An official website of the United States government
Abstract 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.
more »
« less
Cross-species pathogen spillover across ecosystem boundaries: mechanisms and theory
Pathogen spillover between different host species is the trigger for many infectious disease outbreaks and emergence events, and ecosystem boundary areas have been suggested as spatial hotspots of spillover. This hypothesis is largely based on suspected higher rates of zoonotic disease spillover and emergence in fragmented landscapes and other areas where humans live in close vicinity to wildlife. For example, Ebola virus outbreaks have been linked to contacts between humans and infected wildlife at the rural-forest border, and spillover of yellow fever via mosquito vectors happens at the interface between forest and human settlements. Because spillover involves complex interactions between multiple species and is difficult to observe directly, empirical studies are scarce, particularly those that quantify underlying mechanisms. In this review, we identify and explore potential ecological mechanisms affecting spillover of pathogens (and parasites in general) at ecosystem boundaries. We borrow the concept of ‘permeability’ from animal movement ecology as a measure of the likelihood that hosts and parasites are present in an ecosystem boundary region. We then discuss how different mechanisms operating at the levels of organisms and ecosystems might affect permeability and spillover. This review is a step towards developing a general theory of cross-species parasite spillover across ecosystem boundaries with the eventual aim of improving predictions of spillover risk in heterogeneous landscapes. This article is part of the theme issue ‘Dynamic and integrative approaches to understanding pathogen spillover’.
more »
« less
- PAR ID:
- 10589615
- Publisher / Repository:
- eScholarship.org
- Date Published:
- Journal Name:
- Philosophical Transactions of the Royal Society B: Biological Sciences
- Volume:
- 374
- Issue:
- 1782
- ISSN:
- 0962-8436
- Page Range / eLocation ID:
- 20180344
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
Abstract Pathogen spillover from wildlife to humans or domestic animals requires a series of conditions to align with space and time. Comparing these conditions between times and locations where spillover does and does not occur presents opportunities to understand the factors that shape spillover risk. Bovine rabies transmitted by vampire bats was first confirmed in 1911 and has since been detected across the distribution of vampire bats. However, Uruguay is an exception. Uruguay was free of bovine rabies until 2007, despite high-cattle densities, the presence of vampire bats and a strong surveillance system. To explore why Uruguay was free of bovine rabies until recently, we review the historic literature and reconstruct the conditions that would allow rabies invasion into Uruguay. We used available historical records on the abundance of livestock and wildlife, the vampire bat distribution and occurrence of rabies outbreaks, as well as environmental modifications, to propose four alternative hypotheses to explain rabies virus emergence and spillover: bat movement, viral invasion, surveillance failure and environmental changes. While future statistical modelling efforts will be required to disentangle these hypotheses, we here show how a detailed historical analysis can be used to generate testable predictions for the conditions leading to pathogen spillover.more » « less
-
Low, Jenny (Ed.)Yellow fever virus (YFV) is the etiological agent of yellow fever (YF), an acute hemorrhagic vector-borne disease with a significant impact on public health, is endemic across tropical regions in Africa and South America. The virus is maintained in two ecologically and evolutionary distinct transmission cycles: an enzootic, sylvatic cycle, where the virus circulates between arboreal Aedes species mosquitoes and non-human primates, and a human or urban cycle, between humans and anthropophilic Aedes aegypti mosquitoes. While the urban transmission cycle has been eradicated by a highly efficacious licensed vaccine, the enzootic transmission cycle is not amenable to control interventions, leading to recurrent epizootics and spillover outbreaks into human populations. The nature of YF transmission dynamics is multifactorial and encompasses a complex system of biotic, abiotic, and anthropogenic factors rendering predictions of emergence highly speculative. The recent outbreaks in Africa and Brazil clearly remind us of the significant impact YF emergence events pose on human and animal health. The magnitude of the Brazilian outbreak and spillover in densely populated areas outside the recommended vaccination coverage areas raised the specter of human — to — human transmission and re-establishment of enzootic cycles outside the Amazon basin. Herein, we review the factors that influence the re-emergence potential of YFV in the neotropics and offer insights for a constellation of coordinated approaches to better predict and control future YF emergence events.more » « less
-
ABSTRACT Zoonotic pathogens pose a significant risk to human health, with spillover into human populations contributing to chronic disease, sporadic epidemics, and occasional pandemics. Despite the widely recognized burden of zoonotic spillover, our ability to identify which animal populations serve as primary reservoirs for these pathogens remains incomplete. This challenge is compounded when prevalence reaches detectable levels only at specific times of year. In these cases, statistical models designed to predict the timing of peak prevalence could guide field sampling for active infections. Here we develop a general model that leverages routinely collected serosurveillance data to optimize sampling for elusive pathogens. Using simulated data sets we show that our methodology reliably identifies times when pathogen prevalence is expected to peak. We then apply our method to two putativeEbolavirusreservoirs, straw-colored fruit bats (Eidolon helvum) and hammer-headed bats (Hypsignathus monstrosus) to predict when these species should be sampled to maximize the probability of detecting active infections. In addition to guiding future sampling of these species, our method yields predictions for the times of year that are most likely to produce future spillover events. The generality and simplicity of our methodology make it broadly applicable to a wide range of putative reservoir species where seasonal patterns of birth lead to predictable, but potentially short-lived, pulses of pathogen prevalence. AUTHOR SUMMARYMany deadly pathogens, such as Ebola, Lassa, and Nipah viruses, originate in wildlife and jump to human populations. When this occurs, human health is at risk. At the extreme, this can lead to pandemics such as the West African Ebola epidemic and the COVID-19 pandemic. Despite the widely recognized risk wildlife pathogens pose to humans, identifying host species that serve as primary reservoirs for many pathogens remains challenging. Ebola is a notable example of a pathogen with an unconfirmed wildlife reservoir. A key obstacle to confirming reservoir hosts is sampling animals with active infections. Often, disease prevalence fluctuates seasonally in wildlife populations and only reaches detectable levels at certain times of year. In these cases, statistical models designed to predict the timing of peak prevalence could guide efficient field sampling for active infections. Therefore, we have developed a general model that uses serological data to predict times of year when pathogen prevalence is likely to peak. We demonstrate with simulated data that our method produces reliable predictions, and then apply our method to two hypothesized reservoirs for Ebola virus, straw-colored fruit bats and hammer-headed bats. Our method can be broadly applied to a range of potential reservoir species where seasonal patterns of birth can lead to predictable pulses of peak pathogen prevalence. Overall, our method can guide future sampling of reservoir populations and can also be used to make predictions for times of year that future outbreaks in human populations are most likely to occur.more » « less
-
Abstract Interactions among humans, livestock, and wildlife within disturbed ecosystems, such as those impacted by climate change, can facilitate pathogen spillover transmission and increase disease emergence risks. The study of future climate change impacts on the distribution of free-ranging bats is therefore relevant for forecasting potential disease burden. This study used current and future climate data and historic occurrence locations of the vampire bat speciesDesmodus rotundus, a reservoir of the rabies virus to assess the potential impacts of climate change on disease reservoir distribution. Analyses included a comprehensive comparison of different climate change periods, carbon emission scenarios, and global circulation models (GCMs) on final model outputs. Models revealed that, although climatic scenarios and GCMs used have a significant influence on model outputs, there was a consistent signal of range expansion across the future climates analyzed. Areas suitable forD. rotundusrange expansion include the southern United States and south-central portions of Argentina and Chile. Certain areas in the Amazon Rainforest, which currently rests at the geographic center ofD. rotundus’ range, may become climatically unsuitable for this species within the context of niche conservatism. While the impacts of rabies virus transmitted byD. rotunduson livestock are well known, an expansion ofD. rotundusinto novel areas may impact new mammalian species and livestock with unexpected consequences. Some areas in the Americas may benefit from an assessment of their preparedness to deal with an expectedD. rotundusrange expansion.more » « less
- Free Publicly Accessible Full Text
-
Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1098/rstb.2018.0344
