Department of Physics,Research Center for Academic Excellence in Applied Physics,Faculty of Science,Naresuan University,Phitsanulok 65000,Thailand.
Institute for Disease Modeling,Bellevue,WA 98005,USA.
Epidemiol Infect. 2018 Oct;146(13):1654-1662. doi: 10.1017/S0950268818001917. Epub 2018 Jul 9.
Human movement contributes to the probability that pathogens will be introduced to new geographic locations. Here we investigate the impact of human movement on the spatial spread of Chikungunya virus (CHIKV) in Southern Thailand during a recent re-emergence. We hypothesised that human movement, population density, the presence of habitat conducive to vectors, rainfall and temperature affect the transmission of CHIKV and the spatiotemporal pattern of cases seen during the emergence. We fit metapopulation transmission models to CHIKV incidence data. The dates at which incidence in each of 151 districts in Southern Thailand exceeded specified thresholds were the target of model fits. We confronted multiple alternative models to determine which factors were most influential in the spatial spread. We considered multiple measures of spatial distance between districts and adjacency networks and also looked for evidence of long-distance translocation (LDT) events. The best fit model included driving-distance between districts, human movement, rubber plantation area and three LDT events. This work has important implications for predicting the spatial spread and targeting resources for control in future CHIKV emergences. Our modelling framework could also be adapted to other disease systems where population mobility may drive the spatial advance of outbreaks.
人类活动增加了病原体传播到新地理区域的可能性。本研究调查了在泰国南部最近一次基孔肯雅热(CHIKV)疫情重新爆发期间,人类活动对 CHIKV 空间传播的影响。我们假设人类活动、人口密度、有利于病媒滋生的栖息地的存在、降雨量和温度会影响 CHIKV 的传播以及疫情爆发期间病例的时空分布模式。我们拟合了虫媒病毒传播模型来分析 CHIKV 的发病数据。拟合模型的目标是泰国南部 151 个地区中每个地区发病率超过特定阈值的日期。我们对比了多个替代模型,以确定哪些因素对空间传播的影响最大。我们考虑了地区之间的多种空间距离度量和邻接网络,并寻找远距离转移(LDT)事件的证据。最佳拟合模型包括地区之间的行车距离、人类活动、橡胶种植园面积和三个 LDT 事件。这项工作对于预测未来 CHIKV 疫情的空间传播和定位控制资源具有重要意义。我们的建模框架还可以适应其他可能因人口流动而导致疫情空间推进的疾病系统。