Construction and Application of a Refined Spatiotemporal Transmission Risk Assessment System for Urban Respiratory Infectious Diseases
Objective This study aims to develop a decision support system that can effectively assess the transmission risk of respiratory infectious diseases at a high spatial resolution within an urban environment,with the aid of multi-source urban big data.Methods With the focus of respiratory diseases like influenza,this study integrates multi-source big data such as epidemics,human activity,and geographic environments,and develops a transmission risk assessment model through the Delphi method at a 500-meter grid.We then develop a spatiotemporal transmission simulation model for intra-urban epidemic spread based on population movements,projecting future epidemic trend at both spatial and temporal dimensions with a high resolution.Then,the high-risk areas of infectious disease transmission were selected as the critical spatial control nodes,and the spatiotemporal transmission simulation model is used to assess the effectiveness of controlling these critical nodes.Results Taking Shenzhen city as an example,a spatiotemporal transmission risk assessment system for respiratory infectious diseases with a high spatial resolution has been developed.Conclusion This study offers a transmission risk assessment system for the spatiotemporal spread of respiratory infectious diseases at an intra-urban scale,enabling the assessment of spatiotemporal epidemic trends and rapid prediction of the effectiveness of control measures at various stages of an epidemic outbreak,providing technical support for a more precise epidemic control.
respiratory infectious diseasesepidemic modelspatiotemporal big Datapopulation movementgeographic information decision support system
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