ArticleBMJ public health2024
Addressing data quality issues to assess clinical and epidemiological risk factors for COVID-19 among documented cases in Liberia: a single-centre, retrospective, observational study.
Article in BMJ public health, 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
Introduction: Identification of risk factors for severe COVID-19 can help to inform case management in resource-constrained settings. We aimed to rigorously but retroactively address data issues to identify risk factors for COVID-19 morbidity and mortality among cases seeking care in Liberia. Methods: Chart data on confirmed cases were extracted at the national COVID-19 treatment unit. Due to the use of paper charts, assignment of non-unique identifiers and incomplete documentation, data required cleaning to remove duplicates per three sets of predefined criteria. Associations between epidemiological, clinical and demographic variables and indicators of disease severity were assessed using multivariable logistic regression. Results: The raw data set for patients classified between 15 March and 1 September 2020 included 2703 cases or 107% more than the 1303 cases reported by the national surveillance system during the same period. The median age of cases was found to be 38 years (IQR: 27-50); most cases were men (65%). The rates of continuous positive airway pressure (CPAP) use for breathing support and of case fatality were 5% (71/1330) and 5% (52/981), respectively. Increased odds of breathing assistance with CPAP use were associated with self-reported diabetes (aOR: 4.37; 95% CI: 1.72 to 10.4) and/or hypertension (aOR: 4.86; 95% CI: 1.81 to 12.2) and increasing age (aOR: 1.06; 95% CI: 1.04 to 1.08). Recent travel history (aOR: 5.13; 95% CI: 1.13 to 19.3) and residence outside of urban Montserrado County (aOR: 22.7; 95% CI: 8.08 to 76.4) were associated with increased odds of death. Conclusions: Results from this retrospective analysis highlight self-reported non-communicable diseases as well as residence outside of largely urbanised Montserrado County as factors associated with COVID-19 severity among presenting cases in Liberia. The findings, both in terms of analytical results and data quality concerns, offer insight into how access to the highly centralised health systems and processes in Liberia may have affected populations distant from the central response in terms not only of COVID-19 disease outcomes but also care-seeking behaviour and surveillance effectiveness. This has implications for surveillance and response across priority diseases.
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