Katie Portacci

The impact of movements and animal density on continental scale cattle disease outbreaks in the United States.

Globalization has increased the potential for the introduction and spread of novel pathogens over large spatial scales necessitating continental-scale disease models to guide emergency preparedness. Livestock disease spread models, such as those for the 2001 foot-and-mouth disease (FMD) epidemic in the United Kingdom, represent some of the best case studies of large-scale disease spread. However, generalization of these models to explore disease outcomes in other systems, such as the United States’s cattle industry, has been hampered by differences in system size and complexity and the absence of suitable livestock movement data. Here, a unique database of US cattle shipments allows estimation of synthetic movement networks that inform a near-continental scale disease model of a potential FMD-like (i.e., rapidly spreading) epidemic in US cattle. The largest epidemics may affect over one-third of the US and 120,000 cattle premises, but cattle movement restrictions from infected counties, as opposed to national movement moratoriums, are found to effectively contain outbreaks. Slow detection or weak compliance may necessitate more severe state-level bans for similar control. Such results highlight the role of large-scale disease models in emergency preparedness, particularly for systems lacking comprehensive movement and outbreak data, and the need to rapidly implement multi-scale contingency plans during a potential US outbreak.

A Bayesian Approach for Modeling Cattle Movements in the United States: Scaling up a Partially Observed Network

Networks are rarely completely observed and prediction of unobserved edges is an important problem, especially in disease spread modeling where networks are used to represent the pattern of contacts. We focus on a partially observed cattle movement network in the U.S. and present a method for scaling up to a full network based on Bayesian inference, with the aim of informing epidemic disease spread models in the United States. The observed network is a 10% state stratified sample of Interstate Certificates of Veterinary Inspection that are required for interstate movement; describing approximately 20,000 movements from 47 of the contiguous states, with origins and destinations aggregated at the county level. We address how to scale up the 10% sample and predict unobserved intrastate movements based on observed movement distances. Edge prediction based on a distance kernel is not straightforward because the probability of movement does not always decline monotonically with distance due to underlying industry infrastructure. Hence, we propose a spatially explicit model where the probability of movement depends on distance, number of premises per county and historical imports of animals. Our model performs well in recapturing overall metrics of the observed network at the node level (U.S. counties), including degree centrality and betweenness; and performs better compared to randomized networks. Kernel generated movement networks also recapture observed global network metrics, including network size, transitivity, reciprocity, and assortativity better than randomized networks. In addition, predicted movements are similar to observed when aggregated at the state level (a broader geographic level relevant for policy) and are concentrated around states where key infrastructures, such as feedlots, are common. We conclude that the method generally performs well in predicting both coarse geographical patterns and network structure and is a promising method to generate full networks that incorporate the uncertainty of sampled and unobserved contacts.

A national-scale picture of U.S. cattle movements obtained from Interstate Certificate of Veterinary Inspection data

We present the first comprehensive description of how shipments of cattle connect the geographic extent and production diversity of the United States cattle industry. We built a network of cattle movement from a state-stratified 10% systematic sample of calendar year 2009 Interstate Certificates of Veterinary Inspection (ICVI) data. ICVIs are required to certify the apparent health of cattle moving across state borders and allow us to examine cattle movements at the county scale. The majority of the ICVI sample consisted of small shipments (<20 head) moved for feeding and beef production. Geographically, the central plains states had the most connections, correlated to feeding infrastructure. The entire nation was closely connected when interstate movements were summarized at the state level. At the county-level, the U.S. is still well connected geographically, but significant heterogeneities in the location and identity of counties central to the network emerge. Overall, the network of interstate movements is described by a hub structure, with a few counties sending or receiving extremely large numbers of shipments and many counties sending and receiving few shipments. The county-level network also has a very low proportion of reciprocal movements, indicating that high-order network properties may be better at describing a countys importance than simple summaries of the number of shipments or animals sent and received. We suggest that summarizing cattle movements at the state level homogenizes the network and a county level approach is most appropriate for examining processes influenced by cattle shipments, such as economic analyses and disease outbreaks.

Sources of bovine tuberculosis in the United States

Despite control and eradication efforts, bovine tuberculosis continues to be identified at low levels among cattle in the United States. We evaluated possible external sources of infection by characterizing the genetic relatedness of bovine tuberculosis from a national database of reported infections, comparing strains circulating among US cattle with those of imported cattle, and farmed and wild cervids. Farmed cervids maintained a genetically distinct Mycobacterium bovis strain, and cattle occasionally became infected with this strain. In contrast, wild cervids acted as an epidemiologically distinct group, instead hosting many of the same strains found in cattle, and the data did not show a clear transmission direction. Cattle from Mexico hosted a higher overall richness of strains than US cattle, and many of those strains were found in both US and Mexican cattle. However, these two populations appeared to be well-mixed with respect to their M. bovis lineages, and higher resolution data is necessary to infer the direction of recent transmission. Overall patterns of both host and geographic distributions were highly variable among strains, suggesting that different sources or transmission mechanisms are contributing to maintaining different strains.

Assessment of paper interstate certificates of veterinary inspection used to support disease tracing in cattle

OBJECTIVE To evaluate the differences among each states Interstate Certificate of Veterinary Inspection (ICVI) form and the legibility of data on paper ICVIs used to support disease tracing in cattle. DESIGN Descriptive retrospective cross-sectional study. SAMPLE Examples of ICVIs from 50 states and 7,630 randomly sampled completed paper ICVIs for cattle from 48 states. PROCEDURES Differences among paper ICVI forms from all 50 states were determined. Sixteen data elements were selected for further evaluation of their value in tracing cattle. Completed paper ICVIs for interstate cattle exports in 2009 were collected from 48 states. Each of the 16 data elements was recorded as legible, absent, or illegible on forms completed by accredited veterinarians, and results were summarized by state. Mean values for legibility at the state level were used to estimate legibility of data at the national level. RESULTS ICVIs were inconsistent among states in regard to data elements requested and availability of legible records. A mean ± SD of 70.0 ± 22.1% of ICVIs in each state had legible origin address information. Legible destination address information was less common, with 55.0 ± 21.4% of records complete. Incomplete address information was most often a result of the field having been left blank. Official animal identification was present on 33.1% of ICVIs. CONCLUSIONS AND CLINICAL RELEVANCE The inconsistency among state ICVI forms and quality of information provided on paper ICVIs could lead to delays and the need for additional resources to trace cattle, which could result in continued spread of disease. Standardized ICVIs among states and more thorough recording of information by accredited veterinarians or expanded usage of electronic ICVIs could enhance traceability of cattle during an outbreak.

Shifting brucellosis risk in livestock coincides with spreading seroprevalence in elk

Tracking and preventing the spillover of disease from wildlife to livestock can be difficult when rare outbreaks occur across large landscapes. In these cases, broad scale ecological studies could help identify risk factors and patterns of risk to inform management and reduce incidence of disease. Between 2002 and 2014, 21 livestock herds in the Greater Yellowstone Area (GYA) were affected by brucellosis, a bacterial disease caused by Brucella abortus, while no affected herds were detected between 1990 and 2001. Using a Bayesian analysis, we examined several ecological covariates that may be associated with affected livestock herds across the region. We showed that livestock risk has been increasing over time and expanding outward from the historical nexus of brucellosis in wild elk on Wyoming’s feeding grounds where elk are supplementally fed during the winter. Although elk were the presumed source of cattle infections, occurrences of affected livestock herds were only weakly associated with the density of seropositive elk across the GYA. However, the shift in livestock risk did coincide with recent increases in brucellosis seroprevalence in unfed elk populations. As increasing brucellosis in unfed elk likely stemmed from high levels of the disease in fed elk, disease-related costs of feeding elk have probably been incurred across the entire GYA, rather than solely around the feeding grounds. Our results suggest that focused disease mitigation in areas where seroprevalence in unfed elk is high could reduce the spillover of brucellosis to livestock. We also highlight the need to better understand the epidemiology of spillover events with detailed histories of disease testing, calving, and movement of infected livestock. Finally, we recommend using case-control studies to investigate local factors important to livestock risk.

Assessing the potential for Burkholderia pseudomallei in the southeastern United States

153 Melioidosis is an underreported zoonosis in many countries where environmental conditions are favorable for growth of Burkholderia pseudomallei, the causative agent. The disease is most often detected in tropical areas such as Southeast Asia and northern Australia, where the case fatality rate in humans is estimated to be as high as 50%. Diagnosis is difficult owing to a lack of specific clinical signs and limitations of currently available diagnostic tests. Cases of melioidosis involving animals are sporadically reported, and the global extent of B pseudomallei in the environment is not well understood. Burkholderia pseudomallei has been proposed for inclusion on the USDA’s National List of Reportable Animal Diseases and has been classified as a category B bioterrorism agent by the US Department of Health and Human Services. Burkholderia pseudomallei is also designated as a tier-1 select agent under the Federal Select Agent Program because it is among “the biological agents and toxins that present the greatest risk of deliberate misuse with significant potential for mass casualties or devastating effect to the economy, critical infrastructure, or public confidence and poses a severe threat to public health and safety.” Burkholderia pseudomallei is not known to be present in the continental United States, other than in select research laboratories, but is now considered endemic in Puerto Rico. In addition, the number of human cases diagnosed in the United States has increased in recent years, and not all cases can be attributed to travel outside the United States. The present report describes the epidemiology of B pseudomallei infection in domestic animals and assesses the potential for establishment of the organism in the southeastern United States. To minimize the consequences of environmental contamination and the possibility that the organism will become endemic, veterinarians should be aware of the signs of melioidosis in domestic animals and of procedures for diagnosing and reporting the condition. Assessing the potential for Burkholderia pseudomallei in the southeastern United States

Mapping U.S. cattle shipment networks: Spatial and temporal patterns of trade communities from 2009 to 2011

The application of network analysis to cattle shipments broadens our understanding of shipment patterns beyond pairwise interactions to the network as a whole. Such a quantitative description of cattle shipments in the U.S. can identify trade communities, describe temporal shipment patterns, and inform the design of disease surveillance and control strategies. Here, we analyze a longitudinal dataset of beef and dairy cattle shipments from 2009 to 2011 in the United States to characterize communities within the broader cattle shipment network, which are groups of counties that ship mostly to each other. Because shipments occur over time, we aggregate the data at various temporal scales to examine the consistency of network and community structure over time. Our results identified nine large (>50 counties) communities based on shipments of beef cattle in 2009 aggregated into an annual network and nine large communities based on shipments of dairy cattle. The size and connectance of the shipment network was highly dynamic; monthly networks were smaller than yearly networks and revealed seasonal shipment patterns consistent across years. Comparison of the shipment network over time showed largely consistent shipping patterns, such that communities identified on annual networks of beef and diary shipments from 2009 still represented 41-95% of shipments in monthly networks from 2009 and 41-66% of shipments from networks in 2010 and 2011. The temporal aspects of cattle shipments suggest that future applications of the U.S. cattle shipment network should consider seasonal shipment patterns. However, the consistent within-community shipping patterns indicate that yearly communities could provide a reasonable way to group regions for management.

Model-guided suggestions for targeted surveillance based on cattle shipments in the U.S.

Risk-based sampling is an essential component of livestock health surveillance because it targets resources towards sub-populations with a higher risk of infection. Risk-based surveillance in U.S. livestock is limited because the locations of high-risk herds are often unknown and data to identify high-risk herds based on shipments are often unavailable. In this study, we use a novel, data-driven network model for the shipments of cattle in the U.S. (the U.S. Animal Movement Model, USAMM) to provide surveillance suggestions for cattle imported into the U.S. from Mexico. We describe the volume and locations where cattle are imported and analyze their predicted shipment patterns to identify counties that are most likely to receive shipments of imported cattle. Our results suggest that most imported cattle are sent to relatively few counties. Surveillance at 10 counties is predicted to sample 22-34% of imported cattle while surveillance at 50 counties is predicted to sample 43%-61% of imported cattle. These findings are based on the assumption that USAMM accurately describes the shipments of imported cattle because their shipments are not tracked separately from the remainder of the U.S. herd. However, we analyze two additional datasets - Interstate Certificates of Veterinary Inspection and brand inspection data - to ensure that the characteristics of potential post-import shipments do not change on an annual scale and are not dependent on the dataset informing our analyses. Overall, these results highlight the utility of USAMM to inform targeted surveillance strategies when complete shipment information is unavailable.