Doctoral Dissertation Research: Using Phylogeography To Understand the Spatiotemporal Clustering of Dengue Cases in Bangkok

传染病在流行环境中的时空动态往往特征不佳。在感染持续发生的环境中，很难阐明传播链和病原体在太空中的运动。系统地理学领域提出了一个潜在的解决方案。通过将感染个体的时空位置与感染病原体的基因序列相结合，可以跟踪个体病毒在一个地区移动的谱系。这些信息对于增加反应和理解创造和维持病原体多样性的机制非常有用。这个博士论文研究项目将使用地理编码的家庭地址和感染血清型的6659名患者，这些患者在1995年至2010年期间在曼谷一家医院被诊断出患有登革热的四种血清型之一。此外，将从2006年起对感染病毒的部分病例进行基因组测序。这位博士生将使用调整后的时空统计方法分析登革热病例之间的时空相关性，以了解同一病毒谱系的病例在距离和空间上往往彼此相距多远。此外，病例在时间上的聚集行为将被描述为描述小空间尺度上随时间的空间依赖模式的变化模式，这种模式可以通过特定血清型的社区免疫效应来诱导。登革热是一种潜在威胁生命的蚊媒病毒疾病，每年在全球造成至少3600万例有症状的病例。通过了解感染同一谱系病毒的个体的时空聚集性，该项目将提供对可能推动疾病传播的原因的洞察。此外，了解与传播有关的病例发生的空间和时间范围将有助于确定面临感染风险的人群，并将提供关于在发现指示病例时向邻近家庭喷洒杀虫剂的空间距离的指导。该项目将提供一个机会，以了解在已成为登革热感染关键地点的大型地方性城市环境中疾病生态的潜在驱动因素。本项目中开发的方法将可推广到其他时空点模式，对于这些点，贴在点上的标签存在异质性(例如，基因或物种)，或者在动态系统中，潜在的时空相关性存在变化的模式。作为博士论文研究改进奖，该奖项还将提供支持，使有前途的学生建立一个强大的独立研究生涯。

The spatiotemporal dynamics of infectious diseases in endemic settings often are poorly characterized. In settings where infections are continuously occurring, it is difficult to elucidate transmission chains and the movement of pathogens in space. The field of phylogeography presents a potential solution. By combining the spatiotemporal location of individuals who become infected with the genetic sequence of the infecting pathogen, it is possible to track individual viral lineages as they move through a region. This information can be extremely useful for mounting responses and for understanding the mechanisms that create and maintain pathogen diversity. This doctoral dissertation research project will use geocoded home addresses and infecting serotypes of 6,659 patients who were diagnosed with one of the four serotypes of dengue fever at a Bangkok hospital between 1995 and 2010. In addition, the genome of the infecting virus will be sequenced for a subset of cases from 2006. The doctoral student will analyze spatiotemporal dependence between dengue cases using adapted space-time statistics to understand how far, both in distance and space, cases from the same viral lineage tend to occur from each other. Furthermore, the clustering behavior of cases across time lags will be characterized to describe the changing patterns of spatial dependence at small spatial scales through time that could be induced through serotype-specific community immunity effects.Dengue fever is a potentially life-threatening mosquito-borne viral disease that causes at least 36,000,000 symptomatic cases every year across the globe. By understanding the spatiotemporal clustering of individuals infected with viruses from the same lineage, this project will provide insight into what may be driving the dispersal of the disease. Furthermore, understanding the spatial and temporal extent at which transmission-related cases occur will facilitate the identification of populations at risk of infection and will provide guidance regarding the spatial distances at which to implement insecticide spraying of neighboring homes upon detection of an index case. This project will provide an opportunity to understand the potential drivers of disease ecology in a large endemic urban setting that have become the key location for dengue infections. The approaches developed in this project will be generalizable to other spatiotemporal point patterns for which there are heterogeneities in the labels attached to points (such as genotype or species) or in dynamic systems where there are changing patterns in underlying spatiotemporal dependence. As a Doctoral Dissertation Research Improvement award, this award also will provide support to enable a promising student to establish a strong independent research career.