郑州大学学报（工学版）2025，Vol.46Issue(4)：76-84,9.DOI:10.13705/j.issn.1671-6833.2025.04.003
基于城市接触网络的新发传染病风险监测
Emerging Infectious Disease Risk Surveillance Based on Urban Contact Networks
摘要
Abstract
Given the challenge of limited high-resolution human contact data during the early stages of emerging infectious disease outbreaks,it is difficult to implement early warning strategies via the global structural characteristics of contact networks.Multi-source data-driven sentinel surveillance strategies for infectious diseases were the focuses of this study,and a novel framework for emerging infectious disease risk surveillance based on ur-ban contact networks was proposed.By integrating multi-source census and survey data,a contact network reflecting the characteristics of the urban population structure was constructed to simulate the transmission of emerging infectious disease in specific cities.Based on this,a"one person per household"surveillance strategy was proposed.This strategy leveraged a small number of selected sentinel samples to achieve near-whole population coverage for effective risk surveillance,eliminating the need for prior knowledge of the global network structure.Experimental results demonstrated that during periods of low disease transmissibility(basic reproduction number of 1.2),the proposed household surveillance strategy performed at the same level to the random surveillance strategy,while with lower cost compared with surveillance the whole population.As transmissibility increased(basic reproduction number from 2.0 to 3.0),the early warning performance of household surveillance strategy ranked the second only to the most connected strategy,effectively capturing the transmission of emerging infectious diseases.Notably,it effectively captured the transmission risk of emerging infectious diseases,providing an early warning time of 1.03 d(37%)and 0.69 d(53%)compared with the random surveillance strategy.关键词
接触网络/风险监测/传染病建模/早期预警/大数据挖掘Key words
contact network/risk surveillance/infectious disease modelling/early warning/big data mining分类
信息技术与安全科学引用本文复制引用
徐铭达,杜占玮,王震,高超..基于城市接触网络的新发传染病风险监测[J].郑州大学学报（工学版）,2025,46(4):76-84,9.基金项目
国家重点研发计划资助项目(2022YFE0112300) （2022YFE0112300）
深港澳科技计划项目(C类项目)(SGDX20230821091559022) （C类项目）
