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


ABSTRACT:

Objective

This study aimed to model the precision of SARS-CoV-2 seroprevalence estimates.

Methods

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%.

Results

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.

Conclusions

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.

SUBMITTER: Nikiforuk AM 

PROVIDER: S-EPMC9395286 | biostudies-literature | 2022 Aug

REPOSITORIES: biostudies-literature

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

Nikiforuk A M AM   Sekirov I I   Jassem A N AN  

Public health 20220823


<h4>Objective</h4>This study aimed to model the precision of SARS-CoV-2 seroprevalence estimates.<h4>Methods</h4>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%.<h4>Results</h4>The calculation found that 2% precision was attainable by taking moderately sized sample sets when the expected seroprevalenc  ...[more]

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