibliographic Data
Objectives. To describe the characteristics and outcomes of COVID-19 cases in Jamaica and to explore the risk factors associated with severe COVID-19 from 9 March to 31 December 2020. Methods. A cross-sectional analysis of national surveillance data was conducted using confirmed COVID-19 cases in Jamaica. Definitions of a confirmed case, disease severity, and death were based on World Health Organization guidelines. Chi-square and Fisher exact tests were used to determine association with outcomes. Logistic regression models were used to determine predictors of severe COVID-19. Results. This analysis included 12 169 cases of COVID-19 (median age, 36 years; 6 744 females [ 55.4%]) of which 512 cases (4.2%) presented with severe disease, and of those, 318 patients (62.1%) died (median age at death, 71.5 years). Severe disease was associated with being male (OR 1.4; 95% CI, 1.2-1.7) and 40 years or older (OR, 6.5; 95% CI, 5.1-8.2). COVID-19 death was also associated with being male (OR, 1.4; 95% CI, 1.1-1.7), age 40 years or older (OR, 17.9; 95% CI, 11.6-27.7), and in the Western versus South East Health Region (OR 1.7; 95% CI, 1.2-2.3). Conclusions. The findings of this cross-sectional analysis indicate that confirmed cases of COVID-19 in Jamaica were more likely to be female and younger individuals, whereas COVID-19 deaths occurred more frequently in males and older individuals. There is increased risk of poor COVID-19 outcomes beginning at age 40, with males disproportionately affected. COVID-19 death also varied by geographic region. This evidence could be useful to other countries with similar settings and to policymakers charged with managing outbreaks and health
Coronavirus disease 2019 (COVID-19 · Cross-sectional study · Disease · Infectious disease (medical specialty · Logistic regression · Pathology · COVID-19 and healthcare impacts · COVID-19 Clinical Research Studies · COVID-19 epidemiological studies · Demography · Medicine · Internal Medicine
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