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The spatiotemporal estimation of the risk and the international transmission of COVID-19: a global perspective.
Lin, Yuan-Chien; Chi, Wan-Ju; Lin, Yu-Ting; Lai, Chun-Yeh.
  • Lin YC; Department of Civil Engineering, National Central University, Taoyuan, 32001, Taiwan. yclin@ncu.edu.tw.
  • Chi WJ; Research Center for Hazard Mitigation and Prevention, National Central University, Taoyuan, 32001, Taiwan. yclin@ncu.edu.tw.
  • Lin YT; Department of Civil Engineering, National Central University, Taoyuan, 32001, Taiwan.
  • Lai CY; Department of Civil Engineering, National Central University, Taoyuan, 32001, Taiwan.
Sci Rep ; 10(1): 20021, 2020 11 18.
Article in English | MEDLINE | ID: covidwho-933724
ABSTRACT
An ongoing novel coronavirus outbreak (COVID-19) started in Wuhan, China, in December 2019. Currently, the spatiotemporal epidemic transmission, prediction, and risk are insufficient for COVID-19 but we urgently need relevant information globally. We have developed a novel two-stage simulation model to simulate the spatiotemporal changes in the number of cases and estimate the future worldwide risk. Simulation results show that if there is no specific medicine for it, it will form a global pandemic. Taiwan, South Korea, Hong Kong, Japan, Thailand, and the United States are the most vulnerable. The relationship between each country's vulnerability and days before the first imported case occurred shows an exponential decrease. We successfully predicted the outbreak of South Korea, Japan, and Italy in the early stages of the global pandemic based on the information before February 12, 2020. The development of the epidemic is now earlier than we expected. However, the trend of spread is similar to our estimation.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: Models, Statistical / Pandemics / COVID-19 Type of study: Observational study / Prognostic study Limits: Humans Language: English Journal: Sci Rep Year: 2020 Document Type: Article Affiliation country: S41598-020-77242-4

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Models, Statistical / Pandemics / COVID-19 Type of study: Observational study / Prognostic study Limits: Humans Language: English Journal: Sci Rep Year: 2020 Document Type: Article Affiliation country: S41598-020-77242-4