Extreme Competence: Keystone Hosts of Infections

Martin, Lynn B.; Addison, Bri Anne; Bean, Andrew G. D.; Buchanan, Katherine L.; Crino, Ondi L.; Eastwood, Justin R.; Flies, Andrew S.; Hamede, Rodrigo; Hill, Geoffrey E.; Klaassen, Marcel; Koch, Rebecca E.; Martens, Johanne M.; Napolitano, Constanza; Narayan, Edward; Peacock, Lee; Peel, Alison J.; Peters, Anne; Raven, Nynke; Risely, Alice; Roast, Michael J.; Rollins, Lee A.; Ruiz‐Aravena, Manuel; Selechnik, D.; Stokes, Helena S.; Újvári, Beáta; Grogan, Laura F.

doi:10.1016/j.tree.2018.12.009

Cited by 46 publications

(57 citation statements)

References 72 publications

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“…Our likelihood function may favour excessively short cycles of acute and latent infection because these can provide a wide range of probable serological transition times. Although experimental infection studies have failed to provide reliable data on the patterns and duration of henipavirus shedding [6], our results indicate that acute–latent infection cycles are able to reflect naturally observed variation in serological transition times (perhaps reflecting individual heterogeneity [40] or dose-dependency [41] in immune responses).…”

Section: Discussionmentioning

confidence: 84%

What is stirring in the reservoir? Modelling mechanisms of henipavirus circulation in fruit bat hosts

Glennon

Becker

Peel

et al. 2019

Phil. Trans. R. Soc. B

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Pathogen circulation among reservoir hosts is a precondition for zoonotic spillover. Unlike the acute, high morbidity infections typical in spillover hosts, infected reservoir hosts often exhibit low morbidity and mortality. Although it has been proposed that reservoir host infections may be persistent with recurrent episodes of shedding, direct evidence is often lacking. We construct a generalized SEIR (susceptible, exposed, infectious, recovered) framework encompassing 46 sub-models representing the full range of possible transitions among those four states of infection and immunity. We then use likelihood-based methods to fit these models to nine years of longitudinal data on henipavirus serology from a captive colony of Eidolon helvum bats in Ghana. We find that reinfection is necessary to explain observed dynamics; that acute infectious periods may be very short (hours to days); that immunity, if present, lasts about 1–2 years; and that recurring latent infection is likely. Although quantitative inference is sensitive to assumptions about serology, qualitative predictions are robust. Our novel approach helps clarify mechanisms of viral persistence and circulation in wild bats, including estimated ranges for key parameters such as the basic reproduction number and the duration of the infectious period. Our results inform how future field-based and experimental work could differentiate the processes of viral recurrence and reinfection in reservoir hosts. This article is part of the theme issue ‘Dynamic and integrative approaches to understanding pathogen spillover’.

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Section: Discussionmentioning

confidence: 84%

What is stirring in the reservoir? Modelling mechanisms of henipavirus circulation in fruit bat hosts

Glennon

Becker

Peel

et al. 2019

Phil. Trans. R. Soc. B

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“…While many studies focus on measuring the diversity of host species in the context of disease, the structure of host communities can also be measured in the context of disease using characteristics of host species or host functional traits (Johnson et al ., 2013; Halliday et al ., 2019; Kirk et al ., 2019), resulting in trait‐based measures of host community competence (Stewart Merrill and Johnson, 2020). This approach, which has rapidly gained traction in disease ecology, suggests that host species that are the best able to spread diseases (i.e., the most competent hosts), often share particular suites of physiological traits (Huang et al ., 2013; Martin et al ., 2019; Becker and Han, 2020). Thus, host community competence can be linked to distributions of important host traits across host communities (Johnson et al ., 2015b; Liu et al ., 2017).…”

Section: Introductionmentioning

confidence: 99%

Biodiversity loss underlies the dilution effect of biodiversity

2020

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The dilution effect predicts increasing biodiversity to reduce the risk of infection, but the generality of this effect remains unresolved. Because biodiversity loss generates predictable changes in host community competence, we hypothesised that biodiversity loss might drive the dilution effect. We tested this hypothesis by reanalysing four previously published meta-analyses that came to contradictory conclusions regarding generality of the dilution effect. In the context of biodiversity loss, our analyses revealed a unifying pattern: dilution effects were inconsistently observed for natural biodiversity gradients, but were commonly observed for biodiversity gradients generated by disturbances causing losses of biodiversity. Incorporating biodiversity loss into tests of generality of the dilution effect further indicated that scale-dependency may strengthen the dilution effect only when biodiversity gradients are driven by biodiversity loss. Together, these results help to resolve one of the most contentious issues in disease ecology: the generality of the dilution effect.

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“…However, direct evidence relating to the potential for differences in virulence between BFDV lineages remains lacking to date. In many host-pathogen systems, degrees of resistance and tolerance vary between host species [10,59], leading to heterogeneous prevalence and transmission rates of generalist pathogens [6]. A previous study from our group on Crimson Rosellas showed that prevalence and load can differ strongly even between subspecies, despite phylogenetic clustering of BFDV [24].…”

Section: Plos Onementioning

confidence: 92%

“…Not all hosts are equally likely to be infected and to transmit pathogens, so pathogen prevalence and transmission rates can show high heterogeneity between host species [8,9]. This heterogeneity can be caused by fluctuations in host resistance and tolerance to pathogens [6,10], and by temporal and geographical factors influencing pathogen occurrence [11]. Prevalence and load can also be influenced by host sex, due to sex-specific immune responses [12].…”

Section: Introductionmentioning

confidence: 99%

Beak and feather disease virus (BFDV) prevalence, load and excretion in seven species of wild caught common Australian parrots

et al. 2020

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Pathogens pose a major risk to wild host populations, especially in the face of ongoing biodiversity declines. Beak and feather disease virus (BFDV) can affect most if not all members of one of the largest and most threatened bird orders worldwide , the Psittaciformes. Signs of disease can be severe and mortality rates high. Its broad host range makes it a risk to threatened species in particular, because infection can occur via spill-over from abundant hosts. Despite these risks, surveillance of BFDV in locally abundant wild host species has been lacking. We used qPCR and haemagglutination assays to investigate BFDV prevalence, load and shedding in seven abundant host species in the wild in southeast Australia: Crimson Rosellas (Platycercus elegans), Eastern Rosellas (Platycercus eximius), Galahs (Eolophus roseicapillus), Sulphur-crested Cockatoos (Cacatua galerita), Blue-winged Parrots (Neophema chrysostoma), Rainbow Lorikeets (Trichoglossus moluccanus) and Redrumped Parrots (Psephotus haematonotus). We found BFDV infection in clinically normal birds in six of the seven species sampled. We focused our analysis on the four most commonly caught species, namely Crimson Rosellas (BFDV prevalence in blood samples: 41.8%), Sulphur-crested Cockatoos (20.0%), Blue-winged Parrots (11.8%) and Galahs (8.8%). Species, but not sex, was a significant predictor for BFDV prevalence and load. 56.1% of BFDV positive individuals were excreting BFDV antigen into their feathers, indicative of active viral replication with shedding. Being BFDV positive in blood samples predicted shedding in Crimson Rosellas. Our study confirms that BFDV is endemic in our study region, and can inform targeted disease management by providing comparative data on interspecies variation in virus prevalence, load and shedding.

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Extreme Competence: Keystone Hosts of Infections

Cited by 46 publications

References 72 publications

What is stirring in the reservoir? Modelling mechanisms of henipavirus circulation in fruit bat hosts

What is stirring in the reservoir? Modelling mechanisms of henipavirus circulation in fruit bat hosts

Biodiversity loss underlies the dilution effect of biodiversity

Beak and feather disease virus (BFDV) prevalence, load and excretion in seven species of wild caught common Australian parrots

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