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Bovine Tuberculosis (bTB) roadmap:
Control Strategies

Roadmap for development of disease control strategies for bTB

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Prevalence of disease

Prevalence of disease / infection

Research Question

What are we trying to achieve and why? What is the problem we are trying to solve?

  • Establish how much infection is in a herd, area or territory (country) as this will influence the level of transmission; what are the trends?
  • How well are TB control measures and interventions working?
  • Active and/or passive surveillance in cattle is required at national level depending on prevalence to support trade and ensure food safety.
  • Establishing the prevalence of TB in wildlife via surveillance.
  • Establishing the level of M. bovis infection in humans.
  • Establishing the level of M. tuberculosis in cattle.
  • Development of key performance indicators of testers.

Research Gaps and Challenges

What are the scientific and technological challenges (knowledge gaps needing to be addressed)?

  • Performance characteristics of current tests.
  • Active and passive cattle surveillance tests and lab confirmation, while specific, have well documented variable (moderate) sensitivity and give a measure of apparent prevalence, which underestimates true prevalence.
  • Challenge to maximise yield of test positives within herds using test combinations.
  • Wildlife surveillance tests have relatively limited sensitivity.
  • Testing can be confounded by factors, such as coinfections, non-communicable disease, nutrition, stress etc.
  • Knowing when best to apply the GIFN test.
  • Importance of anergic animals.

Solution Routes

What approaches could/should be taken to address the research question?

  • Regular testing of cattle using diagnostic algorithm i.e., combination of tests based on estimated performance
    characteristics.
  • Routine testing of livestock
  • Capture and testing of wildlife populations or roadkill surveillance.

Dependencies

What else needs to be done before we can solve this need?

  • The development, evaluation, and validation of more rapid, sensitive, and specific diagnostics.
  • Understanding and monitoring test performance characteristics (epidemiology) and configuring testing algorithms.

State Of the Art

Existing knowledge including successes and failures