Seasonal,demographic and density‐related patterns of contact between Tasmanian devils (Sarcophilus harrisii): Implications for transmission of devil facial tumour disease

Abstract Devil facial tumour disease (DFTD), is an emerging infectious cancer thought to be spread by biting. It is causing ongoing, severe population decline of the Tasmanian devil (Sarcophilus harrisii), the largest surviving marsupial carnivore and there are concerns that DFTD may lead to extinction of the devil. Whether extinction is likely depends on contact rates and their relationship to host density. We investigated contact rates using two different datasets. The first consisted of field observations of contact and biting behaviour around prey carcasses and, the second was a 3‐year longitudinal series of injuries in a marked devil population. During feeding interactions at carcasses, contact rates were significantly positively associated with population density and subadults delivered more bites than adult males and females. Injuries from the marked devil population did not differ between adult males and females. In two of the three years, penetrating biting (resulting in injury) increased markedly during the mating season and was more frequent in adults than in subadults. Among injured devils with wounds penetrating the dermal layer, adults were more frequently bitten in the head (the location of primary tumours) in the mating season than in other seasons, and had more head bites than subadults. Our results suggest that the mating season may be the key period for disease transmission. If most penetrating bites occur during mating interactions, DFTD transmission is likely to be frequency dependent, which means that there would be no threshold host density for disease persistence, and disease‐induced extinction is possible.     

Infectious disease and sickness behaviour: tumour progression affects interaction patterns and social network structure in wild Tasmanian devils

Infectious diseases, including transmissible cancers, can have a broad range of impacts on host behaviour, particularly in the latter stages of disease progression. However, the difficulty of early diagnoses makes the study of behavioural influences of disease in wild animals a challenging task. Tasmanian devils (Sarcophilus harrisii) are affected by a transmissible cancer, devil facial tumour disease (DFTD), in which tumours are externally visible as they progress. Using telemetry and mark–recapture datasets, we quantify the impacts of cancer progression on the behaviour of wild devils by assessing how interaction patterns within the social network of a population change with increasing tumour load. The progression of DFTD negatively influences devils'' likelihood of interaction within their network. Infected devils were more active within their network late in the mating season, a pattern with repercussions for DFTD transmission. Our study provides a rare opportunity to quantify and understand the behavioural feedbacks of disease in wildlife and how they may affect transmission and population dynamics in general.     

Infection of the fittest: devil facial tumour disease has greatest effect on individuals with highest reproductive output

Emerging infectious diseases rarely affect all members of a population equally and determining how individuals’ susceptibility to infection is related to other components of their fitness is critical to understanding disease impacts at a population level and for predicting evolutionary trajectories. We introduce a novel state‐space model framework to investigate survival and fecundity of Tasmanian devils (Sarcophilus harrisii) affected by a transmissible cancer, devil facial tumour disease. We show that those devils that become host to tumours have otherwise greater fitness, with higher survival and fecundity rates prior to disease‐induced death than non‐host individuals that do not become infected, although high tumour loads lead to high mortality. Our finding that individuals with the greatest reproductive value are those most affected by the cancer demonstrates the need to quantify both survival and fecundity in context of disease progression for understanding the impact of disease on wildlife populations.     

Longitudinal monitoring of plasma and fecal androgens in the Tasmanian devil (Sarcophilus harrisii) and the spotted-tailed quoll (Dasyurus maculatus)

Improved knowledge of the breeding biology of carnivorous marsupials is warranted given their heightened conservation status. Past studies have focused on smaller dasyurids and little is known of male reproductive physiology in the larger species. This study aimed to characterize the pattern of androgen concentrations in male devils and spotted-tailed quolls and to evaluate fecal steroid measurement as a practical, alternative technique for monitoring reproductive activity. Blood and fecal samples were collected from captive adult devils (n=6) and adult quolls (n=8). Plasma and fecal androgen concentrations were significantly positively correlated. In both species there was a significant effect of season on androgen concentrations; and the annual increase preceded female estrus activity. For devils, fecal androgens were elevated during the austral summer: peak concentrations were observed in January-February, and copulation occurred from late February-late May. In quolls, fecal androgen concentrations were highest during austral autumn/winter: the annual increase began in April and copulation occurred from mid-May to early October. The lengthy period of elevated plasma and fecal androgens and protracted annual period of mating activity implies a period of extended spermatogenesis in both species.     

Scent of a Woman – The Effect of Female Presence on Sexual Cannibalism in an Orb-Weaving Spider (Araneae: Araneidae)

Post-mating sexual cannibalism occurs as a regular element of mating behaviour in a number of spider species. Frequencies of cannibalism, however, are highly variable between and within species. In Argiope bruennichi , males apparently differ in their motivation to escape a female attack but causes for this variability are unknown. We observed that the probability of sexual cannibalism is positively correlated with male age, i.e. the number of days that passed between male maturation and copulation. The mating season in this species is short with 3–4 wk and males mostly mature days before the females, whose maturation phase is longer. Consequently, as the season progresses, the availability of virgin females increases, quickly reaches a peak and then rapidly declines. In addition, the age of still unmated males increases with the season and both of these factors can potentially affect the degree of sexual cannibalism. To separate these factors, males were collected in their penultimate stage and kept until mating either with or without contact to female pheromones. Thereby, we experimentally manipulated the male's perception of female presence. Within each treatment, we formed three male age groups: (1) 2–6 d, (2) 12–16 d and (3) 22–28 d. Our results demonstrate that the probability of cannibalism was independent of male age but was explained by the treatment of males: males exposed to virgin female pheromones were significantly more likely to be cannibalised than males that were kept without female pheromones. This suggests that males change their reproductive strategy according to perceived mating prospects.     

Genomics for conservation: a case study of behavioral genes in the Tasmanian devil

The increased availability of genomic resources for many species has expanded perspectives on problems in conservation by helping to design management strategies for threatened species. Tasmanian devils (Sarcophilus harrisii) are an iconic and endangered marsupial with an intensively managed breeding program aimed at preventing extinction in the wild caused by devil facial tumour disease. Between 2015 and 2017, 85 devils from this program were released to three sites in Tasmania to support wild populations. Of these, 26 were known to have been killed by vehicles shortly after release. A previous analysis indicated that increased generations in captivity was a positive predictor of vehicle strike, with possible behavioural change hypothesised. Here we use 39 resequenced devil genomes to characterise diversity at 35 behaviour-associated genes, which contained 826 single nucleotide polymorphisms (24 were non-synonymous). We tested for a predictor of survival by examining three genes (AVPR1B, OXT and SLC6A4) in 62 released devils with known fates (survived, N?=?39; died, N?=?23), and genome-wide associations via reduced-representation sequencing (1727 single nucleotide polymorphisms [SNPs]), in 55 devils with known fates (survived, N?=?38; died, N?=?17). Overall, there was little evidence of an association between genetic profile and probability of being struck by a vehicle. Despite previous evidence of low genetic diversity in devils, the 35 behaviour-associated genes contained variation that may influence their functions. Our dataset can be used for future research into devil behavioural ecology, and adds to the increasing body of research applying genomics to conservation problems.

     

Network frailty and the geometry of herd immunity

The spread of infectious disease through communities depends fundamentally on the underlying patterns of contacts between individuals. Generally, the more contacts one individual has, the more vulnerable they are to infection during an epidemic. Thus, outbreaks disproportionately impact the most highly connected demographics. Epidemics can then lead, through immunization or removal of individuals, to sparser networks that are more resistant to future transmission of a given disease. Using several classes of contact networks-Poisson, scale-free and small-world-we characterize the structural evolution of a network due to an epidemic in terms of frailty (the degree to which highly connected individuals are more vulnerable to infection) and interference (the extent to which the epidemic cuts off connectivity among the susceptible population that remains following an epidemic). The evolution of the susceptible network over the course of an epidemic differs among the classes of networks; frailty, relative to interference, accounts for an increasing component of network evolution on networks with greater variance in contacts. The result is that immunization due to prior epidemics can provide greater community protection than random vaccination on networks with heterogeneous contact patterns, while the reverse is true for highly structured populations.     

Natural killer cell mediated cytotoxic responses in the Tasmanian devil

The Tasmanian devil (Sarcophilus harrisii), the world's largest marsupial carnivore, is under threat of extinction following the emergence of an infectious cancer. Devil facial tumour disease (DFTD) is spread between Tasmanian devils during biting. The disease is consistently fatal and devils succumb without developing a protective immune response. The aim of this study was to determine if Tasmanian devils were capable of forming cytotoxic antitumour responses and develop antibodies against DFTD cells and foreign tumour cells. The two Tasmanian devils immunised with irradiated DFTD cells did not form cytotoxic or humoral responses against DFTD cells, even after multiple immunisations. However, following immunisation with xenogenic K562 cells, devils did produce cytotoxic responses and antibodies against this foreign tumour cell line. The cytotoxicity appeared to occur through the activity of natural killer (NK) cells in an antibody dependent manner. Classical NK cell responses, such as innate killing of DFTD and foreign cancer cells, were not observed. Cells with an NK-like phenotype comprised approximately 4 percent of peripheral blood mononuclear cells. The results of this study suggest that Tasmanian devils have NK cells with functional cytotoxic pathways. Although devil NK cells do not directly recognise DFTD cancer cells, the development of antibody dependent cell-mediated cytotoxicity presents a potential pathway to induce cytotoxic responses against the disease. These findings have positive implications for future DFTD vaccine research.     

Dynamics and Control of Diseases in Networks with Community Structure

The dynamics of infectious diseases spread via direct person-to-person transmission (such as influenza, smallpox, HIV/AIDS, etc.) depends on the underlying host contact network. Human contact networks exhibit strong community structure. Understanding how such community structure affects epidemics may provide insights for preventing the spread of disease between communities by changing the structure of the contact network through pharmaceutical or non-pharmaceutical interventions. We use empirical and simulated networks to investigate the spread of disease in networks with community structure. We find that community structure has a major impact on disease dynamics, and we show that in networks with strong community structure, immunization interventions targeted at individuals bridging communities are more effective than those simply targeting highly connected individuals. Because the structure of relevant contact networks is generally not known, and vaccine supply is often limited, there is great need for efficient vaccination algorithms that do not require full knowledge of the network. We developed an algorithm that acts only on locally available network information and is able to quickly identify targets for successful immunization intervention. The algorithm generally outperforms existing algorithms when vaccine supply is limited, particularly in networks with strong community structure. Understanding the spread of infectious diseases and designing optimal control strategies is a major goal of public health. Social networks show marked patterns of community structure, and our results, based on empirical and simulated data, demonstrate that community structure strongly affects disease dynamics. These results have implications for the design of control strategies.     

Infectious disease transmission and contact networks in wildlife and livestock

The use of social and contact networks to answer basic and applied questions about infectious disease transmission in wildlife and livestock is receiving increased attention. Through social network analysis, we understand that wild animal and livestock populations, including farmed fish and poultry, often have a heterogeneous contact structure owing to social structure or trade networks. Network modelling is a flexible tool used to capture the heterogeneous contacts of a population in order to test hypotheses about the mechanisms of disease transmission, simulate and predict disease spread, and test disease control strategies. This review highlights how to use animal contact data, including social networks, for network modelling, and emphasizes that researchers should have a pathogen of interest in mind before collecting or using contact data. This paper describes the rising popularity of network approaches for understanding transmission dynamics in wild animal and livestock populations; discusses the common mismatch between contact networks as measured in animal behaviour and relevant parasites to match those networks; and highlights knowledge gaps in how to collect and analyse contact data. Opportunities for the future include increased attention to experiments, pathogen genetic markers and novel computational tools.     

Isotopic niche variation in Tasmanian devils Sarcophilus harrisii with progression of devil facial tumor disease

Devil facial tumor disease (DFTD) is a transmissible cancer affecting Tasmanian devils Sarcophilus harrisii. The disease has caused severe population declines and is associated with demographic and behavioral changes, including earlier breeding, younger age structures, and reduced dispersal and social interactions. Devils are generally solitary, but social encounters are commonplace when feeding upon large carcasses. DFTD tumors can disfigure the jaw and mouth and so diseased individuals might alter their diets to enable ingestion of alternative foods, to avoid conspecific interactions, or to reduce competition. Using stable isotope analysis (δ¹³C and δ¹⁵N) of whiskers, we tested whether DFTD progression, measured as tumor volume, affected the isotope ratios and isotopic niches of 94 infected Tasmanian devils from six sites in Tasmania, comprising four eucalypt plantations, an area of smallholdings and a national park. Then, using tissue from 10 devils sampled before and after detection of tumors and 8 devils where no tumors were detected, we examined whether mean and standard deviation of δ¹³C and δ¹⁵N of the same individuals changed between healthy and diseased states. δ¹³C and δ¹⁵N values were generally not related to tumor volume in infected devils, though at one site, Freycinet National Park, δ¹⁵N values increased significantly as tumor volume increased. Infection with DFTD was not associated with significant changes in the mean or standard deviation of δ¹³C and δ¹⁵N values in individual devils sampled before and after detection of tumors. Our analysis suggests that devils tend to maintain their isotopic niche in the face of DFTD infection and progression, except where ecological conditions facilitate a shift in diets and feeding behaviors, demonstrating that ecological context, alongside disease severity, can modulate the behavioral responses of Tasmanian devils to DFTD.     

Lack of genetic diversity across diverse immune genes in an endangered mammal,the Tasmanian devil (Sarcophilus harrisii)

The Tasmanian devil (Sarcophilus harrisii) is threatened with extinction due to the spread of devil facial tumour disease. Polymorphisms in immune genes can provide adaptive potential to resist diseases. Previous studies in diversity at immune loci in wild species have almost exclusively focused on genes of the major histocompatibility complex (MHC); however, these genes only account for a fraction of immune gene diversity. Devils lack diversity at functionally important immunity loci, including MHC and Toll‐like receptor genes. Whether there are polymorphisms at devil immune genes outside these two families is unknown. Here, we identify polymorphisms in a wide range of key immune genes, and develop assays to type single nucleotide polymorphisms (SNPs) within a subset of these genes. A total of 167 immune genes were examined, including cytokines, chemokines and natural killer cell receptors. Using genome‐level data from ten devils, SNPs within coding regions, introns and 10 kb flanking genes of interest were identified. We found low polymorphism across 167 immune genes examined bioinformatically using whole‐genome data. From this data, we developed long amplicon assays to target nine genes. These amplicons were sequenced in 29–220 devils and found to contain 78 SNPs, including eight SNPS within exons. Despite the extreme paucity of genetic diversity within these genes, signatures of balancing selection were exhibited by one chemokine gene, suggesting that remaining diversity may hold adaptive potential. The low functional diversity may leave devils highly vulnerable to infectious disease, and therefore, monitoring and preserving remaining diversity will be critical for the long‐term management of this species. Examining genetic variation in diverse immune genes should be a priority for threatened wildlife species. This study can act as a model for broad‐scale immunogenetic diversity analysis in threatened species.     

Revealing mechanisms of infectious disease spread through empirical contact networks

The spread of pathogens fundamentally depends on the underlying contacts between individuals. Modeling the dynamics of infectious disease spread through contact networks, however, can be challenging due to limited knowledge of how an infectious disease spreads and its transmission rate. We developed a novel statistical tool, INoDS (Identifying contact Networks of infectious Disease Spread) that estimates the transmission rate of an infectious disease outbreak, establishes epidemiological relevance of a contact network in explaining the observed pattern of infectious disease spread and enables model comparison between different contact network hypotheses. We show that our tool is robust to incomplete data and can be easily applied to datasets where infection timings of individuals are unknown. We tested the reliability of INoDS using simulation experiments of disease spread on a synthetic contact network and find that it is robust to incomplete data and is reliable under different settings of network dynamics and disease contagiousness compared with previous approaches. We demonstrate the applicability of our method in two host-pathogen systems: Crithidia bombi in bumblebee colonies and Salmonella in wild Australian sleepy lizard populations. INoDS thus provides a novel and reliable statistical tool for identifying transmission pathways of infectious disease spread. In addition, application of INoDS extends to understanding the spread of novel or emerging infectious disease, an alternative approach to laboratory transmission experiments, and overcoming common data-collection constraints.     

Patterns of genetic variation in populations of infectious agents

Background  

The analysis of genetic variation in populations of infectious agents may help us understand their epidemiology and evolution. Here we study a model for assessing the levels and patterns of genetic diversity in populations of infectious agents. The population is structured into many small subpopulations, which correspond to their hosts, that are connected according to a specific type of contact network. We considered different types of networks, including fully connected networks and scale free networks, which have been considered as a model that captures some properties of real contact networks. Infectious agents transmit between hosts, through migration, where they grow and mutate until elimination by the host immune system.     

Disease evolution on networks: the role of contact structure

Owing to their rapid reproductive rate and the severe penalties for reduced fitness, diseases are under immense evolutionary pressure. Understanding the evolutionary response of diseases in new situations has clear public-health consequences, given the changes in social and movement patterns over recent decades and the increased use of antibiotics. This paper investigates how a disease may adapt in response to the routes of transmission available between infected and susceptible individuals. The potential transmission routes are defined by a computer-generated contact network, which we describe as either local (highly clustered networks where connected individuals are likely to share common contacts) or global (unclustered networks with a high proportion of long-range connections). Evolution towards stable strategies operates through the gradual random mutation of disease traits (transmission rate and infectious period) whenever new infections occur. In contrast to mean-field models, the use of contact networks greatly constrains the evolutionary dynamics. In the local networks, high transmission rates are selected for, as there is intense competition for susceptible hosts between disease progeny. By contrast, global networks select for moderate transmission rates because direct competition between progeny is minimal and a premium is placed upon persistence. All networks show a very slow but steady rise in the infectious period.     

Brown spider monkeys (Ateles hybridus): a model for differentiating the role of social networks and physical contact on parasite transmission dynamics

Elevated risk of disease transmission is considered a major cost of sociality, although empirical evidence supporting this idea remains scant. Variation in spatial cohesion and the occurrence of social interactions may have profound implications for patterns of interindividual parasite transmission. We used a social network approach to shed light on the importance of different aspects of group-living (i.e. within-group associations versus physical contact) on patterns of parasitism in a neotropical primate, the brown spider monkey (Ateles hybridus), which exhibits a high degree of fission–fusion subgrouping. We used daily subgroup composition records to create a ‘proximity’ network, and built a separate ‘contact’ network using social interactions involving physical contact. In the proximity network, connectivity between individuals was homogeneous, whereas the contact network highlighted high between-individual variation in the extent to which animals had physical contact with others, which correlated with an individual''s age and sex. The gastrointestinal parasite species richness of highly connected individuals was greater than that of less connected individuals in the contact network, but not in the proximity network. Our findings suggest that among brown spider monkeys, physical contact impacts the spread of several common parasites and supports the idea that pathogen transmission is one cost associated with social contact.     

Limited male dispersal in a social spider with extreme inbreeding

Cooperatively breeding animals commonly avoid incestuous mating through pre-mating dispersal. However, a few group-living organisms, including the social spiders, have low pre-mating dispersal, intra-colony mating, and inbreeding. This results in limited gene flow among colonies and sub-structured populations. The social spiders also exhibit female-biased sex ratios because survival benefits to large colonies favour high group productivity, which selects against 1 : 1 sex ratios. Although propagule dispersal of mated females may occasionally bring about limited gene flow, little is known about the role of male dispersal. We assessed the extent of male movement between colonies in natural populations both experimentally and by studying colony sex ratios over the mating season. We show that males frequently move to neighbouring colonies, whereas only 4% of incipient nests were visited by dispersing males. Neighbouring colonies are genetically similar and movement within colony clusters does not contribute to gene flow. Post-mating sex ratio bias was high early in the mating season due to protandry, and also in colonies at the end of the season, suggesting that males remain in the colony when mated females have dispersed. Thus, male dispersal is unlikely to facilitate gene flow between different matrilineages. This is consistent with models of non-Fisherian group-level selection for the maintenance of female biased sex ratios, which predict the elimination of male dispersal.  © 2009 The Linnean Society of London, Biological Journal of the Linnean Society 2009, 97 , 227–234.     

Conservation Management of Tasmanian Devils in the Context of an Emerging, Extinction-threatening Disease: Devil Facial Tumor Disease

An emerging infectious facial cancer threatens Tasmanian devils with extinction. The disease is likely to occur across the range of the devil within 5 years. This urgent time frame requires management options that can be implemented immediately: the establishment of insurance populations, in captivity, wild-living on islands, and aiming for eradication in areas that can be isolated. The long-term options of the spontaneous or assisted evolution of resistance or development of a field-deliverable vaccine are unlikely to be available in time. The disease’s characteristic allograft transmission through intimate contact simplifies isolation of insurance populations and breaking transmission in suppression trials. Better knowledge of contact matrices in wild devils will help focus timing and demographic targets of removals. A metapopulation approach is needed that integrates captive and wild-living island and peninsula (disease suppression) populations to minimize the loss of genetic diversity over 50 years until either extinction and reintroduction can occur, resistance evolves or a field-deliverable vaccine is developed. Given the importance of the insurance populations and the low genetic diversity of devils, a conservative target for retention of 95% genetic diversity is recommended. Encouraging preliminary results of the first disease-suppression trial on a large peninsula show fewer late stage tumors and no apparent population decline. Limiting geographic spread or suppressing the disease on a broadscale are both unlikely to be feasible. Since the synergy of devil decline and impending fox establishment could have devastating consequences for Tasmanian wildlife, it is crucial to manage the dynamics of new and old predator species together.     

Relaxation of risk-sensitive behaviour of prey following disease-induced decline of an apex predator,the Tasmanian devil

Apex predators structure ecosystems through lethal and non-lethal interactions with prey, and their global decline is causing loss of ecological function. Behavioural changes of prey are some of the most rapid responses to predator decline and may act as an early indicator of cascading effects. The Tasmanian devil (Sarcophilus harrisii), an apex predator, is undergoing progressive and extensive population decline, of more than 90% in long-diseased areas, caused by a novel disease. Time since local disease outbreak correlates with devil population declines and thus predation risk. We used hair traps and giving-up densities (GUDs) in food patches to test whether a major prey species of devils, the arboreal common brushtail possum (Trichosurus vulpecula), is responsive to the changing risk of predation when they forage on the ground. Possums spend more time on the ground, discover food patches faster and forage more to a lower GUD with increasing years since disease outbreak and greater devil population decline. Loss of top–down effects of devils with respect to predation risk was evident at 90% devil population decline, with possum behaviour indistinguishable from a devil-free island. Alternative predators may help to maintain risk-sensitive anti-predator behaviours in possums while devil populations remain low.     

The Impact of Contact Tracing in Clustered Populations

The tracing of potentially infectious contacts has become an important part of the control strategy for many infectious diseases, from early cases of novel infections to endemic sexually transmitted infections. Here, we make use of mathematical models to consider the case of partner notification for sexually transmitted infection, however these models are sufficiently simple to allow more general conclusions to be drawn. We show that, when contact network structure is considered in addition to contact tracing, standard “mass action” models are generally inadequate. To consider the impact of mutual contacts (specifically clustering) we develop an improvement to existing pairwise network models, which we use to demonstrate that ceteris paribus, clustering improves the efficacy of contact tracing for a large region of parameter space. This result is sometimes reversed, however, for the case of highly effective contact tracing. We also develop stochastic simulations for comparison, using simple re-wiring methods that allow the generation of appropriate comparator networks. In this way we contribute to the general theory of network-based interventions against infectious disease.