Mathematical modeling for estimating the unidentified infected population of COVID-19

The COVID-19 pandemic continues and causes major damage worldwide for more than a year. To prevent the spread of the infectious disease, it is significantly important to estimate the number of people who are infected but have not yet been confirmed because they can rapidly infect other people. Therefore, a mathematical model is proposed for predicting the unidentified infected population of COVID-19. This is the Susceptible-Unidentified infected-Confirmed (SUC) model, which is simple. Moreover, the proposed model is potentially useful in estimating the unidentified infected population to secure enough supplies for infection prevention, to prepare for testing and treatment of confirmed COVID-19 patients, and to monitor the impact of the new policies such as social distancing and school closures. Therefore, it is critical to estimate the unidentified infected population to control the spread of COVID-19.