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The United States official bovine tuberculosis (bTB) eradication program has utilized genotyping for Mycobacterium bovis isolates since 2000 and whole genome sequencing was implemented in 2013. The program has been highly successful, yet as bTB prevalence has reached historic lows, a small number of new bTB-affected cattle herds occur annually. Therefore, understanding the epidemiology of bTB transmission is critically important, in order to target limited resources for surveillance and achieve eradication. This evaluation described the diversity and epidemiology of M. bovis isolates identified in the USA livestock. Isolates from animals within the bTB endemic area of Michigan were excluded. Broad diversity was found among 1,248 isolates, collected from affected cattle and farmed cervids herds and fed cattle during 1989–2018. Nearly 70% of isolates from 109 herds/cases during 1999–2018 were European clonal complex 1 and 30% were European clonal complex 2. The sources of infection based on the herd investigation were known for 41% of herds/cases and 59% were not epidemiologically linked to another USA origin herd. Whole genome sequencing results were consistent with the investigation findings and previously unrecognized links between herds and cases were disclosed. For herds/cases with an unknown source of infection, WGS results suggested several possible sources, including undocumented cattle movement, imported cattle and humans. The use of WGS in new cases has reduced the time and costs associated with epidemiological investigations. Within herd SNP diversity was evaluated by examining 18 herds with 10 or more isolates sequenced. Forty percent of isolates had not diverged or accumulated any SNPs, and 86% of the isolates had accumulated 3 or fewer SNPs. The results of WGS does not support a bTB reservoir in USA cattle. The bTB eradication program appears to be highly effective as the majority of herds/cases in the USA are unique strains with limited herd to herd transmission.

In 2009, Mycobacterium bovis infection was detected in a herd of 60 elk (Cervus elaphus) and 50 fallow deer (Dama dama) in Nebraska, USA. Upon depopulation of the herd, the prevalence of bovine tuberculosis (TB) was estimated at ∼71–75%, based upon histopathology and culture results. Particularly with elk, gross lesions were often severe and extensive. One year ago, the majority of the elk had been tested for TB by single cervical test (SCT), and all were negative. After initial detection of a tuberculous elk in this herd, 42 of the 59 elk were tested by SCT. Of the 42 SCT-tested elk, 28 were TB-infected with only 3/28 reacting upon SCT. After SCT, serum samples were collected from the infected elk and fallow deer from this herd at necropsy and tested by three antibody detection methods including multiantigen print immunoassay, cervidTB STAT-PAK, and dual path platform VetTB (DPP). Serologic test sensitivity ranged from 79 to 97% depending on the test format and host species. Together, these findings demonstrate the opportunities for use of serodiagnosis in the rapid detection of TB in elk and fallow deer.

BackgroundBovine tuberculosis (TB) control programs generally rely on the tuberculin skin test (TST) for ante-mortem detection of Mycobacterium bovis-infected cattle.ResultsPresent findings demonstrate that a rapid antibody test based on Dual-Path Platform (DPP®) technology, when applied 1-3 weeks after TST, detected 9 of 11 and 34 of 52 TST non-reactive yet M. bovis-infected cattle from the US and GB, respectively. The specificity of the assay ranged from 98.9% (n = 92, US) to 96.0% (n = 50, GB) with samples from TB-free herds. Multi-antigen print immunoassay (MAPIA) revealed the presence of antibodies to multiple antigens of M. bovis in sera from TST non-reactors diagnosed with TB.ConclusionsThus, use of serologic assays in series with TST can identify a significant number of TST non-reactive tuberculous cattle for more efficient removal from TB-affected herds.

A USDA Early Response Team investigated deaths of several horses and a mule in northern Arizona at the request of local animal health officials. Thirteen animals (12 horses and 1 mule) housed at 5 facilities in a 7.4 square mile area died between August 1998 and January 1999. Clinical signs consisted of muscular weakness that rapidly progressed to lateral recumbency. Ten animals had paresis of the tongue, throat, or lips. Affected animals appeared alert and were interested in eating and drinking, even while recumbent. All 13 animals were euthanatized. Clostridium botulinum type C was isolated from feces or intestinal contents from 3 affected horses. Preformed toxin was detected in samples of soil and bird droppings collected from a nearby horse burial site. It was hypothesized that the outbreak was a result of birds, presumably ravens, feeding at the burial site and at horse facilities in the area that transferred toxin to the affected animals.

Our objective was to evaluate the effect that complexity in the form of different levels of spatial, population, and contact heterogeneity has in the predictions of a mechanistic epidemic model. A model that simulates the spatiotemporal spread of infectious diseases between animal populations was developed. Sixteen scenarios of foot-and-mouth disease infection in cattle were analyzed, involving combinations of the following factors: multiple production-types (PT) with heterogeneous contact and population structure versus single PT, random versus actual spatial distribution of population units, high versus low infectivity, and no vaccination versus preemptive vaccination. The epidemic size and duration was larger for scenarios with multiple PT versus single PT. Ignoring the actual unit locations did not affect the epidemic size in scenarios with multiple PT/high infectivity, but resulted in smaller epidemic sizes in scenarios using multiple PT/low infectivity. In conclusion, when modeling fast-spreading epidemics, knowing the actual locations of population units may not be as relevant as collecting information on population and contact heterogeneity. In contrast, both population and spatial heterogeneity might be important to model slower spreading epidemic diseases. Our findings can be used to inform data collection and modeling efforts to inform health policy and planning.

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