Structured surveys of Australian native possum excreta predict Buruli ulcer occurrence in humans

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Abstract

Buruli ulcer (BU) is a neglected tropical disease caused by infection of subcutaneous tissue withMycobacterium ulcerans. BU is commonly reported across rural regions of Central and West Africa but has been increasing dramatically in temperate southeast Australia around the major metropolitan city of Melbourne. Previous research has shown that Australian native possums are reservoirs ofM. ulceransand that they shed the bacteria in their fecal material (excreta). Field surveys show that locales where possums harborM. ulceransoverlap with human cases of BU, raising the possibility of using possum excreta surveys to predict the risk of disease occurrence in humans. We thus established a highly structured 12-month possum excreta surveillance program across an area of 350 km2in the Mornington Peninsula area 70 km south of Melbourne, Australia. The primary objective of our study was to assess ifM. ulceranssurveillance of possum excreta provided useful information for predicting future human BU case locations. Over two sampling campaigns in summer and winter, we collected 2282 possum excreta specimens of which 11% were PCR positive forM. ulcerans-specific DNA. Using the spatial scanning statistical toolSatScan, we observed non-random, co-correlated clustering of bothM. ulceranspositive possum excreta and human BU cases. We next trained a statistical model with the Mornington Peninsula excreta survey data to predict the future likelihood of human BU cases occurring in the region. By observing where human BU cases subsequently occurred, we show that the excreta model performance was superior to a null model trained using the previous year’s human BU case incidence data (AUC 0.66 vs 0.55). We then used data unseen by the excreta-informed model from a new survey of 661 possum excreta specimens in Geelong, a geographically separate BU endemic area to the southwest of Melbourne, to prospectively predict the location of human BU cases in that region. As for the Mornington Peninsula, the excreta-based BU prediction model outperformed the null model (AUC 0.75 vs 0.50) and pinpointed specific locations in Geelong where interventions could be deployed to interrupt disease spread. This study highlights theOne Healthnature of BU by confirming a quantitative relationship between possum excreta shedding ofM. ulceransand humans developing BU. The excreta survey-informed modeling we have described will be a powerful tool for efficient targeting of public health responses to stop BU.

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