Modeling elk‐to‐livestock transmission risk to predict hotspots of brucellosis spillover

Tracking sero-molecular trends of swine brucellosis in Hawai'i and the central Pacific

Introduction

Brucellosis is a zoonotic disease of mammals caused by bacterial species of the Brucella genus. The reservoir for disease is typically mammals, with species of Brucella found infecting amphibians, bats, and marine mammals. Brucella spp. can pass directly to humans through contact with infected animals or their products. Brucella spp. can cause chronic debilitating infections in mammals, including humans, and is associated with spontaneous abortions in infected animals, causing reduced fecundity. In Hawai'i, terrestrial species that could harbor Brucella spp. include swine, cattle, horses, and axis deer among others. The numerous feral swine in Hawai'i are known to carry Brucella suis, with evidence supporting infections in cattle. Brucella suis also poses infection risk to humans, dogs, and potentially horses across the state.

Methods

In this study, 3,274 feral swine serum samples collected from 5 of the 8 main islands over a 15-year span were analyzed for exposure to B. suis. Of the 558 watersheds in the state, 77 were sampled as part of this effort. Spatial analysis was used to identify watersheds of concern. MLVA and whole genome SNP analysis was used for molecular epidemiological analysis.

Results

Statewide seropositivity rates were triple that of feral swine found in the conterminous United States. Smoothed positivity rates were highest on Maui, followed by O'ahu, and the island of Hawai'i. Island-by-island analysis found high brucellosis positivity levels associated with specific watersheds and agricultural areas. Local spatial autocorrelation identified hot spots on O'ahu and Hawai'i. MLVA analysis of available B. suis from Hawai'i found molecular epidemiological connections with B. suis found in French Polynesia and the mainland US while differing from those in Tonga, Western Polynesia. Strains from Hawai'i are phylogenetically closest to strains from the United States. MLVA and SNP analysis found B. suis strains from Hawai'i fell into the genetic group that contains biovar 1 B. suis.

Discussion

This work identified islands and watersheds of high brucellosis seropositivity in feral swine of Hawai'i, highlighting the magnitude of the zoonotic risk. Introduction of strains in recent history is unlikely due to modern animal trade and disease control practices. Genomic analysis of strains in Hawai'i and the Pacific area can provide hidden historical and local clues to brucellosis epidemiology in the state.

Estimating encounter-habitat relationships with scale-integrated resource selection functions

Encounters between animals occur when animals are close in space and time. Encounters are important in many ecological processes including sociality, predation and disease transmission. Despite this, there is little theory regarding the spatial distribution of encounters and no formal framework to relate environmental characteristics to encounters. The probability of encounter could be estimated with resource selection functions (RSFs) by comparing locations where encounters occurred to available locations where they may have occurred, but this estimate is complicated by the hierarchical nature of habitat selection. We developed a method to relate resources to the relative probability of encounter based on a scale-integrated habitat selection framework. This framework integrates habitat selection at multiple scales to obtain an appropriate estimate of availability for encounters. Using this approach, we related encounter probabilities to landscape resources. The RSFs describe habitat associations at four scales, home ranges within the study area, areas of overlap within home ranges, locations within areas of overlap, and encounters compared to other locations, which can be combined into a single scale-integrated RSF. We apply this method to intraspecific encounter data from two species: white-tailed deer (Odocoileus virginianus) and elk (Cervus elaphus) and interspecific encounter data from a two-species system of caribou (Rangifer tarandus) and coyote (Canis latrans). Our method produced scale-integrated RSFs that represented the relative probability of encounter. The predicted spatial distribution of encounters obtained based on this scale-integrated approach produced distributions that more accurately predicted novel encounters than a naïve approach or any individual scale alone. Our results highlight the importance of accounting for the conditional nature of habitat selection in estimating the habitat associations of animal encounters as opposed to 'naïve' comparisons of encounter locations with general availability. This method has direct relevance for testing hypotheses about the relationship between habitat and social or predator-prey behaviour and generating spatial predictions of encounters. Such spatial predictions may be vital for understanding the distribution of encounters driving disease transmission, predation rates and other population and community-level processes.

Fecal and vaginal microbiota of vaccinated and non-vaccinated pregnant elk challenged with Brucella abortus

Introduction

Brucella abortus is the causative agent of brucellosis in cattle and in humans, resulting in economic losses in the agricultural sector and representing a major threat to public health. Elk populations in the American Northwest are reservoirs for this bacterium and transmit the agent to domestic cattle herds. One potential strategy to mitigate the transmission of brucellosis by elk is vaccination of elk populations against B. abortus; however, elk appear to be immunologically distinct from cattle in their responses to current vaccination strategies. The differences in host response to B. abortus between cattle and elk could be attributed to differences between the cattle and elk innate and adaptive immune responses. Because species-specific interactions between the host microbiome and the immune system are also known to affect immunity, we sought to investigate interactions between the elk microbiome and B. abortus infection and vaccination.

Methods

We analyzed the fecal and vaginal microbial communities of B. abortus-vaccinated and unvaccinated elk which were challenged with B. abortus during the periparturient period.

Results

We observed that the elk fecal and vaginal microbiota are similar to those of other ruminants, and these microbial communities were affected both by time of sampling and by vaccination status. Notably, we observed that taxa representing ruminant reproductive tract pathogens tended to increase in abundance in the elk vaginal microbiome following parturition. Furthermore, many of these taxa differed significantly in abundance depending on vaccination status, indicating that vaccination against B. abortus affects the elk vaginal microbiota with potential implications for animal reproductive health.

Discussion

This study is the first to analyze the vaginal microbiota of any species of the genus Cervus and is also the first to assess the effects of B. abortus vaccination and challenge on the vaginal microbiome.

Reproductive Fate of Brucellosis-Seropositive Elk (Cervus canadensis): Implications for Disease Transmission Risk

Brucellosis is a disease caused by the bacterium Brucella abortus that infects elk (Cervus canadensis) and cattle (Bos taurus). There is the potential for transmission from wildlife to livestock through contact with infected material shed during abortions or live births. To understand the impact of exposure on pregnancy rates we captured 30-100 elk per year from 2011 through 2020, testing their blood for serologic exposure to B. abortus. Predicted pregnancy rates for seropositive animals were 9.6% lower in prime-age (2.5-15.5 yr; 85%, 95% confidence interval [CI]: 74-91%) and 37.7% lower in old (>15.5 yr; 43%, 95% CI: 19-71%) elk as compared with seronegative animals. To understand the risk of seropositive elk shedding B. abortus bacteria and the effects of exposure on elk reproductive performance, we conducted a 5-yr longitudinal study monitoring 30 seropositive elk. We estimated the annual probability of a seropositive elk having an abortion as 0.06 (95% CI: 0.02-0.15). We detected B. abortus at three abortions and two live births, using a combination of culture and PCR testing. The predicted probability of a pregnant seropositive elk shedding B. abortus during an abortion or live birth was 0.08 (95% CI: 0.04-0.19). To understand what proportion of seropositive elk harbored live B. abortus bacteria in their tissues, we euthanized seropositive elk at the end of 5 yr of monitoring and sampled tissues for B. abortus. Assuming perfect detection, the predicted probability of a seropositive elk having B. abortus in at least one tissue was 0.18 (95% CI: 0.06-0.43). The transmission risk seropositive elk pose is mitigated by decreased pregnancy rates, low probability of abortion events, low probability of shedding at live birth events, and reasonably low probability of B. abortus in tissues.

Elk migration influences the risk of disease spillover in the Greater Yellowstone Ecosystem

Wildlife migrations provide important ecosystem services, but they are declining. Within the Greater Yellowstone Ecosystem (GYE), some elk Cervus canadensis herds are losing migratory tendencies, which may increase spatiotemporal overlap between elk and livestock (domestic bison Bison bison and cattle Bos taurus), potentially exacerbating pathogen transmission risk.

We combined disease, movement, demographic and environmental data from eight elk herds in the GYE to examine the differential risk of brucellosis transmission (through aborted foetuses) from migrant and resident elk to livestock.

For both migrants and residents, we found that transmission risk from elk to livestock occurred almost exclusively on private ranchlands as opposed to state or federal grazing allotments. Weather variability affected the estimated distribution of spillover risk from migrant elk to livestock, with a 7%–12% increase in migrant abortions on private ranchlands during years with heavier snowfall. In contrast, weather variability did not affect spillover risk from resident elk.

Migrant elk were responsible for the majority (68%) of disease spillover risk to livestock because they occurred in greater numbers than resident elk. On a per‐capita basis, however, our analyses suggested that resident elk disproportionately contributed to spillover risk. In five of seven herds, we estimated that the per‐capita spillover risk was greater from residents than from migrants. Averaged across herds, an individual resident elk was 23% more likely than an individual migrant elk to abort on private ranchlands.

Our results demonstrate links between migration behaviour, spillover risk and environmental variability, and highlight the utility of integrating models of pathogen transmission and host movement to generate new insights about the role of migration in disease spillover risk. Furthermore, they add to the accumulating body of evidence across taxa that suggests that migrants and residents should be considered separately during investigations of wildlife disease ecology. Finally, our findings have applied implications for elk and brucellosis in the GYE. They suggest that managers should prioritize actions that maintain spatial separation of elk and livestock on private ranchlands during years when snowpack persists into the risk period.

The global epidemiology of Brucella infections in terrestrial wildlife: A meta-analysis

Brucellosis is a widespread zoonotic disease with serious consequences on human and animal health. Brucella infections were reported in many terrestrial wild animals, from subtropical and temperate regions to arctic regions. In many areas, the epidemiology of brucellosis in wildlife is closely associated with the occurrence of the disease in livestock. Some wild species may contribute to the re-introduction of Brucella infections in livestock (spillback), even in officially brucellosis-free (OBF) regions. Through meta-regression analysis, this study draws a global picture of the prevalence of Brucella spp. in terrestrial wild animals, trying to determine most affected subgroups as well as preferential sampling and screening methods. For this purpose, a literature search was carried out among publications published from 1983 to 2019. Different subgroups were compared according to animal species, feeding, gender, age as well as the method used for sampling and for brucellosis diagnostic. To determine heterogeneity of studies, chi-squared test was used and a random-effects model (REM) estimated the pooled prevalence among subgroups. A total of 68 publications, comprising 229 data reports/studies, were selected. The most-reported Brucella species in wildlife was Brucella abortus, and the highest prevalence rate was found in American bison, Bison bison (39.9%) followed by Alpine ibex, Capra ibex (33%). Serology was the most widely applied diagnostic approach (66%), while PCR appeared to be highly sensitive (36.62% of positive results). The gender of animals showed no significant association with the prevalence of brucellosis (p > .05). Blood samples and visceral organs constituted the great majority of specimen used for the detection of Brucella spp., while lymph nodes showed a high prevalence of positive samples (94.6%). The present study provides insight into the global epidemiology and enzootic potential of brucellosis in wild terrestrial animals worldwide, aiming at helping the appropriate authorities to strengthen prevention, surveillance and control strategies.

Confronting models with data: the challenges of estimating disease spillover

For pathogens known to transmit across host species, strategic investment in disease control requires knowledge about where and when spillover transmission is likely. One approach to estimating spillover is to directly correlate observed spillover events with covariates. An alternative is to mechanistically combine information on host density, distribution and pathogen prevalence to predict where and when spillover events are expected to occur. We use several case studies at the wildlife-livestock disease interface to highlight the challenges, and potential solutions, to estimating spatio-temporal variation in spillover risk. Datasets on multiple host species often do not align in space, time or resolution, and may have no estimates of observation error. Linking these datasets requires they be related to a common spatial and temporal resolution and appropriately propagating errors in predictions can be difficult. Hierarchical models are one potential solution, but for fine-resolution predictions at broad spatial scales, many models become computationally challenging. Despite these limitations, the confrontation of mechanistic predictions with observed events is an important avenue for developing a better understanding of pathogen spillover. Systems where data have been collected at all levels in the spillover process are rare, or non-existent, and require investment and sustained effort across disciplines. This article is part of the theme issue 'Dynamic and integrative approaches to understanding pathogen spillover'.