Raccoon contact networks predict seasonal susceptibility to rabies outbreaks and limitations of vaccination.

Infectious disease transmission often depends on the contact structure of host populations. Although it is often challenging to capture the contact structure in wild animals, new technology has enabled biologists to obtain detailed temporal information on wildlife social contacts. In this study, we investigated the effects of raccoon contact patterns on rabies spread using network modelling. Raccoons (Procyon lotor) play an important role in the maintenance of rabies in the United States. It is crucial to understand how contact patterns influence the spread of rabies in raccoon populations in order to design effective control measures and to prevent transmission to human populations and other animals. We constructed a dynamic system of contact networks based on empirical data from proximity logging collars on a wild suburban raccoon population and then simulated rabies spread across these networks. Our contact networks incorporated the number and duration of raccoon interactions. We included differences in contacts according to sex and season, and both short-term acquaintances and long-term associations. Raccoons may display different behaviours when infectious, including aggression (furious behaviour) and impaired mobility (dumb behaviour); the network model was used to assess the impact of potential behavioural changes in rabid raccoons. We also tested the effectiveness of different vaccination coverage levels. Our results demonstrate that when rabies enters a suburban raccoon population, the likelihood of a disease outbreak affecting the majority of the population is high. Both the magnitude of rabies outbreaks and the speed of rabies spread depend strongly on the time of year that rabies is introduced into the population. When there is a combination of dumb and furious behaviours in the rabid raccoon population, there are similar outbreak sizes and speed of spread to when there are no behavioural changes due to rabies infection. By incorporating detailed data describing the variation in raccoon contact rates into a network modelling approach, we were able to show that suburban raccoon populations are highly susceptible to rabies outbreaks, that the risk of large outbreaks varies seasonally and that current vaccination target levels may be inadequate to prevent the spread of rabies within these populations. Our findings provide new insights into rabies dynamics in raccoon populations and have important implications for disease control.

Delayed induced silica defences in grasses and their potential for destabilising herbivore population dynamics.

Some grass species mount a defensive response to grazing by increasing their rate of uptake of silica from the soil and depositing it as abrasive granules in their leaves. Increased plant silica levels reduce food quality for herbivores that feed on these grasses. Here we provide empirical evidence that a principal food species of an herbivorous rodent exhibits a delayed defensive response to grazing by increasing silica concentrations, and present theoretical modelling that predicts that such a response alone could lead to the population cycles observed in some herbivore populations. Experiments performed under greenhouse conditions revealed that the rate of deposition of silica defences in the grass Deschampsia caespitosa is a time-lagged, nonlinear function of grazing intensity and that, upon cessation of grazing, these defences take around one year to decay to within 5 % of control levels. Simple coupled grass-herbivore population models incorporating this functional response, and parameterised with empirical data, consistently predict population cycles for a wide range of realistic parameter values for a (Microtus) vole-grass system. Our results support the hypothesis that induced silica defences have the potential to strongly affect the population dynamics of their herbivores. Specifically, the feedback response we observed could be a driving mechanism behind the observed population cycles in graminivorous herbivores in cases where grazing levels in the field become sufficiently large and sustained to trigger an induced silica defence response.

The population dynamical consequences of density-dependent prophylaxis.

When infectious disease transmission is density-dependent, the risk of infection will tend to increase with host population density. Since host defence mechanisms can be costly, individual hosts may benefit from increasing their investment in immunity in response to increasing population density. Such "density-dependent prophylaxis" (DDP) has now indeed been demonstrated experimentally in several species. However, it remains unclear how DDP will affect the population dynamics of the host-pathogen interaction, with previous theoretical work making conflicting predictions. We develop a general host-pathogen model and assess the role of DDP on the population dynamics. The ability of DDP to drive population cycles is critically dependent on the time delay between the change in density and the subsequent phenotypic change in the level of resistance. When the delay is absent or short, DDP destabilises the system. As the delay increases, its destabilising effect first diminishes and then DDP becomes increasingly stabilising. Our work highlights the significance of the time delay and suggests that it must be estimated experimentally or varied in theoretical investigations in order to understand the implications of DDP for the population dynamics of particular systems.

Feline immunodeficiency virus in puma: Estimation of force of infection reveals insights into transmission.

Determining parameters that govern pathogen transmission (such as the force of infection, FOI), and pathogen impacts on morbidity and mortality, is exceptionally challenging for wildlife. Vital parameters can vary, for example across host populations, between sexes and within an individual's lifetime.Feline immunodeficiency virus (FIV) is a lentivirus affecting domestic and wild cat species, forming species-specific viral-host associations. FIV infection is common in populations of puma (Puma concolor), yet uncertainty remains over transmission parameters and the significance of FIV infection for puma mortality. In this study, the age-specific FOI of FIV in pumas was estimated from prevalence data, and the evidence for disease-associated mortality was assessed.We fitted candidate models to FIV prevalence data and adopted a maximum likelihood method to estimate parameter values in each model. The models with the best fit were determined to infer the most likely FOI curves. We applied this strategy for female and male pumas from California, Colorado, and Florida.When splitting the data by sex and area, our FOI modeling revealed no evidence of disease-associated mortality in any population. Both sex and location were found to influence the FOI, which was generally higher for male pumas than for females. For female pumas at all sites, and male pumas from California and Colorado, the FOI did not vary with puma age, implying FIV transmission can happen throughout life; this result supports the idea that transmission can occur from mothers to cubs and also throughout adult life. For Florida males, the FOI was a decreasing function of puma age, indicating an increased risk of infection in the early years, and a decreased risk at older ages.This research provides critical insight into pathogen transmission and impact in a secretive and solitary carnivore. Our findings shed light on the debate on whether FIV causes mortality in wild felids like puma, and our approach may be adopted for other diseases and species. The methodology we present can be used for identifying likely transmission routes of a pathogen and also estimating any disease-associated mortality, both of which can be difficult to establish for wildlife diseases in particular.

Mathematical modeling of influenza A virus dynamics within swine farms and the effects of vaccination.

Influenza A virus infections are widespread in swine herds across the world. Influenza negatively affects swine health and production, and represents a significant threat to public health due to the risk of zoonotic infections. Swine herds can act as reservoirs for potentially pandemic influenza strains. In this study, we develop mathematical models based on experimental data, representing typical breeding and wean-to-finish swine farms. These models are used to explore and describe the dynamics of influenza infection at the farm level, which are at present not well understood. In addition, we use the models to assess the effectiveness of vaccination strategies currently employed by swine producers, testing both homologous and heterologous vaccines. An important finding is that following an influenza outbreak in a breeding herd, our model predicts a persistently high level of infectious piglets. Sensitivity analysis indicates that this finding is robust to changes in both transmission rates and farm size. Vaccination does not eliminate influenza throughout the breeding farm population. In the wean-to-finish herd, influenza infection may persist in the population only if recovered individuals become susceptible to infection again. A homologous vaccine administered to the entire wean-to-finish population after the loss of maternal antibodies eliminates influenza, but a vaccine that only induces partial protection (heterologous vaccine) has little effect on influenza infection levels. Our results have important implications for the control of influenza in swine herds, which is crucial in order to reduce both losses for swine producers and the risk to public health.