University of Cambridge
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.