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The prospective evaluation of the TB strain typing service in England: a mixed methods study
  1. J Mears1,
  2. E Vynnycky2,3,
  3. J Lord4,
  4. M W Borgdorff5,6,
  5. T Cohen7,
  6. D Crisp8,
  7. J A Innes9,
  8. M Lilley10,
  9. H Maguire11,
  10. T D McHugh12,
  11. G Woltmann13,
  12. I Abubakar1,14,
  13. P Sonnenberg1
  1. 1Research Department of Infection and Population Health, University College London, London, UK
  2. 2Modelling and Economics Unit, Public Health England, London, UK
  3. 3Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, UK
  4. 4Health Economics Research Group, Brunel University, London, UK
  5. 5Department of Infectious Diseases, Public Health Service (GGD) Amsterdam, Amsterdam, The Netherlands
  6. 6Department of Clinical Epidemiology, Academic Medical Centre, University of Amsterdam, The Netherlands
  7. 7Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, USA
  8. 8George Elliot NHS Trust, Warwickshire, UK
  9. 9Department of Infection and Tropical Medicine, Birmingham Heartlands Hospital, Heart of England NHS Foundation Trust, Birmingham, UK
  10. 10South Midlands and Hertfordshire Public Health England Centre, Herts, UK
  11. 11Field Epidemiology Services, Public Health England, London, UK
  12. 12Research Department of Infection, University College London, London, UK
  13. 13Department of Respiratory Medicine, University Hospitals Leicester, Glenfield Hospital, Leicester
  14. 14Clinical Trials Unit, Medical Research Council, London, UK
  1. Correspondence to Dr Pam Sonnenberg, Research Department of Infection and Population Health, University College London, Mortimer Market Centre, London WC1E 6JB, UK; p.sonnenberg{at}ucl.ac.uk

Abstract

Background In response to rising TB notification rates in England, universal strain typing was introduced in 2010. We evaluated the acceptability, effectiveness and cost-effectiveness of the TB strain typing service (TB-STS).

Methods We conducted a mixed-methods evaluation using routine laboratory, clinic and public health data. We estimated the effect of the TB-STS on detection of false positive Mycobacterium tuberculosis diagnoses (2010–2012); contact tracing yield (number of infections or active disease per pulmonary TB case); and diagnostic delay. We developed a deterministic age-structured compartmental model to explore the effectiveness of the TB-STS, which informed a cost-effectiveness analysis.

Results Semi-structured interviews explored user experience. Strain typing identified 17 additional false positive diagnoses. The TB-STS had no significant effect on contact tracing yield or diagnostic delay. Mathematical modelling suggested increasing the proportion of infections detected would have little value in reducing TB incidence in the white UK-born population. However, in the non-white UK-born and non-UK-born populations, over 20 years, if detection of latent infection increases from 3% to 13% per year, then TB incidence would decrease by 11%; reducing diagnostic delay by one week could lead to 25% reduction in incidence. The current TB-STS was not predicted to be cost-effective over 20 years (£95 628/quality-adjusted life-years). Interviews found people had mixed experiences, but identified broader benefits, of the TB-STS.

Conclusions To reduce costs, improve efficiency and increase effectiveness, we recommend changes to the TB-STS, including discontinuing routine cluster investigations and focusing on reducing diagnostic delay across the TB programme. This evaluation of a complex intervention informs the future of strain typing in the era of rapidly advancing technologies.

  • Tuberculosis

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