Contact and contagion: Probability of transmission given contact varies with demographic state in bighorn sheep

Pathology of Chronic Mycoplasma ovipneumoniae Carriers in a Declining Bighorn Sheep (Ovis canadensis) Population

Bighorn sheep (Ovis canadensis) across North America commonly experience population-limiting epizootics of respiratory disease. Although many cases of bighorn sheep pneumonia are polymicrobial, Mycoplasma ovipneumoniae is most frequently associated with all-age mortality events followed by years of low recruitment. Chronic carriage of M. ovipneumoniae by adult females serves as a source of exposure of naïve juveniles; relatively few ewes may be responsible for maintenance of infection within a herd. Test-and-remove strategies focused on removal of adult females with evidence of persistent or intermittent shedding (hereafter chronic carriers) may reduce prevalence and mitigate mortality. Postmortem confirmation of pneumonia in chronic carriers has been inadequately reported and the pathology has not been thoroughly characterized, limiting our understanding of important processes shaping the epidemiology of pneumonia in bighorn sheep. Here we document postmortem findings and characterize the lesions of seven ewes removed from a declining bighorn sheep population in Wyoming, USA, following at least two antemortem detections of M. ovipneumoniae within a 14-mo period. We confirmed that 6/7 (85.7%) had variable degrees of chronic pneumonia. Mycoplasma ovipneumoniae was detected in the lung of 4/7 (57.1%) animals postmortem. Four (57.1%) had paranasal sinus masses, all of which were classified as inflammatory, hyperplastic lesions. Pasteurella multocida was detected in all seven (100%) animals, while Trueperella pyogenes was detected in 5/7 (71.4%). Our findings indicate that not all chronic carriers have pneumonia, nor do all have detectable M. ovipneumoniae in the lung. Further, paranasal sinus masses are a common but inconsistent finding, and whether sinus lesions predispose to persistence or result from chronic carriage remains unclear. Our findings indicate that disease is variable in chronic M. ovipneumoniae carriers, underscoring the need for further efforts to characterize pathologic processes and underlying mechanisms in this system to inform management.

Bighorn sheep associations: understanding tradeoffs of sociality and implications for disease transmission

Sociality directly influences mating success, survival rates, and disease, but ultimately likely evolved for its fitness benefits in a challenging environment. The tradeoffs between the costs and benefits of sociality can operate at multiple scales, resulting in different interpretations of animal behavior. We investigated the influence of intrinsic (e.g., relatedness, age) and extrinsic factors (e.g., land cover type, season) on direct contact (simultaneous GPS locations ≤ 25 m) rates of bighorn sheep (Ovis canadensis) at multiple scales near the Waterton-Glacier International Peace Park. During 2002-2012, male and female bighorn were equipped with GPS collars. Indirect contact (GPS locations ≤ 25 m regardless of time) networks identified two major breaks whereas direct contact networks identified an additional barrier in the population, all of which corresponded with prior disease exposure metrics. More direct contacts occurred between same-sex dyads than female-male dyads and between bighorn groups with overlapping summer home ranges. Direct contacts occurred most often during the winter-spring season when bighorn traveled at low speeds and when an adequate number of bighorn were collared in the area. Direct contact probabilities for all dyad types were inversely related to habitat quality, and differences in contact probability were driven by variables related to survival such as terrain ruggedness, distance to escape terrain, and canopy cover. We provide evidence that probabilities of association are higher when there is greater predation risk and that contact analysis provides valuable information for understanding fitness tradeoffs of sociality and disease transmission potential.

The heterogeneous herd: Drivers of close-contact variation in African buffalo and implications for pathogen invasion

Many infectious pathogens are shared through social interactions, and examining host connectivity has offered valuable insights for understanding patterns of pathogen transmission across wildlife species. African buffalo are social ungulates and important reservoirs of directly-transmitted pathogens that impact numerous wildlife and livestock species. Here, we analyzed African buffalo social networks to quantify variation in close contacts, examined drivers of contact heterogeneity, and investigated how the observed contact patterns affect pathogen invasion likelihoods for a wild social ungulate. We collected continuous association data using proximity collars and sampled host traits approximately every 2 months during a 15-month study period in Kruger National Park, South Africa. Although the observed herd was well connected, with most individuals contacting each other during each bimonthly interval, our analyses revealed striking heterogeneity in close-contact associations among herd members. Network analysis showed that individual connectivity was stable over time and that individual age, sex, reproductive status, and pairwise genetic relatedness were important predictors of buffalo connectivity. Calves were the most connected members of the herd, and adult males were the least connected. These findings highlight the role susceptible calves may play in the transmission of pathogens within the herd. We also demonstrate that, at time scales relevant to infectious pathogens found in nature, the observed level of connectivity affects pathogen invasion likelihoods for a wide range of infectious periods and transmissibilities. Ultimately, our study identifies key predictors of social connectivity in a social ungulate and illustrates how contact heterogeneity, even within a highly connected herd, can shape pathogen invasion likelihoods.

Quantifying intra- and inter-species contact rates at supplemental feeding sites in Ethiopia to inform rabies maintenance potential of multiple host species

Rabies, a multi-host pathogen responsible for the loss of roughly 59,000 human lives each year worldwide, continues to impose a significant burden of disease despite control efforts, especially in Ethiopia. However, how species other than dogs contribute to rabies transmission throughout Ethiopia remains largely unknown. In this study, we quantified interactions among wildlife species in Ethiopia with the greatest potential for contributing to rabies maintenance. We observed wildlife at supplemental scavenging sites across multiple landscape types and quantified transmission potential. More specifically, we used camera trap data to quantify species abundance, species distribution, and intra- and inter-species contacts per trapping night over time and by location. We derived a mathematical expression for the basic reproductive number (R₀ ) based on within- and between-species contract rates by applying the next generation method to the susceptible, exposed, infectious, removed model. We calculated R₀ for transmission within each species and between each pair of species using camera trap data in order to identify pairwise interactions that contributed the most to transmission in an ecological community. We estimated which species, or species pairs, could maintain transmission ( R 0 > 1 ${R_0} &gt; 1$ ) and which species, or species pairs, had contact rates too low for maintenance ( R 0 < 1 ${R_0} &lt; 1$ ). Our results identified multiple urban carnivores as candidate species for rabies maintenance throughout Ethiopia, with hyenas exhibiting the greatest risk for rabies maintenance through intra-species transmission. Hyenas and cats had the greatest risk for rabies maintenance through inter-species transmission. Urban and peri-urban sites posed the greatest risk for rabies transmission. The night-time hours presented the greatest risk for a contact event that could result in rabies transmission. Overall, both intra- and inter-species contacts posed risk for rabies maintenance. Our results can be used to target future studies and inform population management decisions.

Pathogen surveillance and epidemiology in endangered Peninsular bighorn sheep (Ovis canadensis nelsoni)

Peninsular bighorn sheep (Ovis canadensis nelsoni) are found exclusively in Southern California and Baja Mexico. They are federally endangered due to multiple threats, including introduced infectious disease. From 1981 - 2017, we conducted surveillance for 16 pathogens and estimated population sizes, adult survival, and lamb survival. We used mixed effects regression models to assess disease patterns at the individual and population levels. Pathogen infection/exposure prevalence varied both spatially and temporally. Our findings indicate that the primary predictor of individual pathogen infection/exposure was the region in which an animal was captured, implying that transmission is driven by local ecological or behavioral factors. Higher Mycoplasma ovipneumoniae seropositivity was associated with lower lamb survival, consistent with lambs having high rates of pneumonia-associated mortality, which may be slowing population recovery. There was no association between M. ovipneumoniae and adult survival. Adult survival was positively associated with population size and parainfluenza-3 virus seroprevalence in the same year, and orf virus seroprevalence in the previous year. Peninsular bighorn sheep are recovering from small population sizes in a habitat of environmental extremes, compounded by infectious disease. Our research can help inform future pathogen surveillance and population monitoring for the long-term conservation of this population.

Social interactions of juvenile rabbits (Oryctolagus cuniculus) and their potential role in lagovirus transmission

Rabbit Haemorrhagic Disease Virus (RHDV), which is a calicivirus, is used as a biocontrol agent to suppress European wild rabbit populations in Australia. The transmission of RHDV can be influenced by social interactions of rabbits; however, there is a paucity of this knowledge about juvenile rabbits and the roles they may play in the transmission of RHDV. We aimed to quantify the social interactions of juvenile (< 900 g) and adult (> 1200 g) rabbits in a locally abundant population in the Central Tablelands of New South Wales, Australia. Twenty-six juvenile and 16 adult rabbits were fitted with VHF proximity loggers to monitor intra- and inter-group pairings. Use of multiple warrens by these rabbits was investigated using VHF base stations at nine warrens and on foot with a hand-held Yagi antenna. Juvenile rabbits were strongly interconnected with both juveniles and adults within and outside their warren of capture, and almost all juveniles were well-connected to other individuals within their own social group. Inter-group pairings were infrequent and fleeting between adults. Both juvenile and adult rabbits used multiple warrens. However, visits to warrens outside their warren of capture, particularly those within 50 m, were more common and longer in duration in juveniles than in adults. The high connectivity of juveniles within and between warrens in close proximity increases potential pathogen exchange between warrens. Therefore, juvenile rabbits could be of greater importance in lagovirus transmission than adult rabbits. The strength of juvenile rabbit inter- and intra-group pairings, and their tendency to use multiple warrens, highlight their potential to act as ‘superspreaders’ of both infection and immunity for lagoviruses and other pathogens with similar lifecycles. Confirmation of this potential is required through examination of disease progress and rabbit age-related immune responses during outbreaks.

Bighorn sheep show similar in-host responses to the same pathogen strain in two contrasting environments

Ecological context-the biotic and abiotic environment, along with its influence on population mixing dynamics and individual susceptibility-is thought to have major bearing on epidemic outcomes. However, direct comparisons of wildlife disease events in contrasting ecological contexts are often confounded by concurrent differences in host genetics, exposure histories, or pathogen strains. Here, we compare disease dynamics of a Mycoplasma ovipneumoniae spillover event that affected bighorn sheep populations in two contrasting ecological contexts. One event occurred on the herd's home range near the Rio Grande Gorge in New Mexico, while the other occurred in a captive facility at Hardware Ranch in Utah. While data collection regimens varied, general patterns of antibody signal strength and symptom emergence were conserved between the two sites. Symptoms appeared in the captive setting an average of 12.9 days postexposure, average time to seroconversion was 24.9 days, and clinical signs peaked at approximately 36 days postinfection. These patterns were consistent with serological testing and subsequent declines in symptom intensity in the free-ranging herd. At the captive site, older animals exhibited more severe declines in body condition and loin thickness, higher symptom burdens, and slower antibody response to the pathogen than younger animals. Younger animals were more likely than older animals to clear infection by the time of sampling at both sites. The patterns presented here suggest that environment may not be a major determinant of epidemiological outcomes in the bighorn sheep-M. ovipneumoniae system, elevating the possibility that host- or pathogen-factors may be responsible for observed variation.

Spatial scaling of gregarious host populations and nonlinearities in infectious disease transmission

Research Highlight: Lunn, T. J., Peel, A. J., Eby, P., Brooks, R., Plowright, R. K., Kessler, M. K., & McCallum, H. (2021). Counterintuitive scaling between population abundance and local density: Implications for modelling transmission of infectious diseases in bat populations. Journal of Animal Ecology, https://doi.org/10.1111/1365-2656.13634. Quantifying the transmission of an infectious disease is often difficult and for natural animal systems it can be a major challenge. Animals move over time and space changing their degree of aggregation and rate of contact, which, in turn, affects the risk of infection and the onward spread of the pathogen. Capturing the fundamentals of these processes requires the identification of both the correct spatial scale at which the processes take place and what constitutes a meaningful host population unit. Lunn et al. collected data on the gregarious Pteropus (flying foxes) bats from roost sites in Australia and investigated whether total bat abundance at the roost level, the spatial scale commonly used to model pathogen spread in bat populations, was representative of bat measurements at the tree level, the scale at which pathogen transmission between bats most likely occurs. Their findings showed that bat population measurements at the sub-plot level were strong predictors for potential transmission at the tree scale, while roost-level measurements were less robust. This study suggests that bat abundance at roost is inadequate to capture the gregarious structure of bat populations and the fundamental processes of transmission at lower scale.

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.

Network models are widely used to understand and predict infectious disease spread in human and animal populations. However, the choice of network model often relies on subjective expert knowledge or disease transmission experiments that are time-consuming and difficult to perform. We developed a novel tool, called INoDS (Identifying contact Networks of infectious Disease Spread), that uses robust statistical approach to establish relevance of a network model in explaining transmission pathways of an infectious disease outbreak. We used computer simulations and real-world dataset to test the accuracy of our tool and robustness to missing data. We found that INoDS is robust to common data-collection constraints, broadly applicable and accurate compared to current approaches. The tool that we have developed can therefore provide immediate epidemiological insights in the event of an epidemic outbreak, and can be used to improve targeted disease control.

Parasite exposure and host susceptibility jointly drive the emergence of epidemics

Parasite transmission is thought to depend on both parasite exposure and host susceptibility to infection; however, the relative contribution of these two factors to epidemics remains unclear. We used interactions between an aquatic host and its fungal parasite to evaluate how parasite exposure and host susceptibility interact to drive epidemics. In six lakes, we tracked the following factors from pre-epidemic to epidemic emergence: (1) parasite exposure (measured observationally as fungal spores attacking wild-caught hosts), (2) host susceptibility (measured experimentally as the number of fungal spores required to produce terminal infection), (3) host susceptibility traits (barrier resistance and internal clearance, both quantified with experimental assays), and (4) parasite prevalence (measured observationally from wild-caught hosts). Tracking these factors over 6 months and in almost 7,000 wild-caught hosts provided key information on the drivers of epidemics. We found that epidemics depended critically on the interaction of exposure and susceptibility; epidemics only emerged when a host population's level of exposure exceeded its individuals' capacity for recovery. Additionally, we found that host internal clearance traits (the hemocyte response) were critical in regulating epidemics. Our study provides an empirical demonstration of how parasite exposure and host susceptibility interact to inhibit or drive disease in natural systems and demonstrates that epidemics can be delayed by asynchronicity in the two processes. Finally, our results highlight how individual host traits can scale up to influence broad epidemiological patterns.

Individual variation creates diverse migratory portfolios in native populations of a mountain ungulate

Ecological theory and empirical studies have demonstrated population-level demographic benefits resulting from a diversity of migratory behaviors with important implications for ecology, conservation, and evolution of migratory organisms. Nevertheless, evaluation of migratory portfolios (i.e., the variation in migratory behaviors across space and time among individuals within populations) has received relatively little attention in migratory ungulates, where research has focused largely on the dichotomous behaviors (e.g., resident and migrant) of partially migratory populations. Using GPS data from 361 female bighorn sheep (Ovis canadensis) across 17 (4 restored, 6 augmented, 7 native) populations in Montana and Wyoming, USA, we (1) characterized migratory portfolios based on behavioral and spatial migratory characteristics and (2) evaluated the relative influence of landscape attributes and management histories on migratory diversity. Native populations, which had been extant on the landscape for many generations, had more diverse migratory portfolios, higher behavioral switching rates, reduced seasonal range fidelity, and broad dispersion of individuals across summer and winter ranges. In contrast, restored populations with an abbreviated history on the landscape were largely non-migratory with a narrow portfolio of migratory behaviors, less behavioral switching, higher fidelity to seasonal ranges, and less dispersion on summer and winter ranges. Augmented populations were more variable and contained characteristics of both native and restored populations. Differences in migratory diversity among populations were associated with management histories (e.g., restored, augmented, or native). Landscape characteristics such as the duration and regularity of green-up, human landscape alterations, topography, and snow gradients were not strongly associated with migratory diversity. We suggest a two-pronged approach to restoring migratory portfolios in ungulates that first develops behavior-specific habitat models and then places individuals with known migratory behaviors into unoccupied areas in an effort to bolster migratory portfolios in restored populations, potentially with synergistic benefits associated with variation among individuals and resulting portfolio effects. Management efforts to restore diverse migratory portfolios may increase the abundance, resilience, and long-term viability of ungulate populations.

Towards a mechanistic understanding of competence: a missing link in diversity-disease research

Biodiversity loss may increase the risk of infectious disease in a phenomenon known as the dilution effect. Circumstances that increase the likelihood of disease dilution are: (i) when hosts vary in their competence, and (ii) when communities disassemble predictably, such that the least competent hosts are the most likely to go extinct. Despite the central role of competence in diversity-disease theory, we lack a clear understanding of the factors underlying competence, as well as the drivers and extent of its variation. Our perspective piece encourages a mechanistic understanding of competence and a deeper consideration of its role in diversity-disease relationships. We outline current evidence, emerging questions and future directions regarding the basis of competence, its definition and measurement, the roots of its variation and its role in the community ecology of infectious disease.

Sex, synchrony, and skin contact: integrating multiple behaviors to assess pathogen transmission risk

Direct pathogen and parasite transmission is fundamentally driven by a population’s contact network structure and its demographic composition and is further modulated by pathogen life-history traits. Importantly, populations are most often concurrently exposed to a suite of pathogens, which is rarely investigated, because contact networks are typically inferred from spatial proximity only. Here, we use 5 years of detailed observations of Indo-Pacific bottlenose dolphins (Tursiops aduncus) that distinguish between four different types of social contact. We investigate how demography (sex and age) affects these different social behaviors. Three of the four social behaviors can be used as a proxy for understanding key routes of direct pathogen transmission (sexual contact, skin contact, and aerosol contact of respiratory vapor above the water surface). We quantify the demography-dependent network connectedness, representing the risk of exposure associated with the three pathogen transmission routes, and quantify coexposure risks and relate them to individual sociability. Our results suggest demography-driven disease risk in bottlenose dolphins, with males at greater risk than females, and transmission route-dependent implications for different age classes. We hypothesize that male alliance formation and the divergent reproductive strategies in males and females drive the demography-dependent connectedness and, hence, exposure risk to pathogens. Our study provides evidence for the risk of coexposure to pathogens transmitted along different transmission routes and that they relate to individual sociability. Hence, our results highlight the importance of a multibehavioral approach for a more complete understanding of the overall pathogen transmission risk in animal populations, as well as the cumulative costs of sociality.

Dose-response and transmission: the nexus between reservoir hosts, environment and recipient hosts

Dose is the nexus between exposure and all upstream processes that determine pathogen pressure, and is thereby an important element underlying disease dynamics. Understanding the relationship between dose and disease is particularly important in the context of spillover, where nonlinearities in the dose-response could determine the likelihood of transmission. There is a need to explore dose-response models for directly transmitted and zoonotic pathogens, and how these interactions integrate within-host factors to consider, for example, heterogeneity in host susceptibility and dose-dependent antagonism. Here, we review the dose-response literature and discuss the unique role dose-response models have to play in understanding and predicting spillover events. We present a re-analysis of dose-response experiments for two important zoonotic pathogens (Middle East respiratory syndrome coronavirus and Nipah virus), to exemplify potential difficulties in differentiating between appropriate models with small exposure experiment datasets. We also discuss the data requirements needed for robust selection between dose-response models. We then suggest how these processes could be modelled to gain more realistic predictions of zoonotic transmission outcomes and highlight the exciting opportunities that could arise with increased collaboration between the virology and epidemiology disciplines. This article is part of the theme issue 'Dynamic and integrative approaches to understanding pathogen spillover'.

Rate of intersexual interactions affects injury likelihood in Tasmanian devil contact networks

Identifying the types of contacts that result in disease transmission is important for accurately modeling and predicting transmission dynamics and disease spread in wild populations. We investigated contacts within a population of adult Tasmanian devils (Sarcophilus harrisii) over a 6-month period and tested whether individual-level contact patterns were correlated with accumulation of bite wounds. Bite wounds are important in the spread of devil facial tumor disease, a clonal cancer cell line transmitted through direct inoculation of tumor cells when susceptible and infected individuals bite each other. We used multimodel inference and network autocorrelation models to investigate the effects of individual-level contact patterns, identities of interacting partners, and position within the social network on the propensity to be involved in bite-inducing contacts. We found that males were more likely to receive potentially disease-transmitting bite wounds than females, particularly during the mating season when males spend extended periods mate-guarding females. The number of bite wounds individuals received during the mating season was unrelated to any of the network metrics examined. Our approach illustrates the necessity for understanding which contact types spread disease in different systems to assist the management of this and other infectious wildlife diseases.

Transmission on empirical dynamic contact networks is influenced by data processing decisions

Dynamic contact data can be used to inform disease transmission models, providing insight into the dynamics of infectious diseases. Such data often requires extensive processing for use in models or analysis. Therefore, processing decisions can potentially influence the topology of the contact network and the simulated disease transmission dynamics on the network. In this study, we examine how four processing decisions, including temporal sampling window (TSW), spatial threshold of contact (SpTh), minimum contact duration (MCD), and temporal aggregation (daily or hourly) influence the information content of contact data (indicated by changes in entropy) as well as disease transmission model dynamics. We found that changes made to information content by processing decisions translated to significant impacts to the transmission dynamics of disease models using the contact data. In particular, we found that SpTh had the largest independent influence on information content, and that some output metrics (R₀, time to peak infection) were more sensitive to changes in information than others (epidemic extent). These findings suggest that insights gained from transmission modeling using dynamic contact data can be influenced by processing decisions alone, emphasizing the need to carefully consideration them prior to using contact-based models to conduct analyses, compare different datasets, or inform policy decisions.

Disease implications of animal social network structure: A synthesis across social systems

The disease costs of sociality have largely been understood through the link between group size and transmission. However, infectious disease spread is driven primarily by the social organization of interactions in a group and not its size. We used statistical models to review the social network organization of 47 species, including mammals, birds, reptiles, fish and insects by categorizing each species into one of three social systems, relatively solitary, gregarious and socially hierarchical. Additionally, using computational experiments of infection spread, we determined the disease costs of each social system. We find that relatively solitary species have large variation in number of social partners, that socially hierarchical species are the least clustered in their interactions, and that social networks of gregarious species tend to be the most fragmented. However, these structural differences are primarily driven by weak connections, which suggest that different social systems have evolved unique strategies to organize weak ties. Our synthetic disease experiments reveal that social network organization can mitigate the disease costs of group living for socially hierarchical species when the pathogen is highly transmissible. In contrast, highly transmissible pathogens cause frequent and prolonged epidemic outbreaks in gregarious species. We evaluate the implications of network organization across social systems despite methodological challenges, and our findings offer new perspective on the debate about the disease costs of group living. Additionally, our study demonstrates the potential of meta-analytic methods in social network analysis to test ecological and evolutionary hypotheses on cooperation, group living, communication and resilience to extrinsic pressures.

Associating sex-biased and seasonal behaviour with contact patterns and transmission risk in Gopherus agassizii

Interactions between wildlife hosts act as transmission routes for directly transmitted pathogens and vary in ways that affect transmission efficiency. Identifying drivers of contact variation can allow both contact inference and estimation of transmission dynamics despite limited data. In desert tortoises, mating strategy, burrow use and seasonal change influence numerous behaviours and likely shape contact patterns. In this study, we ask to what extent tortoise contact behaviour varies between sexes and seasons, and whether space or burrow-use data can be used to infer contact characteristics consistent with those recorded by proximity loggers. We identified sex and season-biased contact behaviour in both wild and captive populations indicative of female-female avoidance and seasonal male mate-seeking behaviour. Space and burrow-use patterns were informative, but did not always predict the extent of sex or seasonal biases on contact. We discuss the implications these findings have for transmission patterns and disease mitigation in tortoise populations.

Contact and contagion: Probability of transmission given contact varies with demographic state in bighorn sheep

Understanding both contact and probability of transmission given contact are key to managing wildlife disease. However, wildlife disease research tends to focus on contact heterogeneity, in part because the probability of transmission given contact is notoriously difficult to measure. Here, we present a first step towards empirically investigating the probability of transmission given contact in free-ranging wildlife. We used measured contact networks to test whether bighorn sheep demographic states vary systematically in infectiousness or susceptibility to Mycoplasma ovipneumoniae, an agent responsible for bighorn sheep pneumonia. We built covariates using contact network metrics, demographic information and infection status, and used logistic regression to relate those covariates to lamb survival. The covariate set contained degree, a classic network metric describing node centrality, but also included covariates breaking the network metrics into subsets that differentiated between contacts with yearlings, ewes with lambs, and ewes without lambs, and animals with and without active infections. Yearlings, ewes with lambs, and ewes without lambs showed similar group membership patterns, but direct interactions involving touch occurred at a rate two orders of magnitude higher between lambs and reproductive ewes than between any classes of adults or yearlings, and one order of magnitude higher than direct interactions between multiple lambs. Although yearlings and non-reproductive bighorn ewes regularly carried M. ovipneumoniae, our models suggest that a contact with an infected reproductive ewe had approximately five times the odds of producing a lamb mortality event of an identical contact with an infected dry ewe or yearling. Consequently, management actions targeting infected animals might lead to unnecessary removal of young animals that carry pathogens but rarely transmit. This analysis demonstrates a simple logistic regression approach for testing a priori hypotheses about variation in the odds of transmission given contact for free-ranging hosts, and may be broadly applicable for investigations in wildlife disease ecology.