Progression from latent infection to active disease in dynamic tuberculosis transmission models: a systematic review of the validity of modelling assumptions

Nicolas A. Menzies*, Emory Wolf, David Connors, Meghan Bellerose, Alyssa N. Sbarra, Ted Cohen, Andrew N. Hill, Reza Yaesoubi, Kara Galer, Peter White, Ibrahim Abubakar, Joshua A. Salomon

*Corresponding author for this work

Research output: Contribution to journalReview articlepeer-review

36 Citations (Scopus)


Mathematical modelling is commonly used to evaluate infectious disease control policy and is influential in shaping policy and budgets. Mathematical models necessarily make assumptions about disease natural history and, if these assumptions are not valid, the results of these studies can be biased. We did a systematic review of published tuberculosis transmission models to assess the validity of assumptions about progression to active disease after initial infection (PROSPERO ID CRD42016030009). We searched PubMed, Web of Science, Embase, Biosis, and Cochrane Library, and included studies from the earliest available date (Jan 1, 1962) to Aug 31, 2017. We identified 312 studies that met inclusion criteria. Predicted tuberculosis incidence varied widely across studies for each risk factor investigated. For population groups with no individual risk factors, annual incidence varied by several orders of magnitude, and 20-year cumulative incidence ranged from close to 0% to 100%. A substantial proportion of modelled results were inconsistent with empirical evidence: for 10-year cumulative incidence, 40% of modelled results were more than double or less than half the empirical estimates. These results demonstrate substantial disagreement between modelling studies on a central feature of tuberculosis natural history. Greater attention to reproducing known features of epidemiology would strengthen future tuberculosis modelling studies, and readers of modelling studies are recommended to assess how well those studies demonstrate their validity.

Original languageEnglish
Pages (from-to)e228-e238
JournalThe Lancet Infectious Diseases
Issue number8
Publication statusPublished - Aug 2018

Bibliographical note

Funding Information:
Acknowledgments, This study was funded by the US Centers for Disease Control and Prevention, National Center for HIV, Viral Hepatitis, STD, and TB Prevention Epidemiologic and Economic Modeling Agreement #5NU38PS004644. PJW received funding from the UK National Institute for Health Research (NIHR) Health Protection Research Unit in Modelling Methodology at Imperial College London, in partnership with Public Health England (HPRU-2012-10080) and the UK Medical Research Council (MR/K010174/1). IA is funded by NIHR (SRF-2011-04-001; NF-SI-0616-10037), the Medical Research Council, and the UK Wellcome Trust. The findings and conclusions in this paper are those of the authors and do not necessarily represent the views of the US Centers for Disease Control and Prevention, the UK Department of Health, MRC, National Health Service, NIHR, Public Health England, or the authors' other affiliated institutions.

Funding Information:
PJW has received research funding from Otsuka SA for a retrospective study of multidrug-resistant tuberculosis treatment in several eastern European countries. The other authors declare no competing interests.

Publisher Copyright:
© 2018 Elsevier Ltd


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