Tuberculosis (TB) remains a significant health problem internationally, causing 1.4 million deaths per year. Over one quarter of these occur in India, prompting the country to announce a goal of universal access to quality TB diagnosis and treatment. This goal is complicated by the complex health care system in India, with many people depending on private providers with no formal medical training or with some training in allopathic or non-allopathic training. While a Revised National Tuberculosis Control Programme (RNTCP) has made progress over the last 15 years in improving TB control in the public sector, many people turn to the public sector only as a last resort. There is a need to extend the current narrow implementation strategy to include the private sector and improve referral networks between the private and public sectors. In this context, combined with improved funding, the Xpert MTB/RIF, a recently implemented tuberculosis (TB) test, has the potential to control the TB epidemic in India.
Xpert MTB/RIF is a new TB diagnostic test with improved sensitivity compared to other currently used diagnostic tests, including the sputum smear microscopy test commonly used in the public sector in India and the even lower-performing tests used in the private sector, such as antibody or interferon-gamma release assays. It is a molecular test that uses semi-automated PCR to detect mycobacterial DNA. It has the added advantage of being able to detect resistance to the most effective TB antibiotic rifampicin, due to inclusion of specific primers. However, the cost of Xpert MTB/RIF is substantial and resource constraints currently dictate that the RNTCP is implementing this test chiefly as a rapid drug susceptibility testing method in vulnerable adults and children with HIV or at high risk of multi-drug resistant TB, rather than as a rapid and sensitive diagnostic test for TB.
In the current study, the research team constructed a mathematical model of tuberculosis transmission, care-seeking behaviour and diagnostic/treatment practices in India to predict the impact on TB incidence if six different rollout strategies were to be implemented. The most effective predicted scenario envisaged adding Xpert MTB/RIF access for 20% of all individuals with TB symptoms seeking diagnosis in the public sector and 20% of individuals seeking care from qualified private practitioners. Compared to the current implementation strategy, this scenario would be predicted to reduce TB incidence by 14.1%. However, it would entail substantial cost as it would require more than 2,200 Xpert machines and reliable treatment referral. It is worth noting that a scenario envisaging encouragement of informal private providers to refer suspected TB cases to the public sector for diagnosis using currently available tests predicted a greater impact on TB incidence than if the Xpert system were scaled up only within the public sector.
While the authors acknowledge that their findings must be interpreted in the light of uncertainties in the assumptions made in the model, they are confident that: “Xpert [MTB/RIF] ... could substantially reduce the burden of TB disease due to poor diagnosis in India; however, this impact depends not only on the accuracy of the test, but also on the behavior of both patients and providers, their level of access to new tools, and quality TB treatment following diagnosis.”
The authors conclude: “any Xpert [MTB/RIF] rollout strategy must also consider the complex health-care infrastructure into which the test is being rolled out. To achieve maximum impact of novel diagnostics, India should engage the private sector, improve quality of care across all sectors, and dramatically increase resources.”
Salje H, Andrews JR, Deo S, Satyanarayana S, Sun AY, et al. (2014) The Importance of Implementation Strategy in Scaling Up Xpert MTB/RIF for Diagnosis of Tuberculosis in the Indian Health-Care System: A Transmission Model. PLoS Med 11(7): e1001674. doi:10.1371/journal.pmed.1001674;
News source: PLoS Medicine