A systematic review of mathematical and economic TB modelling papers
A systematic literature review of the existing academic papers that describe mathematical and economic modelling of TB.
The database to support or encourage anybody with an interest in TB modelling. When using this resource, please acknowledge the TB Modelling and Analysis Consortium (TB MAC) in your publication, and do let us know through firstname.lastname@example.org.
The file can be downloaded on the right hand side (TBmodelling_Mar2013.txt). This holds all the references in the RIS format, which can be imported directly in most reference manager software packages.
PubMed was searched using the following search query: (tuberculosis OR TB) AND ((mathem* AND (model OR models)) OR (mathem* modell*) OR (mathem* modeling) OR (modeling OR modelling) OR "Population Dynamics"[MeSH Terms] OR "Population Dynamics" OR "System Dynamics" OR "Computer Simulation" OR "Computer Simulation"[MeSH Terms])
We also searched mathematical modelling journals for any papers on tuberculosis and scanned references from existing reviews for relevant papers. Also, modellers from the TB MAC steering committee (Richard White, Chris Dye, Anna Vassal, Ted Cohen and David Dowdy) kindly made their personal libraries available.
Inclusion criteria: We included all papers describing mathematical modelling as defined by Garnett et al. (Lancet 2011, 378, pg 515-525) which distinguishes between mathematical and statistical models as follows “statistical models are those used to derive parameter estimates from empirical data, and mathematical models are those used to make predictions on the basis of those parameter estimates.”
With regard to economic modelling, we limited to papers where modelling methods were used to simulate a population or individuals as they progressed through an algorithm (e.g. decision trees).
Period covered, updates and feedback
The databases and literature were searched up to the 30th of March 2013, and the paper collection should be complete up to that date. However, if you know any papers, new or old, that should be included, please contact us at email@example.com. Your contributions are much appreciated.
Email firstname.lastname@example.org to let us know what you think, to give suggestions on how to improve this resource, or to ask a question.