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.Pratha Sah, Michael Otterstatter, Stephan T. Leu, Sivan Leviyang, Shweta Bansa

Testing the robustness of transmission network models to predict ectoparasite loads. One lizard, two ticks and four years

We investigated transmission pathways for two tick species, Bothriocroton hydrosauri and Amblyomma limbatum, among their sleepy lizard (Tiliqua rugosa) hosts in a natural population in South Australia. Our aim was to determine whether a transmission network model continued to predict parasite load patterns effectively under varying ecological conditions. Using GPS loggers we identified the refuge sites used by each lizard on each day. We estimated infectious time windows for ticks that detached from a lizard in a refuge. Time windows were from the time when a detached tick molted and become infective, until the time it died from desiccation while waiting for a new host. Previous research has shown that A. limbatum molts earlier and survives longer than B. hydrosauri. We developed two transmission network models based on these differences in infective time windows for the two tick species. Directed edges were generated in the network if one lizard used a refuge that had previously been used by another lizard within the infectious time window. We used those models to generate values of network node in-strength for each lizard, a measure of how strongly connected an individual is to other lizards in the transmission network, and a prediction of infection risk for each host. The consistent correlations over time between B. hydrosauri infection intensity and network derived infection risk suggest that network models can be robust to environmental variation among years. However, the contrasting lack of consistent correlation in A. limbatum suggests that the utility of the same network models may depend on the specific biology of a parasite species

Where should we meet? Mapping social network interactions of sleepy lizards shows sex-dependent social network structure

Social network analyses allow researchers to describe patterns of social interactions and their consequences in animal societies. Since direct observations in natural settings are often difficult, researchers often use tracking technologies to build proximity-based social networks. However, because both social behaviour (e.g. conspecific attraction) and environmental heterogeneity (e.g. resources attracting individuals independently) affect rates of interaction, identifying the processes that shape social networks is challenging. We tracked sleepy lizards, Tiliqua rugosa, using global positioning system (GPS) telemetry to investigate whether they show conspecific attraction or avoidance beyond any shared space use driven by environmental heterogeneity. Since these lizards have strong pair bonds and nonoverlapping core home ranges, we predicted different interaction rates between inter- and intrasex dyads and compared social network indices among dyad types (maleemale, femaleefemale and intersex) using node-identity permutation tests.We also mapped interactions onto the home ranges (using distance from the centre as an index) and contrasted observed social networks with those expected from a spatially explicit null model. We found that dyad types differed in their interaction patterns. Intersex dyads had stronger connections (higher edge weight) than a null expectation, and stronger than for same-sex dyads. Samesex dyads did not differ in edge weight from the null expectation, but were significantly more common (higher degree). Males had larger home ranges than females and consequently maleemale dyads interacted further away from their home range centres. Moreover, the locations of these interactions also differed from the null expectations more strongly than other dyad types. Hence, we conclude that males predominantly interacted with each other at the peripheries of their home range, presumably reflecting territorial behaviour. By applying a novel analysis technique, we accounted for the nonsocial component of space use and revealed sex-specific interaction patterns and the contribution of conspecific attraction to the social structure in this species. More generally we report how mapping the locations of nonrandom interaction rates provides broad information on the behaviours they represent.Orr Spiegel, Andrew Sih, Stephan T. Leu, C. Michael Bul

Socially interacting or indifferent neighbours? Randomization of movement paths to tease apart social preference and spatial constraints

Understanding how animals interact with their physical and social environment is a major question in ecology, but separating between these factors is often challenging. Observed interaction rates may reflect social behaviour – preferences or avoidance of conspecifics or certain phenotypes. Yet, environmental spatiotemporal heterogeneity also affects individual space use and interaction rates. For instance, clumped and ephemeral resources may force individuals to aggregate independently of sociality. Proximity‐based social networks (PBSNs) are becoming increasingly popular for studying social structures thanks to the parallel improvement of biotracking technologies and network randomization methods. While current methods focus on swapping individual identities among network nodes or in the data streams that underlies the network (e.g. individuals movement paths), we still need better tools to distinguish between the contribution of sociality and other factors towards those interactions. We propose a novel method that randomizes path segments among different time stamps within each individual separately (Part I). Temporal randomization of whole path segments (e.g. full days) retains their original spatial structure while decoupling synchronization among individuals. This allows researchers to compare observed dyadic association rates with those expected by chance given explicit space use of the individuals in each dyad. Further, since environmental changes are commonly much slower than the duration of social interactions, we can differentiate between these two factors (Part II). First, an individual's path is divided into successive time windows (e.g. weeks), and days are randomized within each time window. Then, by exploring how the deviations between randomized and observed networks change as a function of time window length, we can refine our null model to account also for temporal changes in the activity areas. We used biased‐correlated random walk models to simulate populations of socially indifferent or sociable agents for testing our method for both false‐positive and negative errors. Applying the method to a data set of GPS‐tracked sleepy lizards (Tiliqua rugosa) demonstrated its ability to reveal the social organization in free‐ranging animals while accounting for confounding factors of environmental spatiotemporal heterogeneity. We demonstrate that this method is robust to sampling bias and argue that it is applicable for a wide range of systems and tracking techniques, and can be extended to test for preferential phenotypic assortment within PBSNs.Orr Spiegel, Stephan T. Leu, Andrew Sih, C. Michael Bul

When the going gets tough: behavioural type-dependent space use in the sleepy lizard changes as the season dries

Understanding space use remains a major challenge for animal ecology, with implications for species interactions, disease spread, and conservation. Behavioural type (BT) may shape the space use of individuals within animal populations. Bolder or more aggressive individuals tend to be more exploratory and disperse further. Yet, to date we have limited knowledge on how space use other than dispersal depends on BT. To address this question we studied BT-dependent space-use patterns of sleepy lizards (Tiliqua rugosa) in southern Australia. We combined high-resolution global positioning system (GPS) tracking of 72 free-ranging lizards with repeated behavioural assays, and with a survey of the spatial distributions of their food and refuge resources. Bayesian generalized linear mixed models (GLMM) showed that lizards responded to the spatial distribution of resources at the neighbourhood scale and to the intensity of space use by other conspecifics (showing apparent conspecific avoidance). BT (especially aggressiveness) affected space use by lizards and their response to ecological and social factors, in a seasonally dependent manner. Many of these effects and interactions were stronger later in the season when food became scarce and environmental conditions got tougher. For example, refuge and food availability became more important later in the season and unaggressive lizards were more responsive to these predictors. These findings highlight a commonly overlooked source of heterogeneity in animal space use and improve our mechanistic understanding of processes leading to behaviourally driven disease dynamics and social structure

Spatial proximity and asynchronous refuge sharing networks both explain patterns of tick genetic relatedness among lizards, but in different years

A major question for understanding the ecology of parasite infections and diseases in wildlife populations concerns the transmission pathways among hosts. Network models are increasingly used to model the transmission of infections among hosts – however, few studies have integrated host behaviour and genetic relatedness of the parasites transmitted between hosts. In a study of the Australian sleepy lizard Tiliqua rugosa and its three‐host ixodid tick (Bothriocroton hydrosauri ), we asked if patterns of genetic relatedness among ticks were best explained by spatial proximity or the host transmission network. Using synchronous GPS locations of over 50 adult lizards at 10 min intervals across the three‐month activity period, over 2 years, we developed two alternative parasite transmission networks. One alternative was based on the spatial proximity of lizards (at the centre of their home ranges), and the other was based on the frequency of asynchronous shared refuge use between pairs of lizards. In each year, adult ticks were removed from lizards and their genotypes were determined at four polymorphic microsatellite loci. Adult ticks collected from the same host were more related to each other than ticks from different hosts. Similarly, adult ticks collected from different lizards had a higher relatedness if those lizards had a shorter path length connecting them on each of the two networks we explored. The predictors of tick relatedness differed between years. In the first year, the asynchronous shared refuges network was the stronger predictor of tick relatedness, whereas in year two, the spatial proximity‐based network was the stronger predictor of tick relatedness. We speculate on how changing environmental conditions might change the relative importance of alternative processes driving the transmission of parasites.Caroline K. Wohlfeil, Stephanie S. Godfrey, Stephan T. Leu, Jessica Clayton and Michael G. Gardne

Technologies for the automated collection of heat stress data in sheep

The automated collection of phenotypic measurements in livestock is becoming increasingly important to both researchers and farmers. The capacity to non-invasively collect real-time data, provides the opportunity to better understand livestock behaviour and physiology and improve animal management decisions. Current climate models project that temperatures will increase across the world, influencing both local and global agriculture. Sheep that are exposed to high ambient temperatures experience heat stress and their physiology, reproductive function and performance are compromised. Body temperature is a reliable measure of heat stress and hence a good indicator of an animals’ health and well-being. Non-invasive temperature-sensing technologies have made substantial progress over the past decade. Here, we review the different technologies available and assess their suitability for inferring ovine heat stress. Specifically, the use of indwelling probes, intra-ruminal bolus insertion, thermal imaging and implantable devices are investigated. We further evaluate the capacity of behavioural tracking technology, such as global positioning systems, to identify heat stressed individuals based on the exhibition of specific behaviours. Although there are challenges associated with using real-time thermosensing data to make informed management decisions, these technologies provide new opportunities to manage heat stress in sheep. In order to obtain accurate real-time information of individual animals and facilitate prompt intervention, data collection should be entirely automated. Additionally, for accurate interpretation on-farm, the development of software which can effectively collect, manage and integrate data for sheep producer’s needs to be prioritised. Lastly, understanding known physiological thresholds will allow farmers to determine individual heat stress risk and facilitate early intervention to reduce the effects in both current and subsequent generations.Bobbie E. Lewis Baida, Alyce M. Swinbourne, Jamie Barwick, Stephan T. Leu and William H.E.J. van Wetter

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.Patrick L. Taggart, Stephan T. Leu, Orr Spiegel, Stephanie S. Godfrey, Andrew Sih, and C. Michael Bul

Why is social behavior rare in Reptiles? Lessons From Sleepy Lizards

We report on 35. years of research into behavior and ecology of the Australian sleepy lizard, Tiliqua rugosa. We describe the unusually long monogamous pairing period in this lizard before mating takes place each spring, and the long-term persistence of mating pairs, reforming each spring for up to 27. years. We review hypotheses, observations, and experiments and conclude that females drive the pairing, becoming more receptive to males that have provided prolonged attention, because of the advantages they gain through greater awareness of approaching danger. We suggest that long-term pair fidelity has resulted from a higher reproductive efficiency between familiar partners. We then consider the broader social network structure in the sleepy lizard population, suggesting from our analyses that lizards make more contacts with their neighbors, sometimes agonistically, than if they were moving at random. There are few kin-based associations in the networks, but lizards with different personality types have different network positions. The broad social structure of the population is robust to ecological and environmental changes, although various network parameters are adjusted with different climate or habitat conditions. The overall social structure of the sleepy lizard population has an important role in transmission of parasites and pathogens. Finally we consider why this species is one of the very few reptiles for which stable social living has been reported. This may be because reptile social living is relatively under studied. Alternatively, we suggest, many reptile species may be constrained from evolving social structures, because they lack either the necessary cognitive ability or a strong defense against the high risk of pathogen transmission that comes from social living

Gastrointestinal nematode infection affects overall activity in young sheep monitored with tri-axial accelerometers

Animals suffering from parasitism typically display altered grazing behaviour and a voluntary reduction in feed intake. These changes are potentially important as indicators of disease. Recent advances in sensor technologies provide the opportunity to objectively measure animal activity while on pasture. Tri-axial accelerometers measure body movement in terms of acceleration, which can then be used to estimate physical activity over time. This study investigated if tri-axial measures of overall activity can be used to assess the impact of gastrointestinal nematode (GIN) infection in young sheep. To address this, the overall activity, faecal nematode egg count (FEC) and body weight of two treatment groups of Romney X Suffolk ram lambs were compared. Animals were monitored for four days using tri-axial accelerometer sensors mounted on a ram mating harness after 42-days grazing on contaminated pasture. On Day 0, all lambs were given anthelmintics. Subsequently, a Suppressive Treatment Group (n = 12) was treated with anthelmintics every two weeks. An Untreated Group (n = 12) did not receive further anthelmintics. Overall activity levels were monitored from Day 42 – 46. Activity level was calculated as vectorial dynamic body acceleration (VeDBA). Anthelmintic treatment had a significant effect on FEC but there was no evidence found for a treatment effect on body weight growth over the 42-day period. An effect of treatment and lamb starting weight on overall activity was found (beta = –0.74, 95 % CI –1.17 to –0.30, p =  0.002), identifying a negative impact of parasitism on activity in heavier animals. These results highlight the usefulness of this approach in assessing the effect of GIN parasitism on sheep monitored remotely. If a threshold value of activity could be determined, it could provide a useful tool for farmers and managers that serves as an early indicator of parasitism in sheep.Seer J.Ikurior, William E.Pomroy, Ian Scott, Rene Corner-Thomas, Nelly Marquetoux, Stephan T.Le