Data needs for evidence-based decisions: A tuberculosis modeler's 'wish list'

David Dowdy, C. Dye, T. Cohen

Research output: Contribution to journalReview articlepeer-review

Abstract

Infectious disease models are important tools for understanding epidemiology and supporting policy decisions for disease control. In the case of tuberculosis (TB), such models have informed our understanding and control strategies for over 40 years, but the primary assumptions of these models - and their most urgent data needs - remain obscure to many TB researchers and control officers. The structure and parameter values of TB models are informed by observational studies and experiments, but the evidence base in support of these models remains incomplete. Speaking from the perspective of infectious disease modelers addressing the broader TB research and control communities, we describe the basic structure common to most TB models and present a 'wish list' that would improve the evidence foundation upon which these models are built. As a comprehensive TB research agenda is formulated, we argue that the data needs of infectious disease models - our primary long-term decision-making tools - should figure prominently.

Original languageEnglish (US)
Pages (from-to)866-877
Number of pages12
JournalInternational Journal of Tuberculosis and Lung Disease
Volume17
Issue number7
DOIs
StatePublished - Jul 1 2013

Keywords

  • Infectious disease transmission
  • Theoretical models
  • Tuberculosis

ASJC Scopus subject areas

  • Pulmonary and Respiratory Medicine
  • Infectious Diseases

Fingerprint Dive into the research topics of 'Data needs for evidence-based decisions: A tuberculosis modeler's 'wish list''. Together they form a unique fingerprint.

Cite this