Estimation of COVID-19 Transmission and Advice on Public Health Interventions

Qingqing Ji, Xu Zhao, Hanlin Ma, Qing Liu, Yiwen Liu and Qiyue Guan
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Qingqing Ji: University of Chinese Academy of Sciences, Beijing 100049, China
Xu Zhao: Faculty of Science, Beijing University of Technology, Beijing 100124, China
Hanlin Ma: Faculty of Science, Beijing University of Technology, Beijing 100124, China
Qing Liu: Faculty of Science, Beijing University of Technology, Beijing 100124, China
Yiwen Liu: University of Chinese Academy of Sciences, Beijing 100049, China
Qiyue Guan: Party School of the Central Committee of C.P.C (National Academy of Governance), Beijing 100091, China

Mathematics, 2021, vol. 9, issue 22, 1-18

Abstract: At the end of 2019, an outbreak of the novel coronavirus (COVID-19) made a profound impact on the country’s production and people’s daily lives. Up until now, COVID-19 has not been fully controlled all over the world. Based on the clinical research progress of infectious diseases, combined with epidemiological theories and possible disease control measures, this paper establishes a Susceptible Infected Recovered (SIR) model that meets the characteristics of the transmission of the new coronavirus, using the least square estimation (LSE) method to estimate the model parameters. The simulation results show that quarantine and containment measures as well as vaccine and drug development measures can control the spread of the epidemic effectively. As can be seen from the prediction results of the model, the simulation results of the epidemic development of the whole country and Nanjing are in agreement with the real situation of the epidemic, and the number of confirmed cases is close to the real value. At the same time, the model’s prediction of the prevention effect and control measures have shed new light on epidemic prevention and control.

Keywords: novel coronavirus; epidemic control; traffic control measures; least square estimation; SIR model (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2021
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