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. 2011 Dec 22;278(1725):3703-12.
doi: 10.1098/rspb.2011.0522. Epub 2011 May 11.

Urban habituation, ecological connectivity and epidemic dampening: the emergence of Hendra virus from flying foxes (Pteropus spp.)

Raina K Plowright  1 , Patrick Foley, Hume E Field, Andy P Dobson, Janet E Foley, Peggy Eby, Peter Daszak
Affiliations

Urban habituation, ecological connectivity and epidemic dampening: the emergence of Hendra virus from flying foxes (Pteropus spp.)

Raina K Plowright et al. Proc Biol Sci..

Abstract

Anthropogenic environmental change is often implicated in the emergence of new zoonoses from wildlife; however, there is little mechanistic understanding of these causal links. Here, we examine the transmission dynamics of an emerging zoonotic paramyxovirus, Hendra virus (HeV), in its endemic host, Australian Pteropus bats (fruit bats or flying foxes). HeV is a biosecurity level 4 (BSL-4) pathogen, with a high case-fatality rate in humans and horses. With models parametrized from field and laboratory data, we explore a set of probable contributory mechanisms that explain the spatial and temporal pattern of HeV emergence; including urban habituation and decreased migration-two widely observed changes in flying fox ecology that result from anthropogenic transformation of bat habitat in Australia. Urban habituation increases the number of flying foxes in contact with human and domestic animal populations, and our models suggest that, in addition, decreased bat migratory behaviour could lead to a decline in population immunity, giving rise to more intense outbreaks after local viral reintroduction. Ten of the 14 known HeV outbreaks occurred near urbanized or sedentary flying fox populations, supporting these predictions. We also demonstrate that by incorporating waning maternal immunity into our models, the peak modelled prevalence coincides with the peak annual spill-over hazard for HeV. These results provide the first detailed mechanistic framework for understanding the sporadic temporal pattern of HeV emergence, and of the urban/peri-urban distribution of HeV outbreaks in horses and people.

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Figures

Figure 1.
Figure 1.
Epidemic hazard rates for HeV spill-over events. (a) Bayesian posterior epidemic hazard rate for Hendra virus (HeV) spill-over from 1994 to 2010. The grey region is bounded by the 2.5th and 97.5th posterior percentiles for the hazard rate. The grey horizontal line is the flat prior used, bound by the middle 95% of the prior distribution (see the electronic supplementary material, methods). Crosses represent spill-over events. (b) Bayesian monthly posterior epidemic hazard rate for HeV. Crosses indicate spill-over events within the labelled month. The approximate peak timing of life-history events for P. alecto and P. poliocephalus in South Queensland [–18] is indicated at the top of the plot.
Figure 2.
Figure 2.
Continuously occupied flying fox camps and HeV spill-over locations in relation to human population density. ‘Spectacled’, ‘black’ and ‘grey headed’ refer to flying fox species ([–32]; P. Eby 2004, unpublished data; L. Shilton & D. Westcott 2009, personal communication).
Figure 3.
Figure 3.
Herd immunity and epidemic size. Relationship between initial herd immunity, epidemic amplitude (black triangles) and epidemic duration (red circles) in a stochastic metapopulation simulation (N0 = 10 000, β = 4.76E − 05, γ = 0.143, h = 200, c = 0.16). The deterministic threshold number of susceptibles required for disease invasion in this model system is approximately 3000 (initial proportion immune = 0.7). When virus is introduced into a population with initial herd immunity approaching the threshold for invasion, low amplitude, persistent smouldering epidemics may result. When virus is introduced into a more susceptible population, high amplitude, shorter epidemics may result.
Figure 4.
Figure 4.
The effect of decreasing connectivity on viral dynamics. Grey squares, urban populations within the central cluster; black circles, linear rural populations outside the central urban cluster. As connectivity between local populations decreases: (a) the median total number of individuals infected per local epidemic increases; (b) the median maximum amplitude of local epidemics increases; (c) while the median epidemic frequency decreases; (d) the sum of infected individuals in the metapopulation over a 20 year simulation.
Figure 5.
Figure 5.
The total number of infected flying foxes in urban versus rural environments. The graphic below the plot shows the spatial structure of the model flying fox metapopulation with a central urban cluster with linear arms expanding on each side. ‘Position’ is an indicator of population x-coordinates. Infected individuals are tallied over all populations at a given x-coordinate, within each time step (grey line) and over all time steps (black line).
Figure 6.
Figure 6.
Simulated HeV dynamics in urban and rural flying fox populations. Populations in position 80–120 are within an urban cluster (a 4 × 5 matrix with tapering edges—see bottom of figure 5). The linear arms are in position 1–79 and 121–200. Urban populations experience smaller, more frequent epidemics which occasionally seed travelling waves of infection through the rural linear populations (h = 200, β = 4.76E − 05, N0 = 10 000, c = 0.1, s = 20).
Figure 7.
Figure 7.
Temporal dynamics of HeV prevalence over an 18 month period. (a) Temporal dynamics of infected individuals (red) in 200 populations following the spring birth pulse (blue are susceptibles); (b) temporal dynamics when maternal immunity wanes after six months. Note the spike in prevalence is delayed by six months. (h = 200, β = 4.76E − 05, N0 = 10 000, c = 0.1, 1/100 infected individuals were infected for 365 days).
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