Exploration of the Evaluation and Optimization of Community Epidemic Prevention in Wuhan Based on a DEA Model

Int J Environ Res Public Health. 2020 Oct 20;17(20):7633. doi: 10.3390/ijerph17207633.

Abstract

Background-Communities played a key role in preventing the spread of coronavirus, not only during the threshold period of the epidemic but also in the normal stage of prevention. Scientifically evaluating the community's work is necessary for prevention in the normal period of the epidemic and can provide a reference for the management of different countries. Methods-Based on data envelopment analysis (DEA), this article used community worker data to evaluate the matching of service supply and demand during the epidemic period and used co-word analysis to analyze the content and the residents' demands for community service from the threshold period to the normal period of the epidemic. Results-According to the results of the DEA model, early in the epidemic, 13 of the 15 districts' DEA values were invalid, indicating that there was a shortage in community workers in Wuhan. The results of public opinion analysis showed that from the threshold to the normal period of the epidemic, the emphasis on community service gradually transformed from epidemic prevention to an integrated service, which effectively met the composite service needs of community residents for both prevention and life. Conclusions-In the face of public health emergencies, the government should ensure an adequate number of service personnel, mobilize the service resources, refine the service content, and adjust the incentive policy, which can help to improve the quality of residents' lives and the coordination degree of the prevention and control as part of the epidemic control in the emergency period and the social and economic recovery after the epidemic.

Keywords: DEA; co-word analysis; community; epidemic.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • China / epidemiology
  • Community Health Services / organization & administration*
  • Epidemics / prevention & control*
  • Humans
  • Models, Theoretical