Partitioning the risk of tuberculosis transmission in household contact studies

• Published in: PloS one Vol. 14; no. 10; p. e0223966
• Main Authors: McIntosh, Avery I, Jenkins, Helen E, Horsburgh, C Robert, Jones-López, Edward C, Whalen, Christopher C, Gaeddert, Mary, Marques-Rodrigues, Patricia, Ellner, Jerrold J, Dietze, Reynaldo, White, Laura F
• Format: Journal Article
• Language: English
• Published: United States Public Library of Science 22.10.2019; Public Library of Science (PLoS)
• Subjects: Adolescent; Age; Bayes Theorem; Bayesian analysis; Biology and Life Sciences; Brazil - epidemiology; Care and treatment; Child; Child, Preschool; Children; Communities; Contact Tracing - methods; Diagnosis; Disease transmission; Epidemiology; Family Characteristics; Female; Health risks; HIV; Households; Human immunodeficiency virus; Humans; Incidence; Infant; Infant, Newborn; Infections; Infectious diseases; Internet; Male; Medical diagnosis; Medicine; Medicine and Health Sciences; Models, Statistical; Mycobacterium tuberculosis - isolation & purification; People and Places; Public health; Research and Analysis Methods; Risk Factors; Statistical analysis; Studies; Tuberculosis; Tuberculosis, Pulmonary - diagnosis; Tuberculosis, Pulmonary - epidemiology; Tuberculosis, Pulmonary - microbiology; Uganda - epidemiology; Brazil; Uganda; United States > US; Massachusetts
• ISSN: 1932-6203; 1932-6203
• DOI: 10.1371/journal.pone.0223966

Household contact studies of tuberculosis (TB) are a common way to study disease transmission dynamics. However these studies lack a mechanism for accounting for community transmission, which is known to be significant, particularly in high burden settings. We illustrate a statistical approach for estimating both the correlates with transmission of TB in a household setting and the probability of community transmission using a modified Bayesian mixed-effects model. This is applied to two household contact studies in Vitória, Brazil from 2008-2013 and Kampala, Uganda from 1995-2004 that enrolled households with an individual that was recently diagnosed with pulmonary TB. We estimate the probability of community transmission to be higher in Uganda (ranging from 0.21 to 0.69, depending on HHC age and HIV status of the index case) than in Brazil (ranging from 0.13 for young children to 0.50 in adults). These estimates are consistent with a higher overall burden of disease in Uganda compared to Brazil. Our method also estimates an increasing risk of community-acquired TB with age of the household contact, consistent with existing literature. This approach is a useful way to integrate the role of the community in understanding TB disease transmission dynamics in household contact studies.