Abstract
Many communities in low- and middle-income countries globally lack sustainable, cost-effective and mutually beneficial solutions for infectious disease, food, water and poverty challenges, despite their inherent interdependence1,2,3,4,5,6,7. Here we provide support for the hypothesis that agricultural development and fertilizer use in West Africa increase the burden of the parasitic disease schistosomiasis by fuelling the growth of submerged aquatic vegetation that chokes out water access points and serves as habitat for freshwater snails that transmit Schistosoma parasites to more than 200 million people globally8,9,10. In a cluster randomized controlled trial (ClinicalTrials.gov: NCT03187366) in which we removed invasive submerged vegetation from water points at 8 of 16 villages (that is, clusters), control sites had 1.46 times higher intestinal Schistosoma infection rates in schoolchildren and lower open water access than removal sites. Vegetation removal did not have any detectable long-term adverse effects on local water quality or freshwater biodiversity. In feeding trials, the removed vegetation was as effective as traditional livestock feed but 41 to 179 times cheaper and converting the vegetation to compost provided private crop production and total (public health plus crop production benefits) benefit-to-cost ratios as high as 4.0 and 8.8, respectively. Thus, the approach yielded an economic incentive—with important public health co-benefits—to maintain cleared waterways and return nutrients captured in aquatic plants back to agriculture with promise of breaking poverty–disease traps. To facilitate targeting and scaling of the intervention, we lay the foundation for using remote sensing technology to detect snail habitats. By offering a rare, profitable, win–win approach to addressing food and water access, poverty alleviation, infectious disease control and environmental sustainability, we hope to inspire the interdisciplinary search for planetary health solutions11 to the many and formidable, co-dependent global grand challenges of the twenty-first century.
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Data availability
All the data generated or used for this Article are deposited in Zenodo: https://doi.org/10.5281/zenodo.7765059.
Code availability
All the code used for this Article are deposited in Zenodo: https://doi.org/10.5281/zenodo.7765059.
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Acknowledgements
The authors thank the people of Senegal who invited us into their communities to co-develop the research in this Article. This research was supported by a National Institutes of Health grant (R01GM109499) to J.R.R., J.V.R., S.H.S., G.A.D.L., N.J. and G.R. Additionally, this research was supported by grants from the National Science Foundation (EF-1241889, DEB-2109293, DEB-2017785, DEB-2011179 and ICER-2024383), National Institutes of Health (R01 TW010286), and the Indiana Clinical and Translational Sciences Institute to J.R.R.; the National Institutes of Health (K01AI091864) and the National Science Foundation (EAR-1646708 and EAR-1360330) to J.V.R., and the National Science Foundation (CNH grant no. 1414102), National Institutes of Health (R01 TW010286-01), Stanford GDP SEED (grant no. 1183573-100-GDPAO) and SNAP-NCEAS (working group ‘Ecological levers for health: Advancing a Priority Agenda for Disease Ecology and Planetary Health in the 21st Century’) to S.H.S. and G.A.D.L. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
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J.R.R. conceptualized the experiments, directed the project and analyses, and wrote the majority of the manuscript. C.J.E.H. and A.S. contributed to figure development and statistical analyses, and helped to write sections of the manuscript. C.J.E.H., C.D., C.W., S.B. and R.A.N. performed field sampling, data collection and curation of field data. A.J.C. and I.J.J. provided the drone imagery and helped with some of the fieldwork. C.W. acquired the DigitalGlobe grant for the satellite imagery and conducted the remote sensing analyses. A.J.L. conducted the fertilizer use survey that was funded by D.L.-C. C.B.B. and M.J.D. performed economic analyses and contributed to writing those sections of the manuscript and to general editing. N.J., S.S. and G.R. directed the human sampling. A.T.L. collected human infection samples. A.-M.S. curated the human data. N.J. and M.S. oversaw the livestock feed trials. D.J.C. contributed to the original idea development. J.R.R., C.J.E.H., C.W., A.J.C. and I.J.J. collected the data to compare the quadrat and sweep net sampling protocols. J.R.R., G.A.D.L., N.J., J.V.R., G.R. and S.H.S. developed the grant that funded much of this research. G.A.D.L. and S.H.S. contributed to some of the conceptualization and methods development, site selection and baseline analyses. All co-authors contributed to manuscript editing.
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Extended data figures and tables
Extended Data Fig. 1 Google Earth Engine images of the St. Louis/Richard Toll region of Senegal before (1984–1986) and after (2014–2016) the opening of the Diama Dam.
on August 12, 1986, which was constructed to reduce saltwater intrusion and facilitate irrigation of the region. Note the profound increase in the amount of greenery in the landscape after the opening of the Dam. Image attribution: Esri, HERE, DeLorme, MapmyIndia, © OpenStreetMap contributors, and the GIS user community.
Extended Data Fig. 2 Log-transformed estimated quantity of vegetation removed (kg) for each removal round (1–10) during the study.
Each point represents an independent water access point, the dashed line is the median, and the gray rectangles represent a 95% confidence interval.
Extended Data Fig. 3 Amount and effect of onion rot across urea and compost treatments.
Per11m2 subplots, the (A) ln-transformed kg of onions unaffected by onion rot, (B) proportion of kg of onions with onion rot, and (C) ln-transformed kg of onions with onion rot all as a function of crossed compost and urea fertilizer treatments (shown are marginal means and 95% CI; C: compost, TC: tilled compost, NC: no compost, U: urea, NU: no urea; n = six plots for each of the six treatments, three plots at each of two villages).
Extended Data Fig. 4 Human baseline prevalence versus infection post-treatment.
Bi-variate scatterplots (with 95% confidence bands) of human baseline prevalence at 16 sites sampled in 2016 versus infection post-treatment in 2017 (A) and in 2018 (B).
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This file contains appendices 1–4, which include the Supplementary Methods and Discussion. It also contains Supplementary Tables 1–55 and Supplementary Figs. 1–12.
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Rohr, J.R., Sack, A., Bakhoum, S. et al. A planetary health innovation for disease, food and water challenges in Africa. Nature 619, 782–787 (2023). https://doi.org/10.1038/s41586-023-06313-z
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DOI: https://doi.org/10.1038/s41586-023-06313-z
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