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A retrospective analysis of the dynamic transmission routes of the COVID-19 in mainland China.
Jiang, Xiandeng; Chang, Le; Shi, Yanlin.
  • Jiang X; School of Public Finance and Taxation, Southwestern University of Finance and Economics, Chengdu, 611130, Sichuan, People's Republic of China.
  • Chang L; Research School of Finance, Actuarial Studies, and Statistics, Australian National University, Canberra, ACT, 2601, Australia.
  • Shi Y; Department of Actuarial Studies and Business Analytics, Macquarie University, Sydney, NSW, 2109, Australia. yanlin.shi@mq.edu.au.
Sci Rep ; 10(1): 14015, 2020 08 19.
Article in English | MEDLINE | ID: covidwho-724730
ABSTRACT
The fourth outbreak of the Coronaviruses, known as the COVID-19, has occurred in Wuhan city of Hubei province in China in December 2019. We propose a time-varying sparse vector autoregressive (VAR) model to retrospectively analyze and visualize the dynamic transmission routes of this outbreak in mainland China over January 31-February 19, 2020. Our results demonstrate that the influential inter-location routes from Hubei have become unidentifiable since February 4, 2020, whereas the self-transmission in each provincial-level administrative region (location, hereafter) was accelerating over February 4-15, 2020. From February 16, 2020, all routes became less detectable, and no influential transmissions could be identified on February 18 and 19, 2020. Such evidence supports the effectiveness of government interventions, including the travel restrictions in Hubei. Implications of our results suggest that in addition to the origin of the outbreak, virus preventions are of crucial importance in locations with the largest migrant workers percentages (e.g., Jiangxi, Henan and Anhui) to controlling the spread of COVID-19.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: Pneumonia, Viral / Quarantine / Models, Statistical / Coronavirus Infections / Betacoronavirus Type of study: Observational study Limits: Humans Country/Region as subject: Asia Language: English Journal: Sci Rep Year: 2020 Document Type: Article

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Pneumonia, Viral / Quarantine / Models, Statistical / Coronavirus Infections / Betacoronavirus Type of study: Observational study Limits: Humans Country/Region as subject: Asia Language: English Journal: Sci Rep Year: 2020 Document Type: Article