Background: Estimates of the geographical distribution of Culex mosquitoes in the Americas have been limited to state and provincial levels in the United States and Canada and based on data from the 1980s. Since these estimates were made, there have been many more documented observations of mosquitoes and new methods have been developed for species distribution modeling. Moreover, mosquito distributions are affected by environmental conditions, which have changed since the 1980s. This calls for updated estimates of these distributions to understand the risk of emerging and re-emerging mosquito-borne diseases. Methods: We used contemporary mosquito data, environmental drivers, and a machine learning ecological niche model to create updated estimates of the geographical range of seven predominant Culex species across North America and South America: Culex erraticus, Culex nigripalpus, Culex pipiens, Culex quinquefasciatus, Culex restuans, Culex salinarius, and Culex tarsalis. Results: We found that Culex mosquito species differ in their geographical range. Each Culex species is sensitive to both natural and human-influenced environmental factors, especially climate and land cover type. Some prefer urban environments instead of rural ones, and some are limited to tropical or humid areas. Many are found throughout the Central Plains of the USA. Conclusions: Our updated contemporary Culex distribution maps may be used to assess mosquito-borne disease risk. It is critical to understand the current geographical distributions of these important disease vectors and the key environmental predictors structuring their distributions not only to assess current risk, but also to understand how they will respond to climate change. Since the environmental predictors structuring the geographical distribution of mosquito species varied, we hypothesize that each species may have a different response to climate change. Graphical

Ecological niche modeling (ENM) and species distribution modeling (SDM) are sets of tools that allow the estimation of distributional areas on the basis of establishing relationships among known occurrences and environmental variables. These tools have a wide range of applications, particularly in biogeography, macroecology, and conservation biology, granting prediction of species potential distributional patterns in the present and dynamics of these areas in different periods or scenarios. Due to their relevance and practical applications, the usage of these methodologies has significantly increased throughout the years. Here, we provide a manual with the basic routines used in this field and a practical example of its implementation to promote good practices and guidance for new users.

Purpose: Extended-spectrum beta-lactamase-producing (ESBL) Enterobacteriaceae, which includes Escherichia coli, has emerged as a global health threat. ESBL enzymes including CTX-M, TEM, and SHV are the most detected. Here, a systematic review was developed to assess the status of ESBLs in E. coli considering studies performed in the human, animal, food, and environmental realms in South America. Methods: Following PRISMA guidelines, a systematic review was performed using the PubMed database as a primary source to identify studies containing data on ESBL-producing E. coli in South America. To obtain a comprehensive sample, studies in English, Spanish, and Portuguese were included from 1990 to April 2021. Inclusion such as the reporting of sample origin and diagnostic method and exclusion criteria such as review/letter articles were established to complete data extraction steps. Results: Amongst 506 articles retrieved, 130 met the inclusion criteria. Brazil reported 65 (50%) of publications, followed by Argentina, and Ecuador with 11.5% each. According to the category of studies, human studies represented the 56%, animals the 20%, environmental the 11%, and food studies the 6%. Interestingly, studies assessing more than one category (ie, interdisciplinary) represented the 7%. Prevalence of ESBL producing E. coli in animal, food, and environmental studies was widely superior compared to human sources. In clinical studies, Brazil presented the greatest diversity in terms of ESBLs, featuring CTX-M, TEM, SHV, TOHO, OXA, and AmpC. CTX-M enzymes were the most frequent variants with 89.4% detections. Conclusion: The present One Health review of 130 studies conducted over the past 21 years found ESBLs producing E. coli distributed across human, animal, food, and environmental samples across South America. There is a need to increment studies in underrepresented countries and to strengthen multi-sectoral antimicrobial resistance research and surveillance. This information can be used as basis for subsequent implementation of monitoring programs, targeting potential critical points of transmission sources.

Bacillus cereus biovar anthracis (Bcbva) is an emergent bacterium closely related to Bacillus anthracis, the etiological agent of anthrax. The latter has a worldwide distribution and usually causes infectious disease in mammals associated with savanna ecosystems. Bcbva was identified in humid tropical forests of Côte d’Ivoire in 2001. Here, we characterize the potential geographic distributions of Bcbva in West Africa and B. anthracis in sub-Saharan Africa using an ecological niche modeling approach. Georeferenced occurrence data for B. anthracis and Bcbva were obtained from public data repositories and the scientific literature. Combinations of temperature, humidity, vegetation greenness, and soils values served as environmental variables in model calibrations. To predict the potential distribution of suitable environments for each pathogen across the study region, parameter values derived from the median of 10 replicates of the best-performing model for each pathogen were used. We found suitable environments predicted for B. anthracis across areas of confirmed and suspected anthrax activity in sub-Saharan Africa, including an east-west corridor from Ethiopia to Sierra Leone in the Sahel region and multiple areas in eastern, central, and southern Africa. The study area for Bcbva was restricted to West and Central Africa to reflect areas that have likely been accessible to Bcbva by dispersal. Model predicted values indicated potential suitable environments within humid forested environments. Background similarity tests in geographic space indicated statistical support to reject the null hypothesis of similarity when comparing environments associated with B. anthracis to those of Bcbva and when comparing humidity values and soils values individually. We failed to reject the null hypothesis of similarity when comparing environments associated with Bcbva to those of B. anthracis, suggesting that additional investigation is needed to provide a more robust characterization of the Bcbva niche. This study represents the first time that the environmental and geographic distribution of Bcbva has been mapped. We document likely differences in ecological niche—and consequently in geographic distribution—between Bcbva and typical B. anthracis, and areas of possible co-occurrence between the two. We provide information crucial to guiding and improving monitoring efforts focused on these pathogens. Bacillus cereus biovar anthracis (Bcbva) is an emergent pathogen causing anthrax in West and Central African countries. It shares multiple bacteriological and genomic characteristics with Bacillus anthracis, the gram-positive bacterium causing anthrax in mammals worldwide. However, Bcbva has only been isolated in tropical humid forested environments in Africa; thus, we attempted to characterize its potential distribution and the differences with B. anthracis using an ecological niche modeling framework. According to our results, both pathogens are using different environments and their distribution looks complementary with B. anthracis occupying savanna-like environments and Bcbva occupying forested areas; further, we detected some level of overlap between the potential geographic distributions of B. anthracis and Bcbva, despite their lack of overlap in their current environmental space. This is the first time the potential distribution of Bcbva is addressed considering all the available spatial information on the pathogen occurrence available as of 2017. Although our Bcbva models are limited due to sample size, this exploration informs on areas that would likely be considered for further investigation of Bcbva outbreaks with special emphasis on areas where Bcbva and B. anthracis could co-exist.

Background: Vector-borne diseases (VBDs) are important contributors to the global burden of infectious diseases due to their epidemic potential, which can result in significant population and economic impacts. Oropouche fever, caused by Oropouche virus (OROV), is an understudied zoonotic VBD febrile illness reported in Central and South America. The epidemic potential and areas of likely OROV spread remain unexplored, limiting capacities to improve epidemiological surveillance.Methods: To better understand the capacity for spread of OROV, we developed spatial epidemiology models using human outbreaks as OROV transmission-locality data, coupled with high-resolution satellite-derived vegetation phenology. Data were integrated using hypervolume modeling to infer likely areas of OROV transmission and emergence across the Americas.Results: Models based on one-support vector machine hypervolumes consistently predicted risk areas for OROV transmission across the tropics of Latin America despite the inclusion of different parameters such as different study areas and environmental predictors. Models estimate that up to 5 million people are at risk of exposure to OROV. Nevertheless, the limited epidemiological data available generates uncertainty in projections. For example, some outbreaks have occurred under climatic conditions outside those where most transmission events occur. The distribution models also revealed that landscape variation, expressed as vegetation loss, is linked to OROV outbreaks.Conclusions: Hotspots of OROV transmission risk were detected along the tropics of South America. Vegetation loss might be a driver of Oropouche fever emergence. Modeling based on hypervolumes in spatial epidemiology might be considered an exploratory tool for analyzing data-limited emerging infectious diseases for which little understanding exists on their sylvatic cycles. OROV transmission risk maps can be used to improve surveillance, investigate OROV ecology and epidemiology, and inform early detection.