Phylogenetic analyses have increasingly been applied to pathogen populations. By combining the knowledge of when and where individuals get sick with the particular genotype of the infecting pathogen we can track pathogen movements through an area, both in space and in time. This information can be used to design prevention strategies and understand the key drivers of pathogen dispersal and persistence. By characterizing the changing clustering patterns of cases over time, we can potentially detect the spatial scale at which protective immunity is correlated. Identification of spatial pockets of immunity or lack thereof, could identify areas to target with interventions.
Dengue fever is a potentially life threatening viral infection that is transmitted by mosquitoes. It is endemic in many tropical and subtropical regions. We will use data from patients that presented at a Bangkok hospital between 1995 and 2010, including their geocoded home addresses and information on the infecting pathogen to gain insight into the dispersal dynamics of the disease. We hypothesize that there will be significant spatiotemporal clustering between cases of closely related viruses reflecting the dispersal of pathogen as it moves from individual to individual. Furthermore, disease clustering will be followed by a reduction of cases in particular spatial locations due to population immunity. This study will develop a range of geographical and genetic analysis methods. The findings could lead to improved disease intervention efforts and approaches applicable to other diseases. We will support our methods with simulations, demonstrating their robustness to dynamic patterns of spatiotemporal dependence.