Environmental and socio-economic risk modelling for Chagas disease in Bolivia.

摘要: Accurately defining disease distributions and calculating risk is an important step in the control prevention of diseases. Geographical information systems (GIS) remote sensing technologies, with maximum entropy (Maxent) ecological niche modelling computer software, were used to create predictive maps for Chagas Bolivia. Prevalence rates calculated from 2007 2009 household infection survey data Bolivia, while environmental compiled Worldclim database MODIS satellite imagery. Socio-economic obtained Bolivian National Institute Statistics. Disease models identified altitudes at 500-3,500 m above mean sea level (MSL), low annual precipitation (45-250 mm), higher diurnal range temperature (10-19 °C; peak 16 °C) as compatible biological requirements insect vectors. analyses demonstrated importance improved housing materials water source. Home adobe wall having fetch drinking rivers or wells without pump found be highly related distribution by receiver operator characteristic (ROC) area under curve (AUC) (0.69 AUC, 0.67 AUC 0.62 respectively), areas hardwood floors a direct negative relationship (-0.71 AUC). This study demonstrates that Maxent can prevalence incidence studies provide governmental agencies easily learned, understandable method define either high, moderate disease. may resource planning, targeting implementation. However, access high-resolution, sub-municipality socio-economic (e.g. census tracts) would facilitate elucidation relative influence poverty-related factors on regional dynamics.