Risk factors of visceral leishmaniasis in East Africa: a case-control study in Pokot territory of Kenya and Uganda

Abstract

Background: In East Africa, visceral leishmaniasis (VL) is endemic in parts of Sudan, Ethiopia, Somalia, Kenya and Uganda. It is caused by Leishmania donovani and transmitted by the sandfly vector Phlebotomus martini. In the Pokot focus, reaching from western Kenya into eastern Uganda, formulation of a prevention strategy has been hindered by the lack of knowledge on VL risk factors as well as by lack of support from health sector donors. The present study was conducted to establish the necessary evidence-base and to stimulate interest in supporting the control of this neglected tropical disease in Uganda and Kenya.

Methods: A case-control study was carried out from June to December 2006. Cases were recruited at Amudat hospital, Nakapiripirit district, Uganda, after clinical and parasitological confirmation of symptomatic VL infection. Controls were individuals that tested negative using a rK39 antigen-based dipstick, which were recruited at random from the same communities as the cases. Data were analysed using conditional logistic regression.

Results: Ninety-three cases and 226 controls were recruited into the study. Multivariate analysis identified low socio-economic status and treating livestock with insecticide as risk factors for VL. Sleeping near animals, owning a mosquito net and knowing about VL symptoms were associated with a reduced risk of VL.

Conclusions: VL affects the poorest of the poor of the Pokot tribe. Distribution of insecticide-treated mosquito nets combined with dissemination of culturally appropriate behaviour-change education is likely to be an effective prevention strategy.

Figure 1

Framework for socio-economic, household/environmental, behavioral and nutritional/co-infection variables and being infected with visceral leishmaniasis in the Pokot county, East Africa. This approach distinguishes between distal and proximate factors: distal factors rarely have a direct effect on disease outcomes but operate through a number of inter-related proximate determinants which in turn affects directly risk of disease. For example, socio-economic status does not affect directly the risk of VL but may affect VL indirectly through, for example, (i) the likelihood of sleeping outdoors or ownership of bed net, both of which influence in turn the risk of exposure to biting by sandflies or (ii) individual nutritional status which influences susceptibility to disease. Note: Cases were matched to controls by village; sex and age were controlled for in the analysis. These demographic factors are thus not included in the above analysis framework.