Climate predictors of the spatial distribution of human plague cases in the West Nile region of Uganda.

East Africa has been identified as a region where vector-borne and zoonotic diseases are most likely to emerge or re-emerge and where morbidity and mortality from these diseases is significant. Understanding when and where humans are most likely to be exposed to vector-borne and zoonotic disease agents in this region can aid in targeting limited prevention and control resources. Often, spatial and temporal distributions of vectors and vector-borne disease agents are predictable based on climatic variables. However, because of coarse meteorological observation networks, appropriately scaled and accurate climate data are often lacking for Africa. Here, we use a recently developed 10-year gridded meteorological dataset from the Advanced Weather Research and Forecasting Model to identify climatic variables predictive of the spatial distribution of human plague cases in the West Nile region of Uganda. Our logistic regression model revealed that within high elevation sites (above 1,300 m), plague risk was positively associated with rainfall during the months of February, October, and November and negatively associated with rainfall during the month of June. These findings suggest that areas that receive increased but not continuous rainfall provide ecologically conducive conditions for Yersinia pestis transmission in this region. This study serves as a foundation for similar modeling efforts of other vector-borne and zoonotic disease in regions with sparse observational meteorologic networks.

Assessing human risk of exposure to plague bacteria in northwestern Uganda based on remotely sensed predictors.

Plague, a life-threatening flea-borne zoonosis caused by Yersinia pestis, has most commonly been reported from eastern Africa and Madagascar in recent decades. In these regions and elsewhere, prevention and control efforts are typically targeted at fine spatial scales, yet risk maps for the disease are often presented at coarse spatial resolutions that are of limited value in allocating scarce prevention and control resources. In our study, we sought to identify sub-village level remotely sensed correlates of elevated risk of human exposure to plague bacteria and to project the model across the plague-endemic West Nile region of Uganda and into neighboring regions of the Democratic Republic of Congo. Our model yielded an overall accuracy of 81%, with sensitivities and specificities of 89% and 71%, respectively. Risk was higher above 1,300 meters than below, and the remotely sensed covariates that were included in the model implied that localities that are wetter, with less vegetative growth and more bare soil during the dry month of January (when agricultural plots are typically fallow) pose an increased risk of plague case occurrence. Our results suggest that environmental and landscape features play a large part in classifying an area as ecologically conducive to plague activity. However, it is clear that future studies aimed at identifying behavioral and fine-scale ecological risk factors in the West Nile region are required to fully assess the risk of human exposure to Y. pestis.