African swine fever at the wildlife-livestock interface: challenges for management and outbreak response within invasive wild pigs in the United States.

African swine fever (ASF) causes significant morbidity and mortality in both domestic and wild suids (Sus scrofa), and disease outbreaks convey profound economic costs to impacted industries due to death loss, the cost of culling exposed/infected animals as the primary disease control measure, and trade restrictions. The co-occurrence of domestic and wild suids significantly complicates ASF management given the potential for wild populations to serve as persistent sources for spillover. We describe the unique threat of African swine fever virus (ASFV) introduction to the United States from epidemiological and ecological perspectives with a specific focus on disease management at the wild-domestic swine interface. The introduction of ASF into domestic herds would require a response focused on containment, culling, and contact tracing. However, detection of ASF among invasive wild pigs would require a far more complex and intensive response given the challenges of detection, containment, and ultimately elimination among wild populations. We describe the state of the science available to inform preparations for an ASF response among invasive wild pigs, describe knowledge gaps and the associated studies needed to fill those gaps, and call for an integrated approach for preparedness that incorporates the best available science and acknowledges sociological attributes and the policy context needed for an integrated disease response.

Genomic regions associated with pseudorabies virus infection status in naturally infected feral swine (Sus scrofa).

Pseudorabies virus (PRV)-the causative agent of Aujeszky's disease-was eliminated from commercial pig production herds in the United States (US) in 2004; however, PRV remains endemic among invasive feral swine (Sus scrofa). The circulation of PRV among abundant, widespread feral swine populations poses a sustained risk for disease spillover to production herds. Risk-based surveillance has been successfully implemented for PRV in feral swine populations in the US. However, understanding the role of host genetics in infection status may offer new insights into the epidemiology and disease dynamics of PRV that can be applied to management strategies. Genetic mechanisms underlying host susceptibility to PRV are relatively unknown; therefore, we sought to identify genomic regions associated with PRV infection status among naturally infected feral swine using genome-wide association studies (GWAS) and gene set enrichment analysis of single nucleotide polymorphism data (GSEA-SNP). Paired serological and genotypic data were collected from 6,081 feral swine distributed across the invaded range within the contiguous US. Three complementary study populations were developed for GWAS: 1) comprehensive population consisting of feral swine throughout the invaded range within the contiguous US; 2) population of feral swine under high, but temporally variable PRV infection pressure; and 3) population of feral swine under temporally stable, high PRV infection pressure. We identified one intronic SNP associated with PRV infection status within candidate gene AKAP6 on autosome 7. Various gene sets linked to metabolic pathways were enriched in the GSEA-SNP. Ultimately, improving disease surveillance efforts in feral swine will be critical to further understanding of the role host genetics play in PRV infection status, helping secure the health of commercial pork production.

Grassland intensification effects cascade to alter multifunctionality of wetlands within metaecosystems.

Sustainable agricultural intensification could improve ecosystem service multifunctionality, yet empirical evidence remains tenuous, especially regarding consequences for spatially coupled ecosystems connected by flows across ecosystem boundaries (i.e., metaecosystems). Here we aim to understand the effects of land-use intensification on multiple ecosystem services of spatially connected grasslands and wetlands, where management practices were applied to grasslands but not directly imposed to wetlands. We synthesize long-term datasets encompassing 53 physical, chemical, and biological indicators, comprising >11,000 field measurements. Our results reveal that intensification promotes high-quality forage and livestock production in both grasslands and wetlands, but at the expense of water quality regulation, methane mitigation, non-native species invasion resistance, and biodiversity. Land-use intensification weakens relationships among ecosystem services. The effects on grasslands cascade to alter multifunctionality of embedded natural wetlands within the metaecosystems to a similar extent. These results highlight the importance of considering spatial flows of resources and organisms when studying land-use intensification effects on metaecosystems as well as when designing grassland and wetland management practices to improve landscape multifunctionality.

Individual-level patterns of resource selection do not predict hotspots of contact.

Contact among animals is crucial for various ecological processes, including social behaviors, disease transmission, and predator-prey interactions. However, the distribution of contact events across time and space is heterogeneous, influenced by environmental factors and biological purposes. Previous studies have assumed that areas with abundant resources and preferred habitats attract more individuals and, therefore, lead to more contact. To examine the accuracy of this assumption, we used a use-available framework to compare landscape factors influencing the location of contacts between wild pigs (Sus scrofa) in two study areas in Florida and Texas (USA) from those influencing non-contact space use. We employed a contact-resource selection function (RSF) model, where contact locations were defined as used points and locations without contact as available points. By comparing outputs from this contact RSF with a general, population-level RSF, we assessed the factors driving both habitat selection and contact. We found that the landscape predictors (e.g., wetland, linear features, and food resources) played different roles in habitat selection from contact processes for wild pigs in both study areas. This indicated that pigs interacted with their landscapes differently when choosing habitats compared to when they encountered other individuals. Consequently, relying solely on the spatial overlap of individual or population-level RSF models may lead to a misleading understanding of contact-related ecology. Our findings challenge prevailing assumptions about contact and introduce innovative approaches to better understand the ecological drivers of spatially explicit contact. By accurately predicting the spatial distribution of contact events, we can enhance our understanding of contact based ecological processes and their spatial dynamics.

Disease Progression and Serological Assay Performance in Heritage Breed Pigs following Brucella suis Experimental Challenge as a Model for Naturally Infected Feral Swine.

Invasive feral swine (Sus scrofa) are one of the most important wildlife species for disease surveillance in the United States, serving as a reservoir for various diseases of concern for the health of humans and domestic animals. Brucella suis, the causative agent of swine brucellosis, is one such pathogen carried and transmitted by feral swine. Serology assays are the preferred field diagnostic for B. suis infection, as whole blood can be readily collected and antibodies are highly stable. However, serological assays frequently have lower sensitivity and specificity, and few studies have validated serological assays for B. suis in feral swine. We conducted an experimental infection of Ossabaw Island Hogs (a breed re-domesticated from feral animals) as a disease-free proxy for feral swine to (1) improve understanding of bacterial dissemination and antibody response following B. suis infection and (2) evaluate potential changes in the performance of serological diagnostic assays over the course of infection. Animals were inoculated with B. suis and serially euthanized across a 16-week period, with samples collected at the time of euthanasia. The 8% card agglutination test performed best, whereas the fluorescence polarization assay demonstrated no capacity to differentiate true positive from true negative animals. From a disease surveillance perspective, using the 8% card agglutination test in parallel with either the buffered acidified plate antigen test or the Brucella abortus/suis complement fixation test provided the best performance with the highest probability of a positive assay result. Application of these combinations of diagnostic assays for B. suis surveillance among feral swine would improve understanding of spillover risks at the national level.

Role of social structure in establishment of an invasive large mammal after translocation.

BACKGROUND: Data on the movement behavior of translocated wild pigs is needed to develop appropriate response strategies for containing and eliminating new source populations following translocation events. We conducted experimental trials to compare the home range establishment and space-use metrics, including the number of days and distance traveled before becoming range residents, for wild pigs translocated with their social group and individually. RESULTS: We found wild pigs translocated with their social group made less extensive movements away from the release location and established a stable home range ~5 days faster than those translocated individually. We also examined how habitat quality impacted the home range sizes of translocated wild pigs and found wild pigs maintained larger ranges in areas with higher proportion of low-quality habitat. CONCLUSION: Collectively, our findings suggest translocations of invasive wild pigs have a greater probability of establishing a viable population near the release site when habitat quality is high and when released with members of their social unit compared to individuals moved independent of their social group or to low-quality habitat. However, all wild pigs translocated in our study made extensive movements from their release location, highlighting the potential for single translocation events of either individuals or groups to have far-reaching consequences within a much broader landscape beyond the location where they are released. These results highlight the challenges associated with containing populations in areas where illegal introduction of wild pigs occurs, and the need for rapid response once releases are identified. © 2023 The Authors. Pest Management Science published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

Deriving spatially explicit direct and indirect interaction networks from animal movement data.

Quantifying spatiotemporally explicit interactions within animal populations facilitates the understanding of social structure and its relationship with ecological processes. Data from animal tracking technologies (Global Positioning Systems ["GPS"]) can circumvent longstanding challenges in the estimation of spatiotemporally explicit interactions, but the discrete nature and coarse temporal resolution of data mean that ephemeral interactions that occur between consecutive GPS locations go undetected. Here, we developed a method to quantify individual and spatial patterns of interaction using continuous-time movement models (CTMMs) fit to GPS tracking data. We first applied CTMMs to infer the full movement trajectories at an arbitrarily fine temporal scale before estimating interactions, thus allowing inference of interactions occurring between observed GPS locations. Our framework then infers indirect interactions-individuals occurring at the same location, but at different times-while allowing the identification of indirect interactions to vary with ecological context based on CTMM outputs. We assessed the performance of our new method using simulations and illustrated its implementation by deriving disease-relevant interaction networks for two behaviorally differentiated species, wild pigs (Sus scrofa) that can host African Swine Fever and mule deer (Odocoileus hemionus) that can host chronic wasting disease. Simulations showed that interactions derived from observed GPS data can be substantially underestimated when temporal resolution of movement data exceeds 30-min intervals. Empirical application suggested that underestimation occurred in both interaction rates and their spatial distributions. CTMM-Interaction method, which can introduce uncertainties, recovered majority of true interactions. Our method leverages advances in movement ecology to quantify fine-scale spatiotemporal interactions between individuals from lower temporal resolution GPS data. It can be leveraged to infer dynamic social networks, transmission potential in disease systems, consumer-resource interactions, information sharing, and beyond. The method also sets the stage for future predictive models linking observed spatiotemporal interaction patterns to environmental drivers.

Habitat quality influences trade-offs in animal movement along the exploration-exploitation continuum.

To successfully establish itself in a novel environment, an animal must make an inherent trade-off between knowledge accumulation and exploitation of knowledge gained (i.e., the exploration-exploitation dilemma). To evaluate how habitat quality affects the spatio-temporal scale of switching between exploration and exploitation during home range establishment, we conducted experimental trials comparing resource selection and space-use of translocated animals to those of reference individuals using reciprocal translocations between habitat types of differing quality. We selected wild pigs (Sus scrofa) as a model species to investigate hypotheses related to the movement behavior of translocated individuals because they are globally distributed large mammals that are often translocated within their introduced range to facilitate recreational hunting. Individuals translocated to higher quality habitat (i.e. higher proportions of bottomland hardwood habitats) exhibited smaller exploratory movements and began exploiting resources more quickly than those introduced to lower quality areas, although those in lower-quality areas demonstrated an increased rate of selection for preferred habitat as they gained knowledge of the landscape. Our data demonstrate that habitat quality mediates the spatial and temporal scale at which animals respond behaviorally to novel environments, and how these processes may determine the success of population establishment.

An exploration of within-herd dynamics of a transboundary livestock disease: A foot and mouth disease case study.

Transboundary livestock diseases are a high priority for policy makers because of the serious economic burdens associated with infection. In order to make well informed preparedness and response plans, policy makers often utilize mathematical models to understand possible outcomes of different control strategies and outbreak scenarios. Many of these models focus on the transmission between herds and the overall trajectory of the outbreak. While the course of infection within herds has not been the focus of the majority of models, a thorough understanding of within-herd dynamics can provide valuable insight into a disease system by providing information on herd-level biological properties of the infection, which can be used to inform decision making in both endemic and outbreak settings and to inform larger between-herd models. In this study, we develop three stochastic simulation models to study within-herd foot and mouth disease dynamics and the implications of different empirical data-based assumptions about the timing of the onset of infectiousness and clinical signs. We also study the influence of herd size and the proportion of the herd that is initially infected on the outcome of the infection. We find that increasing herd size increases the duration of infectiousness and that the size of the herd plays a more significant role in determining this duration than the number of initially infected cattle in that herd. We also find that the assumptions made regarding the onset of infectiousness and clinical signs, which are based on contradictory empirical findings, can result in the predictions about when infection would be detectable differing by several days. Therefore, the disease progression used to characterize the course of infection in a single bovine host could have significant implications for determining when herds can be detected and subsequently controlled; the timing of which could influence the overall predicted trajectory of outbreaks.

Modeling nation-wide U.S. swine movement networks at the resolution of the individual premises.

The spread of infectious livestock diseases is a major cause for concern in modern agricultural systems. In the dynamics of the transmission of such diseases, movements of livestock between herds play an important role. When constructing mathematical models used for activities such as forecasting epidemic development, evaluating mitigation strategies, or determining important targets for disease surveillance, including between-premises shipments is often a necessity. In the United States (U.S.), livestock shipment data is not routinely collected, and when it is, it is not readily available and mostly concerned with between-state shipments. To bridge this gap in knowledge and provide insight into the complete livestock shipment network structure, we have developed the U.S. Animal Movement Model (USAMM). Previously, USAMM has only existed for cattle shipments, but here we present a version for domestic swine. This new version of USAMM consists of a Bayesian model fit to premises demography, county-level livestock industry variables, and two limited data sets of between-state swine movements. The model scales up the data to simulate nation-wide networks of both within- and between-state shipments at the level of individual premises. Here we describe this shipment model in detail and subsequently explore its usefulness with a rudimentary predictive model of the prevalence of porcine epidemic diarrhea virus (PEDv) across the U.S. Additionally, in order to promote further research on livestock disease and other topics involving the movements of swine in the U.S., we also make 250 synthetic premises-level swine shipment networks with complete coverage of the entire conterminous U.S. freely available to the research community as a useful surrogate for the absent shipment data.

The Importance of Livestock Demography and Infrastructure in Driving Foot and Mouth Disease Dynamics.

Transboundary animal diseases, such as foot and mouth disease (FMD) pose a significant and ongoing threat to global food security. Such diseases can produce large, spatially complex outbreaks. Mathematical models are often used to understand the spatio-temporal dynamics and create response plans for possible disease introductions. Model assumptions regarding transmission behavior of premises and movement patterns of livestock directly impact our understanding of the ecological drivers of outbreaks and how to best control them. Here, we investigate the impact that these assumptions have on model predictions of FMD outbreaks in the U.S. using models of livestock shipment networks and disease spread. We explore the impact of changing assumptions about premises transmission behavior, both by including within-herd dynamics, and by accounting for premises type and increasing the accuracy of shipment predictions. We find that the impact these assumptions have on outbreak predictions is less than the impact of the underlying livestock demography, but that they are important for investigating some response objectives, such as the impact on trade. These results suggest that demography is a key ecological driver of outbreaks and is critical for making robust predictions but that understanding management objectives is also important when making choices about model assumptions.

Optimising response to an introduction of African swine fever in wild pigs.

African swine fever virus (ASFv) is a virulent pathogen that threatens domestic swine industries globally and persists in wild boar populations in some countries. Persistence in wild boar can challenge elimination and prevent disease-free status, making it necessary to address wild swine in proactive response plans. In the United States, invasive wild pigs are abundant and found across a wide range of ecological conditions that could drive different epidemiological dynamics among populations. Information on the size of the control areas required to rapidly eliminate the ASFv in wild pigs and how this area should change with management constraints and local ecology is needed to optimize response planning. We developed a spatially explicit disease transmission model contrasting wild pig movement and contact ecology in two ecosystems in Southeastern United States. We simulated ASFv spread and determined the optimal response area (reported as the radius of a circle) for eliminating ASFv rapidly over a range of detection times (when ASFv was detected relative to the true date of introduction), culling capacities (proportion of wild pigs in the culling zone removed weekly) and wild pig densities. Large radii for response areas (14 km) were needed under most conditions but could be shortened with early detection (≤ 8 weeks) and high culling capacities (≥ 15% weekly). Under most conditions, the ASFv was eliminated in less than 22 weeks using optimal control radii, although ecological conditions with high rates of wild pig movement required higher culling capacities (≥ 10% weekly) for elimination within 1 year. The results highlight the importance of adjusting response plans based on local ecology and show that wild pig movement is a better predictor of the optimal response area than the number of ASFv cases early in the outbreak trajectory. Our framework provides a tool for determining optimal control plans in different areas, guiding expectations of response impacts, and planning resources needed for rapid elimination.

Transmission of antibiotic resistance at the wildlife-livestock interface.

Antibiotic-resistant microorganisms (ARMs) are widespread in natural environments, animals (wildlife and livestock), and humans, which has reduced our capacity to control life threatening infectious disease. Yet, little is known about their transmission pathways, especially at the wildlife-livestock interface. This study investigated the potential transmission of ARMs and antibiotic resistance genes (ARGs) between cattle and wildlife by comparing gut microbiota and ARG profiles of feral swine (Sus scrofa), coyotes (Canis latrans), cattle (Bos taurus), and environmental microbiota. Unexpectedly, wild animals harbored more abundant ARMs and ARGs compared to grazing cattle. Gut microbiota of cattle was significantly more similar to that of feral swine captured within the cattle grazing area where the home range of both species overlapped substantially. In addition, ARMs against medically important antibiotics were more prevalent in wildlife than grazing cattle, suggesting that wildlife could be a source of ARMs colonization in livestock.

Adaptive risk-based targeted surveillance for foreign animal diseases at the wildlife-livestock interface.

Animal disease surveillance is an important component of the national veterinary infrastructure to protect animal agriculture and facilitates identification of foreign animal disease (FAD) introduction. Once introduced, pathogens shared among domestic and wild animals are especially challenging to manage due to the complex ecology of spillover and spillback. Thus, early identification of FAD in wildlife is critical to minimize outbreak severity and potential impacts on animal agriculture as well as potential impacts on wildlife and biodiversity. As a result, national surveillance and monitoring programs that include wildlife are becoming increasingly common. Designing surveillance systems in wildlife or, more importantly, at the interface of wildlife and domestic animals, is especially challenging because of the frequent lack of ecological and epidemiological data for wildlife species and technical challenges associated with a lack of non-invasive methodologies. To meet the increasing need for targeted FAD surveillance and to address gaps in existing wildlife surveillance systems, we developed an adaptive risk-based targeted surveillance approach that accounts for risks in source and recipient host populations. The approach is flexible, accounts for changing disease risks through time, can be scaled from local to national extents and permits the inclusion of quantitative data or when information is limited to expert opinion. We apply this adaptive risk-based surveillance framework to prioritize areas for surveillance in wild pigs in the United States with the objective of early detection of three diseases: classical swine fever, African swine fever and foot-and-mouth disease. We discuss our surveillance framework, its application to wild pigs and discuss the utility of this framework for surveillance of other host species and diseases.

Seasonal variation in space use and territoriality in a large mammal (Sus scrofa).

An individual's spatial behavior is shaped by social and environmental factors and provides critical information about population processes to inform conservation and management actions. Heterogeneity in spatial overlap among conspecifics can be evaluated using estimates of home ranges and core areas and used to understand factors influencing space use and territoriality. To understand and test predictions about spatial behavior in an invasive large mammal, the wild pig (Sus scrofa), we examined variation in space use between sexes and seasons. We predicted that if animals were territorial that there would be a reduction in space-use overlap when comparing overlap of home ranges (HR-HR), to home ranges and core areas (HR-CA), and in-turn between core areas (CA-CA). Home ranges and core areas were estimated for 54 wild pigs at Buck Island Ranch, FL from GPS telemetry data. Overlap indices were calculated to estimate the strength (space-use overlap) and number of potential interactions within three wet seasons (June-October) and two dry seasons (December-April). Among sexes, home range size did not vary seasonally, and males exhibited larger home ranges compared to females (M = 10.36 ± 0.79 km2 (± SE), F = 3.21 ± 0.16 km2). Strength of overlap varied by season with wild pig home ranges overlapping more during the dry season. Males interacted with a greater number of individuals of both sexes, compared to females, and exhibited greater strength of overlap during the dry season. Consistent with our predictions, wild pigs appeared to exhibit territorial behavior, where strength of overlap decreased when comparing HR-HR to HR-CA and HR-CA to CA-CA. Our framework can be used to understand patterns of space use and territoriality in populations, which has important implications in understanding intraspecific interactions and population processes, such as how pathogens and parasites might spread within and among populations.

A model for leveraging animal movement to understand spatio-temporal disease dynamics.

The ongoing explosion of fine-resolution movement data in animal systems provides a unique opportunity to empirically quantify spatial, temporal and individual variation in transmission risk and improve our ability to forecast disease outbreaks. However, we lack a generalizable model that can leverage movement data to quantify transmission risk and how it affects pathogen invasion and persistence on heterogeneous landscapes. We developed a flexible model 'Movement-driven modelling of spatio-temporal infection risk' (MoveSTIR) that leverages diverse data on animal movement to derive metrics of direct and indirect contact by decomposing transmission into constituent processes of contact formation and duration and pathogen deposition and acquisition. We use MoveSTIR to demonstrate that ignoring fine-scale animal movements on actual landscapes can mis-characterize transmission risk and epidemiological dynamics. MoveSTIR unifies previous work on epidemiological contact networks and can address applied and theoretical questions at the nexus of movement and disease ecology.

Case Studies in Pediatric Lipid Disorders and Their Management.

CONTEXT: Identification of modifiable risk factors, including genetic and acquired disorders of lipid and lipoprotein metabolism, is increasingly recognized as an opportunity to prevent premature cardiovascular disease (CVD) in at-risk youth. Pediatric endocrinologists are at the forefront of this emerging public health concern and can be instrumental in beginning early interventions to prevent premature CVD-related events during adulthood. AIM: In this article, we use informative case presentations to provide practical approaches to the management of pediatric dyslipidemia. CASES: We present 3 scenarios that are commonly encountered in clinical practice: isolated elevation of low-density lipoprotein cholesterol (LDL-C), combined dyslipidemia, and severe hypertriglyceridemia. Treatment with statin is indicated when the LDL-C is ≥190 mg/dL (4.9 mmol/L) in children ≥10 years of age. For LDL-C levels between 130 and 189 mg/dL (3.4-4.89 mmol/L) despite dietary and lifestyle changes, the presence of additional risk factors and comorbid conditions would favor statin therapy. In the case of combined dyslipidemia, the primary treatment target is LDL-C ≤130 mg/dL (3.4 mmol/L) and the secondary target non-high-density lipoprotein cholesterol <145 mg/dL (3.7 mmol/L). If the triglyceride is ≥400 mg/dL (4.5 mmol/L), prescription omega-3 fatty acids and fibrates are considered. In the case of triglyceride >1000 mg/dL (11.3 mmol/L), dietary fat restriction remains the cornerstone of therapy, even though the landscape of medications is changing. CONCLUSION: Gene variants, acquired conditions, or both are responsible for dyslipidemia during childhood. Extreme elevations of triglycerides can lead to pancreatitis. Early identification and management of dyslipidemia and cardiovascular risk factors is extremely important.

Spatial variation in direct and indirect contact rates at the wildlife-livestock interface for informing disease management.

Little is known about disease transmission relevant contact rates at the wildlife-livestock interface and the factors shaping them. Indirect contact via shared resources is thought to be important but remains unquantified in most systems, making it challenging to evaluate the impact of livestock management practices on contact networks. Free-ranging wild pigs (Sus scrofa) in North America are an invasive, socially-structured species with an expanding distribution that pose a threat to livestock health given their potential to transmit numerous livestock diseases, such as pseudorabies, brucellosis, trichinellosis, and echinococcosis, among many others. Our objective in this study was to quantify the spatial variations in direct and indirect contact rates among wild pigs and cattle on a commercial cow-calf operation in Florida, USA. Using GPS data from 20 wild pigs and 11 cattle and a continuous-time movement model, we extracted three types of spatial contacts between wild pigs and cattle, including direct contact, indirect contact in the pastoral environment (unknown naturally occurring resources), and indirect contact via anthropogenic cattle resources (feed supplements and water supply troughs). We examined the effects of sex, spatial proximity, and cattle supplement availability on contact rates at the species level and characterized wild pig usage of cattle supplements. Our results suggested daily pig-cattle direct contacts occurred only occasionally, while a significant number of pig-cattle indirect contacts occurred via natural resources distributed heterogeneously across the landscape. At cattle supplements, more indirect contacts occurred at liquid molasses than water troughs or molasses-mineral block tubs due to higher visitation rates by wild pigs. Our results can be directly used for parameterizing epidemiological models to inform risk assessment and optimal control strategies for controlling transmission of shared diseases.

Perceived Stress and Molecular Bacterial Vaginosis in the National Institutes of Health Longitudinal Study of Vaginal Flora.

Vaginal microbiota provide the first line of defense against urogenital infections primarily through protective actions of Lactobacillus species Perceived stress increases susceptibility to infection through several mechanisms, including suppression of immune function. We investigated whether stress was associated with deleterious changes to vaginal bacterial composition in a subsample of 572 women in the Longitudinal Study of Vaginal Flora, sampled from 1999 through 2002. Using Cox proportional hazards models, both unadjusted and adjusted for sociodemographic factors and sexual behaviors, we found that participants who exhibited a 5-unit-increase in Cohen's Perceived Stress Scale had greater risk (adjusted hazard ratio (HR) = 1.40, 95% confidence interval (CI): 1.13, 1.74) of developing molecular bacterial vaginosis (BV), a state with low Lactobacillus abundance and diverse anaerobic bacteria. A 5-unit increase in stress score was also associated with greater risks of transitioning from the L. iners-dominated community state type (26% higher) to molecular-BV (adjusted HR = 1.26, 95% CI: 1.01, 1.56) or maintaining molecular-BV from baseline (adjusted HR = 1.23, 95% CI: 1.01, 1.47). Inversely, women with baseline molecular-BV reporting a 5-unit stress increase were less likely to transition to microbiota dominated by L. crispatus, L. gasseri, or L. jensenii (adjusted HR = 0.81, 95% CI: 0.68, 0.99). These findings suggest that psychosocial stress is associated with vaginal microbiota composition, inviting a more mechanistic exploration of the relationship between psychosocial stress and molecular-BV.

Assessing intrastate shipments from interstate data and expert opinion.

Live animal shipments are a potential route for transmitting animal diseases between holdings and are crucial when modelling spread of infectious diseases. Yet, complete contact networks are not available in all countries, including the USA. Here, we considered a 10% sample of Interstate Certificate of Veterinary Inspections from 1 year (2009). We focused on distance dependence in contacts and investigated how different functional forms affect estimates of unobserved intrastate shipments. To further enhance our predictions, we included responses from an expert elicitation survey about the proportion of shipments moving intrastate. We used hierarchical Bayesian modelling to estimate parameters describing the kernel and effects of expert data. We considered three functional forms of spatial kernels and the inclusion or exclusion of expert data. The resulting six models were ranked by widely applicable information criterion (WAIC) and deviance information criterion (DIC) and evaluated through within- and out-of-sample validation. We showed that predictions of intrastate shipments were mildly influenced by the functional form of the spatial kernel but kernel shapes that permitted a fat tail at large distances while maintaining a plateau-shaped behaviour at short distances better were preferred. Furthermore, our study showed that expert data may not guarantee enhanced predictions when expert estimates are disparate.