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Abstract The spatial organization of populations determines their pathogen dynamics. This is particularly important for communally roosting species, whose aggregations are often driven by the spatial structure of their environment.We develop a spatially explicit model for virus transmission within roosts of Australian tree‐dwelling bats (Pteropusspp.), parameterized to reflect Hendra virus. The spatial structure of roosts mirrors three study sites, and viral transmission between groups of bats in trees was modelled as a function of distance between roost trees. Using three levels of tree density to reflect anthropogenic changes in bat habitats, we investigate the potential effects of recent ecological shifts in Australia on the dynamics of zoonotic viruses in reservoir hosts.We show that simulated infection dynamics in spatially structured roosts differ from that of mean‐field models for equivalently sized populations, highlighting the importance of spatial structure in disease models of gregarious taxa. Under contrasting scenarios of flying‐fox roosting structures, sparse stand structures (with fewer trees but more bats per tree) generate higher probabilities of successful outbreaks, larger and faster epidemics, and shorter virus extinction times, compared to intermediate and dense stand structures with more trees but fewer bats per tree. These observations are consistent with the greater force of infection generated by structured populations with less numerous but larger infected groups, and may flag an increased risk of pathogen spillover from these increasingly abundant roost types.Outputs from our models contribute insights into the spread of viruses in structured animal populations, like communally roosting species, as well as specific insights into Hendra virus infection dynamics and spillover risk in a situation of changing host ecology. These insights will be relevant for modelling other zoonotic viruses in wildlife reservoir hosts in response to habitat modification and changing populations, including coronaviruses like SARS‐CoV‐2.
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Counterintuitive scaling between population abundance and local density: Implications for modelling transmission of infectious diseases in bat populations
Abstract Models of host–pathogen interactions help to explain infection dynamics in wildlife populations and to predict and mitigate the risk of zoonotic spillover. Insights from models inherently depend on the way contacts between hosts are modelled, and crucially, how transmission scales with animal density.Bats are important reservoirs of zoonotic disease and are among the most gregarious of all mammals. Their population structures can be highly heterogeneous, underpinned by ecological processes across different scales, complicating assumptions regarding the nature of contacts and transmission. Although models commonly parameterise transmission using metrics of total abundance, whether this is an ecologically representative approximation of host–pathogen interactions is not routinely evaluated.We collected a 13‐month dataset of tree‐roostingPteropusspp. from 2,522 spatially referenced trees across eight roosts to empirically evaluate the relationship between total roost abundance and tree‐level measures of abundance and density—the scale most likely to be relevant for virus transmission. We also evaluate whether roost features at different scales (roost level, subplot level, tree level) are predictive of these local density dynamics.Roost‐level features were not representative of tree‐level abundance (bats per tree) or tree‐level density (bats per m2or m3), with roost‐level models explaining minimal variation in tree‐level measures. Total roost abundance itself was either not a significant predictor (tree‐level 3D density) or only weakly predictive (tree‐level abundance).This indicates that basic measures, such as total abundance of bats in a roost, may not provide adequate approximations for population dynamics at scales relevant for transmission, and that alternative measures are needed to compare transmission potential between roosts. From the best candidate models, the strongest predictor of local population structure was tree density within roosts, where roosts with low tree density had a higher abundance but lower density of bats (more spacing between bats) per tree.Together, these data highlight unpredictable and counterintuitive relationships between total abundance and local density. More nuanced modelling of transmission, spread and spillover from bats likely requires alternative approaches to integrating contact structure in host–pathogen models, rather than simply modifying the transmission function.
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- Award ID(s):
- 1716698
- PAR ID:
- 10446964
- Publisher / Repository:
- Wiley-Blackwell
- Date Published:
- Journal Name:
- Journal of Animal Ecology
- Volume:
- 91
- Issue:
- 5
- ISSN:
- 0021-8790
- Page Range / eLocation ID:
- p. 916-932
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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