Global Evidence Consensus for Visceral LeishmanisisA survey of the evidence for the presence or absence of visceral leishmaniasis in each province/state in the world (Admin 1)Evidence Consensus for Visceral Leishmanisis 0321.docxGlobal Evidence Consensus for Cutaneous LeishmaniasisA survey of the evidence for the presence or absence of cutaneous leishmaniasis in each province/state in the world (Admin 1)Evidence Consensus for Cutaneous Leishmaniasis 0321.docxDatabase of cutaneous leishmaniasis occurrencesA database containing cutaneous leishmaniasis occurrences used in the boosted regression trees analysisCL_final_dataset.xlsxDatabase of visceral leishmaniasis occurrencesA database containing visceral leishmaniasis occurrences used in the boosted regression trees analysisVL_final_dataset.xlsxPopulations living in areas of environmental risk of LeishmaniasisThese data tables reported the estimated populations living in areas of environmental risk of cutaneous leishmaniasis (CL) or visceral leishmaniasis (VL). For a full methodology and indications of geographic range of these populations, please consult the full publication that this dataset is associated with: Pigott et al. (2014) “Global distribution maps of the leishmaniases”Populations_at_risk_CLVL.docx

The leishmaniases are vector-borne diseases that have a broad global distribution throughout much of the Americas, Africa and Asia. Despite representing a significant public health burden, our understanding of the global distribution of the leishmaniases remains vague, reliant upon expert opinion and limited to poor spatial resolution. A global assessment of the consensus of evidence for leishmaniasis was performed at a sub-national level by aggregating information from a variety of sources. A database of records of cutaneous and visceral leishmaniasis occurrence was compiled from published literature, online reports, strain archives and GenBank accessions. These, with a suite of biologically relevant environmental covariates, were used in a boosted regression tree modelling framework to generate global environmental risk maps for the leishmaniases. These high-resolution evidence-based maps can help direct future surveillance activities, identify areas to target for disease control and inform future burden estimation efforts.