Substantive interests: tropical infectious diseases, global health, human migration/movement patterns, maternal and child health
Methodological approaches: geographic information systems (GIS), spatial and spatiotemporal analysis
recent research has focused on:
Access to effective healthcare
Recent work has focused on the impact of providing community based malaria diagnosis and treatment, coupled with targeted mass drug administration in high prevalence communities, on overall malaria incidence in Kayin State, Myanmar. Our work (with the Malaria Elimination Task Force at Shoklo Malaria Research Unit (SMRU)) shows that by providing easy to access diagnosis and treatment, P. falciparum malaria can be drastically reduced. Complete elimination from a target area likely requires other interventions that are able to detect and treat asymptomatic carriers.
Space-time patterns (clustering/dispersal) of infectious diseases across landscapes (both small- and large-scale)
Some recent micro-scale work has shown that clustering of malaria infections (in Pailin Province of Cambodia and Kayin State of Myanmar) can be quite difficult to predict, frustrating public health interventions that target small spatial units.
We’ve also been working on migration patterns among tuberculosis (and multi-drug resistant tuberculosis) patients on the Thailand-Myanmar border (in collaboration with the TB group at Shoklo Malaria Research Unit). Our work shows that individuals with MDR-TB infections are sometimes quite mobile, and that acquiring and completing proper treatment can be difficult because of their migrant statuses. Not only does this mean that treatment is lacking, but also that the disease can easily be spread across wide-spanning landscapes in the absence of good treatment options.
Exposure to and risk of acquiring infectious diseases or other negative health outcomes
Some recent work on exposure to infectious diseases has included mapping of exposure to Anopheles mosquito bites, using Anopheles salivary biomarkers (in collaboration with colleagues from IRD and SMRU). We’ve shown that hotspots of exposure to Anopheles bites overlap with hotspots of malaria infections, and that heterogeneities in exposure to Anopheles bites can be extreme even at small spatial scales (sub-village level). We are now doing similar work with Aedes salivary biomarkers in collaboration with colleagues at NIAID in Cambodia (protocol paper here).
Empirically defining connectivity matrices
Many spatial analyses (e.g. analyses of spatial autocorrelation, spatial regressions, interpolation) rely on an underlying connectivity matrix. Most times these matrices are specified based on hypotheses or assumptions about potential connections between points or places in the dataset, without any empirical evidence for support. One new line of research in the Parker Group is to empirically define connectivity matrices through measures of human movement patterns between houses, settlements and communities.