Mathematical model suggests a clue as to when the COVID-19 pandemic will become an endemic
Mathematical model suggests a clue as to when the COVID-19 pandemic will become an endemic

Mathematical model suggests a clue as to when the COVID-19 pandemic will become an endemic

A mathematical model showed that high transmission rates among highly vaccinated populations of COVID-19 ultimately reduce the number of serious cases. This model suggests a clue as to when this pandemic will turn into an endemic one.

With the future of the pandemic still uncertain, a research team of mathematicians and medical researchers analyzed a mathematical model that could predict how the altered transmission rate of COVID-19 would affect the unwinding process of the virus as a mild respiratory virus.

The team led by Professor Jae Kyoung Kim of the Department of Mathematical Sciences and Professor Eui-Cheol Shin of the Graduate School of Medical Science and Engineering used a new approach by dividing the human immune response to SARS-CoV-2 into a shorter-term neutralizing antibody response and a long-lasting T-cell immune response and apply them each to a mathematical model. In addition, the analysis was based on the fact that although breakthrough infection may occur frequently, the patient’s immune response will be boosted after recovery from each breakthrough infection.

The results showed that in an environment with a high vaccination rate, although COVID-19 cases may increase temporarily when the transmission rate increases, the ratio of critical cases would eventually decrease, thereby reducing the total number of critical cases and actually settling COVID-19 as a mild respiratory disease faster.

Conditions where the number of cases may increase include relaxing social distance measures or the increase in variants with higher transmission rates such as the Omicron variant. This research did not take into account the less virulent property of the Omicron variant, but focused on the results of its high transmission rate, thereby predicting what may happen in the process of the endemic transition of COVID-19.

The research team pointed out the limitations of their mathematical model, such as the lack of consideration for age or patients with underlying diseases, and explained that the results of this study should be used with caution when compared to high-risk groups. In addition, as medical systems can collapse when the number of cases increases sharply, this study should be interpreted with caution and applied accordingly. The research team therefore emphasized that in order for policies that encourage a gradual return to normality to be successful, sustainable maintenance of public health systems is indispensable.

Professor Kim said, “We have drawn a counterintuitive conclusion in the midst of the unpredictable pandemic through an appropriate mathematical model,” arguing the importance of applying mathematical models to medical research.

Professor Shin said: “Although the Omicron variant has become the dominant tribe and the number of cases is rising rapidly in South Korea, it is important to use scientific approaches to predict the future and apply them to policies instead of fearing the current situation.”

The results of the research were published on on February 11 under the title “Increasing viral transmission paradoxically reduces progression rates to severe COVID-19 during endemic transition.”

This research was funded by the Institute of Basic Science, the Korea Health Industry Development Institute and the National Research Foundation of Korea.

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