Cross-species transmission potential between wild pigs, livestock, poultry, wildlife, and humans: implications for disease risk management in North America

Cross-species disease transmission between wildlife, domestic animals and humans is an increasing threat to public and veterinary health. Wild pigs are increasingly a potential veterinary and public health threat. Here we investigate 84 pathogens and the host species most at risk for transmission with wild pigs using a network approach. We assess the risk to agricultural and human health by evaluating the status of these pathogens and the co-occurrence of wild pigs, agriculture and humans. We identified 34 (87%) OIE listed swine pathogens that cause clinical disease in livestock, poultry, wildlife, and humans. On average 73% of bacterial, 39% of viral, and 63% of parasitic pathogens caused clinical disease in other species. Non-porcine livestock in the family Bovidae shared the most pathogens with swine (82%). Only 49% of currently listed OIE domestic swine diseases had published wild pig surveillance studies. The co-occurrence of wild pigs and farms increased annually at a rate of 1.2% with as much as 57% of all farms and 77% of all agricultural animals co-occurring with wild pigs. The increasing co-occurrence of wild pigs with livestock and humans along with the large number of pathogens shared is a growing risk for cross-species transmission

Estimating and exploring the proportions of inter- and intrastate cattle shipments in the United States

Mathematical models are key tools for the development of surveillance, preparedness and response plans for the potential events of emerging and introduced foreign animal diseases. Creating these types of plans requires data; when data are incomplete, mathematical models can help fill in missing information, provided they are informed by the data that are available. In the United States, the most complete national-scale data available on cattle shipments are based on Interstate Certificates of Veterinary Inspection, which track the shipment of cattle between states; data on intrastate cattle shipments are lacking. Here we develop four new datasets on intrastate cattle shipments in the U.S., including an expert elicitation survey covering 19 states and territories and three state-level brand inspection data sets. The expert elicitation survey provides estimates on the proportion of shipments that travel interstate over multiple regions of the U.S. These survey data also identify differences in shipment patterns between regions, cattle commodity types, and sectors of the cattle industry. These survey data cover more states than any other source of intrastate data; however, one limitation of these data is the small number of participating experts in many of the states, only seven of the 19 responding states and territories had a group size of three or larger. The brand data sets include origin and destination information for both intra- and interstate shipments. These data, therefore, also provide detailed information on the proportion of interstate shipments in three Western states, including the temporal and geographic variation in shipments. Because the survey and brand data overlap in the Western U.S., they can be compared. We find that in the Western U.S. the expert estimates of the overall proportion of cattle shipments matched the brand data well. However, the experts estimated that there would be larger differences in beef and dairy shipments than the brand data show. This suggests the cattle industries in the West may be sending similar proportions of commodity specific cattle shipments over state lines. We additionally used the expert survey data to explore how differences in the proportion of interstate shipments can change predictions about cattle shipment patterns using the example of model-guided suggestions for targeted surveillance in Texas. Together these four data sets are the most extensive and geographically comprehensive information to date on intrastate cattle shipments. Additionally, our analyses on predicted shipment patterns suggest that assumptions about intrastate shipments could have consequences for targeted surveillance

Estimating and exploring the proportions of inter- and intrastate cattle shipments in the United States

Mathematical models are key tools for the development of surveillance, preparedness and response plans for the potential events of emerging and introduced foreign animal diseases. Creating these types of plans requires data; when data are incomplete, mathematical models can help fill in missing information, provided they are informed by the data that are available. In the United States, the most complete national-scale data available on cattle shipments are based on Interstate Certificates of Veterinary Inspection, which track the shipment of cattle between states; data on intrastate cattle shipments are lacking. Here we develop four new datasets on intrastate cattle shipments in the U.S., including an expert elicitation survey covering 19 states and territories and three state-level brand inspection data sets. The expert elicitation survey provides estimates on the proportion of shipments that travel interstate over multiple regions of the U.S. These survey data also identify differences in shipment patterns between regions, cattle commodity types, and sectors of the cattle industry. These survey data cover more states than any other source of intrastate data; however, one limitation of these data is the small number of participating experts in many of the states, only seven of the 19 responding states and territories had a group size of three or larger. The brand data sets include origin and destination information for both intra- and interstate shipments. These data, therefore, also provide detailed information on the proportion of interstate shipments in three Western states, including the temporal and geographic variation in shipments. Because the survey and brand data overlap in the Western U.S., they can be compared. We find that in the Western U.S. the expert estimates of the overall proportion of cattle shipments matched the brand data well. However, the experts estimated that there would be larger differences in beef and dairy shipments than the brand data show. This suggests the cattle industries in the West may be sending similar proportions of commodity specific cattle shipments over state lines. We additionally used the expert survey data to explore how differences in the proportion of interstate shipments can change predictions about cattle shipment patterns using the example of model-guided suggestions for targeted surveillance in Texas. Together these four data sets are the most extensive and geographically comprehensive information to date on intrastate cattle shipments. Additionally, our analyses on predicted shipment patterns suggest that assumptions about intrastate shipments could have consequences for targeted surveillance

Paranannizziopsis spp. infections in wild snakes and a qPCR assay for detection of the fungus

The emergence of ophidiomycosis (or snake fungal disease) in snakes has prompted increased awareness of the potential effects of fungal infections on wild reptile populations. Yet, aside from Ophidiomyces ophidiicola, little is known about other mycoses affecting wild reptiles. The closely related genus Paranannizziopsis has been associated with dermatomycosis in snakes and tuataras in captive collections, and P. australasiensis was recently identified as the cause of skin infections in non-native wild panther chameleons (Furcifer pardalis) in Florida, USA. Here we describe five cases of Paranannizziopsis spp. associated with skin lesions in wild snakes in North America and one additional case from a captive snake from Connecticut, USA. In addition to demonstrating that wild Nearctic snakes can serve as a host for these fungi, we also provide evidence that the genus Paranannizziopsis is widespread in wild snakes, with cases being identified in Louisiana (USA), Minnesota (USA), Virginia (USA), and British Columbia (Canada). Phylogenetic analyses conducted on multiple loci of the fungal strains we isolated identified P. australasiensis in Louisiana and Virginia; the remaining strains from Minnesota and British Columbia did not cluster with any of the described species of Paranannizziopsis, although the strains from British Columbia appear to represent a single lineage. Finally, we designed a pan-Paranannizziopsis real-time PCR assay targeting the internal transcribed spacer region 2. This assay successfully detected DNA of all described species of Paranannizziopsis and the two potentially novel taxa isolated in this study and did not cross-react with closely related fungi or other fungi commonly found on the skin of snakes. The assay was 100% sensitive and specific when screening clinical (skin tissue or skin swab) samples, although full determination of the assay’s performance will require additional follow up due to the small number of clinical samples (n = 14 from 11 snakes) available for testing in our study. Nonetheless, the PCR assay can provide an important tool in further investigating the prevalence, distribution, and host range of Paranannizziopsis spp. and facilitate more rapid diagnosis of Paranannizziopsis spp. infections that are otherwise difficult to differentiate from other dermatomycoses

Pathology and Case Definition of Severe Perkinsea Infection of Frogs

Severe Perkinsea infection (SPI) is an emerging disease of frogs responsible for mass mortalities of tadpoles across the United States. It is caused by protozoa belonging to the phylum Perkinsozoa that form a distinct group referred to as the Pathogenic Perkinsea Clade of frogs. In this work, we provide detailed description of gross and histologic lesions from 178 naturally infected tadpoles, including 10 species from 22 mortality events and 6 amphibian health monitoring studies from diverse geographic areas. On external examination, we observed abdominal distension (10, 5.6%), cutaneous erythema and petechia (3, 1.7%), subcutaneous edema (3, 1.7%), and areas of white skin discoloration (3, 1.7%). On macroscopic examination of internal organs, we found hepatomegaly (68, 38.2%), splenomegaly (51, 28.7%), nephromegaly (47, 26.4%), ascites (15, 8.4%), segmental irregular thickening and white discoloration of the intestine (8, 4.5%), pancreatomegaly (4, 2.2%), and pancreatic petechia (1, 0.6%). Histologically, over 60% of the liver (148/165, 89.7%), kidney (113/147, 76.9%), spleen (96/97, 99%), and pancreas (46/68, 67.6%) were invaded by myriad intracellular and extracellular Perkinsea hypnospore-like and trophozoite-like organisms. Numerous other tissues were affected to a lesser extent. Mild histiocytic inflammation with fewer lymphocytes or eosinophils was commonly observed in areas of infection that were not obscured by lympho-granulocytic hematopoietic tissue. In light of these observations, we suggest a logical pathogenesis sequence. Finally, we propose a case definition for SPI to promote standardized communication of results and prevent misdiagnosis with epidemiological and pathologically overlapping diseases such as ranavirosis

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

tWe present the first comprehensive description of how shipments of cattle connect thegeographic extent and production diversity of the United States cattle industry. We built anetwork of cattle movement from a state-stratified 10% systematic sample of calendar year2009 Interstate Certificates of Veterinary Inspection (ICVI) data. ICVIs are required to certifythe apparent health of cattle moving across state borders and allow us to examine cattlemovements at the county scale. The majority of the ICVI sample consisted of small ship-ments (head) moved for feeding and beef production. Geographically, the central plainsstates had the most connections, correlated to feeding infrastructure. The entire nation wasclosely connected when interstate movements were summarized at the state level. At thecounty-level, the U.S. is still well connected geographically, but significant heterogeneitiesin the location and identity of counties central to the network emerge. Overall, the networkof interstate movements is described by a hub structure, with a few counties sending orreceiving extremely large numbers of shipments and many counties sending and receiv-ing few shipments. The county-level network also has a very low proportion of reciprocalmovements, indicating that high-order network properties may be better at describing acounty’s importance than simple summaries of the number of shipments or animals sentand received. We suggest that summarizing cattle movements at the state level homoge-nizes the network and a county level approach is most appropriate for examining processesinfluenced 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 wellmixed 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

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