BackgroundAfter increases in tuberculosis notification rates, the Chief Medical Officer's Tuberculosis Action Plan in 2004 led to the introduction of the national Tuberculosis Strain-Typing Service (TB-STS), using MIRU-VNTR typing, in England in 2010. In addition to reducing the proportion of individuals who are misdiagnosed as having tuberculosis, the TB-STS could reduce tuberculosis incidence by increasing the detection of latent infections and by accelerating diagnosis of active cases, through better-targeted cluster investigation. Complex public health interventions are often implemented without a prospective assessment. We describe a service-wide evaluation of a TB-STS using laboratory and contact tracing data, and mathematical modelling, to estimate effects on tuberculosis incidence and cost-effectiveness. MethodsThe proportion of false-positive Mycobacterium tuberculosis isolates, which had not been identified before strain-typing results became available, was estimated from laboratory data. The effect of cluster investigations on diagnostic delay (time between symptom onset and date of diagnosis) was estimated for pulmonary tuberculosis cases diagnosed in 2010–11. The contact tracing yield (the median number of individuals with tuberculosis infection or active disease identified per case), according to whether cases were in clusters that were investigated, was estimated from data from north central London and Leicester in 2011. With an age-structured deterministic compartmental model, we explored the effectiveness of the TB-STS in population groups in which the incidence is low (native UK population), medium (similar to the non-white UK-born population), and high (similar to the non-UK-born population). Cost-effectiveness was estimated for various scenarios, with use of outputs from the model and service assessment, costs of establishing and running the service, and estimated costs and quality-adjusted life-year (QALY) effects of tuberculosis infection and disease. FindingsFrom 11 059 isolates typed between June, 2010, and June, 2012, there were 30 incidents of false-positive M tuberculosis isolation, 17 (57%) of which had not been identified before strain-typing results were available. Cluster investigations had no significant effect on the diagnostic delay (median 85 days [IQR 47–155] vs 77 days [41–157]) or on contact tracing yield (mean number of cases with active tuberculosis 0·33, 95% CI 0·1 to 0·6 vs 0·2, −0·0 to 0·5) or latent infection (1·9, 0·3–3·2 vs 1·7, 0·8–2·5). Mathematical modelling suggested that increasing the proportion of infections that are detected would have little effect on tuberculosis incidence and the number of cases prevented in the native UK population. In medium-incidence or high-incidence settings, under base-case assumptions, increasing the proportion of infections detected by a small amount (eg, from 3% per year to 13% per year with strain typing) could lead to about an 11% reduction in tuberculosis incidence over 20 years, ranging between 4% and 12% for pessimistic and optimistic assumptions, respectively, relating to uptake and retention of preventive treatment. In medium-incidence settings and with all other factors remaining unchanged, reducing diagnostic delay by 1 week could lead to greater than 25% reductions in tuberculosis incidence over 20 years. These findings are sensitive to the assumed proportion of immigrants who enter the UK with tuberculosis. Under base case assumptions, the service was not estimated to be cost-effective over a 20-year period (£97 311 per QALY). InterpretationInsufficient baseline and post-implementation data limit direct estimation of public-health outcomes and interpretation of the model. Present models suggest that the TB-STS is not cost-effective. However, the TB-STS provides an invaluable resource for epidemiological and microbiological research and surveillance, informing national and local tuberculosis control efforts; targeting population-level interventions; and contributing to understanding molecular epidemiology in Europe and worldwide. FundingPublic Health England's TB Strain Typing Project Board. JM is funded by a University College London and Public Health England Impact Studentship. IA is funded by an NIHR Senior Research Fellowship.
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