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 work in progress conceptual model based on Using system dynamics principles for conceptual modelling of publicly funded hospitals by HJ Wong et al Journal of the Operational Research Society advance online publication, 27 April 2011 doi:10.1057/jors.2010.164. Linked concepts with annotated definitions.

Downstream and upstream responses, from Jack Homer , Gary HIrsch and Bobby Milstein. Chronic Illness in a Complex Health Economy  Syst. Dyn. Rev. 23, 313-343 (2007). Conference paper available at  http://bit.ly/JCO68V

Linked concept version of Tanner's Clinical Judgment Model used as a scaffolding to start modeling managing the deteriorating patient.

The dynamics of methadone treatment for intravenous opioid users. The major flows in this study were people cycling between being on methadone and off treatment. Monograph pdf

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

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

Simple Bass diffusion modified from Sterman Business Dynamics Ch9, with additional discarding

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

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

Extension of IM-14124 with an adjusted bed capacity stock. For backlog and services see IM-8382

Bond Graph Kinetic Modeling Metabolic Map by J LeFevre  http://www.systemdynamics.org/conferences/2004/SDS_2004/PAPERS/379LEFEV.pdf

See also IM-857 and IM-2235 for more detail

Work in progress based on PA Sorokin's Reconstruction of Humanity, moving from egoistic to altruistic personalities, social institutions and an idealistic cultural supersystem

Rich picture version of Tanner's Clinical Judgment Model, with the addition of clinical reasoning cycle concepts from T Levett-Jones et al Nurse Education Today 30 (2010) 515-520

IPCC Extreme weather events combined context diagrams  FBE WIP

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.