MaxEnt modeling of soil-transmitted helminth infection distributions in Thailand

Systematic review and meta-analysis of soil-transmitted helminth infections in South America (2000-2024)

Soil-transmitted helminths (STHs) are parasitic nematodes commonly found in tropical and subtropical regions, where poor sanitation makes them a significant public health concern. This study provides a comprehensive review and meta-analysis of human STH infections across 13 South American countries from 2000 to 2023. It covers these infections' prevalence, distribution, and diagnosis, highlighting the environmental factors influencing transmission pathways. The review identified 134 studies on human STH infections, revealing Brazil as the most researched country. The meta-analysis found prevalence rates of Ascaris lumbricoides, Trichuris trichiura, hookworms, and Strongyloides stercoralis below 20 %, with notable heterogeneity across studies. Most studies used conventional microscopy for diagnosis, pointing out the need for implementing advanced diagnostic tools. Environmental and climatic factors, including temperature annual range, vegetation density, soil types, and properties were significant predictors of STH prevalence. The study calls for more research performing advanced diagnostic methods and broader geographical coverage to address existing data gaps. Furthermore, it emphasizes the need for holistic public health policies integrating biomedical and environmental approaches to ensure effective disease management.

Spatial analysis of dengue fever incidence and serotype distribution in Vientiane Capital, Laos: A multi-year study

Laos is a hyperendemic country of all 4 dengue serotypes. Various factors contribute to the spread of the disease including viral itself, vectors, and environment. This study aims to analyze dengue data and its incidence in nine districts of Vientiane Capital, Laos spanning from 2019 to 2021 by data collected from Mittaphab Hospital. The Maximum Entropy algorithm (MaxEnt) was applied to assess spatial distribution and identify high-probability locations for dengue occurrence by analyzing crucial environmental and climatic conditions. Dengue cases were more prominent in female (54.88 %) and highest case number was found in worker group (29.02 %) followed by student (28.47 %) and officer (16.92 %). In this study, the age group 21-30 years old had the highest infection rate (42.23 %), followed by 10-20 years old (24.21 %). Most of dengue cases was primary infection (91.61 %). Dengue serotype 2 predominated in 2019 and 2020 and substitute by serotype 1 in 2021. Across the nine districts of Vientiane Capital, the highest incidence of dengue was found in Xaythany district population in 2019, shifting to Chanthabouly district in 2020 and 2021. The MaxEnt revealed potentially most suitable areas for dengue were widely distributed central south part of Vientiane, Laos. Additionally, the best predictive variable for dengue occurrence was normalized difference vegetation index. Understanding of case characteristics and spatial distribution features of dengue will be helpful in effective surveillance and disease control in the future.

Potential distribution of malaria vectors in Central Vietnam: A MaxEnt modeling approach

Background and Aim

In Central Vietnam, Anopheles dirus and Anopheles minimus are the primary malaria vector species. These Anopheles spp.' distribution and prevalence are determined by environmental, climatic, and socioeconomic conditions. This study aimed to predict the potential distribution of these two Anopheles spp. in this region.

Materials and Methods

This study was conducted in 15 Central Vietnamese provinces. From 2014 to 2018, we utilized An. dirus and An. minimus presence records. Proxy data from the Google Earth Engine platform for the study area, encompassing environmental, climatic, and socioeconomic factors. MaxEnt software predicted the potential environmental, climatic, and socioeconomic suitability of these two Anopheles spp. in Central Vietnam.

Results

The test area under the curve values for An. dirus and An. minimus MaxEnt models averaged 0.801 and 0.806, respectively, showing excellent performance. Minimum air temperature had the greatest impact on the distribution of both species. A negative correlation between precipitation and normalized difference water index influences the occurrence of An. dirus. In the temperature range of 13-19.5°C, An. minimus is most likely to be present, with nighttime light detrimentally influencing its distribution. The Central Highlands region is inhabited by both species, with some presence in North-Central and South-Central Coastal areas.

Conclusion

The importance of temperature in determining the presence of both species is emphasized by our findings, with subtle differences in the temperature-related factors shaping their distributions. The results highlight the need for focused malaria vector control and surveillance initiatives in the study area.

MaxEnt modeling of the potential risk of schistosomiasis in the Philippines using bioclimatic factors

Schistosomiasis is a parasitic infection caused by Schistosoma japonicum. It remains a principal local health issue in the Philippines, demonstrating endemicity in 28 provinces and afflicting thousands of Filipino individuals annually. Despite this, no clear distribution maps for the disease have been comprehensively reported. Therefore, species distribution modeling (SDM) employing the MaxEnt algorithm and GIS application techniques was utilized to denote the potential risk of schistosomiasis in the country. With a high AUC score of 0.846, the SDM yielded a favorable and reliable correlative map illustrating a predicted schistosomal temporal distribution concentrated primarily on the country's eastern portion with a more pronounced wet than dry season. The precipitation of the driest quarter was determined to be the most significant contributing factor among the bioclimatic variables evaluated. This suggests a possible increase in adaptations concerning the rainfall and thermal tolerances of the parasites' vectors. Moreover, socioeconomic status between Philippine regions revealed an inverse proportion with the number of schistosomiasis cases. This study also discussed the potential role of climate change on the range shifts and the potential risk of parasite infection in the Philippines.

The Relationship Between Soil-Transmitted Helminth Infections and Environmental Factors in Puerto Iguazú, Argentina: Cross-Sectional Study

BACKGROUND

Soil-transmitted helminths (STHs) are widely distributed throughout the world. Various factors, including the environment, socioeconomic characteristics, and access to water and sanitation, play an important role in the spread and persistence of these parasites within communities. They, in turn, affect the growth and development of members of the community, especially children. Studies in the northern provinces of Argentina have shown variable prevalence of STHs, but the factors associated with their presence have not been completely elucidated.

OBJECTIVE

This cross-sectional study aimed to identify the socioeconomic and environmental factors related to STH infection in indigenous villages located in Puerto Iguazú (Misiones), Argentina.

METHODS

Between 2018 and 2019, stool samples were collected from individuals ≥1 year residing in 3 villages: Mini-Marangatú, Yriapú, and Fortín Mbororé. Standard parasitological methods were used to determine STH prevalence. Standardized questionnaires were used to assess participants' habits, customs, and household characteristics, and environmental data were obtained through satellite imagery. Multilinear regression with Akaike information criterion stepwise variables was used to explore relevant associations.

RESULTS

A total of 342 individuals from the 3 villages participated in this study. The prevalence of STHs varied across villages: 89.6% (43/48), in Mini-Marangatú, 80.8% (101/125) in Yriapú, and 68.5% (115/169) in Fortín Mbororé. Notably, there was a significant difference in hookworm infection among the villages (P=.02). The analysis highlighted the significant influence of specific environmental factors on STH presence and spatial distribution, particularly in relation to hookworm infection. Vegetation patterns represented by the Vegetation Heterogeneity Index, created ad hoc for this study, emerged as a critical factor, with 2 significant predictors related to it (P=.002 and P=.004) alongside impervious surface density with a significant predictor (P<.001). The multilinear regression model yielded a high F test score (F108=4.75, P<.001), indicating a strong fit (R2=0.5465). Furthermore, socioeconomic factors, including walking barefoot in houses with dirt floors and overcrowding, were significantly correlated with hookworm infection intensity (P<.001 and P=.001, respectively). We also used the multilinear regression model to calculate hookworm infection intensity (F110=21.15, P<.001; R2=0.4971).

CONCLUSIONS

Our study underscores the complexity of STH transmission, as villages with similar living conditions and environmental characteristics displayed varied STH prevalence and spatial distribution. Specific environmental factors, such as vegetation pattern and impervious surface density, played major roles in STH presence, demonstrating the crucial relationship between environmental factors and hookworm infection distribution. Moreover, our findings emphasize the significant influence of socioeconomic factors on hookworm infection intensity. By gaining insights into this complex interplay, our research contributes to a better understanding of STH transmission characteristics, thereby informing targeted public health interventions for effective control.

Machine learning to predict risk for community-onset Staphylococcus aureus infections in children living in southeastern United States

Staphylococcus aureus (S. aureus) is known to cause human infections and since the late 1990s, community-onset antibiotic resistant infections (methicillin resistant S. aureus (MRSA)) continue to cause significant infections in the United States. Skin and soft tissue infections (SSTIs) still account for the majority of these in the outpatient setting. Machine learning can predict the location-based risks for community-level S. aureus infections. Multi-year (2002-2016) electronic health records of children <19 years old with S. aureus infections were queried for patient level data for demographic, clinical, and laboratory information. Area level data (Block group) was abstracted from U.S. Census data. A machine learning ecological niche model, maximum entropy (MaxEnt), was applied to assess model performance of specific place-based factors (determined a priori) associated with S. aureus infections; analyses were structured to compare methicillin resistant (MRSA) against methicillin sensitive S. aureus (MSSA) infections. Differences in rates of MRSA and MSSA infections were determined by comparing those which occurred in the early phase (2002-2005) and those in the later phase (2006-2016). Multi-level modeling was applied to identify risks factors for S. aureus infections. Among 16,124 unique patients with community-onset MRSA and MSSA, majority occurred in the most densely populated neighborhoods of Atlanta's metropolitan area. MaxEnt model performance showed the training AUC ranged from 0.771 to 0.824, while the testing AUC ranged from 0.769 to 0.839. Population density was the area variable which contributed the most in predicting S. aureus disease (stratified by CO-MRSA and CO-MSSA) across early and late periods. Race contributed more to CO-MRSA prediction models during the early and late periods than for CO-MSSA. Machine learning accurately predicts which densely populated areas are at highest and lowest risk for community-onset S. aureus infections over a 14-year time span.

Intestinal parasitic infections in a community from Pampa del Indio, Chaco (Argentina) and their association with socioeconomic and environmental factors

Neglected tropical diseases are a group of 20 disabling diseases, which, in particular, are the most common chronic infections in the most vulnerable people. This study aimed to characterize the infection by intestinal parasites (IPs) in dwellings from a peri-urban neighborhood in Pampa del Indio, Chaco (Argentina), and its association with socioeconomic and environmental variables. Single stool samples were collected from all individuals older than 1 year through household visits and processed using coprological sedimentation and flotation techniques. Standardized questionnaires were used at the household level to collect socio-economic information. Environmental variables were obtained from the Planetscope image, Landsat 8 images and remote sensors, while land-use layers were obtained through the use of a maximum likelihood algorithm. Stool samples were provided by 314 individuals. The prevalence of IPs found was 30.6% (n = 96), with a predominance of Giardia lamblia (12.7%, n = 40) and Hymenolepis nana (7.6%, n = 24). The only soil-transmitted helminth found was Strongyloides stercoralis with a 2.5% prevalence (n = 8). Individuals of adult age (> 18 years) were 0.65 times less likely to present parasitic infections with respect to children and adolescents. The only environmental variable that was closely associated with the presence of IPs, was the Normalized Difference Water Index (NDWI), a measure of humidity; being higher around houses with positive individuals. Most of the IPs found in this study were of water-borne transmission and those transmitted directly from person-to-person, therefore fecal contamination is present. We believe that the low prevalence of STH in this area, which requires a passage through the soil, is related to the environmental characteristics, which are unsuitable for the development/permanence of the infective stages of these parasites. The geospatial data and tools used herein proved to be useful for the study of the relationship between the different factors that influence the presence of IPs in a community, from an eco-health approach.

The survey of soil-transmitted helminth species abundance in Slovakia with an emphasis on parameters important for their distribution

Soil-transmitted helminths (STH) can be easily dispensable in socially disadvantaged groups. The Roma people represent the group most at risk in Slovakia. This study aimed to investigate the occurrence of STH infections in minorities living with animals under low hygienic conditions and on contaminated soil. Subsequently, we identified the risk assessment factors of the STH transmissions based on parasitological results. In our study, STHs were predominantly found among the Roma communities living in unsanitary conditions. The prevalence of Ascaris lumbricoides among the majority was 0.79%, and Trichuris trichiura was 0.05 %. On the contrary, a community-based cross-sectional survey across eastern Slovakia also found a prevalence of 22.28 and 3.47% for A. lumbricoides and T. trichiura among the Roma population. Inhabitants that belong to the Roma minority had a 37.12 infection OR times higher than non-Roma inhabitants. The Roma people living in the countryside have a 2.23-fold higher chance of getting infected with STH than Roma living in the city. Therefore, soil and domestic animals were also examined for the presence of the STH eggs to show the environmental burden. In general, the presence of STH eggs was confirmed in 26.26% of the soil examined samples. The detailed description is as follows: eggs of Toxocara spp., Trichuris spp., eggs from the family Ancylostomatidae, and Toxascaris leonina. Ascaris eggs were detected only in the soil from localities with low hygienic standards. The probability of contracting the STH eggs in segregated settlements was 15.94 times higher compared to urban or rural areas. In addition to humans, dogs can also be a source of STH eggs in the soil. The STH eggs were confirmed in 43.55% of dog droppings. The most interesting finding was that the eggs of the genus Ascaris were up to 7.93% of dog droppings from localities with a low hygienic standard were positive. This study revealed that climatic factors and the WASH conditions influenced the distribution of STHs to variable degrees. In addition, ethnicity and sanitation were crucial factors in the distribution of STH infection in eastern Slovakia.

Using newly optimized genetic tools to probe Strongyloides sensory behaviors

The oft-neglected human-parasitic threadworm, Strongyloides stercoralis, infects roughly eight percent of the global population, placing disproportionate medical and economic burden upon marginalized communities. While current chemotherapies treat strongyloidiasis, disease recrudescence and the looming threat of anthelminthic resistance necessitate novel strategies for nematode control. Throughout its life cycle, S. stercoralis relies upon sensory cues to aid in environmental navigation and coordinate developmental progression. Odorants, tastants, gases, and temperature have been shown to shape parasite behaviors that drive host seeking and infectivity; however, many of these sensory behaviors remain poorly understood, and their underlying molecular and neural mechanisms are largely uncharacterized. Disruption of sensory circuits essential to parasitism presents a promising strategy for future interventions. In this review, we describe our current understanding of sensory behaviors - namely olfactory, gustatory, gas sensing, and thermosensory behaviors - in Strongyloides spp. We also highlight the ever-growing cache of genetic tools optimized for use in Strongyloides that have facilitated these findings, including transgenesis, CRISPR/Cas9-mediated mutagenesis, RNAi, chemogenetic neuronal silencing, and the use of fluorescent biosensors to measure neuronal activity. Bolstered by these tools, we are poised to enter an era of rapid discovery in Strongyloides sensory neurobiology, which has the potential to shape pioneering advances in the prevention and treatment of strongyloidiasis.

Mapping the global distribution of Strongyloides stercoralis and hookworms by ecological niche modeling

Background

The WHO has established a control strategy for Strongyloides stercoralis in school-aged children as well as targets and to maintain control programs for Ascaris lumbricoides, Trichuris trichiura and hookworms. For an efficient development of control programs, it is necessary to know the target countries around the world, as well as the areas within each country where efforts should be focused. Therefore, maps that provide information on the areas at risk for soil-transmitted helminth (STH) infections on a national and sub-national scale would allow for a better allocation of resources.

Methods

We used the ecological niche models MaxEnt and Kuenm R library to estimate the global distribution of S. stercoralis and hookworms. We used occurrence points of both species extracted from surveys of two literature reviews and from the Global Atlas of Helminth Infection database, together with 14 raster maps of environmental variables.

Results

We obtained two raster maps with the presence probability of S. stercoralis and hookworm infections at a global level and then estimated the global population at risk to be 2.6 and 3.4 billion, respectively. The population at risk was also estimated at the country level using estimations for areas as small as 25 km². A relationship was found between the probability of the presence of S. stercoralis and its prevalence, and a raster map was generated. Annual precipitation, annual temperature, soil carbon content and land cover were the main associated environmental variables. The ecological niches of Strongyloides stercoralis and hookworms had an overlap of 68%.

Conclusions

Here we provide information that can be used for developing more efficient and integrated control strategies for S. stercoralis and hookworm infections. This information can be annexed to the study of other risk factors or even other diseases to assess the health status of a community.

Graphical Abstarct

Supplementary Information

The online version contains supplementary material available at 10.1186/s13071-022-05284-w.

Feature importance: Opening a soil-transmitted helminth machine learning model via SHAP

In the field of landscape epidemiology, the contribution of machine learning (ML) to modeling of epidemiological risk scenarios presents itself as a good alternative. This study aims to break with the ”black box” paradigm that underlies the application of automatic learning techniques by using SHAP to determine the contribution of each variable in ML models applied to geospatial health, using the prevalence of hookworms, intestinal parasites, in Ethiopia, where they are widely distributed; the country bears the third-highest burden of hookworm in Sub-Saharan Africa. XGBoost software was used, a very popular ML model, to fit and analyze the data. The Python SHAP library was used to understand the importance in the trained model, of the variables for predictions. The description of the contribution of these variables on a particular prediction was obtained, using different types of plot methods. The results show that the ML models are superior to the classical statistical models; not only demonstrating similar results but also explaining, by using the SHAP package, the influence and interactions between the variables in the generated models. This analysis provides information to help understand the epidemiological problem presented and provides a tool for similar studies.

Opisthorchis viverrini and Strongyloides stercoralis mono- and co-infections: Bayesian geostatistical analysis in an endemic area, Thailand

Parasitic infections caused by Opisthorchis viverrini and Strongyloides stercoralis remain a major public health threat in the Greater Mekong Sub-region. An understanding of climate and other environmental influences on the geographical distribution and emergence of parasitic diseases is a crucial step to guide targeted control and prevention programs. A parasitological survey was conducted from 2008 to 2013 and included 12,554 individuals (age between 20 and 60 years) from 142 villages in five districts in Khon Kaen Province, Thailand. Geographical information systems, remote sensing technologies and a Bayesian geostatistical framework were used to develop models for O. viverrini and S. stercoralis mono- and co-infections in areas where both parasites are known to co-occur. The results indicate that male sex, increased age, altitude, precipitation, and land surface temperature have influenced the infection rate and geographical distribution of mono- and co-infections of O. viverrini and S. stercoralis in this area. Males were 6.69 times (95% CrI: 5.26-8.58) more likely to have O. viverrini - S. stercoralis co-infection. We observed that O. viverrini and S. stercoralis mono-infections display distinct spatial pattern, while co-infection is predicted in the center and southeast of the study area. The observed spatial clustering of O. viverrini and S. stercoralis provides valuable information for the spatial targeting of prevention interventions in this area.

Environmental characteristics around the household and their association with hookworm infection in rural communities from Bahir Dar, Amhara Region, Ethiopia

Soil-Transmitted Helminths (STH) are highly prevalent Neglected Tropical Disease in Ethiopia, an estimated 26 million are infected. Geographic Information Systems and Remote Sensing (RS) technologies assist data mapping and analysis, and the prediction of the spatial distribution of infection in relation to environmental variables. The influence of socioeconomic, environmental and soil characteristics on hookworm infection at the individual and household level is explored in order to identify spatial patterns of infection in rural villages from Zenzelema (Amhara region). Inhabitants greater than 5 years old were recruited in order to assess the presence of STH. Socioeconomic and hookworm infection variables at the household level and environmental variables and soil characteristics using RS were obtained. The dominant STH found was hookworm. Individuals which practiced open defecation and those without electricity had a significant higher number of hookworm eggs in their stool. Additionally, adults showed statistically higher hookworm egg counts than children. Nonetheless, the probability of hookworm infection was not determined by socioeconomic conditions but by environmental characteristics surrounding the households, including a combination of vigorous vegetation and bare soil, high temperatures, and compacted soils (high bulk density) with more acidic pH, given a pH of 6.0 is optimal for hatching of hookworm eggs. The identification of high-risk environmental areas provides a useful tool for planning, targeting and monitoring of control measures, including not only children but also adults when hookworm is concerned.

Modeling of Forest Communities’ Spatial Structure at the Regional Level through Remote Sensing and Field Sampling: Constraints and Solutions

This study tests modern approaches to spatial modeling of forest communities at the regional level based on a supervised classification. The study is conducted by the example of mapping the composition of forest communities in a large urbanized region (the Moscow Region, area 4.69 million hectares). A database of 1684 field descriptions is used as sample plots. As environmental variables, Landsat spectral reflectances, vegetation indices (5 images), digital elevation model and morphometric parameters of the relief, 54 layers in total, are used. Additionally, the Palsar-2 radar dataset is included. The main mapped units are formations and groups of associations identified on the basis of the ecological-phytocoenotic classification. Formations and groups of associations are similar in semantics and principles of allocation to units of forest typology. It is shown that the maximum entropy method has a wide range of applications, in particular, for mapping the typological diversity of forest cover. The method is used in combination with geographically structured spatial jack-knifing, spatial rarefication of occurrence data and independent testing of model feature classes and regularization parameters. Spatial rarefication is a critical technique when points are not evenly distributed in space. The resulting model of the spatial structure of forest cover is based on the integration of the best models of each thematic class of different types of forest cover into a single cartographic layer. It is shown that under conditions of uneven and sparse distribution of points, it is possible to provide an average point matching level of 0.45 for formations and 0.29 for association groups. Herewith, the spatial structure and the ratio of the formation’s composition correspond to the official data of the forest inventory. An attempt is made to identify and evaluate the distribution of more detailed syntaxonomic units: association groups. The necessary requirements for improving the quality of the forest cover model of the study area for 2 hierarchical typological units of forest cover are formulated. These include the additional sampling in order to equalize their spatial density, as well as to achieve equality of samples based on stratification according to the resulting map.

Intestinal parasites in rural communities in Nan Province, Thailand: changes in bacterial gut microbiota associated with minute intestinal fluke infection

Gastrointestinal helminth infection likely affects the gut microbiome, in turn affecting host health. To investigate the effect of intestinal parasite status on the gut microbiome, parasitic infection surveys were conducted in communities in Nan Province, Thailand. In total, 1047 participants submitted stool samples for intestinal parasite examination, and 391 parasite-positive cases were identified, equating to an infection prevalence of 37.3%. Intestinal protozoan species were less prevalent (4.6%) than helminth species. The most prevalent parasite was the minute intestinal fluke Haplorchis taichui (35.9%). Amplicon sequencing of 16S rRNA was conducted to investigate the gut microbiome profiles of H. taichui-infected participants compared with those of parasite-free participants. Prevotella copri was the dominant bacterial operational taxonomic unit (OTU) in the study population. The relative abundance of three bacterial taxa, Ruminococcus, Roseburia faecis and Veillonella parvula, was significantly increased in the H. taichui-infected group. Parasite-negative group had higher bacterial diversity (α diversity) than the H. taichui-positive group. In addition, a significant difference in bacterial community composition (β diversity) was found between the two groups. The results suggest that H. taichui infection impacts the gut microbiome profile by reducing bacterial diversity and altering bacterial community structure in the gastrointestinal tract.

Improved agar plate culture conditions for diagnosis of Strongyloides stercoralis

Strongyloides stercoralis infection causes gastrointestinal symptoms and can lead to severe disease in immunocompromised hosts. Live larvae are passed in feces, encouraging the common use of diagnosis by cultivation methods including agar plate culture (APC), the gold-standard technique. Nevertheless, APC has limitations, especially since there can be considerable day-to-day fluctuations in numbers of larvae produced. Herein, we collected stool samples from heavily infected subjects with strongyloidiasis in Khon Kaen Province, Thailand, to evaluate modifications (temperature, pH, nutrition source and salinity) to APC conditions to maximize the number of S. stercoralis worms counted. Best results were obtained using a modified APC with the following conditions: pH 6.0, 0.5% of NaCl, addition of yeast extract for nutrition and incubation at 29-30 °C. This modified APC was more sensitive for detection of S. stercoralis than was standard APC or the formalin-ethyl acetate concentration technique. In brief, this finding suggests that a modification of standard APC conditions increases the counts of S. stercoralis.

Risk map development for soil-transmitted helminth infections in Argentina

BACKGROUND

Soil-transmitted helminths (STHs) comprise a group of helminth parasites that are included in the list of Neglected Tropical Diseases and require a passage through the soil to become infective. Several studies have detected that infection with STHs are associated with certain socioeconomic, environmental and soil characteristics. In Argentina, the presence of these parasites has been detected through a few point studies conducted in localities from 11 of the 23 provinces that comprise the country.

METHODS/PRINCIPAL FINDINGS

The most important characteristics previously associated with the presence of STHs were identified and ranked through the use of an expert survey and the Analytical Hierarchy Process (AHP) in order to construct a risk map of STHs specific for Argentina. Prevalence data from previous studies was used to validate the generated risk map. The map shows that half of Argentina, from the Central provinces to the North, contains localities with the characteristics necessary for the development of these parasites.

CONCLUSIONS/SIGNIFICANCE

The predicted map should serve as a useful tool for guiding the identification of survey areas for the generation of baseline data, detecting hotspots of infection, planning and prioritizing areas for control interventions, and eventually performing post-implementation surveillance activities.

First database of the spatial distribution of Eimeria species of cattle, sheep and goats in Mexico

Ruminant coccidiosis is a gastrointestinal disease caused by parasites of the genus Eimeria. Environmental and climatic factors are relevant for the development, survival, and transmission of coccidiosis because Eimeria oocysts are able to survive in the environment for several weeks or months in favorable conditions of moderate heat and moisture. The aim of the present study was to georeference, for the first time, the locations of Eimeria occurrences in Mexico from 1961 to 2018. A dataset was created for 3414 reports of Eimeria occurrences in cattle, sheep, and goats in Mexico. Twelve species of Eimeria that infect cattle were recorded, 11 Eimeria species of sheep are present in Mexico, and eight species of goats are geographically distributed in the country. In the current findings, it has been observed that Eimeria colonizes mainly the temperate semihumid, temperate humid, warm humid, and warm semihumid areas during spring and summer in animals younger than 1 year of age. Macroenvironmental variables like temperature and rainfall influence the prevalence of Eimeria in cattle, sheep, and goats, and for some species, the rearing system, facility type, farm size, and altitude affect the occurrence of this parasite. Results may support future studies aimed at reducing the disease prevalence of the parasite in endemic regions of Mexico. The use of recorded cases and climate variables yields a more comprehensive perspective of the epidemiology of eimeriosis, which would be difficult to infer from laboratory studies alone.

Ecological Niche Model based on Maximum Entropy for mapping distribution of Bithynia siamensis goniomphalos, first intermediate host snail of Opisthorchis viverrini in Thailand

The snail Bithynia siamensis goniomphalos acts as first intermediate host of the liver fluke, Opisthorchis viverrini, which causes opisthorchiasis in humans. In this study, we used a geographic information system (GIS), remote sensing (RS) and software using the maximum entropy (MaxEnt) algorithm to predict the distribution of B. s. goniomphalos in Thailand on the basis of environmental and climatic factors. The MaxEnt model for B. s. goniomphalos was excellent, with average test AUC values of 0.89. The predicted distribution of B. s. goniomphalos was affected by altitude, land cover, normalized difference vegetation index (NDVI), precipitation in the driest month (BIO 14), land surface temperature (LST) and soil pH. The areas suitable for B. s. goniomphalos were mostly in Northeast Thailand and some northern parts of the country. The presence of B. s. goniomphalos decreases with increasing altitude and increasing NDVI value. Bithynia s. goniomphalos is most likely to occur in paddy fields and cropland. Opisthorchiasis prevalence was directly proportional to the likelihood of snail occurrence as predicted by the model. This is the first time this ecological niche model has been used to predict Bithynia snail distribution and hence to provide a basis for future work of opisthorchiasis prevention in opisthorchiasis-endemic countries.