Pathways to zoonotic spillover

Journal name:
Nature Reviews Microbiology
Year published:
DOI:
doi:10.1038/nrmicro.2017.45
Published online

Abstract

Zoonotic spillover, which is the transmission of a pathogen from a vertebrate animal to a human, presents a global public health burden but is a poorly understood phenomenon. Zoonotic spillover requires several factors to align, including the ecological, epidemiological and behavioural determinants of pathogen exposure, and the within-human factors that affect susceptibility to infection. In this Opinion article, we propose a synthetic framework for animal-to-human transmission that integrates the relevant mechanisms. This framework reveals that all zoonotic pathogens must overcome a hierarchical series of barriers to cause spillover infections in humans. Understanding how these barriers are functionally and quantitatively linked, and how they interact in space and time, will substantially improve our ability to predict or prevent spillover events. This work provides a foundation for transdisciplinary investigation of spillover and synthetic theory on zoonotic transmission.

At a glance

Figures

  1. Pathways to spillover.
    Figure 1: Pathways to spillover.

    The risk of spillover is determined by a series of processes that link the ecological dynamics of infection in reservoir hosts, the microbiological and vector determinants of survival and dissemination outside of reservoir hosts, the epidemiological and behavioural determinants of exposure, and the within-host biological factors that shape the susceptibility of recipient hosts. The distribution and intensity of infection in reservoir hosts, followed by pathogen release, movement, survival and possible development to infectious stage, determine the pathogen pressure, which is defined as the amount of pathogen available to the recipient host at a given point in space and time. Pathogen pressure then interacts with the behaviour of the recipient host (and vector for vector-borne pathogens) to determine the likelihood, dose and route of exposure. A series of within-host barriers then determine host susceptibility, and, therefore, the probability and severity of infection for a given pathogen dose.

  2. Barriers to spillover and dose-response relationships.
    Figure 2: Barriers to spillover and dose–response relationships.

    a | Determinants of spillover are being studied by researchers in many disciplines. b | A pathogen must overcome a series of barriers to transmit from one species to another. If any of these barriers is impenetrable, spillover cannot occur. Spillover of some pathogens requires that gaps (depicted as holes) in all of the barriers align within a narrow window in space and time (indicated by the blue arrow, see Supplementary information S2 (movie)). For other pathogens, protracted survival in the environment (for example, Bacillus anthracis spores109), or wide dissemination (for example, the spread of aerosolized Coxiella burnetii by wind35), may stagger the alignment of barriers to spillover. c | Top panel: hypothetical dose available over time for a given pathogen. In scenario 1 (dashed light blue line), the pathogen is excreted consistently from infected reservoir hosts. In scenario 2 (solid light blue line), the pathogen is excreted in regular but short high-intensity pulses over time. In both scenarios, the mean dose over the time interval is the same. Bottom panel: the likelihood that this dose will translate into infection depends on the functional form of the dose–response relationship. If the dose–response relationship is linear (green line), these two excretion scenarios generate the same total probability of spillover over the time interval shown. However, for nonlinear dose–response relationships, the total probability of spillover differs between scenarios. If the relationship is sigmoidal (red line), there is some probability of spillover whenever the dose exceeds zero (indicated by the intensity of the red shading in the top panel), but the total spillover probability in scenario 2 is markedly higher. In the extreme case in which the recipient host can be infected only by a dose that exceeds a sharp threshold, as suspected for Bacillus anthracis67, 68, 79, the pathogen in scenario 2 will spill over when the dose peaks above the threshold (blue solid line near peak), but the pathogen in scenario 1 will never spill over.

  3. Bottlenecks to spillover.
    Figure 3: Bottlenecks to spillover.

    Different barriers permit or constrain the flow of pathogens from one species to another. The figure is illustrative, owing to the lack of sufficient data for more than one or two barriers for any given system. The width of the gaps in barriers represents the ease with which a pathogen can flow through the barriers and will vary depending on context. The question marks represent points at which the barriers are especially poorly understood and highlight gaps in our knowledge of some pathogens that are of global concern (for example, the lack of information on disease dynamics in reservoir hosts of Ebola virus). Many rabies virus reservoirs, such as domestic dogs, are widely distributed. The prevalence of rabies virus is generally low and the incidence of spillover closely tracks the prevalence of infection in the reservoir host. Rabies virus is almost always fatal to spillover hosts25. Interventions are usually aimed at reducing the prevalence in reservoir hosts through vaccination37. Leptospira interrogans survives in water and soil after being shed in the urine of a wide range of rodents and other reservoir hosts29. Key bottlenecks to the zoonotic spillover of this pathogen are exposure and within-host barriers. For example, during floods in Brazil, many humans that are exposed do not become infected, probably because the initial within-host barrier, the skin, is not penetrated41. However, once L. interrogans penetrates the skin (for example, through skin wounds), 1–10 leptospires may be sufficient to cause systemic infection110. Therefore, wearing protective clothing and boots is an effective control measure41. Important bottlenecks to Escherichia coli O157 spillover include heterogeneous shedding from cattle43, 44 (although it is still unknown whether super-shedding is a characteristic of particular individuals or is a transient phase that occurs in most cattle42). In some contexts, exposure is an important bottleneck; for example, when the pathogen is eliminated from food through cooking. Widespread dispersal leads to uncertainties about the source of many outbreaks46, 47, and weak within-human barriers enable low doses of E. coli to cause infection49, 50. Humans are frequently exposed to Toxoplasma gondii carried by domestic cats and intermediate hosts, but the parasite rarely causes disease because most humans have strong within-host immunological barriers. Cats are widely and densely distributed, but the prevalence of T. gondii is low and cats shed oocysts only once in their lifetime111. However, sporulated oocysts survive in the environment for long periods of time112. Limiting exposure to oocysts may prevent spillover; however, this is challenging when it is unclear whether cats or the environment are the major sources of infection in humans111, 113. Ebola virus has not been isolated from bats and the definitive reservoir bat species is unknown114; therefore, characteristics of infection in bats are unknown114, 115. The pathogen is released through excretion or slaughter, then survives for up to a week, depending on the environmental conditions116. The most tractable bottlenecks for intervention may be the zoonotic exposure of humans through interaction with bats, bushmeat or the carcasses of other species97, 117, 118, because once exposed, the within-host barriers to Ebola virus may be extremely low119.

Videos

  1. Supplementary movie 1
    Video 1: Supplementary movie 1
    Spatiotemporal dynamics of spillover. Gaps in barriers to spillover may be highly dynamic in time and space meaning that the alignment of gaps in all barriers may be rare and brief.

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Author information

Affiliations

  1. Department of Microbiology and Immunology, Montana State University, Bozeman, Montana 59717, USA.

    • Raina K. Plowright
  2. Colin R. Parrish is at the Baker Institute for Animal Health, College of Veterinary Medicine, Cornell University, Ithaca, New York 14853, USA.

  3. Griffith School of Environment, Griffith University, Brisbane, Queensland 4111, Australia.

    • Hamish McCallum
  4. Peter J. Hudson is at the Center for Infectious Disease Dynamics, Pennsylvania State University, State College, Pennsylvania 16802, USA.

  5. Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, Connecticut 06520–8034, USA.

    • Albert I. Ko
  6. Department of Ecology & Evolutionary Biology, Princeton University, Princeton, New Jersey 08544, USA.

    • Andrea L. Graham
  7. Department of Ecology & Evolutionary Biology, University of California, Los Angeles, Los Angeles, California 90095-7239, USA; and at Fogarty International Center, National Institutes of Health, Bethesda, Maryland 20892–2220, USA.

    • James O. Lloyd-Smith

Competing interests statement

The authors declare no competing interests.

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Author details

  • Raina K. Plowright

    Raina K. Plowright is Assistant Professor of Epidemiology at Montana State University, Bozeman, USA. She received her veterinary degree from the University of Sydney, Australia, and then travelled to the USA as an Australian Fulbright and Centennial Scholar to do her Ph.D. in ecology and M.Sc. in epidemiology at the University of California, Davis, USA. She was a David H. Smith Conservation Research Fellow at the Center for Infectious Disease Dynamics at Pennsylvania State University, USA. Her group at Montana State University studies pathogens that spill over from animals to people, the dynamics of zoonotic pathogens in wildlife populations, and pathogens that threaten wildlife conservation.

  • Colin R. Parrish

    Colin R. Parrish is the John M. Olin Professor of Virology in the Baker Institute for Animal Health at the College of Veterinary Medicine, Cornell University, Ithaca, New York, USA. His research focuses on the study of viruses, virus structures and the evolution of new viral host ranges. His studies also examine the general basis of viral emergence, in particular the risk factors that are associated with the origins of new viruses in humans or other animals. For example, he studies canine parvovirus and canine influenza viruses emerging to cause epidemics in dogs.

  • Hamish McCallum

    Hamish McCallum is a professor in the Griffith School of Environment and Environmental Futures Institute at Griffith University, Queensland, Australia. After his B.Sc. at Monash University, Melbourne, Victoria, Australia, he completed his Ph.D. under the supervision of Roy Anderson at Imperial College London, UK. His research primarily focuses on the ecology of infectious diseases in wildlife using quantitative approaches. The systems he works on include Tasmanian devil facial tumour disease, the amphibian chytrid fungus, Hendra virus in pteropid bats and chlamydial disease in koalas.

  • Peter J. Hudson

    Peter J. Hudson is the Willaman Professor of Biology and Director of The Huck Institutes of Life Sciences at Pennsylvania State University, USA. He investigates the dynamics of infections in free-living animal populations, spillover between host species, and patterns of invasion and consequences for wildlife populations. He received his doctorate from the University of Oxford, UK, and he was elected a fellow of the Royal Society in 2008.

  • Albert I. Ko

    Albert I. Ko is Professor of Epidemiology and Department Chair of Epidemiology of Microbial Diseases at the Yale School of Public Health, New Haven, Connecticut, USA. His research centres on the health problems that have emerged as a consequence of rapid urbanization and social inequity. He coordinates a research and training programme on urban slum health in Brazil and is conducting prospective community-based studies on rat-borne leptospirosis, dengue, meningitis and respiratory infections. More recently, his team has mobilized the public health research capacity at their site in the city of Salvador, Brazil to investigate the ongoing outbreak of Zika virus and resulting microcephaly.

  • Andrea L. Graham

    Andrea L. Graham is Associate Professor of Ecology and Evolutionary Biology at Princeton University, New Jersey, USA. She earned her A.B. in biology and sculpture from Mount Holyoke College, South Hadley, Massachusetts, USA, and her Ph.D. in ecology and evolutionary biology from Cornell University, Ithaca, New York, USA, before completing her postdoctoral training at the University of Edinburgh, UK. She then held 2 independent research fellowships at Edinburgh and moved to Princeton University in 2011. Her research interests centre on the causes and consequences of immunological heterogeneity.

  • James O. Lloyd-Smith

    James O. Lloyd-Smith is Professor in the Departments of Ecology and Evolutionary Biology, and Biomathematics at University of California, Los Angeles, USA. His research programme explores the ecological and evolutionary dynamics of infectious diseases in animal and human populations, with emphasis on the emergence of zoonotic pathogens and drug-resistant strains. His group combines mathematical models, statistical analysis, and laboratory, clinical and field studies to learn about diseases such as monkeypox, leptospirosis and influenza. He received his Ph.D. from the University of California, Berkeley, USA, where he studied heterogeneity in disease transmission dynamics, and he carried out his postdoctoral studies at Pennsylvania State University, USA.

Supplementary information

Video

  1. Video 1: Supplementary movie 1 (, Download)
    Spatiotemporal dynamics of spillover. Gaps in barriers to spillover may be highly dynamic in time and space meaning that the alignment of gaps in all barriers may be rare and brief.

PDF files

  1. Supplementary information S1 (box) (81.2 KB)

    A mathematical representation of spillover

Additional data