基于输入输出流的呼吸道传染病时空传播网络建模研究

项目名称： 基于输入输出流的呼吸道传染病时空传播网络建模研究

项目编号： No.41301430

项目类型： 青年科学基金项目

立项/批准年度： 2014

项目学科： 天文学、地球科学

项目作者： 胡碧松

作者单位： 江西师范大学

项目金额： 25万元

中文摘要： 关注呼吸道传染病流行中个体在健康-受感染-发病-就诊-康复过程中的角色转变与位置变化模式所引起的区域之间信息流与物质流的输入与输出交互作用，基于区域节点定义疾病传播输入输出流，依据小世界网络建模方法构建疾病时空传播网络模型，以时空统计分析与复杂网络理论方法探索其时空分布特征、网络结构与演化机制。考虑区域之间交互作用效应及个体活动行为准则与社会关系引起的空间与关系接触传播效果，以SARS流行为例进行模拟实验并对该模型进行有效性验证和精度对比分析。基于输入输出流与时空传播网络的研究可更好解释疾病传播过程中个体角色转变与位置变化引起的区域之间交互作用模式，可从个体和区域两个角度来探索病毒感染扩散的输入与输出传播机制并揭示区域之间信息流与物质流的传播网络结构特征，更有利于探测和揭示大规模疾病流行的整体时空演化特征与潜在传播规律，为未来新型疾病爆发的应急决策与防控措施提供更有效理论依据与技术支撑。

中文关键词： 空间统计学；医学与健康系统建模；时空传播网络；输入输出流；特征分析

英文摘要： For better detecting the changing spatial-temporal pattern of individual susceptible-infected-symptomatic-treated-recovered epidemic process and the interactions of information/material flows between regions, epidemic in-out flow between regions is defined and the corresponding spatial-temporal transmission network is built according to small-world network modeling. The spatiotemporal distribution characteristics of epidemic in-out flow, and the network structure and evolvement mechanism of epidemic spatial-temporal transmission network are explored by spatial statistics and complex network methods. The model is improved by considering the interactive effects between regions and spatial/social contacts between individuals caused by individual behavior rules and social relationships. The simulation experiment is implemented with SARS epidemic as a case study, and the accuracy/precision validation of the proposed model is analyzed. Study on epidemic in-out flow and spatial-temporal transmission network could better explain the changing pattern of individual epidemic roles and the input/output interactions between regions, explore the structural characteristics of transmission network and the epidemic spread mechanism of virus input/output based on individuals and spatial regions, better detect and discover the spa

英文关键词： spatial statistics；medical and health modeling；spatial-temporal transmission network；in-out flow；characteristic analysis