Analysis of tuberculosis prevalence surveys: new guidance on best-practice methods.


Floyd, S; Sismanidis, C; Yamada, N; Daniel, R; Lagahid, J; Mecatti, F; Vianzon, R; Bloss, E; Tiemersma, E; Onozaki, I; Glaziou, P; Floyd, K; (2013) Analysis of tuberculosis prevalence surveys: new guidance on best-practice methods. Emerging themes in epidemiology, 10 (1). p. 10. ISSN 1742-7622 DOI: https://doi.org/10.1186/1742-7622-10-10

[img]
Preview
Text - Published Version
License:

Download (4MB) | Preview

Abstract

BACKGROUND An unprecedented number of nationwide tuberculosis (TB) prevalence surveys will be implemented between 2010 and 2015, to better estimate the burden of disease caused by TB and assess whether global targets for TB control set for 2015 are achieved. It is crucial that results are analysed using best-practice methods. OBJECTIVE To provide new theoretical and practical guidance on best-practice methods for the analysis of TB prevalence surveys, including analyses at the individual as well as cluster level and correction for biases arising from missing data. ANALYTIC METHODS TB prevalence surveys have a cluster sample survey design; typically 50-100 clusters are selected, with 400-1000 eligible individuals in each cluster. The strategy recommended by the World Health Organization (WHO) for diagnosing pulmonary TB in a nationwide survey is symptom and chest X-ray screening, followed by smear microscopy and culture examinations for those with an abnormal X-ray and/or TB symptoms. Three possible methods of analysis are described and explained. Method 1 is restricted to participants, and individuals with missing data on smear and/or culture results are excluded. Method 2 includes all eligible individuals irrespective of participation, through multiple missing value imputation. Method 3 is restricted to participants, with multiple missing value imputation for individuals with missing smear and/or culture results, and inverse probability weighting to represent all eligible individuals. The results for each method are then compared and illustrated using data from the 2007 national TB prevalence survey in the Philippines. Simulation studies are used to investigate the performance of each method. KEY FINDINGS A cluster-level analysis, and Methods 1 and 2, gave similar prevalence estimates (660 per 100,000 aged ≥ 10 years old), with a higher estimate using Method 3 (680 per 100,000). Simulation studies for each of 4 plausible scenarios show that Method 3 performs best, with Method 1 systematically underestimating TB prevalence by around 10%. CONCLUSION Both cluster-level and individual-level analyses should be conducted, and individual-level analyses should be conducted both with and without multiple missing value imputation. Method 3 is the safest approach to correct the bias introduced by missing data and provides the single best estimate of TB prevalence at the population level.

Item Type: Article
Faculty and Department: Faculty of Epidemiology and Population Health > Dept of Infectious Disease Epidemiology
Faculty of Epidemiology and Population Health > Dept of Medical Statistics
Research Centre: Population Studies Group
Tropical Epidemiology Group
Centre for Statistical Methodology
PubMed ID: 24074436
URI: http://researchonline.lshtm.ac.uk/id/eprint/1366885

Statistics


Download activity - last 12 months
Downloads since deposit
249Downloads
350Hits
Accesses by country - last 12 months
Accesses by referrer - last 12 months
Impact and interest
Additional statistics for this record are available via IRStats2

Actions (login required)

Edit Item Edit Item