Figure 1.
Conceptual model of important risk factors affecting malaria prevalence in the African Highlands.
Factors are regrouped in 3 main classes (environmental factors: green label, biological factors: grey label and human related factors: blue label). Dependant variables included in the CART analysis are displayed in red and predictor variables are highlighted in white.
Table 1.
Dependant and predictor variables introduced in the CART analysis.
Figure 2.
Classification trees representing the important risk factors for malaria prevalence.
The high risk groups are displayed in red. In each node 0 stands for negative slide and 1 for positive slide. The following variables were selected by the tree as important risk factors: Anopheles density (Ano-density) with a cut off of 1.5 Anopheles per house; Survey number 1 to 11; Housing (1,2 = poorest housing condition and 3,4 highest housing condition); Age with a cut off of 38 years old.
Table 2.
Ranking of predictor variables for malaria prevalence by their overall power as discriminant.
Figure 3.
Regression trees representing the important risk factors for the Anopheles density per/house (Ano_density).
The selected splitting variables (Minimum temperature the previous month = T°min-1; Distance of the houses to the marsh with a cut off of 500 metres; Area sprayed or not; Monthly rainfall in the current month with a cut off of 96.2 mm) are shown in the nodes.
Table 3.
Ranking of predictor variables for Anopheles density by their overall power as discriminant.