Watanabe2018_State Transition Model with Treatment and Costs

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Short description
Model with functions depending on Age, Male, BP (Blood Pressure). There are 3 disease states: Healthy, Sick, and Dead, where the Dead state is terminal. The yearly transition probabilities are: Healthy to Dead: Age/1000; Healthy to Sick: According to function F1 depending on Age and Male and BP; Sick to Healthy: 0.1; Sick to Dead: according to function F2 depending on Age and Male. Pre-Transition Rules: Age increased by 1 and BP by Age/10 each simulation cycle. Post-Transition Rules: Treatment = BP>140 , becomes 1 when BP crosses 140 threshold; BP =BP-Treatment*10 , meaning a drop of 10 once treatment is applied; CostThisYear = Age + \Treatment*10 , cost depends on age and if treatment was taken; Cost= Cost + CostThisYear , it accumulates cost over time. Initial conditions: Healthy = (50 Male, 50 Female with Age =1,2,...,50 for each individual), BP =120, Sick = (0,0) and Dead = (0,0). Output: Number of men and women in each disease state for years 1-10 and their ages and costs in each state. A stratified report by male and female and young – up to age 30 and old above age 30 is produced.
Format
Original code
Related Publication
  • Toward reproducible disease models using the Systems Biology Markup Language
  • Leandro Watanabe, Jacob Barhak, Chris Myers
  • SAGE journals , 9/ 2018
  • Department of Electrical and Computer Engineering, University of Utah, USA 2Jacob Barhak, Austin, TX, USA
  • Disease modelers have been modeling progression of diseases for several decades using such tools as Markov models or microsimulation. However, they need to address a serious challenge; many models they create are not reproducible. Moreover, there is no proper practice that ensures reproducible models, since modelers rely on loose guidelines that change periodically, rather than well-defined machine-readable standards. The Systems Biology Markup Language (SBML) is one such standard that allows exchange of models between different software tools. Recently, the SBML Arrays package has been developed, which extends the standard to allow handling simulation of populations. This paper demonstrates through several abstract examples how microsimulation disease models can be encoded using the SBML Arrays package, enabling reproducible disease modeling.
Contributors
Leandro Watanabe, Rahuman Sheriff

Metadata information

Curation status
Non-curated
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Model files

Example5.xml SBML Level 3 version 2, representation of Example5: State Transition Model with Treatment and Costs 124.83 KB Preview | Download

  • Model originally submitted by : Leandro Watanabe
  • Submitted: Jan 30, 2019 5:04:10 PM
  • Last Modified: Jan 30, 2019 5:04:10 PM
Revisions
  • Version: 4 public model Download this version
    • Submitted on: Jan 30, 2019 5:04:10 PM
    • Submitted by: Rahuman Sheriff
    • With comment: Edited model metadata online.