Estimation of undetected asymptomatic infections of COVID-19: a mathematical modeling approach.

ABSTRACT: The accurate quantification of asymptomatic infections is crucial for understanding and mitigating the spread of COVID-19. However, estimating the true prevalence of asymptomatic cases remains a significant challenge. This study introduces a novel mathematical modeling approach to estimate key epidemiological parameters associated with asymptomatic infections, leveraging comprehensive COVID-19 data from the Republic of Korea. We develop a refined compartmental model that explicitly incorporates asymptomatic individuals and employs a trajectory matching method, integrating least-squares fitting with gradient matching, to align the model with confirmed cases and deaths. The model successfully reproduces the initial outbreak and subsequent epidemic waves, demonstrating strong agreement with o

SUBMITTER: Choi Y 

PROVIDER: S-EPMC12753718 | biostudies-literature | 2025 Dec

REPOSITORIES: biostudies-literature