Predictability of anthrax infection in the Serengeti, Tanzania

Anthrax is endemic throughout Africa, causing considerable livestock and wildlife losses and severe, sometimes fatal, infection in humans. Predicting the risk of infection is therefore important for public health, wildlife conservation and livestock economies. However, because of the intermittent and variable nature of anthrax outbreaks, associated environmental and climatic conditions, and diversity of species affected, the ecology of this multihost pathogen is poorly understood.We explored records of anthrax from the Serengeti ecosystem in north-west Tanzania where the disease has been documented in humans, domestic animals and a range of wildlife. Using spatial and temporal case-detection and seroprevalence data from wild and domestic animals, we investigated spatial, environmental, climatic and species-specific associations in exposure and disease.Anthrax was detected annually in numerous species, but large outbreaks were spatially localized, mostly affecting a few focal herbivores.Soil alkalinity and cumulative weather extremes were identified as useful spatial and temporal predictors of exposure and infection risk, and for triggering the onset of large outbreaks.Interacting ecological and behavioural factors, specifically functional groups and spatiotemporal overlap, helped to explain the variable patterns of infection and exposure among species.Synthesis and applications. Our results shed light on ecological drivers of anthrax infection and suggest that soil alkalinity and prolonged droughts or rains are useful predictors of disease occurrence that could guide risk-based surveillance. These insights should inform strategies for managing anthrax including prophylactic livestock vaccination, timing of public health warnings and antibiotic provision in high-risk areas. However, this research highlights the need for greater surveillance (environmental, serological and case-detection-orientated) to determine the mechanisms underlying anthrax dynamics.