Modeling Incorporating the Severity-Reducing Long-term Immunity: Higher Viral Transmission Paradoxically Reduces Severe COVID-19 During Endemic Transitionopen accessModeling Incorporating the Severity-Reducing Long-term Immunity: Higher Viral Transmission Paradoxically Reduces Severe COVID-19 During Endemic Transition
- Other Titles
- Modeling Incorporating the Severity-Reducing Long-term Immunity: Higher Viral Transmission Paradoxically Reduces Severe COVID-19 During Endemic Transition
- Authors
- Hong, Hyukpyo; Noh, Ji Yun; Lee, Hyojung; Choi, Sunhwa; Choi, Boseung; Kim, Jae Kyoung; Shin, Eui-Cheol
- Issue Date
- 6월-2022
- Publisher
- KOREA ASSOC IMMUNOLOGISTS
- Keywords
- COVID-19; SARS-CoV-2; Immunity; Severity; Endemic transition
- Citation
- IMMUNE NETWORK, v.22, no.3, pp.1 - 12
- Indexed
- SCIE
SCOPUS
KCI
- Journal Title
- IMMUNE NETWORK
- Volume
- 22
- Number
- 3
- Start Page
- 1
- End Page
- 12
- URI
- https://scholar.korea.ac.kr/handle/2021.sw.korea/143035
- DOI
- 10.4110/in.2022.22.e23
- ISSN
- 1598-2629
- Abstract
- Natural infection with severe acute respiratory syndrome-coronavirus-2 or vaccination induces virus-specific immunity protecting hosts from infection and severe disease. While the infection-preventing immunity gradually declines, the severity-reducing immunity is relatively well preserved. Here, based on the different longevity of these distinct immunities, we develop a mathematical model to estimate courses of endemic transition of coronavirus disease 2019 (COVID-19). Our analysis demonstrates that high viral transmission unexpectedly reduces the rates of progression to severe COVID-19 during the course of endemic transition despite increased numbers of infection cases. Our study also shows that high viral transmission amongst populations with high vaccination coverages paradoxically accelerates the endemic transition of COVID-19 with reduced numbers of severe cases. These results provide critical insights for driving public health policies in the era of 'living with COVID-19.'
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Collections - College of Medicine > Department of Medical Science > 1. Journal Articles
- Graduate School > Department of Economics and Statistics > 1. Journal Articles
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