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Pathogen spillover corresponds to the transmission of a pathogen or parasite from an original host species to a novel host species, preluding disease emergence. Understanding the interacting factors that lead to pathogen transmission in a zoonotic cycle could help identify novel hosts of pathogens and the patterns that lead to disease emergence. We hypothesize that ecological and biogeographic factors drive host encounters, infection susceptibility, and cross‐species spillover transmission. Using a rodent–ectoparasite system in the Neotropics, with shared ectoparasite associations as a proxy for ecological interaction between rodent species, we assessed relationships between rodents using geographic range, phylogenetic relatedness, and ectoparasite associations to determine the roles of generalist and specialist hosts in the transmission cycle of hantavirus. A total of 50 rodent species were ranked on their centrality in a network model based on ectoparasites sharing. Geographic proximity and phylogenetic relatedness were predictors for rodents to share ectoparasite species and were associated with shorter network path distance between rodents through shared ectoparasites. The rodent–ectoparasite network model successfully predicted independent data of seven known hantavirus hosts. The model predicted five novel rodent species as potential, unrecognized hantavirus hosts in South America. Findings suggest that ectoparasite data, geographic range, and phylogenetic relatedness of wildlife species could help predict novel hosts susceptible to infection and possible transmission of zoonotic pathogens. Hantavirus is a high‐consequence zoonotic pathogen with documented animal‐to‐animal, animal‐to‐human, and human‐to‐human transmission. Predictions of new rodent hosts can guide active epidemiological surveillance in specific areas and wildlife species to mitigate hantavirus spillover transmission risk from rodents to humans. This study supports the idea that ectoparasite relationships among rodents are a proxy of host species interactions and can inform transmission cycles of diverse pathogens circulating in wildlife disease systems, including wildlife viruses with epidemic potential, such as hantavirus. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Oropouche virus is the aetiological agent of Oropouche fever, a zoonotic disease mainly transmitted by midges of the species Culicoides paraensis . Although the virus was discovered in 1955, more attention has been given recently to both the virus and the disease due to outbreaks of Oropouche fever in different areas of Brazil and Peru. Serological studies in human and wild mammals have also found Oropouche virus in Argentina, Bolivia, Colombia, and Ecuador. Several mammals act as reservoirs of the disease, although the sylvatic cycle of Oropouche virus remains to be assessed properly. Oropouche fever lacks key symptoms to be differentiated from other arboviral febrile illnesses from the Americas. Sporadic cases of aseptic meningitis have also been described with good prognosis. Habitat loss can increase the likelihood of Oropouche virus emergence in the short-term in South America. [ABSTRACT FROM AUTHOR]

Rabies was known to humans as a disease thousands of years ago. In America, insectivorous bats are natural reservoirs of rabies virus. The bat species Tadarida brasiliensis and Lasiurus cinereus, with their respective, host-specific rabies virus variants AgV4 and AgV6, are the principal rabies reservoirs in Chile. However, little is known about the roles of bat species in the ecology and geographic distribution of the virus. This contribution aims to address a series of questions regarding the ecology of rabies transmission in Chile. Analyzing records from 1985-2011 at the Instituto de Salud Pública de Chile (ISP) and using ecological niche modeling, we address these questions to help in understanding rabies-bat ecological dynamics in South America. We found ecological niche identity between both hosts and both viral variants, indicating that niches of all actors in the system are undifferentiated, although the viruses do not necessarily occupy the full geographic distributions of their hosts. Bat species and rabies viruses share similar niches, and our models had significant predictive power even across unsampled regions; results thus suggest that outbreaks may occur under consistent, stable, and predictable circumstances.