Created in James Madison University's ISAT 341 Simulation and Modeling course by Joseph Straub and Andrew Funkhouser. Based on Mark Heffernan's Glucose-Insulin Insight Maker     Glucose Insulin Model Info:  Translated from Hormone.stm in Dynamic Modeling in the Health Sciences James L hargrove, Spr

Created in James Madison University's ISAT 341 Simulation and Modeling course by Joseph Straub and Andrew Funkhouser. Based on Mark Heffernan's Glucose-Insulin Insight Maker


Glucose Insulin Model Info:

Translated from Hormone.stm in Dynamic Modeling in the Health Sciences James L hargrove, Springer 1998, Ch 24 p255-261, by Mark Heffernan.

 Extension of  IM-7981  with dynamics of daily ward discharges and did not waits. For an adjusted bed capacity stock see  IM-14144 .For backlog and services see  IM-8382

Extension of IM-7981 with dynamics of daily ward discharges and did not waits. For an adjusted bed capacity stock see IM-14144.For backlog and services see IM-8382

 Modified from  Mark Paich et al. 's book : Pharmaceutical product strategy. Fig 4.7 p 69. It formed the basis of a hypertension intervention discussion Aug-Sept 2010

Modified from Mark Paich et al. 's book: Pharmaceutical product strategy. Fig 4.7 p 69. It formed the basis of a hypertension intervention discussion Aug-Sept 2010

WIP Patient Flow improvement strategies for a City Hospital with 3 years historical data and two year planning horizon. Built after a Generic Teaching Hospital Model  IM-10346  A simplified stock flow map is at  IM-399
WIP Patient Flow improvement strategies for a City Hospital with 3 years historical data and two year planning horizon. Built after a Generic Teaching Hospital Model IM-10346 A simplified stock flow map is at IM-399
 Simple rich picture causal loop diagram of single and double loop learning including experiential learning concepts. Launchpad for Learning

Simple rich picture causal loop diagram of single and double loop learning including experiential learning concepts. Launchpad for Learning

 From Tarek KA Hamid's Book Thinking in Circles About Obesity Springer 2009

From Tarek KA Hamid's Book Thinking in Circles About Obesity Springer 2009

WIP example of Services oriented multiscale computable narrative synthesis focussed on Coping carefully with diabetes
WIP example of Services oriented multiscale computable narrative synthesis focussed on Coping carefully with diabetes
From Walrave ISDC2014  paper  Counteracting the success trap in publically owned corporations
From Walrave ISDC2014 paper Counteracting the success trap in publically owned corporations
 Addition of Incident Reporting and Prevention Interventions to a simple error chain of medication errors for patients in hospital  IM-10113  

Addition of Incident Reporting and Prevention Interventions to a simple error chain of medication errors for patients in hospital IM-10113 

 Here we have a basic SEIR model and we will investigate what changes would be appropriate for modelling the 2019 Coronavirus.  We add simple containment meassures that affect two paramenters, the Susceptible population and the rate to become infected.  The initial parametrization is based on the su

Here we have a basic SEIR model and we will investigate what changes would be appropriate for modelling the 2019 Coronavirus.

We add simple containment meassures that affect two paramenters, the Susceptible population and the rate to become infected.

The initial parametrization is based on the suggested current data. The initial population is set for Catalonia.

The questions that we want to answer in this kind of models are not the shape of the curves, that are almost known from the beginning, but, when this happens, and the amplitude of the shapes. This is crucial, since in the current circumstance implies the collapse of certain resources, not only healthcare.

The validation process hence becomes critical, and allows to estimate the different parameters of the model from the data we obtain. This simulation approach allows to obtain somethings that is crucial to make decisions, the causality. We can infer this from the assumptions that are implicit on the model, and from it we can make decisions to improve the system behavior.

Yes, simulation works with causality and Flows diagrams is one of the techniques we have to draw it graphically, but is not the only one. On https://sdlps.com/projects/documentation/1009 you can review soon the same model but represented in Specification and Description Language.

152 7 months ago
 Dynamic system underlying project life cycles From Roberts Edward B The Dynamics of Research and Development p5 Harper & Row NY 1964

Dynamic system underlying project life cycles From Roberts Edward B The Dynamics of Research and Development p5 Harper & Row NY 1964

 Major stocks and flows of Erythropoiesis and Erythropoiesis Stimulating Agents (ESA) Dosing in Anemia due to Renal Failure from Jim Rogers

Major stocks and flows of Erythropoiesis and Erythropoiesis Stimulating Agents (ESA) Dosing in Anemia due to Renal Failure from Jim Rogers

 Services planning for people with intellectual disability concept map. Stock and FLow model is Insight 668 and  RIch Picture is Insight  746

Services planning for people with intellectual disability concept map. Stock and FLow model is Insight 668 and  RIch Picture is Insight  746

 From Adapting ‘Agility’ to Healthcare Service Delivery , by Tom Rust, Khalid Saeed, Isa Bar-On, Oleg Pavlov  Paper  from July 2013 System dynamics Conference Cambridge MA and also 2012 Conference  paper   Could be extended by adding dynamics described in  going solid insight
From Adapting ‘Agility’ to Healthcare Service Delivery, by Tom Rust, Khalid Saeed, Isa Bar-On, Oleg Pavlov Paper from July 2013 System dynamics Conference Cambridge MA and also 2012 Conference paper  Could be extended by adding dynamics described in going solid insight
 Dynamics of Emergency Room Crowding with treatment spaces. Here we investigate the effect of constrained spaces and ignore any changes in treatment time or staffing effects. Many of the consequences occur before treatment with potential arrivals being turned away and arrivals leaving without being

Dynamics of Emergency Room Crowding with treatment spaces. Here we investigate the effect of constrained spaces and ignore any changes in treatment time or staffing effects. Many of the consequences occur before treatment with potential arrivals being turned away and arrivals leaving without being treated.  

 Upgrade of Kermack–McKendrick Epidemic SIR Infectious Disease Model (circa 2015) - Metrics by Guy Lakeman   This is a simple SIR infectious diseases 3 stock model with Susceptibles, Infectives and Recovereds stocks. In the initial description the R signified Removed and could include Deaths, Recove

Upgrade of Kermack–McKendrick Epidemic SIR Infectious Disease Model (circa 2015) - Metrics by Guy Lakeman

This is a simple SIR infectious diseases 3 stock model with Susceptibles, Infectives and Recovereds stocks. In the initial description the R signified Removed and could include Deaths, Recovered with immunity to infection (Resistant) or those who had fled the epidemic. Note the need to initiate the epidemic by adding a pulse of a single infected person at time 0.

Addition of a slider for susceptibles is equivalent to accumulated total cases

SARS, MERS AND COVID are similar virus types only differing in their sub genus

The COVID outbreak has reached 150,000 infected people

This simulation allows an attempt at predicting how long the virus will persist and its longevity dependence on its high speed massive infection numbers that have reached pandemic proportions

SARS reached 8,000 infected total and ran for 9 months before stopping

MERS 2012 is still killing 8 years later with patients dying even after using interferon to try and cure them

 Created in James Madison University's ISAT 341 Simulation and Modeling course by Joseph Straub and Andrew Funkhouser. Based on Mark Heffernan's Glucose-Insulin Insight Maker     Glucose Insulin Model Info:  Translated from Hormone.stm in Dynamic Modeling in the Health Sciences James L hargrove, Spr

Created in James Madison University's ISAT 341 Simulation and Modeling course by Joseph Straub and Andrew Funkhouser. Based on Mark Heffernan's Glucose-Insulin Insight Maker


Glucose Insulin Model Info:

Translated from Hormone.stm in Dynamic Modeling in the Health Sciences James L hargrove, Springer 1998, Ch 24 p255-261, by Mark Heffernan.

 Dynamics of Emergency Room Crowding with treatment spaces and boarders waiting for ward beds (access block if the wait is too long).

Dynamics of Emergency Room Crowding with treatment spaces and boarders waiting for ward beds (access block if the wait is too long).

Gross theory of emotion regulation from Saras Chung ISDC 2015   Abstract   See also Tibor Bosse's Computational model  paper
Gross theory of emotion regulation from Saras Chung ISDC 2015  Abstract 
See also Tibor Bosse's Computational model paper
 Forcings and feedbacks based on Tom Fiddaman, James Hansen and other feedback and cycle diagrams

Forcings and feedbacks based on Tom Fiddaman, James Hansen and other feedback and cycle diagrams

 From  Werner Ulrich 's JORS Articles Operational research and critical systems thinking – an integrated perspective.  Part 1 : OR as applied systems thinking.  Journal of the Operational Research Societ y advance online publication (14 December 2011). and  Part 2  :OR as argumentative practice.  Se

From Werner Ulrich's JORS Articles Operational research and critical systems thinking – an integrated perspective. Part 1: OR as applied systems thinking. Journal of the Operational Research Society advance online publication (14 December 2011). and Part 2 :OR as argumentative practice.

See also insight on Boundary Critique

A SEIR Model of SARS Pandemic With Isolation and Quarantine, based on Introduction to Computational Science by Shiflet and Shiflet    Quarantine is when someone exposed to infected people, whether infected or not, and advised to stay at home.     Isolation is when someone exposed to infected people,
A SEIR Model of SARS Pandemic With Isolation and Quarantine, based on Introduction to Computational Science by Shiflet and Shiflet

Quarantine is when someone exposed to infected people, whether infected or not, and advised to stay at home.

Isolation is when someone exposed to infected people, get infected, detected, and send to hospital.

Assumption:
- No births
- Dead only caused by SARS
- Contact between susceptible and infected are constant. Contact does not affected by population density
- Quarantine factor for susceptible and exposed is same.
- Quarantine and isolation is fully efective. Someone who quarantined or isolated cannot transmit or exposed to SARS
- Someone who has already recovered from SARS gained fully effective immunity, thus cannot re-infected