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.

A combination of qualitative and quantitative methods for implementing a systems approach, including virtual intervention experiments using computer simulation models.
A combination of qualitative and quantitative methods for implementing a systems approach, including virtual intervention experiments using computer simulation models.
From David Rees PhD dissertation "Developing a Theory of Implementation for
Better Chronic Health Management" Health Services Research
Centre, Victoria University of Wellington, New Zealand
From David Rees PhD dissertation "Developing a Theory of Implementation for Better Chronic Health Management" Health Services Research Centre, Victoria University of Wellington, New Zealand
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
 System Zoo Z111 H Bossel p47 a variant of Michaelis Menten Enzyme Kinetics. See also  IM-854  for Hannon and Ruth and  IM-855  for receptor version and  IM-856  for a bond graph view

System Zoo Z111 H Bossel p47 a variant of Michaelis Menten Enzyme Kinetics. See also IM-854 for Hannon and Ruth and IM-855 for receptor version and IM-856 for a bond graph view

Clone of  IM-6072  which is a WIP based on Choice modelling and Mark Paich's Book and NZ work focus on Pre-ED Presentation choices, with ED and Post-ED care.  Addition of After hours 'as is' and 'to be' flow models for Medicare Locals
Clone of IM-6072 which is a WIP based on Choice modelling and Mark Paich's Book and NZ work focus on Pre-ED Presentation choices, with ED and Post-ED care.  Addition of After hours 'as is' and 'to be' flow models for Medicare Locals
WIP Based on Sheldrick Implementation science 2016  article  A system dynamics model of clinical decision thresholds for
the detection of developmental-behavioral disorders. Vensim model modified to show patterns   
WIP Based on Sheldrick Implementation science 2016 article A system dynamics model of clinical decision thresholds for the detection of developmental-behavioral disorders. Vensim model modified to show patterns

 

 SIR model with herd immunity - Metrics by Guy Laekman   A Susceptible-Infected-Recovered (SIR) disease model with herd immunity

SIR model with herd immunity - Metrics by Guy Laekman

A Susceptible-Infected-Recovered (SIR) disease model with herd immunity

 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.

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.

 Adapted from Fig.1. and 2, from Ana V Diez Roux (2011)  Complex Systems Thinking May Help Us Transcend Current Impasses in Health Disparities Research  Am J Public Health 2011;101 1627-1634   http://ajph.aphapublications.org/cgi/content/abstract/101/9/1627?etoc

Adapted from Fig.1. and 2, from Ana V Diez Roux (2011) Complex Systems Thinking May Help Us Transcend Current Impasses in Health Disparities Research Am J Public Health 2011;101 1627-1634  http://ajph.aphapublications.org/cgi/content/abstract/101/9/1627?etoc

BEACH Report 41 A decade of Australian general practice activity 2006–07 to 2015–16  book  University of Sydney 2016
BEACH Report 41 A decade of Australian general
practice activity 2006–07 to 2015–16 book University of Sydney 2016
WIP ideas for group model building representation See later Australian Version Hybrid   Insight
WIP ideas for group model building representation See later Australian Version Hybrid  Insight
SD reformulation of  jama psychiatry article  mason2017 on neurocomputational model of mood instability and reward dysregulation in bipolar disorder
SD reformulation of jama psychiatry article mason2017 on neurocomputational model of mood instability and reward dysregulation in bipolar disorder
 A simplified dynamic model, adapted from Engineering perspectives on healthcare delivery: Can we afford technological innovation in healthcare? Rouse, William B Systems Research and Behavioral Science 2009 Vol 26 (5) p573-582  abstract   Developed by Mark Heffernan. Addition of learning curve effec

A simplified dynamic model, adapted from Engineering perspectives on healthcare delivery: Can we afford technological innovation in healthcare? Rouse, William B Systems Research and Behavioral Science 2009 Vol 26 (5) p573-582 abstract  Developed by Mark Heffernan. Addition of learning curve effects IM-614 to Insight 435

 Adapted from Fig.4, from Ana V Diez Roux (2011)  Complex Systems Thinking May Help Us Transcend Current Impasses in Health Disparities Research  Am J Public Health 2011;101 1627-1634   http://ajph.aphapublications.org/cgi/content/abstract/101/9/1627?etoc

Adapted from Fig.4, from Ana V Diez Roux (2011) Complex Systems Thinking May Help Us Transcend Current Impasses in Health Disparities Research Am J Public Health 2011;101 1627-1634  http://ajph.aphapublications.org/cgi/content/abstract/101/9/1627?etoc

 Rich picture causal loops unfolding version of Insight 714, Based on Lyneis JM and Ford DN System Dynamics Applied to Project Management Syst. Dyn. Rev. 23, 157-189 (2007)

Rich picture causal loops unfolding version of Insight 714, Based on Lyneis JM and Ford DN System Dynamics Applied to Project Management Syst. Dyn. Rev. 23, 157-189 (2007)

 
 Adapted from Fig 13.1 p.523 of the Book: James A. Forte ( 2007),  Human Behavior and The Social Environment: Models, Metaphors and Maps for Applying Theoretical Perspectives to Practice   Thomson Brooks/Cole Belmont ISBN 0-495-00659-9

Adapted from Fig 13.1 p.523 of the Book: James A. Forte ( 2007), Human Behavior and The Social Environment: Models, Metaphors and Maps for Applying Theoretical Perspectives to Practice  Thomson Brooks/Cole Belmont ISBN 0-495-00659-9

 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.  

 Patients on Treatment represented as people in a swimming pool. Fast Switchers change costumes. Lapsed Users sit by the pool. Misdiagnosed people are in the wrong pool. Extended from  IM-305

Patients on Treatment represented as people in a swimming pool. Fast Switchers change costumes. Lapsed Users sit by the pool. Misdiagnosed people are in the wrong pool. Extended from IM-305