Considerations for epidemiological studies investigating emerging post-acute infection syndromes: Long Covid as a case study

TL;DR

This paper reviews how to better design studies on Long Covid to improve understanding of its prevalence and risk factors.

Contribution

The paper provides a framework of methodological considerations for studying emerging post-acute infection syndromes like Long Covid.

Findings

Long Covid prevalence estimates vary due to inconsistent study methods.

Study design, outcome definitions, and statistical techniques significantly affect results.

Robust methodologies are needed to inform public health responses.

Abstract

Epidemiological research studies into Long Covid, currently defined by prolonged symptoms after SARS-CoV-2 infection, have reported widely varying prevalence estimates. As well as rapidly evolving scientific knowledge of Long Covid, these differences are partly driven by substantial methodological heterogeneity between studies, including the outcome definition of Long Covid; duration of follow-up; study design, period and population; sampling frame; data source; and the statistical techniques employed. Having a robust understanding of the prevalence of and risk factors for Long Covid is essential for informing treatment pathways, service provision and policy decisions. In preparation for the public health response to future epidemics and pandemics, this review outlines key epidemiological and statistical considerations and recommendations when designing studies of emerging post-acute infection syndromes, focussing on Long Covid as a case study.

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