From Michael Hiete, Mirjam Merz and Frank Schultmann (2011) Scenario-based impact analysis of a power outage on healthcare facilities in Germany IJDRBE 2,3 p222-244

See reference in diagram notes. WIP for Environment part of primary care regional model

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. Extended based on IM-998 4 hour rule context. Can be replicated to add interventions, as in IM-6167. See IM-9178 for Addition of After hours 'as is' and 'to be' flow models for Medicare Locals

A simple generic rich picture view of interactions among concerned people with needs services and resources and abilities (including learning), which can be used as a pattern for many individual health care insights.

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

Main Page for Resilience

Based on Nate Osgood's CLD in his video on causal loop diagramming  26:09

WIP to explain iterative modelling of linkages over space and time see also causal pathways IM

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

This model shows the dynamics of use of a new medical technology based on its scope of use and perceived relative benefit. The technology needs cumulative usage to fix its glitches, and the benefits will be diluted  as the scope of use widens.

A work in progress model for ED daily average flows based on reported statistics by triage category with all triage categories aggregated. Based on a hospital performance report from  http://www.bhi.nsw.gov.au/publications/hospital_quarterly_3 

A simple generic rich picture view of interactions among concerned people with needs services and resources and abilities (including learning), which can be used as a pattern for many individual health care insights.

WIP Conceptual map of initial scope of the effects of the ED 4 hour rule based on June WA Teleconference. See also the addition of unintended consequences at IM-7775 and the potential wider context map in IM-6167. For a simulation see IM-8237

A general model of flows between hospital and the community with workshop elements. See also IM-3200 for focus on frequent presenters with mental health issues

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.

An element of Perspectives: The Foundation of Understanding and Insights for Effective Action. Register at http://www.systemswiki.org/

Or the self-fulfilling prophecy

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

Diagrams from Greene 2017 nejm article Putting the patient back together Social Medicine, Network Medicine, and the Limits of Reductionism

From SDR Jan 2012 article  and 1988 killian award lectures Youtube

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.

Based on Psychological Medicine Dec 2015 article Depression as a systemic syndrome: mapping the feedback loops of major depressive disorder by A. K. Wittenborn, H. Rahmandad, J. Rick and N. Hosseinichimeh, mentioned here