Agro-ecology, household economics and malaria in Uganda: empirical correlations between agricultural and health outcomes

BACKGROUND: This paper establishes empirical evidence relating the agriculture and health sectors in Uganda. The analysis explores linkages between agricultural management, malaria and implications for improving community health outcomes in rural Uganda. The goal of this exploratory work is to expand the evidence-base for collaboration between the agricultural and health sectors in Uganda. METHODS: The paper presents an analysis of data from the 2006 Uganda National Household Survey using a parametric multivariate Two-Limit Tobit model to identify correlations between agro-ecological variables including geographically joined daily seasonal precipitation records and household level malaria risk. The analysis of agricultural and environmental factors as they affect household malaria rates, disaggregated by age-group, is inspired by a complimentary review of existing agricultural malaria literature indicating a gap in evidence with respect to agricultural management as a form of malaria vector management. Crop choices and agricultural management practices may contribute to vector control through the simultaneous effects of reducing malaria transmission, improving housing and nutrition through income gains, and reducing insecticide resistance in both malaria vectors and agricultural pests. RESULTS: The econometric results show the existence of statistically significant correlations between crops, such as sweet potatoes/yams, beans, millet and sorghum, with household malaria risk. Local environmental factors are also influential- daily maximum temperature is negatively correlated with malaria, while daily minimum temperature is positively correlated with malaria, confirming trends in the broader literature are applicable to the Ugandan context. CONCLUSIONS: Although not necessarily causative, the findings provide sufficient evidence to warrant purposefully designed work to test for agriculture health causation in vector management. A key constraint to modeling the agricultural basis of malaria transmission is the lack of data integrating both the health and agricultural information necessary to satisfy the differing methodologies used by the two sectors. A national platform for collaboration between the agricultural and health sectors could help align programs to achieve better measurements of agricultural interactions with vector reproduction and evaluate the potential for agricultural policy and programs to support rural malaria control.