BMC Infectious Diseases (Feb 2021)

A cross-sectional study of the epidemic situation on COVID-19 in Gansu Province, China – a big data analysis of the national health information platform

  • Xuanchen Yan,
  • Jianjian Wang,
  • Jingwen Yao,
  • Janne Estill,
  • Shouyuan Wu,
  • Jie Lu,
  • Baoping Liang,
  • Hongmin Li,
  • Shengxin Tao,
  • Huanli Bai,
  • Hongliang Liu,
  • Yaolong Chen,
  • on behalf of COVID-19 evidence and recommendations working group

DOI
https://doi.org/10.1186/s12879-020-05743-8
Journal volume & issue
Vol. 21, no. 1
pp. 1 – 7

Abstract

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Abstract Background In December 2019, a pneumonia caused by SARS-CoV-2 emerged in Wuhan, China and has rapidly spread around the world since then. This study is to explore the patient characteristics and transmission chains of COVID-19 in the population of Gansu province, and support decision-making. Methods We collected data from Gansu Province National Health Information Platform. A cross-sectional study was conducted, including patients with COVID-19 confirmed between January 23 and February 6, 2020, and analyzed the gender and age of the patients. We also described the incubation period, consultation time and sources of infection in the cases, and calculated the secondary cases that occurred within Gansu for each imported case. Results We found thirty-six (53.7%) of the patients were women and thirty-one (46.3%) men, and the median ages were 40 (IQR 31–53) years. Twenty-eight (41.8%) of the 67 cases had a history of direct exposure in Wuhan. Twenty-five (52.2%) cases came from ten families, and we found no clear reports of modes of transmission other than family clusters. The largest number of secondary cases linked to a single source was nine. Conclusion More women than men were diagnosed with COVID-19 in Gansu Province. Although the age range of confirmed cases of COVID-19 in Gansu Province covered almost all age groups, most patients with confirmed COVID-19 tend to be middle aged persons. The most common suspected mode of transmission was through family cluster. Gansu and other settings worldwide should continue to strengthen the utilization of big data in epidemic control.

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