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.

Jones AP, Homer JB, Murphy DL, Essien JDK, Milstein B, Seville DA.

Understanding diabetes population dynamics through simulation modeling

and experimentation. American Journal of Public Health 2006;96(3):488-494.

http://ajph.aphapublications.org/cgi/content/abstract/96/3/488

IM-1175 with computable arguments, based on ideas from Micropublications paper about Claims, Evidence, Representations and Context Networks

An adaptation of the URBAN1 Model from Navid Ghaffarzadegan, John Lyneis and George P Richardson's How small system dynamics models can help the public policy process. System Dynamics Review 27: 22-44 (2011) Conference version at http://bit.ly/HlxtZj  and LA Alfeld and AK Graham's Introduction to Urban Dynamics 1974 p 195.

This map is a WIP derived from the MIT D-memo 4641 presentation by Nelson Repenning 1996 and the paper "Nobody Ever Gets Credit for Fixing Problems that Never Happened: Creating and Sustaining Process Improvement" by Nelson P. Repenning and John D Sterman. http://bit.ly/jCXGKL See Insight 9781 for a simulation of this model. This map adds additional features mentioned in the article to the bare bones simulation in IM-9781

High level conceptual model for a Haemophilia charity.

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 David Rees PhD dissertation "Developing a Theory of Implementation for Better Chronic Health Management" Health Services Research Centre, Victoria University of Wellington, New Zealand

Interacting nested fast and slow adaptive cycles from Panarchy Book  ,Resilience thinking Book Brian Walker and David Salt Island Press 2006 and the http://www.resalliance.org/ Website, See also What is Panarchy at http://bit.ly/H9RFkL

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

WIP ideas for group model building representation

Rich picture version of causal loop diagram for medication errors, showing the importance of reporting, analyzing and fixing knowledge and process errors. Medication errors will tend to grow due to the use of more medications in more complex patients. This is exacerbated by the loss of staff knowledge by turnover and goal erosion in places with harmful errors.

From Walrave ISDC2014 paper Counteracting the success trap in publically owned corporations. Similar to the ordinary (efficiency focussed) and dynamic capabilities (explore) insight described by David Teece

Current and proposed Structure of CCP and related Models expanding on the details provided in the Project Completion plan IM-101760

Nations are fighting had to try contain CoviD 19 -Corona virus pandemic worldwide. As of this week a huge number succumbed to the disease while the infections rates continue to be very high. A majority of the countries have reported cases of the virus and have resulted to various measures in order to keep up with the fight. As a treding issue I took I found it wise to model the Covid 19 problem.  Coronavirus Cases:

Latest data shows

614,051

Deaths:

28,234

Recovered:

137,271

WIP for Continuity of care ISO From Wikipedia Initial Insight Representation from ContSys

IM-4008 with split off patient and professional statecharts See IM-2846 for Agent with infectious disease and IM-6913 for ED Physician INteraction

Nested multilevel inquiry across multiple levels of organization of biology concepts. Adapted from Knippels (2002) PhD Thesis at http://bit.ly/GGcKo1 . Note the similarity to the nested adaptive cycles of socio-ecological systems in IM 1169

Suicide Prevention  WIP

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

This common archetype of systems that include relapse or recidivism allows exploration of the unintended effects of increasing upstream capacity and swamping downstream capacity. The increase in the relapse rate eventually returns to swamp upstream capacity as well. A social welfare example, based on a TANF case study, from How Small System Dynamics Models Can Help the Policy Process. N. Ghaffarzadegan, J. Lyneis, GP Richardson. System Dynamics Review 27,1 (2011) 22-44 Conference version at http://bit.ly/HlxtZj

Summary of evolution and the modern synthesis with genetics. See also the more recent extended synthesis IM-2099