Validation of a mapping and prediction model for human fasciolosis transmission in Andean very high altitude endemic areas using remote sensing data
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2001
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Elsevier BV
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Abstract
The present paper aims to validate the usefulness of the Normalized Difference Vegetation Index (NDVI) obtained by satellite remote sensing for the development of local maps of risk and for prediction of human fasciolosis in the Northern Bolivian Altiplano. The endemic area, which is located at very high altitudes (3800-4100 m) between Lake Titicaca and the valley of the city of La Paz, presents the highest prevalences and intensities of fasciolosis known in humans. NDVI images of 1.1 km resolution from the Advanced Very High Resolution Radiometer (AVHRR) sensor on board the National Oceanic and Atmospheric Administration (NOAA) series of environmental satellites appear to provide adequate information for a study area such as that of the Northern Bolivian Altiplano. The predictive value of the remotely sensed map based on NDVI data appears to be better than that from forecast indices based only on climatic data. A close correspondence was observed between real ranges of human fasciolosis prevalence at 13 localities of known prevalence rates and the predicted ranges of fasciolosis prevalence using NDVI maps. However, results based on NDVI map data predicted zones as risk areas where, in fact, field studies have demonstrated the absence of lymnaeid populations during snail surveys, corroborated by the absence of the parasite in humans and livestock. NDVI data maps represent a useful data component in long-term efforts to develop a comprehensive geographical information system control program model that accurately fits real epidemiological and transmission situations of human fasciolosis in high altitude endemic areas in Andean countries.
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Fuentes, M. V., Malone, J. B., & Mas-Coma, S. (2001). Validation of a mapping and prediction model for human fasciolosis transmission in Andean very high altitude endemic areas using remote sensing data. En Acta Tropica (Vol. 79, Issue 1, pp. 87-95). Elsevier BV. https://doi.org/10.1016/s0001-706x(01)00106-1