New Tool May Enable Real-Time Surveillance of Drug-Resistant Tuberculosis


A team of investigators have discovered a new way to link samples submitted for TB testing to individuals who provided them as well as where the sample was collected.

Tuberculosis (TB) is now the leading cause of death by infectious disease in the world, despite the fact that it is a preventable and curable disease. According to the World Health Organization, TB kills 5000 individuals every day, emphasizing a need for innovative strategies to contribute towards ending the global epidemic.

South Africa reports the highest rates of TB cases in the world—about 781 cases per 100,000 individuals each year. In comparison, the United States reported 2.9 cases per 100,000 individuals in 2016, according to the US Centers for Disease Control and Prevention.

In a new study published in PLOS Medicine, a team of investigators discovered a new technique that can link samples submitted for TB testing to the individuals who provided them along with the location the sample was collected from. This new approach provides surveillance needed to eradicate both TB and drug-resistant TB.

“Through this project, we have developed a road map for organizing routinely collected laboratory data from the South Africa National Health Laboratory Service, showing that molecular diagnostics can be transformed into a meaningful surveillance tool,” the authors write.

The investigators set out to find a way to link specimens to individual patients to overcome gaps in information provided in the Western Cape National Health Laboratory Services (NHLS) database, which does not provide unique patient identifiers for samples submitted for TB testing.

The team of investigators was led by Karen Jacobson, MD, assistant professor of medicine Boston University School of Medicine and Boston Medical Center.

For the retrospective study, the investigators assessed 2,219,891 samples from the NHLS database that were collected between January 1, 2008 and June 30, 2013. The investigators used a person-matching algorithm which included name, surname, age, location, and sex to match and link specimen records to individual patients. Through this technique, the investigators linked the samples to 799,779 individuals who could be pinpointed to specific clinic locations.

The investigators determined that 222,735, or 27.8%, of the cases were microbiologically confirmed TB; a total of 10,255 cases had documented resistance to rifampicin. (95% CI: 4.6-4.7)

Through mapping efforts, the investigators were able to conclude that rifampicin resistance was spatially heterogeneous—ranging from 0% to 25% across provinces—and fluctuated from year-to-year in different locations.

A limitation of the study is that the database lacks unique identifiers, and so, the figures are approximations that rely on the person-matching algorithm. Additionally, the database only contains figures from public clinics, therefore, data pertaining to private clinics or non-clinic locations are not included.

Despite these limitations, the person-matching method may serve as a promising tool to better understand TB trends and ultimately work towards eradicating the disease. Efforts to prevent multidrug-resistant TB differ from the control methods used to monitor TB, according to the investigators. Multidrug-resistant surveillance efforts must include a focus on real-time information of incidence of drug-resistant cases in order to initiate proper treatment.

“The epidemic appears very dynamic, requiring constant monitoring,” the authors write. “Improved knowledge of subnational geographic variability of RR-tuberculosis is essential for the improved design and implementation of national and local responses to reduce drug-resistant tuberculosis transmission and for timely context-specific resource allocation.”

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