C M Yuen1, H E Jenkins2, R Chang3, J Mpunga4, M C Becerra5. 1. Division of Global Health Equity, Brigham and Women's Hospital, Boston, Massachusetts, USA ; Department of Global Health and Social Medicine, Harvard Medical School, Boston, Massachusetts, USA. 2. Department of Biostatistics, Boston University School of Public Health, Boston, Massachusetts, USA. 3. Clinton Health Access Initiative, Kigali, Rwanda. 4. National Tuberculosis Control Programme, Lilongwe, Malawi. 5. Division of Global Health Equity, Brigham and Women's Hospital, Boston, Massachusetts, USA ; Department of Global Health and Social Medicine, Harvard Medical School, Boston, Massachusetts, USA ; Partners in Health, Boston, Massachusetts, USA.
Abstract
OBJECTIVE: To allocate resources for household contact investigations, tuberculosis (TB) programs need estimates of the numbers of child contacts requiring care. DESIGN: We developed two methods to estimate annual numbers of child contacts aged 0-14 years requiring evaluation and treatment. Method 1 combines local data using simple formulas. Using publicly available data, Method 2 uses a linear regression model based on Demographic and Health Survey and World Bank data to estimate the number of children per household, then combines these results with case notifications and risk estimates of disease and infection. RESULTS: Applying Method 1 to data from Malawi indicated that every year ~21 000 child contacts require evaluation and ~1900 should be diagnosed with TB. Applying Method 2 to all countries suggested that, globally, 2.41 million (95% uncertainty interval [UI] 2.36-2.46) children aged <5 years, and 5.07 million (95%UI 4.81-5.34) children aged 5-14 years live in households of adult patients with known TB. Of these, 239 014 (95%UI 118 649-478581) and 419 816 (95%UI 140600-1 268805), respectively, will have TB. An additional 848 453 (95%UI 705838-1 017551) and 2660 885 (95%UI 2080517-3 413 189), respectively, will be infected. CONCLUSION: It is feasible to use available data to set programmatic evaluation and treatment targets to improve care for child contacts of patients with TB.
OBJECTIVE: To allocate resources for household contact investigations, tuberculosis (TB) programs need estimates of the numbers of child contacts requiring care. DESIGN: We developed two methods to estimate annual numbers of child contacts aged 0-14 years requiring evaluation and treatment. Method 1 combines local data using simple formulas. Using publicly available data, Method 2 uses a linear regression model based on Demographic and Health Survey and World Bank data to estimate the number of children per household, then combines these results with case notifications and risk estimates of disease and infection. RESULTS: Applying Method 1 to data from Malawi indicated that every year ~21 000 child contacts require evaluation and ~1900 should be diagnosed with TB. Applying Method 2 to all countries suggested that, globally, 2.41 million (95% uncertainty interval [UI] 2.36-2.46) children aged <5 years, and 5.07 million (95%UI 4.81-5.34) children aged 5-14 years live in households of adult patients with known TB. Of these, 239 014 (95%UI 118 649-478581) and 419 816 (95%UI 140600-1 268805), respectively, will have TB. An additional 848 453 (95%UI 705838-1 017551) and 2660 885 (95%UI 2080517-3 413 189), respectively, will be infected. CONCLUSION: It is feasible to use available data to set programmatic evaluation and treatment targets to improve care for child contacts of patients with TB.
Authors: J O'Grady; M Maeurer; R Atun; I Abubakar; P Mwaba; M Bates; N Kapata; G Ferrara; M Hoelscher; A Zumla Journal: Eur Respir J Date: 2011-10 Impact factor: 16.671
Authors: Helen E Jenkins; Arielle W Tolman; Courtney M Yuen; Jonathan B Parr; Salmaan Keshavjee; Carlos M Pérez-Vélez; Marcello Pagano; Mercedes C Becerra; Ted Cohen Journal: Lancet Date: 2014-03-24 Impact factor: 79.321
Authors: Victor F Gomes; Andreas Andersen; Christian Wejse; Ines Oliveira; Fina J Vieira; Luis Carlos Joaquim; Cesaltina S Vieira; Peter Aaby; Per Gustafson Journal: Thorax Date: 2010-12-08 Impact factor: 9.139
Authors: B J Marais; R P Gie; H S Schaaf; A C Hesseling; C C Obihara; J J Starke; D A Enarson; P R Donald; N Beyers Journal: Int J Tuberc Lung Dis Date: 2004-04 Impact factor: 2.373
Authors: Grant Theron; Helen E Jenkins; Frank Cobelens; Ibrahim Abubakar; Aamir J Khan; Ted Cohen; David W Dowdy Journal: Lancet Date: 2015-10-26 Impact factor: 79.321
Authors: Leonardo Martinez; Ye Shen; Andreas Handel; Srijita Chakraburty; Catherine M Stein; LaShaunda L Malone; W Henry Boom; Frederick D Quinn; Moses L Joloba; Christopher C Whalen; Sarah Zalwango Journal: Lancet Respir Med Date: 2017-12-19 Impact factor: 30.700
Authors: Peter J Dodd; Courtney M Yuen; Charalambos Sismanidis; James A Seddon; Helen E Jenkins Journal: Lancet Glob Health Date: 2017-09 Impact factor: 26.763
Authors: Andrew J Brent; Christopher Nyundo; Joyce Langat; Caroline Mulunda; Joshua Wambua; Evasius Bauni; Joyce Sande; Kate Park; Thomas N Williams; Charles R J Newton; Michael Levin; J Anthony G Scott Journal: Emerg Infect Dis Date: 2018-03 Impact factor: 6.883
Authors: Peter J Dodd; Courtney M Yuen; Mercedes C Becerra; Paul Revill; Helen E Jenkins; James A Seddon Journal: Lancet Glob Health Date: 2018-09-25 Impact factor: 26.763
Authors: Youngji Jo; Isabella Gomes; Joseph Flack; Nicole Salazar-Austin; Gavin Churchyard; Richard E Chaisson; David W Dowdy Journal: EClinicalMedicine Date: 2021-01-07