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1. Risk of Human Exposure to the Intestinal Schistosome, Schistosoma mansoni, across Seasons along the Senegal River

   https://doi.org/10.24966/GHR-2566/100038  

   JR, Rohr ( December 2021 , Gastroenterology and Hepatology Research)

   Background: Schistosomiasis is an emerging disease associated with changes to the environment that have increased human contact rates with disease-causing parasites, flatworms that are released from freshwater snails. For example, schistosomiasis remains a major public health problem in Northern Senegal, where prevalence in schoolchildren often reaches 90%. Aim: This study focuses on the impact of seasonality on the risk of human exposure (RHE) to Schistosoma mansoni, defined as the total number of cercariae (the free-living life stage that infects humans) shed from all Biomphalaria pfeifferi snails collected at a site using standardized methods. We focus on RHE because it ismore »rarely quantified and a recent study demonstrated that snails stop shedding cercariae when snail densities increase and thus per capita snail resources become limited [2], suggesting that densities of snails might not be directly proportional to RHE to schistosomes. Method: We sampled four water access points in three villages every other week during the early (Dry1) and later dry seasons (Dry2) and the rainy season, quantifying the abundance of infected and non-infected snail intermediate hosts, cercariae released per infected snail, and water chemistry. We used simple and multiple linear regressions to assess how seasonality and environmental parameters affect non-infected and infected snail abundance and RHE. Results: Although RHE was found across all seasons, the abundance of infected and non-infected snail intermediate hosts and cercariae, as well as prevalence (23.71%), were all highest in the rainy season. In the rainy season, RHE was positively associated with the density of snail hosts and their periphyton food resource. Conclusion: Although previous studies have examined the influence of seasonality on snail densities, few studies have explored the effects of seasonality on cercarial densities, which is the primary source of infection to humans. Our study demonstrates that cercarial densities are greater in the rainy season than in the early or late dry seasons. Given that cercarial densities directly pose risk of infection to humans, unlike non-infected or infected snails, these finding should help to inform decision making and schistosomiasis control efforts in West Africa.« less
2. Deep Learning Segmentation of Satellite Imagery Identifies Aquatic Vegetation Associated with Snail Intermediate Hosts of Schistosomiasis in Senegal, Africa

   https://doi.org/10.3390/rs14061345  

   Liu, Zac Yung-Chun ; Chamberlin, Andrew J. ; Tallam, Krti ; Jones, Isabel J. ; Lamore, Lance L. ; Bauer, John ; Bresciani, Mariano ; Wolfe, Caitlin M. ; Casagrandi, Renato ; Mari, Lorenzo ; et al ( March 2022 , Remote Sensing)

   Schistosomiasis is a debilitating parasitic disease of poverty that affects more than 200 million people worldwide, mostly in sub-Saharan Africa, and is clearly associated with the construction of dams and water resource management infrastructure in tropical and subtropical areas. Changes to hydrology and salinity linked to water infrastructure development may create conditions favorable to the aquatic vegetation that is suitable habitat for the intermediate snail hosts of schistosome parasites. With thousands of small and large water reservoirs, irrigation canals, and dams developed or under construction in Africa, it is crucial to accurately assess the spatial distribution of high-risk environments thatmore »are habitat for freshwater snail intermediate hosts of schistosomiasis in rapidly changing ecosystems. Yet, standard techniques for monitoring snails are labor-intensive, time-consuming, and provide information limited to the small areas that can be manually sampled. Consequently, in low-income countries where schistosomiasis control is most needed, there are formidable challenges to identifying potential transmission hotspots for targeted medical and environmental interventions. In this study, we developed a new framework to map the spatial distribution of suitable snail habitat across large spatial scales in the Senegal River Basin by integrating satellite data, high-definition, low-cost drone imagery, and an artificial intelligence (AI)-powered computer vision technique called semantic segmentation. A deep learning model (U-Net) was built to automatically analyze high-resolution satellite imagery to produce segmentation maps of aquatic vegetation, with a fast and robust generalized prediction that proved more accurate than a more commonly used random forest approach. Accurate and up-to-date knowledge of areas at highest risk for disease transmission can increase the effectiveness of control interventions by targeting habitat of disease-carrying snails. With the deployment of this new framework, local governments or health actors might better target environmental interventions to where and when they are most needed in an integrated effort to reach the goal of schistosomiasis elimination.« less
3. Identification of Snails and Schistosoma of Medical Importance via Convolutional Neural Networks: A Proof-of-Concept Application for Human Schistosomiasis

   https://doi.org/10.3389/fpubh.2021.642895  

   Tallam, Krti ; Liu, Zac Yung-Chun ; Chamberlin, Andrew J. ; Jones, Isabel J. ; Shome, Pretom ; Riveau, Gilles ; Ndione, Raphael A. ; Bandagny, Lydie ; Jouanard, Nicolas ; Eck, Paul Van ; et al ( July 2021 , Frontiers in Public Health)

   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,more »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.« less
4. Visualization of schistosomiasis snail habitats using light unmanned aerial vehicles

   https://doi.org/10.4081/gh.2020.818  

   Chamberlin, Andrew J. ; Jones, Isabel J. ; Lund, Andrea J. ; Jouanard, Nicolas ; Riveau, Gilles ; Ndione, Raphaël ; Sokolow, Susanne H. ; Wood, Chelsea L. ; Lafferty, Kevin D. ; De Leo, Giulio A. ( November 2020 , Geospatial Health)

   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 bemore »educated about the infection risk.« less
5. Transmission potential of human schistosomes can be driven by resource competition among snail intermediate hosts

   https://doi.org/10.1073/pnas.2116512119  

   Civitello, David J. ; Angelo, Teckla ; Nguyen, Karena H. ; Hartman, Rachel B. ; Starkloff, Naima C. ; Mahalila, Moses P. ; Charles, Jenitha ; Manrique, Andres ; Delius, Bryan K. ; Bradley, L. M. ; et al ( February 2022 , Proceedings of the National Academy of Sciences)

   Predicting and disrupting transmission of human parasites from wildlife hosts or vectors remains challenging because ecological interactions can influence their epidemiological traits. Human schistosomes, parasitic flatworms that cycle between freshwater snails and humans, typify this challenge. Human exposure risk, given water contact, is driven by the production of free-living cercariae by snail populations. Conventional epidemiological models and management focus on the density of infected snails under the assumption that all snails are equally infectious. However, individual-level experiments contradict this assumption, showing increased production of schistosome cercariae with greater access to food resources. We built bioenergetics theory to predict how resourcemore »competition among snails drives the temporal dynamics of transmission potential to humans and tested these predictions with experimental epidemics and demonstrated consistency with field observations. This resource-explicit approach predicted an intense pulse of transmission potential when snail populations grow from low densities, i.e., when per capita access to resources is greatest, due to the resource-dependence of cercarial production. The experiment confirmed this prediction, identifying a strong effect of infected host size and the biomass of competitors on per capita cercarial production. A field survey of 109 waterbodies also found that per capita cercarial production decreased as competitor biomass increased. Further quantification of snail densities, sizes, cercarial production, and resources in diverse transmission sites is needed to assess the epidemiological importance of resource competition and support snail-based disruption of schistosome transmission. More broadly, this work illustrates how resource competition can sever the correspondence between infectious host density and transmission potential.« less