The impact of realistic age structure in simple models of tuberculosis transmission

Ellen Brooks-Pollock, Ted Cohen, Megan Murray

Research output: Contribution to journalArticle (Academic Journal)peer-review

38 Citations (Scopus)


BACKGROUND: Mathematical models of tuberculosis (TB) transmission have been used to characterize disease dynamics, investigate the potential effects of public health interventions, and prioritize control measures. While previous work has addressed the mathematical description of TB natural history, the impact of demography on the behaviour of TB models has not been assessed.

METHODS: A simple model of TB transmission, with alternative assumptions about survivorship, is used to explore the effect of age structure on the prevalence of infection, disease, basic reproductive ratio and the projected impact of control interventions. We focus our analytic arguments on the differences between constant and exponentially distributed lifespans and use an individual-based model to investigate the range of behaviour arising from realistic distributions of survivorship.

RESULTS: The choice of age structure and natural (non-disease related) mortality strongly affects steady-state dynamics, parameter estimation and predictions about the effectiveness of control interventions. Since most individuals infected with TB develop an asymptomatic latent infection and never progress to active disease, we find that assuming a constant mortality rate results in a larger reproductive ratio and an overestimation of the effort required for disease control in comparison to using more realistic age-specific mortality rates.

CONCLUSIONS: Demographic modelling assumptions should be considered in the interpretation of models of chronic infectious diseases such as TB. For simple models, we find that assuming constant lifetimes, rather than exponential lifetimes, produces dynamics more representative of models with realistic age structure.

Original languageEnglish
Pages (from-to)e8479
JournalPLoS ONE
Issue number1
Publication statusPublished - 2010


  • Humans
  • Models, Theoretical
  • Prevalence
  • Tuberculosis


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