Kermack–McKendrick Epidemic SIR Infectious Disease Model - 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.

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

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

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

Benefits and context described in Atkinson S et al (2000) Going down to the local: incorporating social organisation and political culture into assessments of decentralised health care Social Science & Medicine 51(4) 619-636 http://dx.doi.org/10.1016/S0277-9536(00)00005-8 in Gilson L, ed. (2012). Health Policy and Systems Research: A Methodology Reader Alliance for Health Policy and Systems Research, World Health Organization p166-183

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.

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/

Love affairs and Differential equations. From Michael J Radzicki (1993) Dyadic processes,tempestuous relationships, and system dynamics Syst. Dyn. Rev. 9 (1) :79-94 

Adapted from Fig.3, 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

Prochaska's transtheoretical model (TTM) of behavior change. See also Agent Based VersionIM-11578

Extension of IM-1401 to clinical judgments of risk and decisions to act  See medical decision making 2016 article abstract