Spatial dynamics of pathogen transmission in communally roosting species: Impacts of changing habitats on bat‐virus dynamics

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 ( Pteropus spp.), 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.

Novel pathogen introduction rapidly alters evolved movement strategies, restructuring animal societies

“…Our infectious pathogen is easily transmitted through proximity, and causes a chronic yet non-fatal disease; though realistic, these assumptions cannot capture the full diversity of pathogens and their dynamics (White et al, 2018 a ; Scherer et al, 2020; Lunn et al, 2021). More detailed mechanistic modelling would have to account for the differential effects of proximity and actual social contacts on transmission (Rimbach et al, 2015).…”

“…Mechanistic, individual-based simulation models can incorporate substantial ecological detail, including an explicit spatial setting (DeAngelis and Diaz, 2019), individual variation in movement strategies (Spiegel et al, 2017; Lunn et al, 2021), and realistic disease transmission (White et al, 2018 a ; Scherer et al, 2020; Lunn et al, 2021). Yet mechanistic movement-disease models thus far focus on immediate ecological outcomes, such as infection persistence, and do not have an evolutionary component (White et al, 2018 a ; Scherer et al, 2020; Lunn et al, 2021). Limiting movement-disease models to an ecological scale could miss important feedbacks between the ecological outcomes of infectious disease and the consequences for the evolution of host behaviour (Cantor et al, 2021 b ).…”

Ecological conditions experienced by bat reservoir hosts predict the intensity of Hendra virus excretion over space and time

“…Despite a long-standing recognition of spatial and temporal scale in ecological research [79], replication across both axes remains challenging, particularly over relevant time intervals [80]. Spatiotemporal sampling is especially critical in the study of infectious disease [9,11], because pathogen shedding and transmission are both inherently spatial and temporal processes [63,81]. Connecting such data with changing ecology of wildlife further requires studies of abiotic and biotic correlates and host behavior and demography at similar or biologically meaningful spatial and temporal scales [7,14,82].…”

“…Across eastern Australia, habitats for the winter-flowering plants that drive flying fox nomadism have been reduced through land clearance, in turn driving nutritionally stressed bats into novel urban and agricultural environments outside their typical overwintering range (Eby et al, in review) [27,32,36,37]. Prior work has proposed, but not tested, that HeV shedding from flying foxes is driven by this process [23][24][25]63]. Acute food shortages could produce cumulative effects with other energetic and seasonal stressors (e.g., pregnancy, thermoregulation), as well as reliance on poor-quality, non-native food in agricultural and urban habitats, to alter within-host dynamics of viruses in bats [22,23].…”

“…Spatiotemporal sampling is especially critical in the study of infectious disease [9,11], because pathogen shedding and transmission are both inherently spatial and temporal processes [63,81].…”