Modeling how and why aquatic vegetation removal can free rural households from poverty-disease traps.

Proc Natl Acad Sci U S A

Department of Biological Sciences, Environmental Change Initiative, Eck Institute of Global Health, University of Notre Dame, Notre Dame, IN 46556.

Published: December 2024

Infectious disease can reduce labor productivity and incomes, trapping subpopulations in a vicious cycle of ill health and poverty. Efforts to boost African farmers' agricultural production through fertilizer use can inadvertently promote the growth of aquatic vegetation that hosts disease vectors. Recent trials established that removing aquatic vegetation habitat for snail intermediate hosts reduces schistosomiasis infection rates in children, while converting the harvested vegetation into compost boosts agricultural productivity and incomes. We develop a bioeconomic model that interacts an analytical microeconomic model of agricultural households' behavior, health status, and incomes over time with a dynamic model of schistosomiasis disease ecology. We calibrate the model with field data from northern Senegal. We show analytically and via simulation that local conversion of invasive aquatic vegetation to compost changes the feedback among interlinked disease, aquatic, and agricultural systems, reducing schistosomiasis infection and increasing incomes relative to the current status quo, in which villagers rarely remove aquatic vegetation. Aquatic vegetation removal disrupts the poverty-disease trap by reducing habitat for snails that vector the infectious helminth and by promoting the production of compost that returns to agricultural soils nutrients that currently leach into surface water from on-farm fertilizer applications. The result is healthier people, more productive labor, cleaner water, more productive agriculture, and higher incomes. Our model illustrates how this ecological intervention changes the feedback between the human and natural systems, potentially freeing rural households from poverty-disease traps.

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Source
http://dx.doi.org/10.1073/pnas.2411838121DOI Listing

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