Schistosomiasis remains a significant public health concern in tropical and subtropical regions, especially in low-and-middle-income countries. In Brazil, control measures have reduced the disease's prevalence, creating low-endemic areas. However, environmental and climate dynamics, coupled with inadequate urbanization, pose risks of re-emergence. The middle Paranapanema basin, S & atilde;o Paulo state, exemplifies such a region. Here, the presence of Biomphalaria snail species (B. glabrata, B. straminea, and B. tenagophila), inadequate sanitation, and environmental changes signal potential schistosomiasis resurgence. This study aimed to develop a methodological framework to better understand schistosomiasis transmission mechanisms in low-endemic areas. It integrated demographic, environmental, malacological, and climatic data to identify transmission risk areas. The framework comprised a spatial hydrological model to assess fecal-contaminated water bodies, an exploratory spatial model for transmission hotspots, and snail dispersal analysis within drainage networks, incorporating climate projections. The methodology used geoprocessing tools to analyze hydrological, demographic, malacological, and climatic datasets. A spatial hydrological model combined sewage treatment and population density data with digital elevation models to identify potential transmission foci. Snail occurrence and schistosomiasis cases were spatially analyzed, with climate indices (1951-2022) providing rainfall trend projections. Land use datasets facilitated host habitat assessments, and outputs correlated potential foci with disease incidence. Results revealed that streams near urban areas with high concentrations of blackwater were associated with schistosomiasis cases. Streams hosting B. glabrata upstream had the strongest association with disease, while mixed-species habitats underscored hydrological connectivity's role. Urban and agricultural land-use areas overlapped with snail habitats, identifying high-risk zones. Climate projections indicated increasing extreme rainfall events, enhancing flooding and erosion, which may facilitate snail dispersal and extend schistosomiasis foci downstream. Effluent from municipalities like Ourinhos could intensify contamination, impacting neighboring areas like Salto Grande. The findings emphasize integrating hydrological, climatic, and ecological perspectives into schistosomiasis control strategies. Simple hydrological models assessing fecal-contaminated water bodies provide valuable insights for sanitation policies, and climate-related snail dispersal scenarios highlight emerging risks in connected areas. Addressing these challenges is crucial for eliminating schistosomiasis, particularly in low-endemic regions. This study's novel integrated hydrological-spatial models, based on freely available data, offer reproducible methods for identifying schistosomiasis transmission risks and guiding surveillance and control efforts in similar settings across Brazil.

The complex relationship between temperature and schistosomiasis, an environmentally mediated neglected tropical disease affecting 250 million people globally, with hyperendemicity mostly in Africa, is poorly characterized. Here, we explored how seasonal temperature fluctuation affects the persistence, dynamics, and geographic distribution of schistosomiasis in Africa. We used a temperature-sensitive, mechanistic model of schistosomiasis dynamics that accounts for the adaptive behaviors of intermediate snail hosts and derived the disease's thermal response curve for different patterns of seasonal temperature fluctuations. Changing the amplitude of seasonal temperature fluctuations can influence both the thermal optimum and critical thermal thresholds which imply accurately drawing the thermal response curves requires accounting for seasonality in addition to mean annual temperature. Moreover, our simulations can reproduce the documented persistence of schistosomiasis at locations with strong seasonal temperature fluctuations and mean annual temperatures near or above the critical thermal maxima for snail hosts only when snail adaptive behavior (e.g., aestivation, movement into cooler depths or shade) is included in the model. These results suggest that future climate change impacting the amplitude and timing of these fluctuations will likely alter the future geographic distribution of schistosomiasis in African regions. Our work demonstrates that a comprehensive understanding of schistosomiasis and, potentially, other environmentally mediated diseases in Africa, necessitates the inclusion of seasonal temperature fluctuations and host behavioral adaptations in process-based mechanistic models.

Species distribution models (SDMs) are increasingly popular tools for profiling disease risk in ecology, particularly for infectious diseases of public health importance that include an obligate non-human host in their transmission cycle. SDMs can create high-resolution maps of host distribution across geographical scales, reflecting baseline risk of disease. However, as SDM computational methods have rapidly expanded, there are many outstanding methodological questions. Here we address key questions about SDM application, using schistosomiasis risk in Brazil as a case study. Schistosomiasis is transmitted to humans through contact with the free-living infectious stage of Schistosoma spp. parasites released from freshwater snails, the parasite’s obligate intermediate hosts. In this study, we compared snail SDM performance across machine learning (ML) approaches (MaxEnt, Random Forest, and Boosted Regression Trees), geographic extents (national, regional, and state), types of presence data (expert-collected and publicly-available), and snail species (Biomphalaria glabrata, B. straminea, and B. tenagophila). We used high-resolution (1km) climate, hydrology, land-use/land-cover (LULC), and soil property data to describe the snails’ ecological niche and evaluated models on multiple criteria. Although all ML approaches produced comparable spatially cross-validated performance metrics, their suitability maps showed major qualitative differences that required validation based on local expert knowledge. Additionally, our findings revealed varying importance of LULC and bioclimatic variables for different snail species at different spatial scales. Finally, we found that models using publicly-available data predicted snail distribution with comparable AUC values to models using expert-collected data. This work serves as an instructional guide to SDM methods that can be applied to a range of vector-borne and zoonotic diseases. In addition, it advances our understanding of the relevant environment and bioclimatic determinants of schistosomiasis risk in Brazil.

Background Schistosomiasis, a chronic parasitic disease, remains a public health issue in tropical and subtropical regions, especially in low and moderate-income countries lacking assured access to safe water and proper sanitation. A national prevalence survey carried out by the Brazilian Ministry of Health from 2011 to 2015 found a decrease in human infection rates to 1%, with 19 out of 26 states still classified as endemic areas. There is a risk of schistosomiasis reemerging as a public health concern in low-endemic regions. This study proposes an integrated landscape-based approach to aid surveillance and control strategies for schistosomiasis in low-endemic areas. Methodology/Principal findings In the Middle Paranapanema river basin, specific landscapes linked to schistosomiasis were identified using a comprehensive methodology. This approach merged remote sensing, environmental, socioeconomic, epidemiological, and malacological data. A team of experts identified ten distinct landscape categories associated with varying levels of schistosomiasis transmission potential. These categories were used to train a supervised classification machine learning algorithm, resulting in a 92.5% overall accuracy and a 6.5% classification error. Evaluation revealed that 74.6% of collected snails from water collections in five key municipalities within the basin belonged to landscape types with higher potential for S. mansoni infection. Landscape connectivity metrics were also analysed. Conclusions/Significance This study highlights the role of integrated landscape-based analyses in informing strategies for eliminating schistosomiasis. The methodology has produced new schistosomiasis risk maps covering the entire basin. The region’s low endemicity can be partly explained by the limited connectivity among grouped landscape-units more prone to triggering schistosomiasis transmission. Nevertheless, changes in social, economic, and environmental landscapes, especially those linked to the rising pace of incomplete urbanization processes in the region, have the potential to increase risk of schistosomiasis transmission. This study will help target interventions to bring the region closer to schistosomiasis elimination.

The geographical range of schistosomiasis is affected by the ecology of schistosome parasites and their obligate host snails, including their response to temperature. Previous models predicted schistosomiasis' thermal optimum at 21.7 °C, which is not compatible with the temperature in sub-Saharan Africa (SSA) regions where schistosomiasis is hyperendemic. We performed an extensive literature search for empirical data on the effect of temperature on physiological and epidemiological parameters regulating the free-living stages of S. mansoni and S. haematobium and their obligate host snails, i.e., Biomphalaria spp. and Bulinus spp., respectively. We derived nonlinear thermal responses fitted on these data to parameterize a mechanistic, process-based model of schistosomiasis. We then re-cast the basic reproduction number and the prevalence of schistosome infection as functions of temperature. We found that the thermal optima for transmission of S. mansoni and S. haematobium range between 23.1-27.3 °C and 23.6-27.9 °C (95 % CI) respectively. We also found that the thermal optimum shifts toward higher temperatures as the human water contact rate increases with temperature. Our findings align with an extensive dataset of schistosomiasis prevalence in SSA. The refined nonlinear thermal-response model developed here suggests a more suitable current climate and a greater risk of increased transmission with future warming for more than half of the schistosomiasis suitable regions with mean annual temperature below the thermal optimum.

ABSTRACTSchistosomiasis is a neglected tropical disease caused bySchistosomaparasites.Schistosomaare obligate parasites of freshwaterBiomphalariasnails, 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 competentBiomphalariathroughout Brazil. We identified key features influencing the distribution of suitable habitat and determined howBiomphalariahabitat 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 inBiomphalariadistribution – while accounting for non-linearities that are difficult to detect from local case studies – can help inform schistosomiasis control strategies.

Schistosomiasis is a neglected tropical disease caused by Schistosoma parasites. Schistosoma are obligate parasites of freshwater Biomphalaria and Bulinus snails, thus 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 used machine learning, remote sensing, and 30 years of snail occurrence records to map the historical and current distribution of forward-transmitting Biomphalaria hosts 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. Schistosomiasis is an emerging urban and peri-urban disease in Brazil and freshwater snails are an obligate host of the causative parasite. Here, the authors investigate the ecological suitability for the three freshwater snail hosts in Brazil and identify changes over time driven by climate and urbanisation.

IntroductionBiomphalaria glabrata, B. tenagophila, and B. straminea occurrence are crucial for estimating the risk of infectious human schistosomiasis in the neotropics. How different geographic sample strategies influence snail genetic diversity estimations were here investigated for three Schistosoma mansoni hosts.MethodsMitochondrial gene sequences were employed for Cytochrome C Oxidase I (COI), ribosomal RNA (rRNA) 16S, and a dataset with concatenated gene sequences (COI+16S), resulting in an improved scientific hypothesis regarding the geographical distribution of snail species. This study compared the sequences of snails from the Middle Paranapanema (MP) hydrographic basin in a geographically restricted area (inner group) to snails widely distributed across a broad geographical range in São Paulo (outer group), Brazil from 1999 to 2017. DNA sequence polymorphisms and haplotype diversity were estimated using DNAsp software. Haplotype network trees were constructed using a network program. The geographical distribution of the haplotypes was mapped using QGIS. Haplotype variation and distribution were tested for population structure using analysis of molecular variance (AMOVA).Results and discussionThe genetic diversity of B. glabrata, sampled from disconnected but geographically close freshwater collections, was partitioned into two sequence groups. The haplotype network showed that the diversity of B. straminea was more spatially partitioned than in B. tenagophila, which exhibited two population groups. The haplotype distribution pattern for B. tenagophila showed many unique and exclusive haplotypes for all three loci. AMOVA showed that genetic diversity could be high in species inhabiting small geographical areas, and a large river is not a local geographical barrier for snail migration. This study found that the survey dimensions and snail samplings influenced the genetic diversity results obtained by mitochondrial DNA molecular markers.

INTRODUCTION:Ourinhos is a municipality located between the Pardo and Paranapanema rivers, and it has been characterized by the endemic transmission of schistosomiasis since 1952. We used geospatial analysis to identify areas prone to human schistosomiasis infections in Ourinhos. We studied the association between the sewage network, co-occurrence of Biomphalaria snails (identified as intermediate hosts [IHs] of Schistosoma mansoni), and autochthonous cases. METHODS:Gi spatial statistics, Ripley's K12-function, and kernel density estimation were used to evaluate the association between schistosomiasis data reported during 2007-2016 and the occurrence of IHs during 2015-2017. These data were superimposed on the municipality sewage network data. RESULTS:We used 20 points with reported IH; they were colonized predominantly by Biomphalaria glabrata, followed by B. tenagophila and B. straminea. Based on Gi statistics, a significant cluster of autochthonous cases was superimposed on the Christoni and Água da Veada water bodies, with distances of approximately 300 m and 2200 m from the points where B. glabrata and B. straminea were present, respectively. CONCLUSIONS:The residence geographical location of autochthonous cases allied with the spatial analysis of IHs and the coverage of the sewage network provide important information for the detection of human-infection areas. Our results demonstrated that the tools used for direct surveillance, control, and elimination of schistosomiasis are appropriate.

The Middle Paranapanema region in the state of Sao Paulo, Brazil, is an area with high diversity for Biomphalaria species, with municipalities historically marked by cases of schistosomiasis transmission. The objectives of the study were to evaluate the current distribuition and predict the future distribution of habitats of Biomphalaria species at a high spatial resolution along 114 freshwater sites in the Middle Paranapanema watershed. The modelling encompassed 55 municipalities of the Middle Paranapanema region, which were analyzed through the maximum entropy algorithm. All geographic coordinates of the Biomphalaria species collected from 2015-2018 and environmental data were obtained through WorldClim, HydroSHEDS, TOPODATA and Secretaria do Meio Ambiente for the 1970-2017 period. For the 2041-2060 period we used the HadGEM2-ES climate model. Due to climate change, MaxEnt showed that there was a high probability for the maintenance of B. glabrata habitats near Ourinhos and Assis, an expansion of scattered spots, and a 50% probability that the species will spread throughout new suitable areas. The results showed that the geographical range of B. straminea will most likely expand in the future along the Middle Paranapanema hydrographic basin, especially in the municipalities near Ourinhos. For B. glabrata and B. straminea, the geographic expansion was related to the predicted increase in the annual temperature range. The habitats suitable for B. tenagophila and B. peregrina seemed to slightly expand around the west border of the Middle Paranapanema region. Biomphalaria occidentalis may have a small reduction in its distribution due to climate change. The variables that contributed the most to the future modelling for these three species were precipitation and temperature. Identifying the sites with intermediate hosts for schistosomiasis may guide public health measures to avoid or reduce future transmissions in this region.

Approximately 240 million people worldwide are infected by Schistosoma. In Brazil, one of the main intermediate hosts of this parasite is Biomphalaria glabrata snails. The early detection of larval stages in intermediate hosts is an important challenge to public health, but it also represents an opportunity as a new alternative to indicate earlier natural infections before cercariae differentiation and emergence. In this context, we demonstrated that PCR amplification of a 28S gene fragment from the parasite does demonstrate S. mansoni infection in snails 14 days post infection. This conventional polymerase chain reaction amplified clear bands and was able to detect parasitic infection in the intermediate host B. glabrata under experimental conditions. However, we reinforce that this approach requires deeper investigations and further comparisons to confirm its specificity and sensitivity in earlier time points after miracidia infection. This approach has relevant potential as an effective molecular-based strategy for the monitoring of schistosomiasis transmission.

Abstract: Morphological and molecular identifications were carried out for Biomphalaria occidentalis, Biomphalaria oligoza, Biomphalaria peregrina, Biomphalaria schrammi, Biomphalaria straminea and Biomphalaria tenagophila collected from 55 sites located along the upper basin of Tietê River in the Southeast Region of Brazil. Morphological analysis considered aspects of the shell, mantle, excretory organs and reproductive system. Molecular data included 122 sequences of Cytochrome C Oxidase I gene (COI). Our results showed that some shell characters, as well as other characters related to the mantle and the reproductive system, are fundamental for the identification of the six Biomphalaria species included in this study. The use of DNA barcoding together with morphological taxonomy generated more reliable results, proving to be a very useful approach, even for malacological surveillance services.

Introduction: The Middle Paranapanema watershed is known for the transmission of schistosomiasis, and there have been autochthonous cases since 1952. This study aimed to describe this disease in space and time and evaluate its current importance as a public health problem. Methods: Thematic maps showing the risk areas for transmission of schistosomiasis, using scan statistics. and flow maps were created in the period 1978-2016. Incidence was calculated, and the existence of spatial dependence between autochthonous and imported cases was evaluated using Ripley's K12-function. Species of snails were identified in high-risk clusters. Results: A total of 1,511 autochthonous cases were reported in eight of the 25 municipalities in the study area, of which 92.8% occurred in Ourinhos. A total of 2.189 imported cases were reported (27% in Ourinhos and 20% in Assis), mainly originating in the states of Parana and Minas Gerais. Clusters of autochthonous and imported cases with higher risk were identified in Ourinhos, Assis and Ipaussu. However, over the years, the cases began to occur in low density in Ourinhos and no longer in other municipalities in the region. The cluster detected in the period 2007-2016 in Ourinhos still has risk for the transmission of schistosomiasis. K12-function analysis indicated positive spatial dependence between autochthonous and imported cases. Conclusions: The study showed that, currently, schistosomiasis as a public health problem in Middle Paranapanema is restricted to Ourinhos. This fact may be related to the presence of Biomphalaria glahrata at a specific point and low coverage of basic sanitation.

The Middle Paranapanema River region of São Paulo, Brazil is home to significant diversity of Biomphalaria species and is very vulnerable to health and environmental impacts such as schistosomiasis. This study updates freshwater malacological surveys for ecosystems in one portion of the Middle Paranapanema River Basin, with emphasis on the genus Biomphalaria. Snails were collected from 114 distinct bodies of water between 2015 and 2018. Biomphalaria specimens were identified according to morphological and molecular characteristics, while animals in other genera (Drepanotrema, Lymnaea, Melanoides, Physa and Pomacea) were identified solely according to shell characteristics. A geographic information system was used to update intermediate host colonization sites and consequently assist in identifying probable hotspots for intermediate hosts of schistosomiasis. The sequences of the COI gene relating to the DNA barcode stretch were tested for similarity against sequences found in GenBank, for monophyly through Maximum Likelihood phylogenetic inference, and analyzed in ABDG, bPTP and GMYC for the delimitation of putative species. Of the 10,722 snails collected, 86.7% were in the Planorbidae family (75.5% Biomphalaria and 11.2% Drepanotrema) and 13.3% were other non-Planorbidae species (Lymnaea, Melanoides, Physa and Pomacea). The taxonomic COI reference sequences in the NCBI nucleotide database used for DNA sequence comparison, and phylogenetic analysis used to test the monophyly of the groups, resulted in more reliable taxonomic units than delimitation of the COI sequences in MOTUs using statistical taxonomic models. Analysis of the species distribution shows that B. glabrata and B. tenagophila are heterogeneously distributed in the study area. B. glabrata colonizes only five water bodies, in the study area, most of them in Ourinhos, while B. tenagophila predominates in water bodies in Ipaussu. Contrasting with this, B. straminea, B. occidentalis and B. peregrina are evenly distributed throughout the study area.

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The radular apparatus of Biomphalaria occidentalis Paraense, 1981, Biomphalaria oligoza Paraense, 1971, Biomphalaria peregrina (d'Orbigny, 1835), Biomphalaria schrammi (Crosse, 1864) and Biomphalaria tenagophila (d'Orbigny, 1835) from the Metropolitan Region of Sao Paulo, Brazil were analyzed from Scanning Electron Microscope (SEM) micrographs. The data support the usage of characters of central, lateral and intermediate teeth in the species identification of Biomphalaria. The use of SEM provided additional quantitative and structural details to radula descriptions, which are extremely important for elucidating the taxonomy of Biomphalaria species.

DNA barcoding and morphological characters were used to identify adult snails belonging to the genus Biomphalaria from 17 municipalities in the state of São Paulo, Brazil. The DNA barcode analysis also included twenty-nine sequences retrieved from GenBank. The final data set of 104 sequences of the mitochondrial cytochrome oxidase I (COI) gene was analyzed for K2P intraspecific and interspecific divergences, through tree-reconstruction methods (Neighbor-Joining, Maximum Likelihood and Bayesian inference), and by applying different models (ABGD, bPTP, GMYC) to partition the sequences according to the pattern of genetic variation. Twenty-seven morphological parameters of internal organs were used to identify specimens. The molecular taxonomy of Biomphalaria agreed with the morphological identification of specimens from the same collection locality. DNA barcoding may therefore be a useful supporting tool for identifying Biomphalaria snails in areas at risk for schistosomiasis.