Schistosomiasis, bilharzia, or ‘snail fever’ is a chronic disease caused by flatworms native to sub-Saharan Africa. Transmitted through fresh water during daily activities, the disease has impairing impacts on people’s health, i.e. people do not necessarily die from it, but their quality of life is severely reduced. In 2016, 206 million people worldwide were suffering from Schistosomiasis.
As infected people are often too weak to work, the disease directly impacts the economic development of affected countries. Therefore the main objective of this project is to identify the impact of schistosomiasis on economic development in sub-Saharan Africa. In the process, the project will create economic indicators using agriculture and migration to explain the dynamics of the disease.
The main research questions to be addressed are:
– What is the impact of schistosomiasis on agricultural production?
– What is the place of schistosomiasis in the optimal resource allocation of farmers?
– What is the impact that the development of water resources and human mobility have on spreading the disease?
The research methodology combines several axes: an empirical study on the impact of schistosomiasis on agricultural production; the development of a unitary dataset linking the characteristics of agricultural production to the variables characteristic to the evolution of schistosomiasis; the use of machine learning to select the model which best captures the link between the disease, agricultural development and migration.
Irrigation schemes are one of the most important policy responses designed to reduce poverty, particularly in sub-Saharan Africa. Concomitantly, they facilitate the propagation of schistosomiasis, a water-based debilitating disease that is endemic in many developing countries. I study the economic impact of schistosomiasis in Burkina Faso via the estimation of its burden on agricultural production with new data and new methods and identify it as a productivity shock. I show that the disease is both a driver and a consequence of poverty and that returns to water resources development are significantly reduced once its health effects are taken into account. I reconcile these results with a theoretical framework, which shows how the joint dynamics of schistosomiasis and the production decisions of farmers create Pareto-inferior endemic Nash equilibria, and how the wealth-dependent disease reproduction rate (the R0) can generate poverty traps. A stochastic extension of the model shows how this rate controls the probability flow between the system attractors. Social optima require deviations from separable allocations proportional to the disease burden on the maximized utility paths. Complete information on the feedback between wealth and disease can potentially allow farmers to escape the poverty trap.
The Graduate Institute
The Graduate Institute
Best – i3E, Ouagadougou
Ecole Polytechnique Fédérale, Lausanne
Swiss Tropical and Public Health Institute, Basel