Fig 1.
Probability of Rift Valley fever occurrence in Tanzania overlaid with locations of RVF outbreaks in domestic ruminants 1930–2007.
Key for regions: 1- Pwani; 2- Simiyu; 3- Geita; 4- Singida; 5- Iringa; 6- Rukwa; 7- Kagera; 8- Kigoma; 9- Lindi; 10- Dar es Salaam; 11- Dodoma; 12- Tanga; 13- Mtwara; 14- Njombe; 15- Tabora; 16- Kilimanjaro; 17- Shinyanga; 18- Mara; 19- Ruvuma; 20- Mwanza; 21- Mbeya; 22- Arusha; 23- Morogoro; 24- Katavi and 25- Manyara.
Table 1.
Pearson correlation coefficient for pairs of predictor variables associated with occurrence of RVF.
Table 2.
Percentage contribution of individual predictor variables in eight ecological niche models describing the spatial distribution of habitat suitability for RVF occurrence in Tanzania.
The number in each model (i.e. 1 to 8) indicates the number of predictor variables that model contained.
Fig 2.
Jackknife of regularized training gain for RVF occurrence.
Fig 3.
Jackknife test of predictor variables importance on RVF occurrence as determined by the area under the curve (AUC) of the final model.
Fig 4.
Probability of RVF occurrence in relation to soil types.
The red columns present mean response of all 10 replicates, while blue and light green indicate standard deviation of the mean. The key to soil types: 1, chernozems; 2, andosols; 3, acrisols; 4, ferralsols, 5, luvisols; 6, cambisols, 7, planosols and 8, lixisols.
Fig 5.
Probability of RVF occurrence in relation to livestock density.
The red curved present mean response of all 10 replicates of the model, while blue indicates standard deviation of the mean.
Fig 6.
Probability of RVF occurrence in relation to precipitation of wettest quarter.
The red curved present mean response of all 10 replicates of the model, while blue indicates standard deviation of the mean.