Comparison of the capture–recapture method and seroprevalence survey for estimation of COVID-19 prevalence in the Islamic Republic of Iran

Abstract

Background: Reliable estimation of prevalence is important for monitoring and evaluation of COVID-19 prevention programmes among at-risk populations. Aims: We compared the capture–recapture method with a seroprevalence survey for accurate estimation of the prevalence of COVID-19 during a 1-year period in Guilan Province, northern Islamic Republic of Iran. Methods: We used the capture–recapture method to estimate the prevalence of COVID-19. Records from the primary care registry system and the Medical Care Monitoring Center were compared, using 4 matching approaches based on combinations of the following variables: name, age, gender, date of death, positive or negative cases, and alive or dead cases. Results: The estimated prevalence of COVID-19 in the study population from the beginning of the pandemic in February 2020 until the end of January 2021 was 16.2–19.8%, depending on the matching approach used, which was lower than in previous studies. Conclusion: The capture–recapture method may provide better accuracy than seroprevalence surveys in measuring the prevalence of COVID-19. This method may also reduce the bias in the estimation of prevalence and correct the misconception of policymakers about seroprevalence survey results