The ecology of Ebola virus

Groseth, Allison; Feldmann, Heinz; Strong, James E.

doi:10.1016/j.tim.2007.08.001

Cited by 215 publications

(225 citation statements)

References 49 publications

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“…Although the host spectrum and reservoir of infection have not been determined conclusively, three bat species are considered putative virus reservoirs (Leroy et al 2005). There can be limited onward transmission in humans (e.g., person-to-person transmission), mainly resulting from close contact with blood, secretions, or tissues of infected individuals (Groseth et al 2007). Public health responses are normally adequate to control and eliminate the outbreak in the human host population.…”

Section: Ebolamentioning

confidence: 99%

Modeling of Wildlife-Associated Zoonoses: Applications and Caveats

Alexander

Lewis

Marathe

et al. 2012

Vector-Borne and Zoonotic Diseases

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Wildlife species are identified as an important source of emerging zoonotic disease. Accordingly, public health programs have attempted to expand in scope to include a greater focus on wildlife and its role in zoonotic disease outbreaks. Zoonotic disease transmission dynamics involving wildlife are complex and nonlinear, presenting a number of challenges. First, empirical characterization of wildlife host species and pathogen systems are often lacking, and insight into one system may have little application to another involving the same host species and pathogen. Pathogen transmission characterization is difficult due to the changing nature of population size and density associated with wildlife hosts. Infectious disease itself may influence wildlife population demographics through compensatory responses that may evolve, such as decreased age to reproduction. Furthermore, wildlife reservoir dynamics can be complex, involving various host species and populations that may vary in their contribution to pathogen transmission and persistence over space and time. Mathematical models can provide an important tool to engage these complex systems, and there is an urgent need for increased computational focus on the coupled dynamics that underlie pathogen spillover at the humanwildlife interface. Often, however, scientists conducting empirical studies on emerging zoonotic disease do not have the necessary skill base to choose, develop, and apply models to evaluate these complex systems. How do modeling frameworks differ and what considerations are important when applying modeling tools to the study of zoonotic disease? Using zoonotic disease examples, we provide an overview of several common approaches and general considerations important in the modeling of wildlife-associated zoonoses.

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Section: Ebolamentioning

confidence: 99%

Modeling of Wildlife-Associated Zoonoses: Applications and Caveats

Alexander

Lewis

Marathe

et al. 2012

Vector-Borne and Zoonotic Diseases

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“…Stress has also been suggested as a factor influencing a wide range of diseases in wildlife, including Chlamydia infection in koalas (Brearley et al 2013), toxoplasmosis in various marsupials (Thompson et al 2010), chytridimycosis in amphibians (Blaustein et al 2012;Kindermann et al 2012;Gabor et al 2013), avian influenza in migratory birds (Weber and Stilianakis 2007) and white nose syndrome (Cryan et al 2010) and zoonotic (spread from animals to humans) viruses in bats, including Ebola and Hendra virus (HeV) (Groseth et al 2007;Plowright et al 2014). However, associations between stress and disease in wildlife are not commonly empirically tested.…”

Section: Introductionmentioning

confidence: 99%

The relationship between physiological stress and wildlife disease: consequences for health and conservation

et al. 2016

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Wildlife populations are under increasing pressure from a variety of threatening processes, ranging from climate change to habitat loss, that can incite a physiological stress response. The stress response influences immune function, with potential consequences for patterns of infection and transmission of disease among and within wildlife, domesticated animals and humans. This is concerning because stress may exacerbate the impact of disease on species vulnerable to extinction, with consequences for biodiversity conservation globally. Furthermore, stress may shape the role of wildlife in the spread of emerging infectious diseases (EID) such as Hendra virus (HeV) and Ebola virus. However, we still have a limited understanding of the influence of physiological stress on infectious disease in wildlife.We highlight key reasons why an improved understanding of the relationship between stress and wildlife disease could benefit conservation, and animal and public health, and discuss approaches for future investigation. In particular, we recommend that increased attention be given to the influence of anthropogenic stressors including climate change, habitat loss and management interventions on disease dynamics in wildlife populations.Additional keyword: physiology.

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“…1 EBOV was first discovered in 1976 in central Africa, where regular outbreaks have continued to occur in mostly isolated rural communities. 2,3 The virus' recent emergence in West Africa, 4 beginning in Guinea in December 2013 and spreading into more populated areas of neighboring Sierra Leone, Liberia, and beyond, has claimed more lives than all previous outbreaks combined; showing no sign of abating. 5 Global demand for information from these countries with extremely limited public health resources has highlighted the need for innovative analysis of every bit of data available.…”

mentioning

confidence: 99%