Mechanistic movement models reveal ecological drivers of tick-borne pathogen spread

Identifying ecological drivers of tick-borne pathogen spread has great value for tick-borne disease management. However, theoretical investigations into the consequences of host movement behaviour on pathogen spread dynamics in heterogeneous landscapes remain limited because spatially explicit epidemiological models that incorporate more realistic mechanisms governing host movement are rare. We built a mechanistic movement model to investigate how the interplay between multiple ecological drivers affects the risk of tick-borne pathogen spread across heterogeneous landscapes. We used the model to generate simulations of tick dispersal by migratory birds and terrestrial hosts across theoretical landscapes varying in resource aggregation, and we performed a sensitivity analysis to explore the impacts of different parameters on the infected tick spread rate, tick infection prevalence and infected tick density. Our findings highlight the importance of host movement and tick population dynamics in explaining the infected tick spread rate into new regions. Tick infection prevalence and infected tick density were driven by predictors related to the infection process and tick population dynamics, respectively. Our results suggest that control strategies aiming to reduce tick burden on tick reproduction hosts and encounter rate between immature ticks and pathogen amplification hosts will be most effective at reducing tick-borne disease risk.

Epidemic growth rates and host movement patterns shape management performance for pathogen spillover at the wildlife–livestock interface

Managing pathogen spillover at the wildlife–livestock interface is a key step towards improving global animal health, food security and wildlife conservation. However, predicting the effectiveness of management actions across host–pathogen systems with different life histories is an on-going challenge since data on intervention effectiveness are expensive to collect and results are system-specific. We developed a simulation model to explore how the efficacies of different management strategies vary according to host movement patterns and epidemic growth rates. The model suggested that fast-growing, fast-moving epidemics like avian influenza were best-managed with actions like biosecurity or containment, which limited and localized overall spillover risk. For fast-growing, slower-moving diseases like foot-and-mouth disease, depopulation or prophylactic vaccination were competitive management options. Many actions performed competitively when epidemics grew slowly and host movements were limited, and how management efficacy related to epidemic growth rate or host movement propensity depended on what objective was used to evaluate management performance. This framework offers one means of classifying and prioritizing responses to novel pathogen spillover threats, and evaluating current management actions for pathogens emerging at the wildlife–livestock interface. This article is part of the theme issue ‘Dynamic and integrative approaches to understanding pathogen spillover’.

Can pathogens optimize both transmission and dispersal by exploiting sexual dimorphism in their hosts?

Pathogens often rely on their host for dispersal. Yet, maximizing fitness via replication can cause damage to the host and an associated reduction in host movement, incurring a trade-off between transmission and dispersal. Here, we test the idea that pathogens might mitigate this trade-off between reproductive fitness and dispersal by taking advantage of sexual dimorphism in their host, tailoring responses separately to males and females. Using experimental populations of Daphnia magna and its bacterial pathogen Pasteuria ramosa as a test-case, we find evidence that this pathogen can use male hosts as a dispersal vector, and the larger females as high-quality resource patches for optimized production of transmission spores. As sexual dimorphism in dispersal and body size is widespread across the animal kingdom, this differential exploitation of the sexes by a pathogen might be an unappreciated phenomenon, possibly evolved in various systems.

Parasite-induced shifts in host movement may explain the transient coexistence of high- and low-pathogenic disease strains

Many parasites induce decreased host movement, known as lethargy, which can impact disease spread and the evolution of virulence. Mathematical models have investigated virulence evolution when parasites cause host death, but disease-induced decreased host movement has received relatively less attention. Here, we consider a model where, due to the within-host parasite replication rate, an infected host can become lethargic and shift from a moving to a resting state, where it can die. We find that when the lethargy and disease-induced mortality costs to the parasites are not high, then evolutionary bistability can arise, and either moderate or high virulence can evolve depending on the initial virulence and the magnitude of mutation. These results suggest, firstly, the transient coexistence of strains with different virulence, which may explain the coexistence of low- and high-pathogenic strains of avian influenza and human immunodeficiency viruses, and secondly, that medical interventions to treat the symptoms of lethargy or prevent disease-induced host deaths can result in a large jump in virulence and the rapid evolution of high virulence. In complement to existing results that show bistability when hosts are heterogeneous at the population-level, we show that evolutionary bistability may arise due to transmission heterogeneity at the individual host-level.

Epidemic Growth Rates and Host Movement Patterns Shape Management Performance for Pathogen Spillover at The Wildlife-livestock Interface

ABSTRACTManaging pathogen spillover at the wildlife-livestock interface is a key step toward improving global animal health, food security, and wildlife conservation. However, predicting the effectiveness of management actions across host-pathogen systems with different life histories is an on-going challenge since data on intervention effectiveness are expensive to collect and results are system-specific. We developed a simulation model to explore how the efficacies of different management strategies vary according to host movement patterns and epidemic growth rates. The model suggested that fast-growing, fast-moving epidemics like avian influenza were best-managed with actions like biosecurity or containment, which limited and localized overall spillover risk. For fast-growing, slower-moving diseases like foot-and-mouth disease, depopulation or prophylactic vaccination were competitive management options. Many actions performed competitively when epidemics grew slowly and host movements were limited, and how management efficacy related to epidemic growth rate or host movement propensity depended on what objective was used to evaluate management performance. This framework may be a useful step in advancing how we classify and prioritise responses to novel pathogen spillover threats, and evaluate current management actions for pathogens emerging at the wildlife-livestock interface.

Endure your parasites: Sleepy Lizard (Tiliqua rugosa) movement is not affected by their ectoparasites

Movement is often used to indicate host vigour, as it has various ecological and evolutionary implications, and has been shown to be affected by parasites. We investigate the relationship between tick load and movement in the Australian Sleepy Lizard (Tiliqua rugosa (Gray, 1825)) using high resolution GPS tracking. This allowed us to track individuals across the entire activity season. We hypothesized that tick load negatively affects host movement (mean distance moved per day). We used a multivariate statistical model informed by the ecology and biology of the host and parasite, their host–parasite relationship, and known host movement patterns. This allowed us to quantify the effects of ticks on lizard movement above and beyond effects of other factors such as time in the activity season, lizard body condition, and stress. We did not find any support for our hypothesis. Instead, our results provide evidence that lizard movement is strongly driven by internal state (sex and body condition independent of tick load) and by external factors (environmental conditions). We suggest that the Sleepy Lizard has largely adapted to natural levels of tick infection in this system. Our results conform to host–parasite arms race theory, which predicts varying impacts of parasites on hosts in natural systems.