2015
DOI: 10.1093/aje/kwv160
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Age- and Sex-Specific Social Contact Patterns and Incidence ofMycobacterium tuberculosisInfection

Abstract: We aimed to model the incidence of infection with Mycobacterium tuberculosis among adults using data on infection incidence in children, disease prevalence in adults, and social contact patterns. We conducted a cross-sectional face-to-face survey of adults in 2011, enumerating “close” (shared conversation) and “casual” (shared indoor space) social contacts in 16 Zambian communities and 8 South African communities. We modeled the incidence of M. tuberculosis infection in all age groups using these contact patte… Show more

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Cited by 138 publications
(189 citation statements)
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References 27 publications
(29 reference statements)
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“…Being male was a strong predictor of LTBI on our study. Recent evidence suggests that social mixing and interaction vary significant by age and gender [45]. The higher rate of LTBI in urban males we observed may be due to the high risk of TB transmission in social gathering places, such as informal alcohol drinking establishments (shebeens) [39, 46], which are more frequented by men than women.…”
Section: Discussionmentioning
confidence: 74%
“…Being male was a strong predictor of LTBI on our study. Recent evidence suggests that social mixing and interaction vary significant by age and gender [45]. The higher rate of LTBI in urban males we observed may be due to the high risk of TB transmission in social gathering places, such as informal alcohol drinking establishments (shebeens) [39, 46], which are more frequented by men than women.…”
Section: Discussionmentioning
confidence: 74%
“…It has been suggested that older males have increased exposure through greater social contact, particularly to other adult males in the community [34]. An increased prevalence of risk factors among males like smoking [9] and alcoholism [35], which increase susceptibility to Mtb infection, could also explain the higher rate of infection in older males.…”
Section: Discussionmentioning
confidence: 99%
“…As a consequence, mathematical modeling of infectious diseases, initially based on simplifying theory-driven assumptions [1] such as homogeneous mixing, have gradually shifted towards using empirical evidence on real individuals’ interactions. In particular, over the past decade, field data on social contacts patterns have been gathered through diary-based surveys for a number of countries in Europe [27], North America [8], Oceania [9], Asia [6,1014], South America [15], and Africa [1618]. Age-specific mixing matrices built on the gathered data have been largely used to model the spread of epidemics driven by close-contact interactions [1922], and the transmission of endemic childhood infections [2327].…”
Section: Introductionmentioning
confidence: 99%