Watanabe2018_Simple markov model for a disease model
Ontology highlight
ABSTRACT:
SUBMITTER: 
Leandro Watanabe
PROVIDER: MODEL1803120002 | BioModels | 2019-01-30
REPOSITORIES: BioModels
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Project description:State transition diagram of a three-state Markov model.
There are 3 disease states: Healthy, Sick, and Dead, where the Dead state is terminal
The yearly transition probabilities are:
Healthy to Dead: 0.01; Healthy to Sick: 0.2; Sick to Healthy: 0.1;Sick to Dead: 0.3.
Initial conditions: Healthy = 100, Sick = 0 and Dead = 0.
Output: Number of people in each state for years 1-10.
2019-01-30 | MODEL1803120003 | BioModels
Project description:Simple Markov model.
There are 3 disease states: Healthy, Sick, and Dead, where the Dead state is terminal.
The yearly transition probabilities are:
Healthy to Dead: 0.01; Healthy to Sick: 0.2 for Male and 0.1 for Female; Sick to Healthy: 0.1; Sick to Dead: 0.3.
The transition probability now depends on the cohort (Male or Female) and can be expressed as a function of a Boolean covariate Male.
Initial conditions: Healthy = (50 Male, 50 Female), Sick = (0,0) and Dead = (0,0).
Output: Number of men and women in each disease state for years 1-10.
2019-01-30 | MODEL1803120004 | BioModels
Project description:Model dependent on changing parameters.
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 parameters; Sick to Healthy: 0.1; Sick to Dead: according to function F2 depending on Age and Male parameters. Pre-Transition Rules: Age increased by 1 each cycle.
Initial conditions: Healthy = (50 Male, 50 Female with Age =1,2,…,50 for each individual), Sick = (0,0) and Dead = (0,0).
Output: Number of men and women in each disease state for years 1-10 and their ages in each state.
2019-01-30 | MODEL1803120005 | BioModels
Project 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.
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