ArticlePloS one2026
Construction of a public health emergency information system framework: A case study of Zhuhai city, China.
Article in PloS one, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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8 authors.
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Abstract
backgroundA public health emergency information system serves as a critical tool for collecting and analyzing data from sudden public health events, thereby providing a scientific basis for governmental decision-making. However, research on the systematic construction of such information system frameworks within China's public health infrastructure is lacking.
objectiveTaking Zhuhai city as a case study, this study aims to construct a comprehensive public health emergency information system framework applicable to public health departments at the municipal, county, and street/township levels.
methodsFirst, through a literature review and expert group discussion, the preliminary framework of system indicators is determined. Second, through two rounds of the Delphi method, 41 experts are invited to qualitatively select the system framework indicators, with the aim of obtaining consensus among experts. Finally, the system is improved through application, feedback, and redesign.
resultsAfter two rounds of consultation, the final system at the city and county levels consists of 5 first-level indicator modules and 21 second-level indicator modules, whereas the system at the city, county, and street/township levels consists of 4 first-level indicator modules and 17 second-level indicator modules. Most of the indicators in the "emergency preparedness" and "emergency response" modules are considered important and should be retained as they can play a role in collecting and analysing information on infectious disease outbreaks through practical applications.
conclusionThe public health emergency information system constructed in this study can be applied to public health departments such as disease prevention and control centres. Promotion can improve the efficiency of handling infectious disease outbreaks and provide a scientific basis for decision-making analysis.
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