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.

Circulating vaccine-derived poliovirus (cVDPV) outbreaks can occur when oral poliovirus vaccine strains (most often, Sabin monovalent oral poliovirus vaccine type 2 [mOPV2]) undergo prolonged circulation in undervaccinated populations, resulting in genetic reversion to neurovirulence. A novel type 2 oral poliovirus vaccine (nOPV2) has been developed, which has been shown in clinical trials to be less likely than mOPV2 to revert to paralytic variants and to have limited genetic modifications in initial field use (1–4). Approximately 700 million doses of nOPV2 have been administered worldwide in response to outbreaks of cVDPV type 2 (cVDPV2). cVDPV2 detections originating from nOPV2 use from initial rollout during March 2021–September 7, 2023, are described in this report.

To reduce the veterinary, public health, environmental, and economic burden associated with anthrax outbreaks, it is vital to identify the spatial distribution of areas suitable for Bacillus anthracis, the causative agent of the disease. Bayesian approaches have previously been applied to estimate uncertainty around detected areas of B. anthracis suitability. However, conventional simulation-based techniques are often computationally demanding. To solve this computational problem, we use Integrated Nested Laplace Approximation (INLA) which can adjust for spatially structured random effects, to predict the suitability of B. anthracis across Uganda. We apply a Generalized Additive Model (GAM) within the INLA Bayesian framework to quantify the relationships between B. anthracis occurrence and the environment. We consolidate a national database of wildlife, livestock, and human anthrax case records across Uganda built across multiple sectors bridging human and animal partners using a One Health approach. The INLA framework successfully identified known areas of species suitability in Uganda, as well as suggested unknown hotspots across Northern, Eastern, and Central Uganda, which have not been previously identified by other niche models. The major risk factors for B. anthracis suitability were proximity to water bodies (0-0.3 km), increasing soil calcium (between 10 and 25 cmolc/kg), and elevation of 140-190 m. The sensitivity of the final model against the withheld evaluation dataset was 90% (181 out of 202 = 89.6%; rounded up to 90%). The prediction maps generated using this model can guide future anthrax prevention and surveillance plans by the relevant stakeholders in Uganda.

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.

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 (ENM) framework, we developed updated maps of the global predicted environmental 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 concentered throughout Eurasia, sub-Saharan Africa, the Americas, Southeast Asia, Australia, and Oceania. Suitable environments for B. anthracis at the circumpolar extent extend above the Arctic Circle into portions of Russia, Canada, Iceland, Alaska, and northern Scandinavia. Environmental factors driving B. anthracis suitability globally include vegetation (EVI), land surface temperature (LST), soil characteristics, primary climate conditions, and topography. While, 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, eastern Australia, Anatolia, the Caucasus region, Central Asia, the Balkans, Spain, Uruguay, eastern China, United States, Canada, and East Africa. This study expands on previous work that predicted the potential environmental niche of anthrax by providing enhanced knowledge on the potential spatial distribution of anthrax risk 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. This article is protected by copyright. All rights reserved.

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.

Schistosomiasis is a neglected tropical disease (NTD) found throughout tropical and sub-tropical 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. © 2022 by the author. Licensee MDPI, Basel, Switzerland.

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.IMPORTANCE B. 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.