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There is little information about the amount of recent tuberculosis transmission in low-income settings. Genetic clustering can help identify ongoing transmission events. A retrospective observational study was performed on Mycobacterium tuberculosis isolates from persons living with HIV (PLHIV) and HIV-seronegative participants who submitted samples to a referral tuberculosis laboratory in Guatemala City, Guatemala from 2010 to 2014. Genotyping results were classified according to the international spoligotyping database, SITVIT2. Spoligotype patterns were categorized as clustered or nonclustered depending on their genotype. The proportion of clustering and the index of recent transmission index (RTIn-1) were estimated. In the RTIn-1 method, clustered cases represent recent transmission, whereas nonclustered cases represent reactivation of older tuberculosis infections. As a secondary aim, the potential risk factors associated with clustering in isolates from the subset of participants living with HIV were explored. From 2010 to 2014, a total of 479 study participants were confirmed as culture-positive tuberculosis cases. Among the 400 available isolates, 71 spoligotype patterns were identified. Overall, the most frequent spoligotyping families were Latin American-Mediterranean (LAM) (39%), followed by T (22%) and Haarlem (14%). Out of the 400 isolates, 365 were grouped in 36 clusters (range of cluster size: 2–92). Thus, the proportion of clustering was 91% and the RTIn-1 was 82%. Among PLHIV, pulmonary tuberculosis was associated with clustering (OR = 4.3, 95% CI 1.0–17.7). Our findings suggest high levels of ongoing transmission of M. tuberculosis in Guatemala as revealed by the high proportion of isolates falling into genomic clusters.
Financial support: MEC was supported by the Schlumberger Foundation Faculty, Houston, TX, for the Future Fellowship.
Authors’ addresses: María Eugenia Castellanos, Global Health Institute, College of Public Health, University of Georgia, Athens, GA, Department of Epidemiology and Biostatistics, College of Public Health, University of Georgia, Athens, GA, and Public Health and Tropical Medicine, College of Public Health, Medical and Veterinary Sciences, James Cook University, Townsville, Queensland, Australia, E-mail: firstname.lastname@example.org. Dalia Lau-Bonilla, Department of Biochemistry and Microbiology, Universidad del Valle de Guatemala, Guatemala, E-mail: email@example.com. Anneliese Moller and Eduardo Arathoon, Asociación de Salud Integral, Guatemala City, Guatemala, E-mails: firstname.lastname@example.org and email@example.com. Blanca Samayoa, Asociación de Salud Integral, Guatemala City, Guatemala, and Facultad de Ciencias Químicas y Farmacia, Universidad de San Carlos de Guatemala, Guatemala, E-mail: firstname.lastname@example.org. Frederick Quinn, Department of Infectious Diseases, College of Veterinary Medicine, University of Georgia, Athens, GA, E-mail: email@example.com. Mark Ebell and Kevin Dobbin, Department of Epidemiology and Biostatistics, College of Public Health, University of Georgia, Athens, GA, E-mails: firstname.lastname@example.org and email@example.com. Christopher Whalen, Global Health Institute, College of Public Health, University of Georgia, Athens, GA, and Department of Epidemiology and Biostatistics, College of Public Health, University of Georgia, Athens, GA, E-mail: firstname.lastname@example.org.