Comparative and quantitative analysis of COVID-19 epidemic interventions in Chinese provinces

Huan Liu; Zhiwei Rong; Xinye Qi; Jinming Fu; Hao Huang; Lei Cao; Linghan Shan; Yashuang Zhao; Kang Li; Yanhua Hao; Mingli Jiao; Qunhong Wu; Xue Zhang

Results in Physics (Jun 2021)

Comparative and quantitative analysis of COVID-19 epidemic interventions in Chinese provinces

Huan Liu,
Zhiwei Rong,
Xinye Qi,
Jinming Fu,
Hao Huang,
Lei Cao,
Linghan Shan,
Yashuang Zhao,
Kang Li,
Yanhua Hao,
Mingli Jiao,
Qunhong Wu,
Xue Zhang

Affiliations

Huan Liu: Department of Health Policy, Health Management College, Harbin Medical University, Harbin, Heilongjiang Province, China; Department of Social Medicine, School of Public Health, Harbin Medical University, Harbin, Heilongjiang Province, China
Zhiwei Rong: Department of Biostatistics, School of Public Health, Harbin Medical University, Harbin, Heilongjiang Province, China
Xinye Qi: Department of Health Policy, Health Management College, Harbin Medical University, Harbin, Heilongjiang Province, China; Department of Social Medicine, School of Public Health, Harbin Medical University, Harbin, Heilongjiang Province, China
Jinming Fu: Department of Epidemiology, School of Public Health, Harbin Medical University, Harbin, Heilongjiang Province, China
Hao Huang: Department of Epidemiology, School of Public Health, Harbin Medical University, Harbin, Heilongjiang Province, China
Lei Cao: Department of Biostatistics, School of Public Health, Harbin Medical University, Harbin, Heilongjiang Province, China
Linghan Shan: Department of Health Policy, Health Management College, Harbin Medical University, Harbin, Heilongjiang Province, China; Department of Social Medicine, School of Public Health, Harbin Medical University, Harbin, Heilongjiang Province, China
Yashuang Zhao: Department of Epidemiology, School of Public Health, Harbin Medical University, Harbin, Heilongjiang Province, China
Kang Li: Department of Biostatistics, School of Public Health, Harbin Medical University, Harbin, Heilongjiang Province, China
Yanhua Hao: Department of Health Policy, Health Management College, Harbin Medical University, Harbin, Heilongjiang Province, China; Department of Social Medicine, School of Public Health, Harbin Medical University, Harbin, Heilongjiang Province, China
Mingli Jiao: Department of Health Policy, Health Management College, Harbin Medical University, Harbin, Heilongjiang Province, China; Department of Social Medicine, School of Public Health, Harbin Medical University, Harbin, Heilongjiang Province, China
Qunhong Wu: Department of Health Policy, Health Management College, Harbin Medical University, Harbin, Heilongjiang Province, China; Department of Social Medicine, School of Public Health, Harbin Medical University, Harbin, Heilongjiang Province, China; Corresponding authors at: Department of Health Policy, Health Management College, Harbin Medical University, Harbin, Heilongjiang Province, China. Department of Social Medicine, Health Management College, Harbin Medical University, Harbin, Heilongjiang Province, China (Q. Wu). NHC and CAMS Key Laboratory of Molecular Probe and Targeted Theragnostic, Harbin Medical University, Harbin, Heilongjiang Province, China (X. Zhang).
Xue Zhang: NHC and CAMS Key Laboratory of Molecular Probe and Targeted Theragnostic, Harbin Medical University, Harbin, Heilongjiang Province, China; Corresponding authors at: Department of Health Policy, Health Management College, Harbin Medical University, Harbin, Heilongjiang Province, China. Department of Social Medicine, Health Management College, Harbin Medical University, Harbin, Heilongjiang Province, China (Q. Wu). NHC and CAMS Key Laboratory of Molecular Probe and Targeted Theragnostic, Harbin Medical University, Harbin, Heilongjiang Province, China (X. Zhang).

Journal volume & issue: Vol. 25
p. 104305

Abstract

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A mathematical model was developed to evaluate and compare the effects and intensity of the coronavirus disease 2019 prevention and control measures in Chinese provinces. The time course of the disease with government intervention was described using a dynamic model. The estimated government intervention parameters and area difference between with and without intervention were considered as the intervention intensity and effect, respectively. The model of the disease time course without government intervention predicted that by April 30, 2020, about 3.08% of the population would have been diagnosed with coronavirus disease 2019 in China. Guangdong Province averted the most cases. Comprehensive intervention measures, in which social distancing measures may have played a greater role than isolation measures, resulted in reduced infection cases. Shanghai had the highest intervention intensity. In the context of the global coronavirus disease 2019 pandemic, the prevention and control experience of some key areas in China (such as Shanghai and Guangdong) can provide references for outbreak control in many countries.

Published in Results in Physics

ISSN: 2211-3797 (Online)
Publisher: Elsevier
Country of publisher: Netherlands
LCC subjects: Science: Physics
Website: http://www.journals.elsevier.com/results-in-physics/

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