Adapted from Fig 10.1 p.393 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

Simplified version of IM-852  Erythropoiesis Stimulating Agents (ESA) Dosing in Anemia due to Renal Failure from Jim Rogers See Stock Flow Map  Insight 810 

Work in progress with Jim Rogers

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.

Causal Loop Rich Picture unfolding from Repenning, N. and J. Sterman (2002). Capability Traps and Self-Confirming Attribution Errors in the Dynamics of Process Improvement. Administrative Science Quarterly, 47: 265 - 295. http://jsterman.scripts.mit.edu/docs/Repenning-2002-CapabilityTraps.pdf

Simple Bass diffusion modified from Sterman Business Dynamics Ch9. Compare with the SI infectious disease model Insight 584.

Clone of model: https://insightmaker.com/insight/610/Diffusion-of-Innovation-Bass-Model

From Rudolph JW Morrison JB and Carroll JS (2009) The Dynamics of Action-Oriented Problem Solving: Linking Interpretation and Choice. Academy of Management Review 34 (4) p733-756 Available online . This paper won the Forrester Award for 2012 and the presentation talk video is available. The presentation  paper abstract is available in System Dynamics Review 2013 here

Personal versus Situational Dynamics: Implications of Barry Richmond’s Models of Classic Experiments in Social Psychology James K. Doyle, Khalid Saeed, Jeanine Skorinko Department of Social Science and Policy Studies Worcester Polytechnic Institute 2008. For background on the infamous 1971 study that pitted students v students in the roles of prisoners & guards see http://www.prisonexp.org 

From MIT ESD work (de Weck Ilities ) esp on Survivability (Medecki) http://bit.ly/HVsceb and Unarticulated Value (Ross) 2006 PhD pdf

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.

From Robert Wears Thesis, Modified from Hollnagel & Sunstrom 2006 p 341 and urban disaster risk stresses and shocks for comparison

SIR model with herd immunity - Metrics by Guy Laekman

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