Skip to main content
    • Aa
    • Aa

Revisiting Styblo's law: could mathematical models aid in estimating incidence from prevalence data?

  • M. BEGUN (a1), A. T. NEWALL (a1), G. B. MARKS (a2) (a3) and J. G. WOOD (a1)

Estimation of the true incidence of tuberculosis (TB) is challenging. The approach proposed by Styblo in 1985 is known to be inaccurate in the modern era where there is widespread availability of treatment for TB. This study re-examines the relationship of incidence to prevalence and other disease indicators that can be derived from surveys. We adapt a simple, previously published model that describes the epidemiology of TB in the presence of treatment to investigate a revised ratio-based approach to estimating incidence. We show that, following changes to treatment programmes for TB, the ratio of incidence to prevalence reaches an equilibrium value rapidly; long before other model indicators have stabilized. We also show that this ratio relies on few parameters but is strongly dependent on, and requires knowledge of, the efficacy and timeliness of treatment.

Corresponding author
* Author for correspondence: Mr M. Begun, School of Public Health and Community Medicine, Faculty of Medicine, University of New South Wales, Sydney, NSW, Australia. (Email:
Hide All
4. C Dye , Measuring tuberculosis burden, trends, and the impact of control programmes. Lancet Infectious Diseases 2008; 8: 233243.

8. F Van Leth . Prevalence of tuberculous infection and incidence of tuberculosis; a re-assessment of the Styblo rule. Bulletin of the World Health Organization 2008; 86: 2026.

10. C Ozcaglar , Epidemiological models of Mycobacterium tuberculosis complex infections. Mathematical Biosciences 2012; 236: 7796.

12. M Van der Werf , MW Borgdorff . Targets for tuberculosis control: how confident can we be about the data? Bulletin of the World Health Organization 2007; 85: 370376.

13. NB Hoa , National survey of tuberculosis prevalence in Viet Nam. Bulletin of the World Health Organization 2010; 88: 273280.

Recommend this journal

Email your librarian or administrator to recommend adding this journal to your organisation's collection.

Epidemiology & Infection
  • ISSN: 0950-2688
  • EISSN: 1469-4409
  • URL: /core/journals/epidemiology-and-infection
Please enter your name
Please enter a valid email address
Who would you like to send this to? *



Full text views

Total number of HTML views: 7
Total number of PDF views: 29 *
Loading metrics...

Abstract views

Total abstract views: 206 *
Loading metrics...

* Views captured on Cambridge Core between September 2016 - 17th October 2017. This data will be updated every 24 hours.