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Global health and development communities lack sustainable, cost-effective, mutually beneficial solutions for infectious disease, food, water, and poverty challenges despite their regular interdependence worldwide1–7. Here, we show that agricultural development and fertilizer use in west Africa increase the devastating tropical disease schistosomiasis by fueling the growth of submerged aquatic vegetation that chokes out water access points and serves as habitat for snails that transmit Schistosoma parasites to >200 million people globally8–10. In a randomized control trial where we removed invasive submerged vegetation from water points, control sites had 124% higher fecal Schistosoma reinfection rates in schoolchildren and lower open water access than removal sites without any detectable long-term adverse effects of the removal on local water quality or freshwater biodiversity. The removed vegetation was as effective as traditional livestock feed but 41-179 times cheaper and converting the vegetation to compost yielded private crop production and total (public health plus private benefits) benefit-to-cost ratios as high as 4.0 and 8.8, respectively. Thus, we provide an economic incentive – with important public health co-benefits – to maintain cleared waterways and return nutrients captured in aquatic plants back to agriculture with great promise of breaking poverty-disease traps. To facilitate targeting and scaling of this intervention, we lay the foundation for using remote sensing technology to detect snail habitat. By offering a rare, profitable, win-win innovation for food and water access, poverty, infectious disease emergence, and environmental sustainability, we hope to inspire the interdisciplinary search for other planetary health solutions11 to the numerous and formidable, co-dependent global grand challenges of the 21st century.

Significance Here, we show how a conservation–health care exchange in rural Borneo preserved globally important forest carbon and simultaneously improved human health and well-being, in a region of historically intense environmental destruction, widespread poverty, and unmet health needs. To evaluate this long-term conservation and health intervention, we analyzed earth observation data, clinic health records, and socioeconomic surveys to quantify conservation, health, and sustainable development outcomes simultaneously. Results demonstrate an actionable framework for aligning cross-sectoral goals and objectively quantifying intervention outcomes across both conservation and human health targets., Tropical forest loss currently exceeds forest gain, leading to a net greenhouse gas emission that exacerbates global climate change. This has sparked scientific debate on how to achieve natural climate solutions. Central to this debate is whether sustainably managing forests and protected areas will deliver global climate mitigation benefits, while ensuring local peoples’ health and well-being. Here, we evaluate the 10-y impact of a human-centered solution to achieve natural climate mitigation through reductions in illegal logging in rural Borneo: an intervention aimed at expanding health care access and use for communities living near a national park, with clinic discounts offsetting costs historically met through illegal logging. Conservation, education, and alternative livelihood programs were also offered. We hypothesized that this would lead to improved health and well-being, while also alleviating illegal logging activity within the protected forest. We estimated that 27.4 km2 of deforestation was averted in the national park over a decade (∼70% reduction in deforestation compared to a synthetic control, permuted P = 0.038). Concurrently, the intervention provided health care access to more than 28,400 unique patients, with clinic usage and patient visitation frequency highest in communities participating in the intervention. Finally, we observed a dose–response in forest change rate to intervention engagement (person-contacts with intervention activities) across communities bordering the park: The greatest logging reductions were adjacent to the most highly engaged villages. Results suggest that this community-derived solution simultaneously improved health care access for local and indigenous communities and sustainably conserved carbon stocks in a protected tropical forest.

Schistosome parasites infect more than 200 million people annually, mostly in sub-Saharan Africa, where people may be co-infected with more than one species of the parasite. Infection risk for any single species is determined, in part, by the distribution of its obligate intermediate host snail. As the World Health Organization reprioritizes snail control to reduce the global burden of schistosomiasis, there is renewed importance in knowing when and where to target those efforts, which could vary by schistosome species. This study estimates factors associated with schistosomiasis risk in 16 villages located in the Senegal River Basin, a region hyperendemic for Schistosoma haematobium and S. mansoni. We first analyzed the spatial distributions of the two schistosomes’ intermediate host snails (Bulinus spp. and Biomphalaria pfeifferi, respectively) at village water access sites. Then, we separately evaluated the relationships between human S. haematobium and S. mansoni infections and (i) the area of remotely-sensed snail habitat across spatial extents ranging from 1 to 120 m from shorelines, and (ii) water access site size and shape characteristics. We compared the influence of snail habitat across spatial extents because, while snail sampling is traditionally done near shorelines, we hypothesized that snails further from shore also contribute to infection risk. We found that, controlling for demographic variables, human risk for S. haematobium infection was positively correlated with snail habitat when snail habitat was measured over a much greater radius from shore (45 m to 120 m) than usual. S. haematobium risk was also associated with large, open water access sites. However, S. mansoni infection risk was associated with small, sheltered water access sites, and was not positively correlated with snail habitat at any spatial sampling radius. Our findings highlight the need to consider different ecological and environmental factors driving the transmission of each schistosome species in co-endemic landscapes., Author summary Schistosome parasites infect more than 200 million people worldwide, mainly in sub-Saharan Africa, where many people are at-risk for infection by multiple schistosome species simultaneously. To reduce the global burden of schistosomiasis, control of the parasites’ intermediate host–specific species of freshwater snails–has been elevated in priority to complement mass drug administration campaigns in endemic areas. To maximize the efficacy and efficiency of snail control efforts, a better understanding of where to target intermediate host snails is badly needed. This includes a better understanding of the spatial scale at which snails in the environment contribute to human infection risk, and, in co-endemic settings, how ecological determinants of infection risk vary by schistosome species. We used quantitative snail sampling and remotely-sensed data at 16 villages in the Senegal River Basin to compare and contrast ecological correlates and spatial scales of infection risk from freshwater snails that transmit Schistosoma haematobium versus S. mansoni. We found that infection risk for S. haematobium was associated with snail habitat at a larger spatial radius than is typically considered for schistosomiasis monitoring and control, whereas infection risk for S. mansoni was not positively correlated with snail habitat at any spatial sampling radius, but was associated with small water access sites enclosed by emergent vegetation. Our findings highlight the need to consider the different ecological and environmental factors driving the transmission of each schistosome species in co-endemic landscapes.

In recent decades, computer vision has proven remarkably effective in addressing diverse issues in public health, from determining the diagnosis, prognosis, and treatment of diseases in humans to predicting infectious disease outbreaks. Here, we investigate whether convolutional neural networks (CNNs) can also demonstrate effectiveness in classifying the environmental stages of parasites of public health importance and their invertebrate hosts. We used schistosomiasis as a reference model. Schistosomiasis is a debilitating parasitic disease transmitted to humansviasnail intermediate hosts. The parasite affects more than 200 million people in tropical and subtropical regions. We trained our CNN, a feed-forward neural network, on a limited dataset of 5,500 images of snails and 5,100 images of cercariae obtained from schistosomiasis transmission sites in the Senegal River Basin, a region in western Africa that is hyper-endemic for the disease. The image set included both images of two snail genera that are relevant to schistosomiasis transmission – that is,Bulinusspp. andBiomphalaria pfeifferi– as well as snail images that are non-component hosts for human schistosomiasis. Cercariae shed fromBi. pfeifferi and Bulinusspp. snails were classified into 11 categories, of which only two,S. haematobiumandS. mansoni, are major etiological agents of human schistosomiasis. The algorithms, trained on 80% of the snail and parasite dataset, achieved 99% and 91% accuracy for snail and parasite classification, respectively, when used on the hold-out validation dataset – a performance comparable to that of experienced parasitologists. The promising results of this proof-of-concept study suggests that this CNN model, and potentially similar replicable models, have the potential to support the classification of snails and parasite of medical importance. In remote field settings where machine learning algorithms can be deployed on cost-effective and widely used mobile devices, such as smartphones, these models can be a valuable complement to laboratory identification by trained technicians. Future efforts must be dedicated to increasing dataset sizes for model training and validation, as well as testing these algorithms in diverse transmission settings and geographies.

Significance Schistosomiasis is a parasitic disease that affects ∼206 million people globally. The World Health Organization recently endorsed control of the freshwater snails that host schistosome infectious stages, and here, we show how to better target those snail control efforts. Schistosomiasis infection occurred on a local scale at our study sites in northwestern Senegal, suggesting that small-scale interventions can suppress transmission. However, snail clusters were so ephemeral that attempts to target them for removal would be inefficient. Instead, we found easy-to-measure environmental proxies that were more effective than snail variables at predicting human infections, including area of snail habitat within the site and total site area. Our work indicates that satellite- or drone-based precision mapping could efficiently identify high-transmission areas., Recently, the World Health Organization recognized that efforts to interrupt schistosomiasis transmission through mass drug administration have been ineffective in some regions; one of their new recommended strategies for global schistosomiasis control emphasizes targeting the freshwater snails that transmit schistosome parasites. We sought to identify robust indicators that would enable precision targeting of these snails. At the site of the world’s largest recorded schistosomiasis epidemic—the Lower Senegal River Basin in Senegal—intensive sampling revealed positive relationships between intermediate host snails (abundance, density, and prevalence) and human urogenital schistosomiasis reinfection (prevalence and intensity in schoolchildren after drug administration). However, we also found that snail distributions were so patchy in space and time that obtaining useful data required effort that exceeds what is feasible in standard monitoring and control campaigns. Instead, we identified several environmental proxies that were more effective than snail variables for predicting human infection: the area covered by suitable snail habitat (i.e., floating, nonemergent vegetation), the percent cover by suitable snail habitat, and size of the water contact area. Unlike snail surveys, which require hundreds of person-hours per site to conduct, habitat coverage and site area can be quickly estimated with drone or satellite imagery. This, in turn, makes possible large-scale, high-resolution estimation of human urogenital schistosomiasis risk to support targeting of both mass drug administration and snail control efforts.

Background The risk of infectious diseases, including snail-borne schistosomiasis, is determined by three inter-related components: exposure, hazard, and vulnerability. For schistosomiasis, exposure occurs through behaviours involving water contact, but not without the environmental hazard of snails and parasites in the water. Socioeconomic vulnerability makes it difficult to reduce exposure in the presence of hazard, because it increases reliance on hazardous activities and environments. We aimed to quantify the contributions of exposure, hazard, and vulnerability to schistosome re-infection presence and intensity. Methods We used cross-sectional parasitological data from 821 school-aged children (5–15 years) in 13 villages along the Senegal River, survey data from 411 households where those children resided, and ecological data from all 24 village water contact sites. We fitted mixed-effects logistic and negative binomial regressions with indices of exposure, hazard, and vulnerability as explanatory variables of Schistosoma haematobium infection, along with demographic control variables. Multimodel inference was used to determine the relative importance of each component of risk and model averaging was used to quantify associations between infection outcomes and indices of hazard, exposure, and vulnerability. Findings The most important component of S haematobium presence was hazard (Σwi=0·95), followed by vulnerability (Σwi=0·91), and the most important component of S haematobium intensity was exposure (Σwi=1·00), followed by hazard (Σwi=0·76). Hazard was positively associated with infection presence (odds ratio [OR]=1·49, 95% CI 1·12–1·97), whereas exposure was positively associated with infection intensity. Interpretation Our findings highlight how social (exposure and vulnerability) and environmental (hazard) processes act together to facilitate the acquisition and accumulation of schistosome infection from the environment across time and space. This approach can inform targeting of social and environmental interventions as complements to mass drug administration. Funding National Science Foundation Couple Natural Human Systems programme (1414102), Bill and Melinda Gates Foundation (OPP1114050), James and Nancy Kelso Fellowship through the Stanford Interdisciplinary Graduate Fellowship programme at Stanford University (AJL), Michigan Society of Fellows at the University of Michigan, a Sloan Research Fellowship from the Alfred P Sloan Foundation, a UW Innovation Award and a grant from the National Science Foundation (CLW; OCE-1829509).

Schistosomiasis, or “snail fever”, is a parasitic disease affecting over 200 million people worldwide. People become infected when exposed to water containing particular species of freshwater snails. Habitats for such snails can be mapped using lightweight, inexpensive and field-deployable consumer-grade Unmanned Aerial Vehicles (UAVs), also known as drones. Drones can obtain imagery in remote areas with poor satellite imagery. An unexpected outcome of using drones is public engagement. Whereas sampling snails exposes field technicians to infection risk and might disturb locals who are also using the water site, drones are novel and fun to watch, attracting crowds that can be educated about the infection risk.

In recent decades, computer vision has proven remarkably effective in addressing diverse issues in public health, from determining the diagnosis, prognosis, and treatment of diseases in humans to predicting infectious disease outbreaks. Here, we investigate whether convolutional neural networks (CNNs) can also demonstrate effectiveness in classifying the environmental stages of parasites of public health importance and their invertebrate hosts. We used schistosomiasis as a reference model. Schistosomiasis is a debilitating parasitic disease transmitted to humans via snail intermediate hosts. The parasite affects more than 200 million people in tropical and subtropical regions. We trained our CNN, a feed-forward neural network, on a limited dataset of 5,500 images of snails and 5,100 images of cercariae obtained from schistosomiasis transmission sites in the Senegal River Basin, a region in western Africa that is hyper-endemic for the disease. The image set included both images of two snail genera that are relevant to schistosomiasis transmission – that is, Bulinus spp. and Biomphalaria pfeifferi – as well as snail images that are non-component hosts for human schistosomiasis. Cercariae shed from Bi. pfeifferi and Bulinus spp. snails were classified into 11 categories, of which only two, S. haematobium and S. mansoni, are major etiological agents of human schistosomiasis. The algorithms, trained on 80% of the snail and parasite dataset, achieved 99% and 91% accuracy for snail and parasite classification, respectively, when used on the hold-out validation dataset – a performance comparable to that of experienced parasitologists. The promising results of this proof-of-concept study suggests that this CNN model, and potentially similar replicable models, have the potential to support the classification of snails and parasite of medical importance. In remote field settings where machine learning algorithms can be deployed on cost-effective and widely used mobile devices, such as smartphones, these models can be a valuable complement to laboratory identification by trained technicians. Future efforts must be dedicated to increasing dataset sizes for model training and validation, as well as testing these algorithms in diverse transmission settings and geographies.

Giulio A De Leo and colleagues consider the effect of changing climates and human activity on schistosomiasis transmission and potential solutions to contain its spread

Background Infectious disease risk is driven by three interrelated components: exposure, hazard, and vulnerability. For schistosomiasis, exposure occurs through contact with water, which is often tied to daily activities. Water contact, however, does not imply risk unless the environmental hazard of snails and parasites is also present in the water. By increasing reliance on hazardous activities and environments, socio-economic vulnerability can hinder reductions in exposure to a hazard. We aimed to quantify the contributions of exposure, hazard, and vulnerability to the presence and intensity of Schistosoma haematobium re-infection. Methodology/Principal findings In 13 villages along the Senegal River, we collected parasitological data from 821 school-aged children, survey data from 411 households where those children resided, and ecological data from all 24 village water access sites. We fit mixed-effects logistic and negative binomial regressions with indices of exposure, hazard, and vulnerability as explanatory variables of Schistosoma haematobium presence and intensity, respectively, controlling for demographic variables. Using multi-model inference to calculate the relative importance of each component of risk, we found that hazard (Ʃwi = 0.95) was the most important component of S. haematobium presence, followed by vulnerability (Ʃwi = 0.91). Exposure (Ʃwi = 1.00) was the most important component of S. haematobium intensity, followed by hazard (Ʃwi = 0.77). Model averaging quantified associations between each infection outcome and indices of exposure, hazard, and vulnerability, revealing a positive association between hazard and infection presence (OR = 1.49, 95% CI 1.12, 1.97), and a positive association between exposure and infection intensity (RR 2.59–3.86, depending on the category; all 95% CIs above 1) Conclusions/Significance Our findings underscore the linkages between social (exposure and vulnerability) and environmental (hazard) processes in the acquisition and accumulation of S. haematobium infection. This approach highlights the importance of implementing both social and environmental interventions to complement mass drug administration., Author summary While the impacts of natural hazards tend to be described in terms of social determinants such as exposure and vulnerability, the risk for infectious disease is often expressed in terms of environmental determinants without fully considering the socio-ecological processes that put people in contact with infective agents of disease. In the case of schistosomiasis, risk is determined by human interactions with freshwater environments where schistosome parasites circulate between people and aquatic snails. In this study, we quantified the relative contributions of exposure, hazard, and vulnerability to schistosome re-infection among schoolchildren in an endemic region of northern Senegal. We find that hazard and vulnerability influence whether a child becomes infected, while exposure and hazard influence the burden of worms once infection is acquired. Increasing numbers of worms is known to be positively associated with increasing severity of disease. Our findings underscore the importance of evaluating social and environmental determinants of disease simultaneously; omitting measures of exposure, hazard or vulnerability may limit our understanding of risk.

Background Schistosomiasis is responsible for the second highest burden of disease among neglected tropical diseases globally, with over 90 percent of cases occurring in African regions where drugs to treat the disease are only sporadically available. Additionally, human re-infection after treatment can be a problem where there are high numbers of infected snails in the environment. Recent experiments indicate that aquatic factors, including plants, nutrients, or predators, can influence snail abundance and parasite production within infected snails, both components of human risk. This study investigated how snail host abundance and release of cercariae (the free swimming stage infective to humans) varies at water access sites in an endemic region in Senegal, a setting where human schistosomiasis prevalence is among the highest globally. Methods/Principal findings We collected snail intermediate hosts at 15 random points stratified by three habitat types at 36 water access sites, and counted cercarial production by each snail after transfer to the laboratory on the same day. We found that aquatic vegetation was positively associated with per-capita cercarial release by snails, probably because macrophytes harbor periphyton resources that snails feed upon, and well-fed snails tend to produce more parasites. In contrast, the abundance of aquatic macroinvertebrate snail predators was negatively associated with per-capita cercarial release by snails, probably because of several potential sublethal effects on snails or snail infection, despite a positive association between snail predators and total snail numbers at a site, possibly due to shared habitat usage or prey tracking by the predators. Thus, complex bottom-up and top-down ecological effects in this region plausibly influence the snail shedding rate and thus, total local density of schistosome cercariae. Conclusions/Significance Our study suggests that aquatic macrophytes and snail predators can influence per-capita cercarial production and total abundance of snails. Thus, snail control efforts might benefit by targeting specific snail habitats where parasite production is greatest. In conclusion, a better understanding of top-down and bottom-up ecological factors that regulate densities of cercarial release by snails, rather than solely snail densities or snail infection prevalence, might facilitate improved schistosomiasis control., Author summary Over 800 million people are at risk of schistosomiasis and environmental factors that regulate densities of cercariae parasites that infect humans remain poorly understood. We sampled a spatially extensive area at 36 water-access points in northern Senegal, and quantified densities of snail intermediate hosts, snail predators, and aquatic vegetation in each sample, as well as cercariae released from snails after they were brought to the laboratory. We found that the quantity of submerged aquatic vegetation, particularly Ceratophyllum spp., was positively associated with schistosome cercariae released per infected snail, and total potential cercariae released by the collected snails per water access site. In contrast, the abundance of aquatic predators near infected snails (in the same sweep) was negatively associated with the per-capita cercarial release by infected snails, but positively associated with total snail abundance per site. Additionally, snail densities and potential cercarial densities (estimated as the sum of cercariae released by all collected, infected snails at a site) were only weakly correlated, suggesting that snail densities alone might not accurately reflect total potential of those snails to emit schistosome cercariae. Overall, a better understanding of aquatic factors that can influence the production of schistosome cercariae under field conditions, rather than snail host abundance alone, might facilitate improvements in schistosomiasis monitoring and control.

Background: Every day, billions of people - especially those living in poverty - are exposed to infectious pathogens in the environment and are at risk of contracting 'environmentally mediated' infections: those with environmental reservoirs that affect disease persistence and control. The complex ecology of environmental pathogens creates a global health problem not easily solved with medical treatment alone. Methods: Here, we quantified the global disease burden caused by environmentally mediated infections and used a structural equation modeling approach to explore correlated factors at the global scale. Findings: We found that 80% of pathogen species known to infect humans are environmentally mediated, causing about 40% of today's burden of infectious disease (global loss of 130 million years of healthy life annually). More than 91% of environmentally mediated burden occurs in tropical countries, and the poorest countries carry the highest burdens across all latitudes. We found weak or absent effects of biodiversity or agricultural land use at the global scale. In contrast, the strongest proximate indicator of environmentally mediated infectious disease burden is rural poor livelihoods. Political stability and wealth are associated with improved sanitation, better health care, and lower proportions of rural poor people, indirectly resulting in lower burdens of environmentally mediated infections. Interpretation: The high and uneven burden of environmentally mediated infections highlights the need for innovative social and ecological interventions to complement biomedical advances in the pursuit of global health and sustainability goals. Funding Statement: SHS, IJJ, and GADL received support from the Stanford Institute for Innovation in Developing Economies Global Development and Poverty Initiative. SHS and GADL also received support from the Bill & Melinda Gates Foundation (OPP1114050), National Institutes of Health (NIH) grant #1R01TW010286, National Science Foundation Coupled Natural and Human Systems grant #1414102, and the National Institute for Mathematical and Biological Synthesis through the Working Group "Optimal Control of Neglected Tropical Diseases.” IJJ was also funded by National Science Foundation Graduate Research Fellowship #1656518. SHS, SRH, CLW, KDL, MBonds, and GADL were supported by a grant from the National Center for Ecological Analysis and Synthesis through the Science for Nature and People Partnership program. AJL was supported by the Davis Family E-IPER Fellowship at Stanford and the Stanford Interdisciplinary Graduate Fellowship from the Stanford Vice Provost for Graduate Education. NN was supported by the Stanford Bing Fellowship in Honor of Paul Ehrlich. CLW was supported by a Sloan Research Fellowship from the Alfred P. Sloan Foundation and by the Michigan Society of Fellows at the University of Michigan. AJP was supported by a Queensland Government Accelerate Postdoctoral Research Fellowship and the DARPA PREEMPT program Cooperative Agreement # D18AC00031. Declaration of Interests: The authors declare no competing interests.