Tsetse fly (G. f. fuscipes) distribution in the Lake Victoria basin of Uganda

Abstract

Tsetse flies transmit trypanosomes, the causative agent of human and animal African trypanosomiasis. The tsetse vector is extensively distributed across sub-Saharan Africa. Trypanosomiasis maintenance is determined by the interrelationship of three elements: vertebrate host, parasite and the vector responsible for transmission. Mapping the distribution and abundance of tsetse flies assists in predicting trypanosomiasis distributions and developing rational strategies for disease and vector control. Given scarce resources to carry out regular full scale field tsetse surveys to up-date existing tsetse maps, there is a need to devise inexpensive means for regularly obtaining dependable area-wide tsetse data to guide control activities. In this study we used spatial epidemiological modelling techniques (logistic regression) involving 5000 field-based tsetse-data (G. f. fuscipes) points over an area of 40,000 km2, with satellite-derived environmental surrogates composed of precipitation, temperature, land cover, normalised difference vegetation index (NDVI) and elevation at the sub-national level. We used these extensive tsetse data to analyse the relationships between presence of tsetse (G. f. fuscipes) and environmental variables. The strength of the results was enhanced through the application of a spatial autologistic regression model (SARM). Using the SARM we showed that the probability of tsetse presence increased with proportion of forest cover and riverine vegetation. The key outputs are a predictive tsetse distribution map for the Lake Victoria basin of Uganda and an improved understanding of the association between tsetse presence and environmental variables. The predicted spatial distribution of tsetse in the Lake Victoria basin of Uganda will provide significant new information to assist with the spatial targeting of tsetse and trypanosomiasis control.

Fig 1. Binary map of tsetse presence and absence, illustrating the extensive nature of the field survey.

It shows the tsetse survey outcome categorised as ‘present’ and ‘absent’. All tsetse traps which had tsetse flies where categorised as ‘present’ while those without tsetse flies where categorised as ‘absent’. G.f.fuscipes were captured in only 28.8% of the sampling sites (“present”). This implies that 71.2% of the trapping sites registered zero catches (“absent”). A total of 14,899 G.f.fuscipes flies (females = 7138, males = 7271 and 108 unidentified sex) were caught during the survey.

Fig 2. Spatial autocorrelation in the residuals from autologistic regression.

Residual variogram of residuals from autologistic regression. This is evidence for reduced spatial autocorrelation in the residuals.

Fig 3. Use of two-graph receiver operating characteristic (ROC) curves.

This is the plot of sensitivity and false positives (1-specificity) against expected probabilities and indicates that probability cut-off point is at 0.28, leading to a sensitivity and specificity of 53%. This is the threshold value for the prediction of tsetse presence where both specificity and specificity are maximised.

Fig 4. Predicted distribution of probabilities of G.f.fuscipes presence in the study area based on a logistic regression model.

Fig 5. Predicted distribution of probabilities of G.f.fuscipes presence in the study area based on an autologistic regression model.