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.

BackgroundThe national tuberculosis strain typing service (TB-STS) was introduced in England in 2010. The TB-STS involves MIRU-VNTR typing of isolates from all TB patients for the prospective identification, reporting and investigation of TB strain typing clusters. As part of a mixed-method evaluation, we report on a repeated cross-sectional survey to illustrate the challenges surrounding the evaluation of a complex national public health intervention.MethodsAn online initial and follow-up questionnaire survey assessed the knowledge, attitudes and practices of public health staff, physicians and nurses working in TB control in November 2010 and March 2012. It included questions on the implementation, experience and uptake of the TB-STS. Participants that responded to both surveys were included in the analysis.Results248 participants responded to the initial survey and 137 of these responded to the follow-up survey (56% retention).Knowledge: A significant increase in knowledge was observed, including a rise in the proportion of respondents who had received training (28.6% to 67.9%, p = 0.003), and the self-rated knowledge of how to use strain typing had improved (‘no knowledge’ decreased from 43.2% to 27.4%).Attitudes: The majority of respondents found strain typing useful; the proportion that reported strain typing to be useful was similar across the two surveys (95.7% to 94.7%, p = 0.67).Practices: There were significant increases between the initial and follow-up surveys in the number of respondents who reported using strain typing (57.0% to 80.5%, p < 0.001) and the proportion of time health protection staff spent on investigating TB (2.74% to 7.08%, p = 0.04).ConclusionsEvaluation of a complex public health intervention is challenging. In this example, the immediate national roll-out of the TB-STS meant that a controlled survey design was not possible. This study informs the future development of the TB-STS by identifying the need for training to reach wider professional groups, and argues for its continuation based on service users’ perception that it is useful. By highlighting the importance of a well-defined sampling frame, collecting baseline information, and including all stakeholders, it provides lessons for the implementation of similar services in other countries and future evaluations of public health interventions.Electronic supplementary materialThe online version of this article (doi:10.1186/1471-2458-14-1023) contains supplementary material, which is available to authorized users.

ObjectivesTo systematically review the evidence for the impact of study design and setting on the interpretation of tuberculosis (TB) transmission using clustering derived from Mycobacterial Interspersed Repetitive Units-Variable Number Tandem Repeats (MIRU-VNTR) strain typing.Data sourcesMEDLINE, EMBASE, CINHAL, Web of Science and Scopus were searched for articles published before 21st October 2014.Review methodsStudies in humans that reported the proportion of clustering of TB isolates by MIRU-VNTR were included in the analysis. Univariable meta-regression analyses were conducted to assess the influence of study design and setting on the proportion of clustering.ResultsThe search identified 27 eligible articles reporting clustering between 0% and 63%. The number of MIRU-VNTR loci typed, requiring consent to type patient isolates (as a proxy for sampling fraction), the TB incidence and the maximum cluster size explained 14%, 14%, 27% and 48% of between-study variation, respectively, and had a significant association with the proportion of clustering.ConclusionsAlthough MIRU-VNTR typing is being adopted worldwide there is a paucity of data on how study design and setting may influence estimates of clustering. We have highlighted study design variables for consideration in the design and interpretation of future studies.

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