A user-friendly, open-source tool to project impact and cost of diagnostic tests for tuberculosis

  1. David W Dowdy  Is a corresponding author
  2. Jason R Andrews
  3. Peter J Dodd
  4. Robert H Gilman
  1. Johns Hopkins Bloomberg School of Public Health, United States
  2. Massachusetts General Hospital, United States
  3. University of Sheffield, United Kingdom

Abstract

Most existing models of infectious diseases, including tuberculosis (TB), do not allow end-users to customize results to local conditions. We created a dynamic transmission model to project TB incidence, TB mortality, multidrug-resistant (MDR) TB prevalence, and incremental costs over five years after scale-up of nine alternative diagnostic strategies including combinations of sputum smear microscopy, Xpert MTB/RIF, microcolony-based culture, and same-day diagnosis. We developed a corresponding web-based interface that allows users to specify local costs and epidemiology. Full model code - including the ability to change any input parameter - is also included. The impact of improved diagnostic testing was greater for mortality and MDR-TB prevalence than TB incidence, and was maximized in high-incidence, low-HIV settings. More costly interventions generally had greater impact. In settings with little capacity for up-front investment, same-day microscopy had greatest impact on TB incidence and became cost-saving within five years if feasible to deliver at $10/test. In settings where more initial investment was possible, population-level scale-up of either Xpert MTB/RIF or microcolony-based culture offered substantially greater benefits, often averting ten times more TB cases than narrowly-targeted diagnostic strategies at minimal incremental long-term cost. Where containing MDR-TB is the overriding concern, Xpert for smear-positives has reasonable impact on MDR-TB incidence, but at substantial price and little impact on overall TB incidence and mortality. This novel, user-friendly modeling framework improves decision-makers' ability to evaluate the impact of TB diagnostic strategies, accounting for local conditions.

Article and author information

Author details

  1. David W Dowdy

    Johns Hopkins Bloomberg School of Public Health, Baltimore, United States
    For correspondence
    ddowdy@jhsph.edu
    Competing interests
    The authors declare that no competing interests exist.
  2. Jason R Andrews

    Massachusetts General Hospital, Boston, United States
    Competing interests
    The authors declare that no competing interests exist.
  3. Peter J Dodd

    University of Sheffield, Sheffield, United Kingdom
    Competing interests
    The authors declare that no competing interests exist.
  4. Robert H Gilman

    Johns Hopkins Bloomberg School of Public Health, Baltimore, United States
    Competing interests
    The authors declare that no competing interests exist.

Copyright

© 2014, Dowdy et al.

This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.

Metrics

  • 10
    citations

Views, downloads and citations are aggregated across all versions of this paper published by eLife.

Citations by DOI

Download links

A two-part list of links to download the article, or parts of the article, in various formats.

Downloads (link to download the article as PDF)

Open citations (links to open the citations from this article in various online reference manager services)

Cite this article (links to download the citations from this article in formats compatible with various reference manager tools)

  1. David W Dowdy
  2. Jason R Andrews
  3. Peter J Dodd
  4. Robert H Gilman
(2014)
A user-friendly, open-source tool to project impact and cost of diagnostic tests for tuberculosis
eLife 3:e02565.
https://doi.org/10.7554/eLife.02565

Share this article

https://doi.org/10.7554/eLife.02565