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Prediction of COVID-19 transmission dynamics using a mathematical model considering behavior changes
Kim Soyoung.
Seo Yu Bin.
Jung Eunok.
Acceso Abierto
Atribución-NoComercial-SinDerivadas
10.4178/epih.e2020026
Objectives:Since the report of the first confirmed case in Daegu on February 18, 2020, local transmission of COVID-19 in the Republic of Korea has continued. In this study, we aimed to identify the pattern of local transmission of COVID-19 using mathematical modeling and predict the epidemic size and the timing of the end of the spread. Methods:We modeled the COVID-19 outbreak in the Republic of Korea by applying a mathematical model of transmission that factors in behavioral changes. We used the Korea Centers for Disease Control and Prevention data of daily confirmed cases in the country to estimate the nationwide and Daegu/Gyeongbuk area-specific transmission rates as well as behavioral change parameters using a least-squares method. Results:The number of transmissions per infected patient was estimated to be about 10 times higher in the Daegu/Gyeongbuk area than the average of nationwide. Using these estimated parameters, our models predicts that about 13,800 cases will occur nationwide and 11,400 cases in the Daegu/Gyeongbuk area until mid-June. Conclusion:We mathematically demonstrate that the relatively high per-capita rate of transmission and the low rate of changes in behavior have caused a large-scale transmission of COVID-19 in the Daegu/Gyeongbuk area in the Republic of Korea. Since the outbreak is expected to continue until May, nonpharmaceutical interventions that can be sustained over the long term are required.
Epidemiology and Health
2020
Artículo
http://www.e-epih.org/upload/pdf/epih-e2020026-AOP.pdf
Inglés
VIRUS RESPIRATORIOS
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