Transmission of drug-resistant TB threatens gains in global TB and HIV control, particularly in high-burden settings such as South Africa. Recent data suggests the majority of drug-resistant cases worldwide arise due to transmission, however, studies are needed to characterize the nature (e.g., location, timing) of transmission. In KwaZulu-Natal province, South Africa, we have demonstrated that up to 83% of XDR TB cases are genotypically-clustered, using IS6110 RFLP and targeted gene sequencing, suggesting person-to-person transmission is driving the XDR TB epidemic in this high-HIV prevalence setting. In the current study, we employed social network analysis to further characterize patterns of transmission.
We enrolled patients diagnosed with XDR TB by culture and drug-susceptibility testing in KwaZulu-Natal from 2010–2014. Patients were interviewed at the time of diagnosis about their social networks at home, work, and other community locations, as well as about hospitalizations in the five years preceding their XDR TB diagnosis. An epidemiologic link was defined as two participants having either a social network connection or overlapping admission at the same hospital.
Among 404 patients with XDR TB, the median age was 34 (IQR 28–43) and 58% were female. 311 (77%) patients were HIV-infected, with a median CD4 count of 255 cells/mm3 (IQR 117–431); 177 (57%) were on ART at the time of their XDR TB diagnosis and 155 (88%) had an undetectable viral load. Epidemiologic links were identified for 287 (71%) patients. 83 (21%) patients were linked as social network contacts; of these, 92% lived in the same home, 4% worked together, and 4% spent time together in a congregate setting (e.g., church, bar). 267 (66%) patients overlapped with other XDR TB patients in the hospital, 66 of whom were hospitalized at more than one hospital. There were 63 (16%) patients with both hospital and social network links to other XDR TB patients, four of whom are depicted in Figure 1.
The XDR TB epidemic in this high HIV prevalence setting in South Africa is being driven by direct transmission of drug-resistant TB strains in both hospitals and households. Social network analysis has provided valuable insights into the multitude of interactions associated with transmission. This more comprehensive understanding is important for designing interventions that both limit exposure in hospitals and focus contact tracing efforts to households where the majority of transmission is occurring.