Browsing by Author "Giles, John R."

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Conditions affecting the timing and magnitude of Hendra virus shedding across pteropodid bat populations in Australia
(2017-09) Paez, David J.; Giles, John R.; McCallum, Hamish I.; Field, H.; Jordan, D.; Peel, Alison J.; Plowright, Raina K.
Understanding infection dynamics in animal hosts is fundamental to managing spillover and emergence of zoonotic infections. Hendra virus is endemic in Australian pteropodid bat populations and can be lethal to horses and humans. However, we know little about the factors driving Hendra virus prevalence in resevoir bat populations, making spillover difficult to predict. We use Hendra virus prevalence data collected from 13 000 pooled bat urine samples across space and time to determine if pulses of prevalence are periodic and synchronized across sites. We also test whether site-specific precipitation and temperature affect the amplitude of the largest annual prevalence pulses. We found little evidence for a periodic signal in Hendra virus prevalence. Although the largest amplitude pulses tended to occur over winter, pulses could also occur in other seasons. We found that Hendra virus prevalence was weakly synchronized across sites over short distances, suggesting that prevalence is driven by local-scale effects. Finally, we found that drier conditions in previous seasons and the abundance of Pteropus alecto were positively correlated with the peak annual values of Hendra virus prevalence. Our results suggest that in addition to seasonal effects, bat density and local climatic conditions interact to drive Hendra virus infection dynamics.
Optimizing noninvasive sampling of a zoonotic bat virus
(Wiley, 2021-08) Giles, John R.; Peel, Alison J.; Wells, Konstans; Plowright, Raina K.; McCallum, Hamish; Restif, Olivier
Outbreaks of infectious viruses resulting from spillover events from bats have brought much attention to bat- borne zoonoses, which has motivated increased ecological and epidemiological studies on bat populations. Field sampling methods often collect pooled samples of bat excreta from plastic sheets placed under-roosts. However, positive bias is introduced because multiple individuals may contribute to pooled samples, making studies of viral dynamics difficult. Here, we explore the general issue of bias in spatial sample pooling using Hendra virus in Australian bats as a case study. We assessed the accuracy of different under- roost sampling designs using generalized additive models and field data from individually captured bats and pooled urine samples. We then used theoretical simulation models of bat density and under- roost sampling to understand the mechanistic drivers of bias. The most commonly used sampling design estimated viral prevalence 3.2 times higher than individual- level data, with positive bias 5–7 times higher than other designs due to spatial autocorrelation among sampling sheets and clustering of bats in roosts. Simulation results indicate using a stratified random design to collect 30–40 pooled urine samples from 80 to 100 sheets, each with an area of 0.75–1 m2, and would allow estimation of true prevalence with minimum sampling bias and false negatives. These results show that widely used under- roost sampling techniques are highly sensitive to viral presence, but lack specificity, providing limited information regarding viral dynamics. Improved estimation of true prevalence can be attained with minor changes to existing designs such as reducing sheet size, increasing sheet number, and spreading sheets out within the roost area. Our findings provide insight into how spatial sample pooling is vulnerable to bias for a wide range of systems in disease ecology, where optimal sampling design is influenced by pathogen prevalence, host population density, and patterns of aggregation.
Pathogen spillover driven by rapid changes in bat ecology
(Springer Science and Business Media LLC, 2023-01) Eby, Peggy; Peel, Alison J.; Hoegh, Andrew; Madden, Wyatt; Giles, John R.; Hudson, Peter J.; Plowright, Raina K.
During recent decades, pathogens that originated in bats have become an increasing public health concern. A major challenge is to identify how those pathogens spill over into human populations to generate a pandemic threat1. Many correlational studies associate spillover with changes in land use or other anthropogenic stressors2,3, although the mechanisms underlying the observed correlations have not been identified4. One limitation is the lack of spatially and temporally explicit data on multiple spillovers, and on the connections among spillovers, reservoir host ecology and behaviour and viral dynamics. We present 25 years of data on land-use change, bat behaviour and spillover of Hendra virus from Pteropodid bats to horses in subtropical Australia. These data show that bats are responding to environmental change by persistently adopting behaviours that were previously transient responses to nutritional stress. Interactions between land-use change and climate now lead to persistent bat residency in agricultural areas, where periodic food shortages drive clusters of spillovers. Pulses of winter flowering of trees in remnant forests appeared to prevent spillover. We developed integrative Bayesian network models based on these phenomena that accurately predicted the presence or absence of clusters of spillovers in each of the 25 years. Our long-term study identifies the mechanistic connections between habitat loss, climate and increased spillover risk. It provides a framework for examining causes of bat virus spillover and for developing ecological countermeasures to prevent pandemics.