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Modelled effects of prawn aquaculture on poverty alleviation and schistosomiasis control

Abstract

Recent evidence suggests that snail predators may aid efforts to control the human parasitic disease schistosomiasis by eating aquatic snail species that serve as intermediate hosts of the parasite. Here, potential synergies between schistosomiasis control and aquaculture of giant prawns are evaluated using an integrated bioeconomic–epidemiological model. Combinations of stocking density and aquaculture cycle length that maximize cumulative, discounted profit are identified for two prawn species in sub-Saharan Africa: the endemic, non-domesticated Macrobrachium vollenhovenii and the non-native, domesticated Macrobrachium rosenbergii. At profit-maximizing densities, both M. rosenbergii and M. vollenhovenii may substantially reduce intermediate host snail populations and aid schistosomiasis control efforts. Control strategies drawing on both prawn aquaculture to reduce intermediate host snail populations and mass drug administration to treat infected individuals are found to be superior to either strategy alone. Integrated aquaculture-based interventions can be a win–win strategy in terms of health and sustainable development in schistosomiasis endemic regions of the world.

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Data availability

All data used to conduct this analysis are freely available at https://github.com/cmhoove14/Prawn_fisheries_Public_health, provided in the Supplementary Code and Data folder and available from the corresponding author on request.

Code availability

All code used to conduct this analysis is freely available at https://github.com/cmhoove14/Prawn_fisheries_Public_health, provided in the Supplementary Code and Data folder and available from the corresponding author on request.

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Acknowledgements

C.M.H., J.V.R., G.A.D.L., I.J.J., A.J.L., S.H.S., G.R. and J.R.R. were supported by National Institutes of Health grant R01TW010286 (to J.R.R. and J.V.R.). C.M.H. and J.V.R. were additionally supported in part by National Science Foundation ‘Water Sustainability and Climate’ grants (1360330 and 1646708 to J.V.R.), National Institutes of Health grant R01AI125842 (to J.V.R.) and the University of California Multicampus Research Programs and Initiatives award MRP-17-446315 (to J.V.R.). G.A.D.L., I.J.J., A.J.L. and S.H.S. were additionally funded by a grant from the Bill and Melinda Gates Foundation (OPP1114050) and a GDP SEED grant from the Freeman Spogli Institute at Stanford University. G.A.D.L., I.J.J., A.J.L., S.H.S. and J.N.S. were also supported by National Science Foundation ‘Dynamics of Coupled Natural and Human Systems’ grant 1414102. G.A.D.L., S.H.S., C.M.H., J.V.R., J.N.S., R.C., L.M. and M.G. were also supported by NIMBioS through the working group on the Optimal Control of Environmentally Transmitted Disease. J.P.-S. and A.R. acknowledge funds provided by the Swiss National Science Foundation via the project ‘Optimal control of intervention strategies for waterborne disease epidemics’ (200021-172578/1). C.L.W. was supported by the Michigan Society of Fellows at the University of Michigan and by a Sloan Research Fellowship from the Alfred P. Sloan Foundation. R.C. and L.M. were also supported by Politecnico di Milano through the Polisocial Award programme (project MASTR-SLS).

Author information

G.A.D.L. and S.H.S. conceived the problem and designed the general modelling framework. C.M.H., S.H.S., J.K., J.V.R. and G.A.D.L. developed the analysis. C.M.H. and J.K. wrote the simulation scripts. G.R. collected field data to parameterize the epidemiological model. S.H.S. provided experimental data to parameterize the predation component of the model. J.N.S. provided guidance on profit estimation of the prawn aquaculture model. A.Savaya, S.C. and A.Sagi. provided guidance on the dynamics of the aquaculture model. C.M.H., J.K., J.N.S., J.V.R. and G.A.D.L. drafted the manuscript. All authors contributed to editing the manuscript.

Correspondence to Giulio A. De Leo.

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Supplementary information

Supplementary Information

Supplementary methods, Tables 1–3, Figs. 1–9 and references 1–25

Supplementary Code and Data

A ZIP file containing all R code and the data files necessary to reproduce the analysis. This can also be found on GitHub at https://github.com/cmhoove14/Prawn_fisheries_Public_health

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Fig. 1: A model schematic representing the three components of the integrated aquaculture–epidemiological model.
Fig. 2: Prawn aquaculture model dynamics.
Fig. 3: Grid search to identify optimum management decisions for each prawn species.
Fig. 4: Outputs of the integrated model under different intervention scenarios implemented over ten years, followed by ten years of no intervention.