Geographical distribution of the Cryptococcus gattii species complex: a systematic review.

The taxonomy of the Cryptococcus gattii species complex continues to evolve, and has been divided into five pathogenic species. The objective of this systematic review was to summarise the geographical distribution of the C gattii species complex and the species within the C gattii species complex. We searched PubMed for articles related to human, animal, ecological, or laboratory-based studies of C gattii species complex isolates with traceable geographical origin published from January, 1970, until September, 2021. Having extracted their geographical origin, we used ArcMap to construct maps according to the highest degree of resolution allowed by their reported taxonomy, to reflect the most likely area of transmission on the basis of published reports of human isolates. 604 such articles were included in the study. This review indicated that although C gattii species complex isolates have been reported globally, understanding their heterogeneous geographical distribution by species can have implications for researchers and clinicians in formulating research questions and considering diagnostic quandaries.

Drivers and potential distribution of anthrax occurrence and incidence at national and sub-county levels across Kenya from 2006 to 2020 using INLA.

Anthrax is caused by, Bacillus anthracis, a soil-borne bacterium that infects grazing animals. Kenya reported a sharp increase in livestock anthrax cases from 2005, with only 12% of the sub-counties (decentralised administrative units used by Kenyan county governments to facilitate service provision) accounting for almost a third of the livestock cases. Recent studies of the spatial extent of B. anthracis suitability across Kenya have used approaches that cannot capture the underlying spatial and temporal dependencies in the surveillance data. To address these limitations, we apply the first Bayesian approach using R-INLA to analyse a long-term dataset of livestock anthrax case data, collected from 2006 to 2020 in Kenya. We develop a spatial and a spatiotemporal model to investigate the distribution and socio-economic drivers of anthrax occurrence and incidence at the national and sub-county level. The spatial model was robust to geographically based cross validation and had a sensitivity of 75% (95% CI 65-75) against withheld data. Alarmingly, the spatial model predicted high intensity of anthrax across the Northern counties (Turkana, Samburu, and Marsabit) comprising pastoralists who are often economically and politically marginalized, and highly predisposed to a greater risk of anthrax. The spatiotemporal model showed a positive link between livestock anthrax risk and the total human population and the number of exotic dairy cattle, and a negative association with the human population density, livestock producing households, and agricultural land area. Public health programs aimed at reducing human-animal contact, improving access to healthcare, and increasing anthrax awareness, should prioritize these endemic regions.

Modelling the ecological niche of naturally occurring anthrax at global and circumpolar extents using an ensemble modelling framework.

Bacillus anthracis, the causative agent of anthrax, is a spore-forming bacterium that primarily affects herbivorous livestock, wildlife and humans exposed to direct contact with infected animal carcasses or products. To date, there are a limited number of studies that have delineated the potential global distribution of anthrax, despite the importance of the disease from both an economic and public health standpoint. This study compiled occurrence data (n = 874) of confirmed human and animal cases from 1954 to 2021 in 94 countries. Using an ensemble ecological niche model framework, we developed updated maps of the global predicted ecological suitability of anthrax to measure relative risk at multiple scales of analysis, including a model for circumpolar regions. Additionally, we produced maps quantifying the disease transmission risk associated with anthrax to cattle, sheep and goat populations. Environmental suitability for B. anthracis globally is concentred throughout Eurasia, sub-Saharan Africa, the Americas, Southeast Asia, Australia and Oceania. Suitable environments for B. anthracis at the circumpolar scale extend above the Arctic Circle into portions of Russia, Canada, Alaska and northern Scandinavia. Environmental factors driving B. anthracis suitability globally include vegetation, land surface temperature, soil characteristics, primary climate conditions and topography. At the circumpolar scale, suitability is influenced by soil factors, topography and the derived climate characteristics. The greatest risk to livestock is concentrated within the Indian subcontinent, Australia, Anatolia, the Caucasus region, Central Asia, the European Union, Argentina, Uruguay, China, the United States, Canada and East Africa. This study expands on previous work by providing enhanced knowledge of the potential spatial distribution of anthrax in the Southern Hemisphere, sub-Saharan Africa, Asia and circumpolar regions of the Northern Hemisphere. We conclude that these updated maps will provide pertinent information to guide disease control programs, inform policymakers and raise awareness at the global level to lessen morbidity and mortality among animals and humans located in environmentally suitable areas.

Ecological Niche Model of Bacillus cereus Group Isolates Containing a Homologue of the pXO1 Anthrax Toxin Genes Infecting Metalworkers in the United States.

While Bacillus cereus typically causes opportunistic infections in humans, within the last three decades, severe and fatal infections caused by isolates of the B. cereus group harboring anthrax toxin genes have been reported in the United States. From 1994 to 2020, seven cases of anthrax-like illness resulting from these isolates have been identified. With one exception, the cases have occurred in the Gulf States region of the United States among metalworkers. We aimed to develop an ecological niche model (ENM) to estimate a spatial area conducive to the survival of these organisms based on the presence of known human infections and environmental variables. The estimated ecological niche for B. cereus was modeled with the maximum entropy algorithm (Maxent). Environmental variables contributing most to the model were soil characteristics (cation exchange capacity, carbon content, soil pH), temperature, enhanced vegetation index (EVI), and land surface temperature (LST). Much of the suitable environments were located throughout the Gulf Coast Plain, Texas Backland Prairies, East Central Texas Plains, Edwards Plateau, Cross Timbers, Mississippi Alluvial Plain, and Central Great Plains. These findings may provide additional guidance to narrow potential risk areas to efficiently communicate messages to metalworkers and potentially identify individuals who may benefit from the anthrax vaccine.

Predictive Risk Mapping of Schistosomiasis in Madagascar Using Ecological Niche Modeling and Precision Mapping.

Schistosomiasis is a neglected tropical disease (NTD) found throughout tropical and subtropical Africa. In Madagascar, the condition is widespread and endemic in 74% of all administrative districts in the country. Despite the significant burden of the disease, high-resolution risk maps have yet to be produced to guide national control programs. This study used an ecological niche modeling (ENM) and precision mapping approach to estimate environmental suitability and disease transmission risk. The results show that suitability for schistosomiasis is widespread and covers 264,781 km2 (102,232 sq miles). Covariates of significance to the model were the accessibility to cities, distance to water, enhanced vegetation index (EVI), annual mean temperature, land surface temperature (LST), clay content, and annual precipitation. Disease transmission risk is greatest in the central highlands, tropical east coast, arid-southwest, and northwest. An estimated 14.9 million people could be at risk of schistosomiasis; 11.4 million reside in rural areas, while 3.5 million are in urban areas. This study provides valuable insight into the geography of schistosomiasis in Madagascar and its potential risk to human populations. Because of the focal nature of the disease, these maps can inform national surveillance programs while improving understanding of areas in need of medical interventions.

Distribution of tungiasis in latin America: Identification of areas for potential disease transmission using an ecological niche model.

Background: Tungiasis is a neglected tropical disease (NTD) found in Sub-Saharan Africa and Latin America. Despite the high frequency in marginalized populations, little information is available on the geography and estimates of the population at risk in endemic regions. Here we used a geostatistical model to map the potential geographic distribution of areas suitable for tungiasis transmission in Latin America and estimated the at-risk population. Methods: We developed an ecological niche model (ENM) using tungiasis occurrence records and remotely sensed environmental and socioeconomic data. The potential geographic distribution was then compared to the current population distribution of the region to derive the total population living in urban and rural areas. Findings: We identified a total of 138 records of occurrences of tungiasis in Latin America, ranging from Mexico to Argentina; 27 reports were not included in the modeling, due to missing detailed geographic information. The occurrences with detailed geographic information (n = 112) included 17 countries in Latin America and the Caribbean. The locations were in environments that primarily consisted of forests (29%), croplands (16•5%), and shrublands (10•9%). We predicted environmentally suitable areas for tungiasis transmission in 45 countries. The estimated human population living in these areas is 450,546,547 with urban centers accounting for 347,007,103 and rural areas 103,539,444. Countries with significant ecological suitability and documented occurrences include Brazil, Colombia, Mexico, Argentina, Bolivia, Ecuador, French Guyana, Guatemala, Haiti, Paraguay, Peru, Trinidad and Tobago, and Venezuela. Interpretation: This is the first study mapping the potential distribution of tungiasis in Latin America, evidencing the need for population-based studies and elaboration of integrated control measures. Funding: This project was supported in part by an appointment to the Research Participation Program at the Centers for Disease Control and Prevention administered by the Oak Ridge Institute for Science and Education through an interagency agreement between the U.S. Department of Energy and the Centers for Disease Control and Prevention.

Genomic Diversity of Burkholderia pseudomallei in Ceara, Brazil.

Burkholderia pseudomallei is a Gram-negative bacterium that causes the sapronotic disease melioidosis. An outbreak in 2003 in the state of Ceara, Brazil, resulted in subsequent surveillance and environmental sampling which led to the recognition of B. pseudomallei as an endemic pathogen in that area. From 2003 to 2015, 24 clinical and 12 environmental isolates were collected across Ceara along with one from the state of Alagoas. Using next-generation sequencing, multilocus sequence typing, and single nucleotide polymorphism analysis, we characterized the genomic diversity of this collection to better understand the population structure of B. pseudomallei associated with Ceara. We found that the isolates in this collection form a distinct subclade compared to other examples from the Western Hemisphere. Substantial genetic diversity among the clinical and environmental isolates was observed, with 14 sequence types (STs) identified among the 37 isolates. Of the 31,594 core single-nucleotide polymorphisms (SNPs) identified, a high proportion (59%) were due to recombination. Because recombination events do not follow a molecular clock, the observation of high occurrence underscores the importance of identifying and removing recombination SNPs prior to evolutionary reconstructions and inferences in public health responses to B. pseudomallei outbreaks. Our results suggest long-term B. pseudomallei prevalence in this recently recognized region of melioidosis endemicity.IMPORTANCEB. pseudomallei causes significant morbidity and mortality, but its geographic prevalence and genetic diversity are not well characterized, especially in the Western Hemisphere. A better understanding of the genetic relationships among clinical and environmental isolates will improve knowledge of the population structure of this bacterium as well as the ability to conduct epidemiological investigations of cases of melioidosis.

The Geography of Farmworker Health in Colorado: An Examination of Disease Clusters and Healthcare Accessibility.

Background: Known by some as the "invisible" people because of their precarious work and low social status, migratory and seasonal farmworkers (MSFW) are a critical and underappreciated component to the agriculture industry in the United States. Despite advances in knowledge about the health needs of this population, identifying geographies of high-risk remains a challenging task for community health workers and farmworker advocacy organizations.Methods: Using patient encounter data (2011-2015) from regional Community and Migrant Health Centers (C/MHC), this study investigates the geography of farmworker chronic disease (diabetes, obesity, hypertension) and associated risk factors (anxiety, stress, depression, tobacco use) in Northeastern Colorado through the lens of Geographic Information Science (GIS).Results: Spatial scan statistics (SaTScan) identified disease cluster hot spots in 151 zip codes and chronic disease risk factor clusters in 44 zip codes. Additionally, 13487 farmworkers or 82% of the total population is found in zip codes designated as chronic disease hot spots, while 10,115 or 62% of the population reside in zip codes identified as risk factor hot spots. GIS-based Network Analysis determined that 1,269 farmworkers lived greater than 30 minutes from a C/MHC, or 7.7% of the total population in the study area (n = 16,419).Conclusions: The findings of this study confirm the need for geospatial analytics in farmworker population healthcare management. These methods, combined with multiple contextual and methodological perspectives, will inform appropriate outreach, research, and policy strategies, and further, serve to address the unique geographic challenges facing MSFW's in Northeastern Colorado.

Mapping the Geographic Distribution of Tungiasis in Sub-Saharan Africa.

The geographic distribution of tungiasis is poorly understood, despite the frequent occurrence of the disease in marginalized populations of low socioeconomic status. To date, little work is available to define the geography of this neglected tropical disease (NTD). This exploratory study incorporated geostatistical modeling to map the suitability for tungiasis transmission in sub-Saharan Africa (SSA). In SSA, environmental suitability is predicted in 44 countries, including Angola, Nigeria, Ghana, Cameroon, Cote de Ivoire, Mali, Ethiopia, the Democratic Republic of the Congo, Kenya, Gabon, Uganda, Rwanda, Tanzania, Zambia, Zimbabwe, Madagascar, and South Africa. In total, an estimated 668 million people live in suitable areas, 46% (304 million) of which reside in East Africa. These evidence-based maps provide vital evidence of the potential geographic extent of SSA. They will help to guide disease control programs, inform policymakers, and raise awareness at the global level. Likewise, these results will hopefully provide decisionmakers with the pertinent information necessary to lessen morbidity and mortality in communities located in environmentally suitable areas.

Mapping Disease Transmission Risk of Nipah Virus in South and Southeast Asia.

Since 1998, Nipah virus (NiV) (genus: Henipavirus; family: Paramyxoviridae), an often-fatal and highly virulent zoonotic pathogen, has caused sporadic outbreak events. Fruit bats from the genus Pteropus are the wildlife reservoirs and have a broad distribution throughout South and Southeast Asia, and East Africa. Understanding the disease biogeography of NiV is critical to comprehending the potential geographic distribution of this dangerous zoonosis. This study implemented the R packages ENMeval and BIOMOD2 as a means of modeling regional disease transmission risk and additionally measured niche similarity between the reservoir Pteropus and the ecological characteristics of outbreak localities with the Schoener's D index and I statistic. Results indicate a relatively high degree of niche overlap between models in geographic and environmental space (D statistic, 0.64; and I statistic, 0.89), and a potential geographic distribution encompassing 19% (2,963,178 km²) of South and Southeast Asia. This study should contribute to current and future efforts to understand the critical ecological contributors and geography of NiV. Furthermore, this study can be used as a geospatial guide to identify areas of high disease transmission risk and to inform national public health surveillance programs.