An Integrated Approach to Evaluating the Spatial Allocation Efficiency of Urban Public Health Surveillance

Contingency epidemic outbreaks, such as the novel coronavirus (COVID-19) pandemic in 2020, have underscored the vital function of public health emergency response systems within national strategic frameworks. Public health surveillance and early warnings are imperative for safeguarding peoples’ lives, maintaining social stability, and promoting economic development. Existing studies are inadequate for accurately evaluating the efficiency of an urban public health surveillance system from a comprehensive perspective. In this work, an integrated framework was proposed for the evaluation of the spatial allocation efficiency of urban public health surveillance. This integrated approach incorporates three key aspects, spatial coverage, overlap, and accessibility, enabling a measurable evaluation of the overall spatial allocation efficiency. We utilized the proposed method to investigate the placement efficiency of the nucleic acid testing sites during the epidemic in Nanchang, China. The findings showed that using the integrated evaluation method based on coverage, overlap, and accessibility provides a more accurate reflection of the efficiency of existing site placements. It offers a flexible measurement system for evaluating urban surveillance site allocation strategies. This study introduces a novel perspective for the efficiency assessment of public health surveillance site placements, contributes to the development of public health emergency response systems, and provides a technical foundation for future contingency planning in public health surveillance.

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Publication Details

Journal
ISPRS International Journal of Geo-Information
Published
2026-02-14
DOI
https://doi.org/10.3390/ijgi15020081
Primary Topic
Data-Driven Disease Surveillance
Type
article
Field-Weighted Citation Impact
0.00

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article

An Integrated Approach to Evaluating the Spatial Allocation Efficiency of Urban Public Health Surveillance

Shuzhen Xiao, Bisong Hu
ISPRS International Journal of Geo-Information
Data-Driven Disease Surveillance
article

An Integrated Approach to Evaluating the Spatial Allocation Efficiency of Urban Public Health Surveillance

Shuzhen Xiao, Bisong Hu
article en

Abstract

Contingency epidemic outbreaks, such as the novel coronavirus (COVID-19) pandemic in 2020, have underscored the vital function of public health emergency response systems within national strategic frameworks. Public health surveillance and early warnings are imperative for safeguarding peoples’ lives, maintaining social stability, and promoting economic development. Existing studies are inadequate for accurately evaluating the efficiency of an urban public health surveillance system from a comprehensive perspective. In this work, an integrated framework was proposed for the evaluation of the spatial allocation efficiency of urban public health surveillance. This integrated approach incorporates three key aspects, spatial coverage, overlap, and accessibility, enabling a measurable evaluation of the overall spatial allocation efficiency. We utilized the proposed method to investigate the placement efficiency of the nucleic acid testing sites during the epidemic in Nanchang, China. The findings showed that using the integrated evaluation method based on coverage, overlap, and accessibility provides a more accurate reflection of the efficiency of existing site placements. It offers a flexible measurement system for evaluating urban surveillance site allocation strategies. This study introduces a novel perspective for the efficiency assessment of public health surveillance site placements, contributes to the development of public health emergency response systems, and provides a technical foundation for future contingency planning in public health surveillance.

ISPRS International Journal of Geo-InformationVol. 15(2)
Jiangxi Normal University (CN)
National Natural Science Foundation of China
Sustainable cities and communities
Openalex Percentile: Top 54%
Data-Driven Disease Surveillance
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