Anthropogenic resource subsidies and host-parasite dynamics in wildlife

Peer reviewe

The problem of scale in the prediction and management of pathogen spillover

Disease emergence events, epidemics and pandemics all underscore the need to predict zoonotic pathogen spillover. Because cross-species transmission is inherently hierarchical, involving processes that occur at varying levels of biological organization, such predictive efforts can be complicated by the many scales and vastness of data potentially required for forecasting. A wide range of approaches are currently used to forecast spillover risk (e.g. macroecology, pathogen discovery, surveillance of human populations, among others), each of which is bound within particular phylogenetic, spatial and temporal scales of prediction. Here, we contextualize these diverse approaches within their forecasting goals and resulting scales of prediction to illustrate critical areas of conceptual and pragmatic overlap. Specifically, we focus on an ecological perspective to envision a research pipeline that connects these different scales of data and predictions from the aims of discovery to intervention. Pathogen discovery and predictions focused at the phylogenetic scale can first provide coarse and pattern-based guidance for which reservoirs, vectors and pathogens are likely to be involved in spillover, thereby narrowing surveillance targets and where such efforts should be conducted. Next, these predictions can be followed with ecologically driven spatio-temporal studies of reservoirs and vectors to quantify spatio-temporal fluctuations in infection and to mechanistically understand how pathogens circulate and are transmitted to humans. This approach can also help identify general regions and periods for which spillover is most likely. We illustrate this point by highlighting several case studies where long-term, ecologically focused studies (e.g. Lyme disease in the northeast USA, Hendra virus in eastern Australia, Plasmodium knowlesi in Southeast Asia) have facilitated predicting spillover in space and time and facilitated the design of possible intervention strategies. Such studies can in turn help narrow human surveillance efforts and help refine and improve future large-scale, phylogenetic predictions. We conclude by discussing how greater integration and exchange between data and predictions generated across these varying scales could ultimately help generate more actionable forecasts and interventions

Contact Networks and Mortality Patterns Suggest Pneumonia-Causing Pathogens may Persist in Wild Bighorn Sheep

Efficacy of disease control efforts is often contingent on whether the disease persists locally in the host population or is repeatedly introduced from an alternative host species. Local persistence is partially determined by the interaction between host contact structure and disease transmission rates: relatively isolated host groups facilitate pathogen persistence by slowing the rate at which highly transmissible pathogens access new susceptibles; alternatively, isolated host groups impede persistence for pathogens with low transmission rates by limiting the number of available hosts and forcing premature fade-out. Here, we use long-term data from the Hells Canyon region to investigate whether variable host contact patterns are associated with survival outcomes for 46 cohorts of bighorn sheep (Ovis canadensis) lambs subject to recurrent pneumonia outbreaks. We build social contact networks for each lamb cohort, and quantify variation in lamb mortality attributable to populations, years, and groups. We then refine estimates of chronic carriage rates in ewes, and disease-induced mortality rates in lambs, by finding parameters for the disease process that produce lamb morality rates similar to those observed when simulated on the observed host contact networks. Our results suggest that summer lamb hazards are spatially structured at the subpopulation level: 92.5 percent of the variation in lamb hazards during pneumonia outbreak years was attributable to sub-population-level groups, whereas 1.7 percent and 5.6 percent were attributable to year and population, respectively.  Additionally, the posterior distribution generated by our disease transmission model suggests that pneumonia-causing pathogens may persist locally in bighorn sheep populations, even during apparently healthy years

Disease Introduction Is Associated With a Phase Transition in Bighorn Sheep Demographics

Ecological theory suggests that pathogens are capable of regulating or limiting host population dynamics, and this relationship has been empirically established in several settings. However, although studies of childhood diseases were integral to the development of disease ecology, few studies show population limitation by a disease affecting juveniles. Here, we present empirical evidence that disease in lambs constrains population growth in bighorn sheep (Ovis canadensis) based on 45 years of population‐level and 18 years of individual‐level monitoring across 12 populations. While populations generally increased (λ = 1.11) prior to disease introduction, most of these same populations experienced an abrupt change in trajectory at the time of disease invasion, usually followed by stagnant‐to‐declining growth rates (λ = 0.98) over the next 20 years. Disease‐induced juvenile mortality imposed strong constraints on population growth that were not observed prior to disease introduction, even as adult survival returned to pre‐invasion levels. Simulations suggested that models including persistent disease‐induced mortality in juveniles qualitatively matched observed population trajectories, whereas models that only incorporated all‐age disease events did not. We use these results to argue that pathogen persistence may pose a lasting, but under‐recognized, threat to host populations, particularly in cases where clinical disease manifests primarily in juveniles

Climate change could increase the geographic extent of Hendra virus spillover risk

Disease risk mapping is important for predicting and mitigating impacts of bat-borne viruses, including Hendra virus (Paramyxoviridae:Henipavirus), that can spillover to domestic animals and thence to humans. We produced two models to estimate areas at potential risk of HeV spillover explained by the climatic suitability for its flying fox reservoir hosts, Pteropus alecto and P. conspicillatus. We included additional climatic variables that might affect spillover risk through other biological processes (such as bat or horse behaviour, plant phenology and bat foraging habitat). Models were fit with a Poisson point process model and a log-Gaussian Cox process. In response to climate change, risk expanded southwards due to an expansion of P. alecto suitable habitat, which increased the number of horses at risk by 175–260% (110,000–165,000). In the northern limits of the current distribution, spillover risk was highly uncertain because of model extrapolation to novel climatic conditions. The extent of areas at risk of spillover from P. conspicillatus was predicted shrink. Due to a likely expansion of P. alecto into these areas, it could replace P. conspicillatus as the main HeV reservoir. We recommend: (1) HeV monitoring in bats, (2) enhancing HeV prevention in horses in areas predicted to be at risk, (3) investigate and develop mitigation strategies for areas that could experience reservoir host replacements

Optimal foraging in seasonal environments: implications for residency of Australian flying foxes in food-subsidized urban landscapes

Bats provide important ecosystem services such as pollination of native forests; they are also a source of zoonotic pathogens for humans and domestic animals. Human-induced changes to native habitats may have created more opportunities for bats to reside in urban settings, thus decreasing pollination services to native forests and increasing opportunities for zoonotic transmission. In Australia, fruit bats (Pteropus spp. flying foxes) are increasingly inhabiting urban areas where they feed on anthropogenic food sources with nutritional characteristics and phenology that differ from native habitats. We use optimal foraging theory to investigate the relationship between bat residence time in a patch, the time it takes to search for a new patch (simulating loss of native habitat) and seasonal resource production. We show that it can be beneficial to reside in a patch, even when food productivity is low, as long as foraging intensity is low and the expected searching time is high. A small increase in the expected patch searching time greatly increases the residence time, suggesting nonlinear associations between patch residence and loss of seasonal native resources. We also found that sudden increases in resource consumption due to an influx of new bats has complex effects on patch departure times that again depend on expected searching times and seasonality. Our results suggest that the increased use of urban landscapes by bats may be a response to new spatial and temporal configurations of foraging opportunities. Given that bats are reservoir hosts of zoonotic diseases, our results provide a framework to study the effects of foraging ecology on disease dynamics.This research was supported by the State of Queensland, the State of New South Wales and the Commonwealth of Australia under the National Hendra Virus Research Program and by an IDEAS RCN research exchange grant awarded to D.P. to visit O.R. R.K.P. and O.R. are supported by National Science Foundation DEB-1716698; R.K.P. is supported by funding from the Defense Advanced Research Projects Agency (DARPA; D16AP00113), the National Institute of General Medical Sciences of the National Institutes of Health under Award Number P20GM103474 and P30GM110732, and SERDP RC-2633

Climate Change and Infectious Disease Dynamics

The International Panel on Climate Change has made an unequivocal case that the earth\u27s climate is changing in profound ways, and that human activities are contributing significantly to climate disruption (IPCC 2007). The weight of evidence demonstrates warming global temperatures, changing patterns of precipitation, and increasing climate variability, with more extreme events. Thus, the physical underpinnings of ecology are changing, with pervasive effects on disease dynamics. Interactions among environment, hosts, and pathogens drive disease processes, and climate change will influence every interaction in this triad, directly and indirectly

Estimating viral prevalence with data fusion for adaptive two-phase pooled sampling.

The COVID-19 pandemic has highlighted the importance of efficient sampling strategies and statistical methods for monitoring infection prevalence, both in humans and in reservoir hosts. Pooled testing can be an efficient tool for learning pathogen prevalence in a population. Typically, pooled testing requires a second-phase retesting procedure to identify infected individuals, but when the goal is solely to learn prevalence in a population, such as a reservoir host, there are more efficient methods for allocating the second-phase samples.To estimate pathogen prevalence in a population, this manuscript presents an approach for data fusion with two-phased testing of pooled samples that allows more efficient estimation of prevalence with less samples than traditional methods. The first phase uses pooled samples to estimate the population prevalence and inform efficient strategies for the second phase. To combine information from both phases, we introduce a Bayesian data fusion procedure that combines pooled samples with individual samples for joint inferences about the population prevalence.Data fusion procedures result in more efficient estimation of prevalence than traditional procedures that only use individual samples or a single phase of pooled sampling.The manuscript presents guidance on implementing the first-phase and second-phase sampling plans using data fusion. Such methods can be used to assess the risk of pathogen spillover from reservoir hosts to humans, or to track pathogens such as SARS-CoV-2 in populations

Climatic suitability influences species specific abundance patterns of Australian flying foxes and risk of Hendra virus spillover

Hendra virus is a paramyxovirus of Australian flying fox bats. It was first detected in August 1994, after the death of 20 horses and one human. Since then it has occurred regularly within a portion of the geographical distribution of all Australian flying fox (fruit bat) species. There is, however, little understanding about which species are most likely responsible for spillover, or why spillover does not occur in other areas occupied by reservoir and spillover hosts. Using ecological niche models of the four flying fox species we were able to identify which species are most likely linked to spillover events using the concept of distance to the niche centroid of each species. With this novel approach we found that 20 out of 27 events occur disproportionately closer to the niche centroid of two species (P. alecto and P. conspicillatus). With linear regressions we found a negative relationship between distance to the niche centroid and abundance of these two species. Thus, we suggest that the bioclimatic niche of these two species is likely driving the spatial pattern of spillover of Hendra virus into horses and ultimately humans

Transmission or within-host dynamics driving pulses of zoonotic viruses in reservoir-host populations

Progress in combatting zoonoses that emerge from wildlife is often constrained by limited knowledge of the biology of pathogens within reservoir hosts. We focus on the host–pathogen dynamics of four emerging viruses associated with bats: Hendra, Nipah, Ebola, and Marburg viruses. Spillover of bat infections to humans and domestic animals often coincides with pulses of viral excretion within bat populations, but the mechanisms driving such pulses are unclear. Three hypotheses dominate current research on these emerging bat infections. First, pulses of viral excretion could reflect seasonal epidemic cycles driven by natural variations in population densities and contact rates among hosts. If lifelong immunity follows recovery, viruses may disappear locally but persist globally through migration; in either case, new outbreaks occur once births replenish the susceptible pool. Second, epidemic cycles could be the result of waning immunity within bats, allowing local circulation of viruses through oscillating herd immunity. Third, pulses could be generated by episodic shedding from persistently infected bats through a combination of physiological and ecological factors. The three scenarios can yield similar patterns in epidemiological surveys, but strategies to predict or manage spillover risk resulting from each scenario will be different. We outline an agenda for research on viruses emerging from bats that would allow for differentiation among the scenarios and inform development of evidence-based interventions to limit threats to human and animal health. These concepts and methods are applicable to a wide range of pathogens that affect humans, domestic animals, and wildlife