Mycetoma is a neglected tropical disease caused by bacterial and fungal infections leading to chronic inflammation and eventually deformities, if untreated. The disease has been reported in 102 countries, but Sudan currently has the world's highest case burden.
In hope of helping to detect and manage cases in Sudan, this study sought to identify environmental predictors of the disease while mapping probability and identifying potential hotspots.
Based on a database of locations of patients at the onset of symptoms, researchers constructed an ensemble model using a wide range of candidate predictors, including data on climate, soil, livestock, waterways, vegetation and GBIF-mediated occurrences of thorny trees—believed to be a major cause of wounds through which infections can happen.
For eumycetoma (caused by fungal infections) cases, probability increased with proximity the nearest waterway and greater diversity of thorny trees. The latter, however, had no effect on probability of actinomycetoma (caused by bacterial infections), which in addition to proximity to waterways was affected by mean temperature, aridity and soil sodium concentration.
The maps produced for the study showed geographic variation in the risk of mycetoma linked to environmental factors, predicting the highest occurrence in the central and southeastern parts of Sudan and along the Nile and its tributaries.