Sampling scale and season influence the observed relationship between the density of deer and questing Ixodes ricinus nymphs

Using mechanistic models to highlight research priorities for tick-borne zoonotic diseases: Improving our understanding of the ecology and maintenance of Kyasanur Forest Disease in India

The risk of spillover of zoonotic diseases to humans is changing in response to multiple environmental and societal drivers, particularly in tropical regions where the burden of neglected zoonotic diseases is highest and land use change and forest conversion is occurring most rapidly. Neglected zoonotic diseases can have significant impacts on poor and marginalised populations in low-resource settings but ultimately receive less attention and funding for research and interventions. As such, effective control measures and interventions are often hindered by a limited ecological evidence base, which results in a limited understanding of epidemiologically relevant hosts or vectors and the processes that contribute to the maintenance of pathogens and spillover to humans. Here, we develop a generalisable next generation matrix modelling framework to better understand the transmission processes and hosts that have the greatest contribution to the maintenance of tick-borne diseases with the aim of improving the ecological evidence base and framing future research priorities for tick-borne diseases. Using this model we explore the relative contribution of different host groups and transmission routes to the maintenance of a neglected zoonotic tick-borne disease, Kyasanur Forest Disease Virus (KFD), in multiple habitat types. The results highlight the potential importance of transovarial transmission and small mammals and birds in maintaining this disease. This contradicts previous hypotheses that primates play an important role influencing the distribution of infected ticks. There is also a suggestion that risk could vary across different habitat types but currently more research is needed to evaluate this relationship. In light of these results, we outline the key knowledge gaps for this system and future research priorities that could inform effective interventions and control measures.

The Impact of Host Abundance on the Epidemiology of Tick-Borne Infection

Tick-borne diseases are an increasing global public health concern due to an expanding geographical range and increase in abundance of tick-borne infectious agents. A potential explanation for the rising impact of tick-borne diseases is an increase in tick abundance which may be linked to an increase in density of the hosts on which they feed. In this study, we develop a model framework to understand the link between host density, tick demography and tick-borne pathogen epidemiology. Our model links the development of specific tick stages to the specific hosts on which they feed. We show that host community composition and host density have an impact on tick population dynamics and that this has a consequent impact on host and tick epidemiological dynamics. A key result is that our model framework can exhibit variation in host infection prevalence for a fixed density of one host type due to changes in density of other host types that support different tick life stages. Our findings suggest that host community composition may play a crucial role in explaining the variation in prevalence of tick-borne infections in hosts observed in the field.

Biodiversity in the Lyme-light: ecological restoration and tick-borne diseases in Europe

Biodiversity loss and the emergence of zoonotic diseases are two major global challenges. An urgent question is how ecosystems and wildlife communities can be restored whilst minimizing the risk of zoonotic diseases carried by wildlife. Here, we evaluate how current ambitions to restore Europe's natural ecosystems may affect the hazard of diseases vectored by the tick Ixodes ricinus at different scales. We find that effects of restoration efforts on tick abundance are relatively straightforward but that the interacting effects of vertebrate diversity and abundance on pathogen transmission are insufficiently known. Long-term integrated surveillance of wildlife communities, ticks, and their pathogens is needed to understand their interactions and to prevent nature restoration from increasing tick-borne disease (TBD) hazard.

Recreation reduces tick density through fine-scale risk effects on deer space-use

Altered interactions between pathogens, their hosts and vectors have potential consequences for human disease risk. Notably, tick-borne pathogens, many of which are associated with growing deer abundance, show global increasing prevalence and pose increasing challenges for disease prevention. Human activities can largely affect the patterns of deer space-use and can therefore be potential management tools to alleviate human-wildlife conflicts. Here, we tested how deer space-use patterns are influenced by human recreational activities, and how this in turn affects the spatial distribution of the sheep tick (Ixodes ricinus), a relevant disease vector of zoonoses such as Lyme borrelioses. We compared deer dropping and questing tick density on transects near (20 m) and further away from (100 m) forest trails that were either frequently used (open for recreation) or infrequently used (closed for recreation, but used by park managers). In contrast to infrequently used trails, deer dropping density was 31% lower near (20 m) than further away from (100 m) frequently used trails. Similarly, ticks were 62% less abundant near (20 m) frequently used trails compared to further away from (100 m) these trails, while this decline in tick numbers was only 14% near infrequently used trails. The avoidance by deer of areas close to human-used trails was thus associated with a similar reduction in questing tick density near these trails. As tick abundance generally correlates to pathogen prevalence, the use of trails for recreation may reduce tick-borne disease risk for humans on and near these trails. Our study reveals an unexplored effect of human activities on ecosystems and how this knowledge could be potentially used to mitigate zoonotic disease risk.

No net effect of host density on tick-borne disease hazard due to opposing roles of vector amplification and pathogen dilution

To better understand vector‐borne disease dynamics, knowledge of the ecological interactions between animal hosts, vectors, and pathogens is needed. The effects of hosts on disease hazard depends on their role in driving vector abundance and their ability to transmit pathogens. Theoretically, a host that cannot transmit a pathogen could dilute pathogen prevalence but increase disease hazard if it increases vector population size. In the case of Lyme disease, caused by Borrelia burgdorferi s.l. and vectored by Ixodid ticks, deer may have dual opposing effects on vectors and pathogen: deer drive tick population densities but do not transmit B. burgdorferi s.l. and could thus decrease or increase disease hazard. We aimed to test for the role of deer in shaping Lyme disease hazard by using a wide range of deer densities while taking transmission host abundance into account. We predicted that deer increase nymphal tick abundance while reducing pathogen prevalence. The resulting impact of deer on disease hazard will depend on the relative strengths of these opposing effects. We conducted a cross‐sectional survey across 24 woodlands in Scotland between 2017 and 2019, estimating host (deer, rodents) abundance, questing Ixodes ricinus nymph density, and B. burgdorferi s.l. prevalence at each site. As predicted, deer density was positively associated with nymph density and negatively with nymphal infection prevalence. Overall, these two opposite effects canceled each other out: Lyme disease hazard did not vary with increasing deer density. This demonstrates that, across a wide range of deer and rodent densities, the role of deer in amplifying tick densities cancels their effect of reducing pathogen prevalence. We demonstrate how noncompetent host density has little effect on disease hazard even though they reduce pathogen prevalence, because of their role in increasing vector populations. These results have implications for informing disease mitigation strategies, especially through host management.

A roadmap towards predicting species interaction networks (across space and time)

Networks of species interactions underpin numerous ecosystem processes, but comprehensively sampling these interactions is difficult. Interactions intrinsically vary across space and time, and given the number of species that compose ecological communities, it can be tough to distinguish between a true negative (where two species never interact) from a false negative (where two species have not been observed interacting even though they actually do). Assessing the likelihood of interactions between species is an imperative for several fields of ecology. This means that to predict interactions between species-and to describe the structure, variation, and change of the ecological networks they form-we need to rely on modelling tools. Here, we provide a proof-of-concept, where we show how a simple neural network model makes accurate predictions about species interactions given limited data. We then assess the challenges and opportunities associated with improving interaction predictions, and provide a conceptual roadmap forward towards predictive models of ecological networks that is explicitly spatial and temporal. We conclude with a brief primer on the relevant methods and tools needed to start building these models, which we hope will guide this research programme forward. This article is part of the theme issue 'Infectious disease macroecology: parasite diversity and dynamics across the globe'.