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

doi:10.1016/j.rinp.2021.104305

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

Results Phys. 2021 Jun:25:104305. doi: 10.1016/j.rinp.2021.104305. Epub 2021 May 13.

Authors

Huan Liu^{1

2}, Zhiwei Rong³, Xinye Qi^{1

2}, Jinming Fu⁴, Hao Huang⁴, Lei Cao³, Linghan Shan^{1

2}, Yashuang Zhao⁴, Kang Li³, Yanhua Hao^{1

2}, Mingli Jiao^{1

2}, Qunhong Wu^{1

2}, Xue Zhang⁵

Affiliations

¹ Department of Health Policy, Health Management College, Harbin Medical University, Harbin, Heilongjiang Province, China.
² Department of Social Medicine, School of Public Health, Harbin Medical University, Harbin, Heilongjiang Province, China.
³ Department of Biostatistics, School of Public Health, Harbin Medical University, Harbin, Heilongjiang Province, China.
⁴ Department of Epidemiology, School of Public Health, Harbin Medical University, Harbin, Heilongjiang Province, China.
⁵ NHC and CAMS Key Laboratory of Molecular Probe and Targeted Theragnostic, Harbin Medical University, Harbin, Heilongjiang Province, China.

Abstract

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.

Keywords: CDC, Chinese Center for Disease Control and Prevention; COVID-19, coronavirus disease 2019; Chinese provinces; Coronavirus disease 2019; Intervention effect intensity; Net-SEAIHRQ model; QR, healthy quick response; R0, basic reproduction number; Rt, effective reproduction number; SARS, severe acute respiratory syndrome; WHO, World Health Organization.