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Levels of economic growth and cross-province spread of the COVID-19 in China
  1. Qiqing Mo1,2,3,
  2. Xinguang Chen2,4,
  3. Bin Yu2,
  4. Zhenyu Ma1
  1. 1 School of Public Health, Guangxi Medical University, Nanning, China
  2. 2 Department of Epidemiology, University of Florida, Gainesville, Florida, USA
  3. 3 Guilin Peoples Hospital, Guilin, China
  4. 4 Global Health Institute, Wuhan University, Wuhan, China
  1. Correspondence to Dr Zhenyu Ma, School of Public Health, Guangxi Medical University, Nanning 530021, China; ma_zhenyu{at}


Background After the first COVID-19 case detected on 8 December 2019 in Wuhan, the Provincial Capital of Hubei, the epidemic quickly spread throughout the whole country of China. Low developmental levels are often associated with infectious disease epidemic, this study attempted to test this notion with COVID-19 data.

Methods Data by province from 8 December 2019 to 16 February 2020 were analysed using regression method. Outcomes were days from the first COVID-19 case in the origin of Hubei Province to the date when case was first detected in a destination province, and cumulative number of confirmed cases. Provincial gross domestic products (GDPs) were used to predict the outcomes while considering spatial distance and population density.

Results Of the total 70 548 COVID-19 cases in all 31 provinces, 58 182 (82.5%) were detected in Hubei and 12 366 (17.5%) in other destination provinces. Regression analysis of data from the 30 provinces indicated that GDP was negatively associated with days of virus spreading (β=−0.2950, p<0.10) and positively associated with cumulative cases (β=97.8709, p<0.01) after controlling for spatial distance. The relationships were reversed with β=0.1287 (p<0.01) for days and β=−54.3756 (p<0.01) for cumulative cases after weighing in population density and controlling for spatial distance.

Conclusion Higher levels of developmental is a risk factor for cross-province spread of COVID-19. This study adds new data to literature regarding the role of economic growth in facilitating spatial spreading of infectious diseases, and provides timely data informing antiepidemic strategies and developmental plan to balance economic growth and people’s health.

  • epidemics
  • health policy
  • social epidemiology
  • socio-economic

Data availability statement

All data relevant to the study are included in the article or uploaded as supplementary information. The data in our study were public available and collected from official websites.

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Data availability statement

All data relevant to the study are included in the article or uploaded as supplementary information. The data in our study were public available and collected from official websites.

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  • Contributors QM conducted data collection, data management, the analysis and drafted the manuscript. XC designed the study and conducted data management, revised the manuscript. BY undertook the statistical analysis and revised the draft. ZM designed the study and wrote the protocol, references management and revised the draft. All authors contributed to and have approved the final manuscript.

  • Funding The authors have not declared a specific grant for this research from any funding agency in the public, commercial or not-for-profit sectors.

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  • Competing interests None declared.

  • Provenance and peer review Not commissioned; externally peer reviewed.