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

Abstract

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.

Keywords: Covid-19; SARS-CoV-2; cross-sectional studies; epidemiology; infectious diseases; prevalence; severe acute respiratory syndrome coronavirus 2.

FIGURE 1

PRISMA flowchart of the literature search

FIGURE 2

Map of countries and specific regions with prevalence surveys. Red dots represent regions and cities where the initiatives were performed. In nationwide studies, the point was placed in the centre of the country

FIGURE 3

Timeline of population‐based Covid‐19 prevalence surveys conducted worldwide, with the duration of each survey and an overview of the most represented periods. Black dots on the left represent the date of the first confirmed case in the country of each survey

FIGURE 4

Risk of bias assessment summary table across all studies. *No weights were applied for different studies. †Not applicable was selected in ‘sample size adequate’ because the study had zero prevalence (impossible to calculate the sample size required)

FIGURE 5

Correspondence analysis of seven important variables of population‐based Covid‐19 prevalence surveys. The categories of row (continent, coverage, biological samples, test validation and sensitivity) and column (risk of bias and prevalence) variables are represented in blue and red, respectively. Light red, yellow and green ellipses represent high, intermediate and low risk of bias, respectively. BioS, biological sample; S, sensitivity; P, prevalence; ValT: test validation