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Peel, A. J.

Publications and source records attributed to Peel, A. J..

9 recordsLinked to original sources
bioRxiv2026

'Who Goes There?' Quantifying Scavenger-Carcass Activity at Mass Mortality Events

1.Mass mortality events (MMEs) create sudden pulses of carrion that can alter how vertebrate scavengers use carcass resources, including the frequency, duration, and timing of species-carcass contacts. These changes could have implications for pathogen transmission at the scavenger-carcass interface. We aimed to develop and apply a reproducible analytical framework for using camera-trap data to quantify transmission-relevant vertebrate activity at carcass sites under differing carrion biomass scenarios. We studied experimental carcass plots (single carcass [~]43 kg; mass mortality plots [10 carcasses, >350 kg total]; 6 of each) in Australias alpine ecosystem. The framework integrated descriptive summaries (bipartite network analysis, Kaplan-Meier curves) and marked temporal point-process models to characterise structural and temporal dimensions of species-carcass activity. Mass mortality plots had greater overall visitation duration, occurring as sustained activity (50% of visitation event volume by day 17), compared with intense then rapidly declining activity at single carcasses (50% by day 8). Mass mortality plots also had higher predicted daily arrival probability and contact hours across most species, indicating an extended window for pathogen transmission. This framework provides empirically derived contact parameters for MME-related disease spread models using camera-trap data to identify potential transmission pathways at the scavenger-carcass interface.

ecology↗
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

Novel Hendra virus variant detected by sentinel surveillance of Australian horses.

A novel Hendra virus (HeV) variant, not detected by routine testing, was identified and isolated from a Queensland horse that suffered acute, fatal disease consistent with HeV infection. Whole genome sequencing and phylogenetic analysis demonstrated the variant to have ~83% nucleotide identity to the prototype HeV strain. An updated RT-qPCR assay was designed for routine HeV surveillance. In silico and in vitro comparison of the receptor-binding protein with prototypic HeV showed that the human monoclonal antibody m102.4 used for post-exposure prophylaxis, as well as the current equine vaccine, should be effective against this variant. Genetic similarity of this virus to sequences detected from grey-headed flying-foxes suggests the variant circulates at-least in this species. Studies determining infection kinetics, pathogenicity, reservoir-species associations, viral-host co-evolution and spillover dynamics for this virus are urgently needed. Surveillance and biosecurity practices should be updated to appreciate HeV spillover risk across all regions frequented by flying foxes.

molecular biology↗
bioRxiv2019

Relation of seasonal birth pulses and maternal immunity with viral invasion and persistence: A case study of Hendra virus infection in a population of black flying foxes (Pteropus alecto)

Increasing outbreaks of emerging infectious diseases, originating from wildlife, has intensified interest in understanding the dynamics of these diseases in their wildlife reservoir hosts. Until recently, the effect of seasonal birth pulses and subsequent waning of maternally derived antibodies on epidemics in a wild mammal population has received little attention and has remained obscure. In this study, we explore how population structure, influenced by seasonal breeding and maternally derived immunity, affects viral invasion and persistence, using a hypothetical system loosely based on Hendra virus infection in black flying foxes (Pteropus alecto). We used deterministic epidemic models to simulate transient epidemics, following viral introduction into an infection-free population, with a variety of timings within a year and different levels of pre-existing herd immunity. Moreover, we applied different levels of birth synchrony and different modelling methods of waning maternal immunity to examine the effect of birth pulses and maternally derived immunity, both individually and in combination. The presence of waning maternal immunity dispersed the supply time of susceptible individuals in seasonally breeding populations, hence diminishing the effect of birth pulse. Dampened epidemics, caused by waning maternal immunity, made viral invasion and persistence easier. This study enhanced our understanding of viral invasion, persistence, and timing of epidemics in wildlife populations.

epidemiology↗
bioRxiv2018

Interpreting mosquito feeding patterns in Australia through an ecological lens; an analysis of blood meal studies.

Mosquito-borne pathogens contribute significantly to the global burden of disease, infecting millions of people each year. Mosquito feeding is critical to the transmission dynamics of pathogens, and thus it is important to understanding and interpreting mosquito feeding patterns. In this paper we explore mosquito feeding patterns and their implications for disease ecology through a meta-analysis of published blood meal results collected across Australia from more than 12,000 blood meals from 22 species. To assess mosquito-vertebrate associations and identify mosquitoes on a spectrum of generalist or specialist feeders, we analysed blood meal data in two ways; first using a novel odds ratio analysis, and secondly by calculating Shannon diversity scores. We find that each mosquito species had a unique feeding association with different vertebrates, suggesting species-specific feeding patterns. Broadly, mosquito species could be grouped broadly into those that were primarily ornithophilic and those that fed more often on livestock. Aggregated feeding patterns observed across Australia were not explained by intrinsic variables such as mosquito genetics or larval habitats. We discuss the implications for disease transmission by vector mosquito species classified as generalist-feeders (such as Aedes vigilax and Culex annulirostris), or specialists (such as Aedes aegypti) in light of potential influences on mosquito host choice. Overall, we find that whilst existing blood meal studies in Australia are useful for investigating mosquito feeding patterns, standardisation of blood meal study methodologies and analyses, including the incorporation of vertebrate surveys, would improve predictions of the impact of vector-host interactions on disease ecology. Our analysis can also be used as a framework to explore mosquito-vertebrate associations, in which host availability data is unavailable, in other global systems.

ecology↗
bioRxiv2018

Optimizing non-invasive sampling of an infectious bat virus

Notable outbreaks of infectious viruses resulting from spillover events from bats have brought much attention to the ecological origins of bat-borne zoonoses, resulting in an increase in ecological and epidemiological studies on bat populations in Africa, Asia, and Australia. The aim of many of these studies is to identify new viral agents with field sampling methods that collect pooled urine samples from large plastic sheets placed under a bat roost. The efficiency of under-roost sampling also makes it an attractive method for gathering roost-level prevalence data. However, the method allows multiple individuals to contribute to a pooled sample, potentially introducing positive bias. To assess the ability of under-roost sampling to accurately estimate viral prevalence, we constructed a probabilistic model to explore the relationship between four sampling designs (quadrant, uniform, stratified, and random) and estimation bias. We modeled bat density and movement with a Poisson cluster process and spatial kernels, and simulated the four underroost sheet sampling designs by manipulating a spatial grid of hexagonal tiles. We performed global sensitivity analyses to identify major sources of estimation bias and provide recommendations for field studies that wish to estimate roost-level prevalence. We found that the quadrant-based design had a positive bias 5-7 times higher than other designs due to spatial auto-correlation among sampling sheets and clustering of bats in the roost. The sampling technique is therefore highly sensitive to viral presence; but lacks specificity, providing poor information regarding dynamics in viral prevalence. Given population sizes of 5000-14000, our simulation results indicate that using a stratified random design to collect 30-40 urine samples from 80-100 sheets, each with an area of 0.75-1m2, would provide sufficient estimation of true prevalence with minimum sampling bias and false negatives. However, acknowledging the general problem of data aggregation, we emphasize that robust inference of true prevalence from field data require information of underpinning roost sizes. Our findings refine our understanding of the underroost sampling technique with the aim of increasing its specificity, and suggest that the method be further developed as an efficient non-invasive sampling technique that provides roost-level estimates of viral prevalence within a bat population.

ecology↗