Abstract
The potential value of MODIS satellite sensor data on Normalized Difference Vegetation Index (NDVI) and land surface temperatures (LST) for describing the distribution of the Schistosoma mansoni-"Biomphalaria pfeifferi"/Biomphalaria sudanica parasite-snail system in inland Uganda, were tested by developing annual and seasonal composite models, and iteratively analysing for their relationship with parasite and snail distribution. The dry season composite model predicted an endemic area that produced the best fit with the distribution of schools with > or =5% prevalence. NDVI values of 151-174, day temperatures of 26-36 degrees C, and night temperatures of 15-20 degrees C were used as criteria for the prediction model. Using the same approach with host snail data indicated that most of Uganda is suitable "B. pfeifferi"/B. sudanica habitat, except for possibly the north-eastern region of the country. The parasite, however, appears to be restricted in its distribution in both the north-eastern and the south-western regions of Uganda. The absence of disease in the south-west can not be attributed to the absence of snail hosts. Results suggest a combination of satellite sensor data on temperature and standard climate data on precipitation, as the best ecological determinants of the S. mansoni-"B. pfeifferi"/B. sudanica system. Satellite composite models and logistic regression analysis, suggest low night time temperature as one of the significant factors inhibiting S. mansoni transmission in the south-western highland areas of Uganda. The developed models are, however, unique, representing species-specific ecologic preferences of the S. mansoni-"B. Pfeifferi"/B. sudanica system in inland Uganda. Further validation studies are needed to test the value of the model in other countries in East Africa.
Original language | English |
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Journal | Parassitologia |
Volume | 47 |
Issue number | 1 |
Pages (from-to) | 115-25 |
Number of pages | 11 |
ISSN | 0048-2951 |
Publication status | Published - Mar 2005 |
Keywords
- Animals
- Biomphalaria
- Child
- Computer Simulation
- Disease Vectors
- Ecosystem
- Endemic Diseases
- Fresh Water
- Geographic Information Systems
- Humans
- Models, Theoretical
- Prevalence
- Schistosoma mansoni
- Schistosomiasis mansoni
- Schools
- Seasons
- Temperature
- Topography, Medical
- Uganda