Population-based prevalence surveys during the Covid-19 pandemic: A systematic review

Population-based prevalence surveys of Covid-19 contribute to establish the burden of infection, the role of asymptomatic and mild infections in transmission, and allow more precise decisions about reopen policies. We performed a systematic review to evaluate qualitative aspects of these studies, assessing their reliability and compiling practices that can influence the methodological quality. We searched MEDLINE, EMBASE, bioRxiv and medRxiv, and included cross-sectional studies using molecular and/or serological tests to estimate the prevalence of Covid-19 in the general population. Survey quality was assessed using the Joanna Briggs Institute Critical Appraisal Checklist for Prevalence Studies. A correspondence analysis correlated methodological parameters of each study to identify patterns related to higher, intermediate and lower risks of bias. The available data described 37 surveys from 19 countries. The majority were from Europe and America, used antibody testing, and reached highly heterogeneous sample sizes and prevalence estimates. Minority communities were disproportionately affected by Covid-19. Important risk of bias was detected in four domains: sample size, data analysis with sufficient coverage, measurements in standard way and response rate. The correspondence analysis showed few consistent patterns for high risk of bias. Intermediate risk of bias was related to American and European studies, municipal and regional initiatives, blood samples and prevalence >1%. Low risk of bias was related to Asian studies, nationwide initiatives, reverse-transcriptase polymerase chain reaction tests and prevalence <1%. We identified methodological standards applied worldwide in Covid-19 prevalence surveys, which may assist researchers with the planning, execution and reporting of future population-based surveys.

Automated summary

Population-based prevalence surveys of Covid-19 from 37 studies in 19 countries revealed that most studies were from Europe and America, using antibody testing with highly variable sample sizes and prevalence estimates. Minority communities were disproportionately affected, and important risks of bias were detected in sample size, data analysis, standard measurements, and response rates. Few consistent patterns for high risk of bias were found, with intermediate risk related to American and European studies, municipal initiatives, blood samples, and prevalence above 1%. Low risk of bias was associated with Asian studies, nationwide initiatives, RT-PCR tests, and prevalence below 1%. Identifying methodological standards may assist in future population-based surveys.