Biology subjects

Sokolow, S. H.

Publications and source records attributed to Sokolow, S. H..

5 recordsLinked to original sources

bioRxiv2024

Climate variables and urbanization drive changes in the distribution of S. mansoni competent snails in Brazil: novel results from a counterfactual analysis

Schistosomiasis is a neglected tropical disease caused by Schistosoma parasites. Schistosoma are obligate parasites of freshwater Biomphalaria snails, so controlling snail populations is critical to reducing transmission risk. As snails are sensitive to environmental conditions, we expect their distribution is significantly impacted by global change. Here, we leveraged machine learning, remote sensing, and 30 years of snail occurrence records to map the historical and current distribution of competent Biomphalaria throughout Brazil. We identified key features influencing the distribution of suitable habitat and determined how Biomphalaria habitat has changed with climate and urbanization over the last three decades. Our models show that climate change has driven broad shifts in snail host range, whereas expansion of urban and peri-urban areas has driven localized increases in habitat suitability. Elucidating change in Biomphalaria distribution - while accounting for non-linearities that are difficult to detect from local case studies - can help inform schistosomiasis control strategies.

ecology↗

bioRxiv2021

Identifying low risk insecticides to address both food shortages and the biocontrol of human schistosomiasis

Use of agrochemicals, including insecticides, is vital to food production and predicted to increase 2-5 fold by 2050. Previous studies have shown a positive association between agriculture and the human infectious disease schistosomiasis, which is problematic as this parasitic disease infects approximately 250 million people worldwide. Certain insecticides might runoff fields and be highly toxic to invertebrates, such as prawns in the genus Macrobrachium, that are biocontrol agents for snails that transmit the parasites causing schistosomiasis. We used a laboratory dose-response experiment and an observational field study to determine the relative toxicities of three pyrethroid (esfenvalerate, {lambda}-cyhalothrin, and permethrin) and three organophosphate (chlorpyrifos, malathion, and terbufos) insecticides to Macrobrachium prawns. In the lab, pyrethroids were consistently several orders of magnitude more toxic than organophosphate insecticides, and more likely to runoff fields at lethal levels according to modeling data. In the field, we found that Macrobrachium prawn survival at 31 water contact sites in the lower basin of the Senegal River where schistosomiasis is endemic was predicted by pyrethroid application rates to nearby crop fields after controlling for abiotic and prawn-level factors. Our findings suggest that widely used pyrethroid insecticides can have strong non-target effects on Macrobrachium prawns that are biocontrol agents where 400 million people are at risk of human schistosomiasis. Understanding the ecotoxicology of high-risk insecticides may help improve human health in schistosomiasis-endemic regions undergoing agricultural expansion.

ecology↗

bioRxiv2019

Identification of snails and parasites of medical importance via convolutional neural network: an application for human schistosomiasis

Schistosomiasis is a debilitating parasitic disease infecting over 250 million people with nearly 800 million people at risk worldwide, primarily in sub-Saharan Africa. Transmission to humans involves freshwater snails as intermediate hosts, which are particularly prevalent in developing countries where dams and water resource projects have expanded freshwater snail habitat. At our study sites in the lower Senegal River Basin, we have collected more than 5,500 images of the 7 freshwater snail species (grouped into 4 categories) most frequently encountered in this aquatic ecosystem, 5 of which amplify and transmit either urinary or intestinal human schistosomiasis, with the other 2 species responsible for the transmission of less common parasitic diseases of humans and/or livestock. We have also collected over 5,100 images of 11 classes of trematodes, including human and non-human schistosomes. It takes a great deal of training and expertise to accurately classify these organisms morphologically. In recent years, deep convolutional neural networks (CNNs) have proven to be highly efficient for image recognition tasks across many object categories. Here we demonstrate classification capacity for snail and parasite images and test our models performance against 8 highly-trained human parasitologists with experience taxonomically classifying snail and parasite species from the Senegal River Basin in West Africa. We establish and train a single CNN end-to-end directly from images with only pixels and labels as inputs. Applying this state-of-the-art algorithm, we are able to classify images of 4 snail categories with 99.64% accuracy and images of 11 parasite categories with 88.14% accuracy, which rivals highly-trained human parasitologists. The trained algorithm could next be deployed to mobile devices for use in remote field settings by local technicians, and significantly improve monitoring snail and parasite occurrence in the field for disease control purposes.\n\nAuthor SummarySchistosomiasis is a neglected tropical disease (NTD) infecting over 250 million people worldwide. The current approach to mitigate this disease in endemic regions is community or school-based mass drug administration. However, parasites are primarily transmitted through environmental reservoirs where freshwater snails serve as intermediate hosts. People use the contaminated water sources for their daily tasks and get re-infected after drug treatment. Therefore, drug administration alone is not effective for schistosomiasis control in such high transmission settings. Recent studies show that snail population control is essential to reduce disease transmission risks. To discern between parasitic worms of humans in snails and those of other non-human species is a necessary step to precisely quantify transmission risk for human schistosomiasis. However, it takes a great deal of expertise to train lab and field technicians to accurately classify snail and parasite species. Artificial intelligence (AI)-powered computer vision algorithms have recently proven to be highly efficient for image recognition tasks. We have collected thousands of snail and parasite images in Senegal during 2015-2018. Using these images as training data, we developed an AI model that classifies images of 4 snail categories and 11 parasite categories with, in some cases, higher accuracy than well-trained human parasitologists. This model could next be deployed to mobile devices for use in remote field settings to support local technicians to identify transmission hotspots and target control.

bioinformatics↗

bioRxiv2018

Prawn aquaculture as a method for schistosomiasis control and poverty alleviation: a win-win approach to address a critical infectious disease of poverty

Recent evidence suggests crustacean snail predators may aid schistosomiasis control programs by targeting the environmental component of the parasites life cycle through predation of the snail species that serve as intermediate hosts of the parasite. We evaluate costs, benefits, and potential synergies between schistosomiasis control and aquaculture of giant prawns using an integrated bio-economic-epidemiologic model. We identified combinations of stocking density and aquaculture cycle length that maximize profit and offer disease control benefits for sustainable schistosomiasis control. We consider two prawn species in sub-Saharan Africa: the endemic, non-domesticated Macrobrachium vollenhovenii, and the non-native, domesticated Macrobrachium rosenbergii. We find that, at profit-optimal densities, both M. rosenbergii and M. vollenhovenii can complement conventional control approaches (mass drug treatment of people) and lead to sustainable schistosomiasis control. We conclude that integrated aquaculture strategies can be a win-win strategy in terms of health and sustainable development in schistosomiasis endemic regions of the world.

epidemiology↗

bioRxiv2017

Agrochemical pollution increases risk of human exposure to schistosome parasites

Roughly 10% of the global population is at risk of schistosomiasis, a snail-borne parasitic disease that ranks among the most important water-based diseases of humans in developing countries1-3. Increased prevalence, infection intensity, and spread of human schistosomiasis to non-endemic areas has been consistently linked with water resource management related to agricultural expansion, such as dam construction, which has resulted in increased snail habitat1,4-6. However, the role of agrochemical pollution in human schistosome transmission remains unexplored, despite strong evidence of agrochemicals increasing snail-borne diseases of wildlife7-9 and a projected 2- to 5-fold increase in global agrochemical use by 205010 that will disproportionately occur in schistosome-endemic regions. Using a field mesocosm experiment, we show that environmentally relevant concentrations of fertilizer, the common herbicide atrazine, and the common insecticide chlorpyrifos, individually and as mixtures, increase densities of schistosome-infected snails by increasing the algae snails eat (fertilizer and atrazine) and decreasing densities of snail predators (chlorpyrifos). Epidemiological models indicate that these agrochemical effects can increase transmission of schistosomiasis. Hence, the rapid agricultural changes occurring in schistosome-endemic regions11,12 that are driving increased agrochemical use and pollution could potentially increase the burden of schistosomiasis in these areas. Identifying agricultural practices or agrochemicals that minimize disease risk will be critical to meeting growing food demands while improving human wellbeing13,14.

ecology↗