Simple approximation of sample size for precise estimates of SARS-CoV-2 infection from point-seroprevalence studies

• Published in: Public health (London) Vol. 212; pp. 7 - 9
• Main Authors: Nikiforuk, A.M., Sekirov, I., Jassem, A.N.
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01.11.2022; Published by Elsevier Ltd on behalf of The Royal Society for Public Health
• Subjects: Epidemiology; Precision; Prevalence; SARS-CoV-2; Serological survey; Short Communication; Study design; Study design; SARS-CoV-2; Prevalence; Precision; Epidemiology; Serological survey
• ISSN: 0033-3506; 1476-5616
• DOI: 10.1016/j.puhe.2022.08.008

This study aimed to model the precision of SARS-CoV-2 seroprevalence estimates. Sample size and precision estimates were calculated using the normal approximation to the binomial distribution. The relationship between sample size and precision was visualized across a range of assumed SARS-CoV-2 seroprevalence from 2% to 75%. The calculation found that 2% precision was attainable by taking moderately sized sample sets when the expected seroprevalence of SARS-CoV-2 infection exceeds 2%. In populations with a low incidence of SARS-CoV-2 infection and an expected seroprevalence of less than 2%, larger samples are required for precise estimates. Taking a sample of 177–1000 participants can provide precise prevalence estimates of SARS-CoV-2 infection in vaccinated and unvaccinated populations. Larger sample sizes are only necessary in low prevalence settings.