Biology subjects

Eby, P.

Publications and source records attributed to Eby, P..

4 recordsLinked to original sources

bioRxiv2024

Integrating predictors of host condition into spatiotemporal multi-scale models of virus shedding

Understanding where and when pathogens occur in the environment has implications for reservoir population health and infection risk. In reservoir hosts, infection status and pathogen shedding are affected by processes interacting across different scales: from landscape features affecting host location and transmission to within-host processes affecting host immunity and infectiousness. While uncommonly done, simultaneously incorporating processes across multiple scales may improve pathogen shedding predictions. In Australia, the black flying fox (Pteropus alecto) is a natural host for the zoonotic Hendra virus, which is hypothesized to cause latent infections in bats. Re-activation and virus shedding may be triggered by poor host condition, leading to virus excretion through urine. Here, we developed a statistical modeling approach that combined data at multiple spatial and temporal scales to capture ecological and biological processes potentially affecting virus shedding. We parameterized these models using existing datasets and compared model performance to under-roost virus shedding data from 2011-2014 in 23 roosts across a 1200-km transect. Our approach enabled comparisons among multiple model structures to determine which variables at which scales are most influential for accurate predictions of virus shedding in space and time. We identified environmental predictors and temporal lags of these features that were important for determining where reservoirs are located and multiple independent proxies for reservoir condition. The best-performing multi-scale model delineated periods of low and high virus prevalence, reflecting observed shedding patterns from pooled under-roost samples. Incorporating regional indicators of food scarcity enhanced model accuracy while incorporating other stress indicators at local scales confounded this signal. This multiscale modeling approach enabled the combination of processes from different ecological scales and identified environmental variables influencing Hendra virus shedding, highlighting how integrating data across scales may improve risk forecasts for other pathogen systems.

ecology↗

bioRxiv2023

Environmental and ecological signals predict periods of nutritional stress for Eastern Australian flying fox populations.

Food availability determines where animals use space across a landscape and therefore affects the risk of encounters that lead to zoonotic spillover. This relationship is evident in Australian flying foxes (Pteropus spp; fruit bats), where acute food shortages precede clusters of Hendra virus spillovers. Using explainable artificial intelligence, we predicted months of food shortages from climatological and ecological covariates (1996-2022) in eastern Australia. Overall accuracy in predicting months of low food availability on a test set from 2018 up to 2022 reached 93.33% and 92.59% based on climatological and bat-level features, respectively. Seasonality and Oceanic El Nino Index were the most important environmental features, while the number of bats in rescue centers and their body weights were the most important bat-level features. These models support predictive signals up to nine months in advance, facilitating action to mitigate spillover risk.

ecology↗

bioRxiv2023

Periodic shifts in viral load increase risk of spillover from bats

Prediction and management of zoonotic pathogen spillover requires an understanding of infection dynamics within reservoir host populations. Transmission risk is often assessed using prevalence of infected hosts, with infection status based on the presence of genomic material. However, detection of viral genomic material alone does not necessarily indicate the presence of infectious virus, which could decouple prevalence from transmission risk. We undertook a multi-faceted investigation of Hendra virus shedding in Pteropus bats, combining insights from virus isolation, viral load proxies, viral prevalence, and longitudinal patterns of shedding, from 6,151 samples. In addition to seasonal and interannual fluctuation in prevalence, we found evidence for periodic shifts in the distribution of viral loads. The proportion of bats shedding high viral loads was higher during peak prevalence periods during which spillover events were observed, and lower during non-peak periods when there were no spillovers. We suggest that prolonged periods of low viral load and low prevalence reflect prolonged shedding of non-infectious RNA, or viral loads that are insufficient or unlikely to overcome dose barriers to spillover infection. These findings show that incorporating viral load (or proxies of viral load) into longitudinal studies of virus excretion will better inform predictions of spillover risk than prevalence alone. Significance statementWe present a comprehensive analysis of a high-profile bat-virus system (Hendra virus in Australian flying-foxes) to demonstrate that both prevalence and viral loads can shift systematically over time, resulting in concentrated periods of increased spillover risk when prevalence and viral loads are high. We further suggest that prolonged periods of low-prevalence, low-load shedding may not reflect excretion of infectious virus, resolving the outstanding puzzle of why spillovers have not been observed during periods of low off-season prevalence in subtropical Australia, or more frequently in tropical Australia despite consistent low-prevalence shedding. The consideration of viral loads (or proxies of viral load) along with prevalence may improve risk inference from longitudinal surveys of zoonotic viruses across wildlife reservoir hosts.

ecology↗

bioRxiv2021

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

The ecological conditions experienced by wildlife reservoir hosts affect the amount of pathogen they excrete into the environment. This then shapes pathogen pressure, the amount of pathogen available to recipient hosts over space and time, which affects spillover risk. Few systems have data on both long-term ecological conditions and pathogen pressure, yet such data are critical for advancing our mechanistic understanding of ecological drivers of spillover risk. To identify these ecological drivers, we here reanalyze shedding data from a spatially replicated, multi-year study of Hendra virus excretion from Australian flying foxes in light of 25 years of long-term data on changing ecology of the bat reservoir hosts. Using generalized additive mixed models, we show that winter virus shedding pulses, previously considered idiosyncratic, are most pronounced after recent food shortages and in bat populations that have been displaced to novel habitats. We next derive the area under each annual shedding curve (representing cumulative virus excretion) and show that pathogen pressure is also affected by the ecological conditions experienced by bat populations. Finally, we illustrate that pathogen pressure positively predicts observed spillover frequency. Our study suggests that recent ecological conditions of flying fox hosts are shifting the timing, magnitude, and cumulative intensity of Hendra virus shedding in ways that shape the landscape of spillover risk. This work provides a mechanistic approach to understanding and estimating risk of spillover from reservoir hosts in complex ecological systems and emphasizes the importance of host ecological context in identifying the determinants of pathogen shedding.

ecology↗