Literature DB >> 21481448

Mathematical models in the evaluation of health programmes.

Geoffrey P Garnett1, Simon Cousens, Timothy B Hallett, Richard Steketee, Neff Walker.   

Abstract

Modelling is valuable in the planning and evaluation of interventions, especially when a controlled trial is ethically or logistically impossible. Models are often used to calculate the expected course of events in the absence of more formal assessments. They are also used to derive estimates of rare or future events from recorded intermediate points. When developing models, decisions are needed about the appropriate level of complexity to be represented and about model structure and assumptions. The degree of rigor in model development and assessment can vary greatly, and there is a danger that existing beliefs inappropriately influence judgments about model assumptions and results.
Copyright © 2011 Elsevier Ltd. All rights reserved.

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Year:  2011        PMID: 21481448     DOI: 10.1016/S0140-6736(10)61505-X

Source DB:  PubMed          Journal:  Lancet        ISSN: 0140-6736            Impact factor:   79.321


  100 in total

1.  EpiModel: An R Package for Mathematical Modeling of Infectious Disease over Networks.

Authors:  Samuel M Jenness; Steven M Goodreau; Martina Morris
Journal:  J Stat Softw       Date:  2018-04-20       Impact factor: 6.440

Review 2.  Structural Design and Data Requirements for Simulation Modelling in HIV/AIDS: A Narrative Review.

Authors:  Xiao Zang; Emanuel Krebs; Linwei Wang; Brandon D L Marshall; Reuben Granich; Bruce R Schackman; Julio S G Montaner; Bohdan Nosyk
Journal:  Pharmacoeconomics       Date:  2019-10       Impact factor: 4.981

Review 3.  A critical review of cost-effectiveness analyses of vaccinating males against human papillomavirus.

Authors:  Yiling Jiang; Aline Gauthier; Maarten J Postma; Laureen Ribassin-Majed; Nathalie Largeron; Xavier Bresse
Journal:  Hum Vaccin Immunother       Date:  2013-07-23       Impact factor: 3.452

4.  gems: An R Package for Simulating from Disease Progression Models.

Authors:  Nello Blaser; Luisa Salazar Vizcaya; Janne Estill; Cindy Zahnd; Bindu Kalesan; Matthias Egger; Thomas Gsponer; Olivia Keiser
Journal:  J Stat Softw       Date:  2015-03       Impact factor: 6.440

5.  Prioritizing Additional Data Collection to Reduce Decision Uncertainty in the HIV/AIDS Response in 6 US Cities: A Value of Information Analysis.

Authors:  Xiao Zang; Hawre Jalal; Emanuel Krebs; Ankur Pandya; Haoxuan Zhou; Benjamin Enns; Bohdan Nosyk
Journal:  Value Health       Date:  2020-10-03       Impact factor: 5.725

6.  Double trouble: modelling the impact of low risk perception and high-risk sexual behaviour on chlamydia transmission.

Authors:  Daphne A van Wees; Chantal den Daas; Mirjam E E Kretzschmar; Janneke C M Heijne
Journal:  J R Soc Interface       Date:  2018-04       Impact factor: 4.118

Review 7.  Modeling cholera outbreaks.

Authors:  Dennis L Chao; Ira M Longini; J Glenn Morris
Journal:  Curr Top Microbiol Immunol       Date:  2014       Impact factor: 4.291

Review 8.  Conceptual framework and research methods for migration and HIV transmission dynamics.

Authors:  Susan Cassels; Samuel M Jenness; Aditya S Khanna
Journal:  AIDS Behav       Date:  2014-12

Review 9.  Data needs for evidence-based decisions: a tuberculosis modeler's 'wish list'.

Authors:  D W Dowdy; C Dye; T Cohen
Journal:  Int J Tuberc Lung Dis       Date:  2013-07       Impact factor: 2.373

Review 10.  Alignment of new tuberculosis drug regimens and drug susceptibility testing: a framework for action.

Authors:  William A Wells; Catharina C Boehme; Frank G J Cobelens; Colleen Daniels; David Dowdy; Elizabeth Gardiner; Jan Gheuens; Peter Kim; Michael E Kimerling; Barry Kreiswirth; Christian Lienhardt; Khisi Mdluli; Madhukar Pai; Mark D Perkins; Trevor Peter; Matteo Zignol; Alimuddin Zumla; Marco Schito
Journal:  Lancet Infect Dis       Date:  2013-03-24       Impact factor: 25.071

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