Computational modeling of COVID-19 transmission and intervention strategies in South Korea

We present computational modeling of COVID-19 transmission and intervention strategies including vaccination and social-distancing. Furthermore, epidemiological distributions of the coronavirus disease 2019 (COVID-19), including the intervals from symptom onset to diagnosis, reporting, or death, are important for developing effective disease-control strategies. COVID-19 case data from a national database maintained by the Korea Disease Control and Prevention Agency (KDCA) and the Central Disease Control Headquarters were analysed.  

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Arizona ,United States ,United Kingdom ,South Korea ,Korea ,British ,Carlos Castillo Chavez ,University Of British Columbia ,Arizona State University ,Department Of Mathematics At Soongsil University ,Prevention Agency ,Korea Disease Control ,Central Disease Control Headquarters ,Central Disease Control ,Soongsil University ,British Columbia ,