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Published on: November 22, 2017
Confidence intervals for the COVID-19 neutralizing antibody retention rate in the Korean population
Catherine Apio1, Md Kamruzzaman2, Taesung Park1,2
1Interdisplinary Program in Bioinformatics, Department of Statistics, Seoul National University, Seoul 08826, Korea.
Insights
Estimating COVID-19 antibody rates in Korea is crucial for understanding pandemic spread. This study provides 95% confidence intervals for antibody prevalence, revealing at least 32,602 unconfirmed infections by September 2020.
Area of Science:
- Epidemiology
- Immunology
- Biostatistics
Background:
- The COVID-19 pandemic necessitates accurate seroprevalence data.
- Convalescent plasma therapy relies on widespread antibody screening.
- Simple prevalence estimates can be misleading without confidence intervals.
Purpose of the Study:
- To review the significance of antibody studies in pandemics.
- To calculate 95% confidence intervals for COVID-19 antibody rates in the Korean population.
- To compare different statistical methods for confidence interval estimation with sparse data.
Main Methods:
- Review of antibody study importance.
- Application of Asymptotic, Exact, and Bayesian methods for confidence interval calculation.
- Analysis of data from two recent Korean antibody tests.
Main Results:
- Comparison of confidence interval widths across different statistical methods.
- Identification of the narrowest intervals from Wald (Asymptotic), mid p-value (Exact), and Jeffrey's (Bayesian) methods.
- Conservative estimation indicating at least 32,602 unconfirmed COVID-19 infections in Korea as of September 15, 2020.
Conclusions:
- Accurate confidence intervals are essential for interpreting COVID-19 seroprevalence data.
- Various statistical methods yield different interval estimates, impacting conclusions.
- The study highlights the challenge of estimating prevalence with limited data, providing a conservative estimate of undetected infections.
Abstract:
The coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has become a global pandemic. No specific therapeutic agents or vaccines for COVID-19 are available, though several antiviral drugs, are under investigation as treatment agents for COVID-19. The use of convalescent plasma transfusion that contain neutralizing antibodies for COVID-19 has become the major focus. This requires mass screening of populations for these antibodies. While several countries started reporting population based antibody rate, its simple point estimate may be misinterpreted without proper estimation of standard error and confidence intervals. In this paper, we review the importance of antibody studies and present the 95% confidence intervals COVID-19 antibody rate for the Korean population using two recently performed antibody tests in Korea. Due to the sparsity of data, the estimation of confidence interval is a big challenge. Thus, we consider several confidence intervals using Asymptotic, Exact and Bayesian estimation methods. In this article, we found that the Wald method gives the narrowest interval among all Asymptotic methods whereas mid p-value gives the narrowest among all Exact methods and Jeffrey's method gives the narrowest from Bayesian method. The most conservative 95% confidence interval estimation shows that as of 00:00 on September 15, 2020, at least 32,602 people were infected but not confirmed in Korea.
