How to incorporate mutation-induced infection waves of COVID-19?

Seung-ho Baek

University of Science and Technology / Korea Institute of Science and Technology / Korea Disease Control Agency, /AI-Information-Reasoning Laboratory

"How to incorporate mutation-induced infection waves of COVID-19?"

During the COVID-19 pandemic in past three years, a series of computational and mathematical approaches have been suggested to figure out the epidemic characteristics, which include the effectiveness of social distancing, vaccinations, and the spread itself. In spite of these efforts, high evolution rate of SARS-CoV-2 bears dominant variants of COVID-19 every four to eight months, which leads to failures of improving feasibility of long-term models and understandings. We also witnessed the latest dominant variant Omicron shows a three times higher transmission rate and limits two-dose vaccination against symptomatic infection. We suggest a intergrated mathemathical model, which incorperates three variants of COVID-19 at once, to understand daily pattern from October 2021 to June 2022. It separates subsequent dominant variant occupying twenty percent of the reported cases to GISAID. Indistinguishable patterns are observed in COVID-19 cases from USA, UK, Japan, and in South Korea. We are able to improve the viability of a four months COVID-19 incidence model by dividing the models according to the dominant variant in each period respectively. Based on these, we suggest that consideration of a change of dominant variant of SARS-CoV-2 is necessary in improvement of feasibility of short-term designed stochastic models to a longer-term prediction.
Additional authors: Seungho Baek1,2, Haneol Cho2, Myungsu Yoo3, Kyuhwan Lee2, Donghyuk Kwon3 Yeonju Kim3* , Chansoo Kim1,2*

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