![]() However, the number of contacts varied markedly by age as shown in Figure S2. The median number of daily contacts per participant was 30 (IQR: 12–54). ![]() For every 1-year age increase, hours spent in indoor locations decreased by 0.002 (95%CI: −0.04 – −0.039), although this finding did not reach statistical significance (p = 0.90). The median daily time spent indoors per participant was 19.1 hours (IQR: 14.6–22.7). Own household, other household, transport, crèche or school, and work locations accounted for 97.2% (10,460.2 / 10,765.0) of indoor time and 80.4% (20,175 / 25,098) of indoor contacts. A graphical summary of these data across 11 locations is shown in Figure S1. The total hours spent in indoor locations (10,765 hours) and the total number of indoor contacts met (n = 25,098) by 571 township residents during a 24-hour period stratified by age and location are shown in Tables S1 and S2. Total Hours Spent and Number of Contacts Met in Indoor Locations Contact information was then stratified by age and location in order to establish age-related social mixing patterns and postulate the potential impact on TB transmission. We therefore determined the types of indoor locations frequented by the township residents, together with the numbers of contacts met and the time spent within each location. As we had previously reported high rates of TB disease and high annual risk of TB infection in children in this community, we went on to measure social mixing within indoor locations that might be driving transmission. The objective of the initial study was to use inter-personal contact information to model the potential for epidemic spread of an acute respiratory epidemic in a crowded township population. In 2010, we conducted a social mixing study among a randomly selected sample of residents of a Cape Town African township. In order to maintain high TB infection rates in the general population, there must be intense exposure of the susceptible population to prevalent infectious TB cases. The annual rate of TB infection increases throughout childhood to 7% per annum during adolescence, resulting in a TB infection prevalence of 80% in young adulthood. The acquisition of TB infection in Cape Town is very high during childhood and adolescence, with childhood infection rates, determined by tuberculin skin testing, remaining at approximately 4% per annum, which has resulted in a TB infection prevalence of 20% in children starting school –. The TB notification rates in the young HIV-negative Cape Town population are very similar to those recorded in early 20th century Europe prior to the implementation of effective chemotherapy,. The TB notification rate within the HIV-uninfected population of Cape Town was extremely high at 386/100,000, with the largest proportions of new TB rates notified in young children (511/100,00) and young adults (553/100,000). Cape Town, a city of 3.4 million residents, notified almost 30,000 new cases of TB in 2009 to the national TB control program. While the human immunodeficiency virus (HIV) epidemic has undoubtedly contributed significantly to the increased burden, , the underlying TB burden among the HIV-uninfected population has also remained extremely high. ![]() Tuberculosis (TB) notification rates in South Africa have increased progressively over the past 20 years. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.Ĭompeting interests: The authors have declared that no competing interests exist. SDL was funded by the Wellcome Trust, London, UK. KM was funded by The Wellcome Trust Strategic award: Clinical infectious diseases research initiative WT084323MA. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.įunding: RW was funded in part by the International Epidemiologic Database to Evaluate Aids with a grant from the National Institute of Allergy and Infectious Diseases (NIAID: 5U01AI069924-02) Cost-Effectiveness of Preventing AIDS Complications (CEPAC) funded by the National Institutes of Health (NIH, 5 R01AI058736-02) USAID Right to Care (CA 674 A 00 08 0000 700), and the South African Centre for Epidemiological Modeling and Analysis (SACEMA). Received: MaAccepted: Published: June 29, 2012Ĭopyright: © 2012 Wood et al. PLoS ONE 7(6):Įditor: Patrick Tang, University of British Columbia, Canada (2012) Indoor Social Networks in a South African Township: Potential Contribution of Location to Tuberculosis Transmission. Citation: Wood R, Racow K, Bekker L-G, Morrow C, Middelkoop K, Mark D, et al.
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