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논문 기본 정보

자료유형
학술저널
저자정보
Hyukpyo Hong (Korea Advanced Institute of Science and Technology) Ji Yun Noh (Korea Advanced Institute of Science and Technology) Hyojung Lee (Kyungpook National University) Sunhwa Choi (National Institute for Mathematical Sciences) Boseung Choi (Institute for Basic Science) Jae Kyoung Kim (Korea Advanced Institute of Science and Technology) Eui-Cheol Shin (Korea Advanced Institute of Science and Technology)
저널정보
대한면역학회 Immune Network Immune Network Vol.22 No.3
발행연도
2022.6
수록면
47 - 58 (12page)

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초록· 키워드

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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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ABSTRACT
INTRODUCTION
MATERIALS AND METHODS
RESULTS
DISCUSSION
REFERENCES

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