This is the third in a series of models that explore the dynamics of infectious diseases. This model looks at the impact of two types of suppression policies.      Press the simulate button to run the model with no policy.  Then explore what happens when you set up a lockdown and quarantining polic
This is the third in a series of models that explore the dynamics of infectious diseases. This model looks at the impact of two types of suppression policies. 

Press the simulate button to run the model with no policy.  Then explore what happens when you set up a lockdown and quarantining policy by changing the settings below.  First explore changing the start date with a policy duration of 60 days.
 Spring, 2020: in the midst of on-line courses, due to the pandemic of Covid-19.      With the onset of the Covid-19 coronavirus crisis, we focus on SIRD models, which might realistically model the course of the disease.     We start with an SIR model, such as that featured in the MAA model featured
Spring, 2020: in the midst of on-line courses, due to the pandemic of Covid-19.

With the onset of the Covid-19 coronavirus crisis, we focus on SIRD models, which might realistically model the course of the disease.

We start with an SIR model, such as that featured in the MAA model featured in

Without mortality, with time measured in days, with infection rate 1/2, recovery rate 1/3, and initial infectious population I_0=1.27x10-4, we reproduce their figure

With a death rate of .005 (one two-hundredth of the infected per day), an infectivity rate of 0.5, and a recovery rate of .145 or so (takes about a week to recover), we get some pretty significant losses -- about 3.2% of the total population.

Resources:
This model simulates the basic dynamics of a water reservoir, including the impact of rainfall, community water consumption, conservation efforts, and evaporation. The model shows how the reservoir’s water level changes over time based on natural inflows and human , nature water use.
This model simulates the basic dynamics of a water reservoir, including the impact of rainfall, community water consumption, conservation efforts, and evaporation. The model shows how the reservoir’s water level changes over time based on natural inflows and human , nature water use.
A student thought of this model.  It is based on the water flow data and projections on pages 68 and 69 of LTG30.   It models all the available freshwater in rivers and dams in one year, which is represented as a stock.   The water flowing in is all the world's runoff, and the water flowing out is i
A student thought of this model.  It is based on the water flow data and projections on pages 68 and 69 of LTG30.  
It models all the available freshwater in rivers and dams in one year, which is represented as a stock. 
The water flowing in is all the world's runoff, and the water flowing out is in two categories: Water used by people, and water not used by people.
This model uses a converter which allowed us to enter the UN projection of water use in 2050.  Click on the converter to see how it works.
  About
the Model  

 This
model is designed to simulate the youth population in Bourke, specifically
focusing on the number of criminals and incarcerated dependent on a few key
variables. 

 Within the model, a young person living in Bourke can be classified as being in any of five states:  Young C

About the Model

This model is designed to simulate the youth population in Bourke, specifically focusing on the number of criminals and incarcerated dependent on a few key variables.

Within the model, a young person living in Bourke can be classified as being in any of five states:

Young Community Member: The portion of the youth population that is not committing crime and will not commit crime in the future. Essentially the well behaved youths. A percentage of these youths will become alienated and at risk.

Alienated and At Risk Youths: The youths of Bourke that are on the path of becoming criminals, this could be caused by disruptive home lives, alcohol and drug problems, and peer pressure, among other things.

Criminal: The youths of Bourke who are committing crimes. Of these criminals a percentage will be caught and convicted and become imprisoned, while the remainder will either go back to being at risk and commit more crimes, or change their behaviour and go back to being a behaving community member.

Imprisoned: The youths of Bourke who are currently serving time in a juvenile detention centre. Half of the imprisoned are released every period at a delay of 6 months.

Released: Those youths that have been released from a detention centre. All released youths either rehabilitate and go back to being a community member or are likely to re-offend and become an alienated and at risk youth.

The variables used in the model are:

Police- This determines the police expenditure in Bourke, which relates to the number of police officers, the investment in surveillance methods and investment in criminal investigations. The level of expenditure effects how many youths are becoming criminals and how many are being caught. An increase in police expenditure causes an increase in imprisoned youths and a decrease in criminals.

Community Engagement Programs- The level of investment in community engagement programs that are targeted to keep youths in Bourke from becoming criminals. The programs include sporting facilities and clubs, educational seminars, mentoring programs and driving lessons. Increasing the expenditure in community engagement programs causes more young community members and less criminals and at risk youths.

Community Service Programs- The level of investment in community service programs that are provided for youths released from juvenile detention to help them rehabilitate and reintegrate back into the community. An increase in community service expenditure leads to more released prisoners going back into the community, rather than continuing to be at risk. Since community service programs are giving back to the community, the model also shows that an increase in expenditure causes a decrease in the amount of at risk youths.

All three of these variables are adjustable. The number of variables has been kept at three in order to ensure the simulation runs smoothly at all times without complicated outputs, limitations have also been set on how the variables can be adjusted as the simulation does not act the same out of these boundaries.

Key Assumptions:

The model does not account for the youths’ memory or learning.

There is no differentiation in the type of criminals and the sentences they serve. Realistically, not all crimes would justify juvenile detention and some crimes would actually have a longer than six-month sentence.

The constants within in the calculations of the model have been chosen arbitrarily and should be adjusted based on actual Bourke population data if this model were to be a realistic representation of Bourke’s population.

The model assumes that there are no other factors affecting youth crime and imprisonment in Bourke.

There are 1500 youths in Bourke. At the beginning of the simulation:

Young Community Member = 700

Alienated and At Risk Youth = 300

Criminal = 300

Imprisoned = 200

Noteworthy observations:

Raising Police expenditure has a very minimal effect on the number of at risk youths. This can be clearly seen by raising Police expenditure to the maximum of twenty and leaving the other two variables at a minimum. The number of Alienated and at Risk Youths is significantly higher than the other states.

Leaving Police expenditure at the minimum of one and increasing community development programs and community service programs to their maximum values shows that, in this model, crime can be decreased to nearly zero through community initiatives alone.

Leaving all the variables at the minimum position results in a relatively large amount of crime, a very low amount of imprisoned youth, and a very large proportion of the population alienated and at risk.

An ideal and more realistic simulation can be found by using the settings: Police = 12, Community Engagement Programs = 14, Community Service Programs = 10. This results in a large proportion of the population being young community members and relatively low amounts of criminals and imprisoned.



Insight Maker model based on the Z415 System Zoo model originally developed in Vensim. Adaptation of this model. The adaptation involves adding sliders to improve interaction with the model. This model does not include findings of additional resource reserves. In that respect it is static.
Insight Maker model based on the Z415 System Zoo model originally developed in Vensim. Adaptation of this model. The adaptation involves adding sliders to improve interaction with the model.
This model does not include findings of additional resource reserves. In that respect it is static.
WIP for planning  some relevant online M&S Learning Communities for Health
WIP for planning  some relevant online M&S Learning Communities for Health
Builds on earlier model for the Thinking Systemically segment of STCP. Develops EaBT approach. Describes innovation in a service delivery/consulting organisation whose clients expect/demand "innovation" due to their own lack of ability to improve.
Builds on earlier model for the Thinking Systemically segment of STCP. Develops EaBT approach.
Describes innovation in a service delivery/consulting organisation whose clients expect/demand "innovation" due to their own lack of ability to improve.

 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  

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

 From  Werner Ulrich 's JORS Articles Operational research and critical systems thinking – an integrated perspective.  Part 1 : OR as applied systems thinking.  Journal of the Operational Research Societ y advance online publication (14 December 2011). and  Part 2  :OR as argumentative practice.

From Werner Ulrich's JORS Articles Operational research and critical systems thinking – an integrated perspective. Part 1: OR as applied systems thinking. Journal of the Operational Research Society advance online publication (14 December 2011). and Part 2 :OR as argumentative practice.

 From  Werner Ulrich 's JORS Articles Operational research and critical systems thinking – an integrated perspective.  Part 1 : OR as applied systems thinking.  Journal of the Operational Research Societ y advance online publication (14 December 2011). and  Part 2  :OR as argumentative practice.

From Werner Ulrich's JORS Articles Operational research and critical systems thinking – an integrated perspective. Part 1: OR as applied systems thinking. Journal of the Operational Research Society advance online publication (14 December 2011). and Part 2 :OR as argumentative practice.

 Spring, 2020: in the midst of on-line courses, due to the pandemic of Covid-19.      With the onset of the Covid-19 coronavirus crisis, we focus on SIRD models, which might realistically model the course of the disease.     We start with an SIR model, such as that featured in the MAA model featured
Spring, 2020: in the midst of on-line courses, due to the pandemic of Covid-19.

With the onset of the Covid-19 coronavirus crisis, we focus on SIRD models, which might realistically model the course of the disease.

We start with an SIR model, such as that featured in the MAA model featured in

Without mortality, with time measured in days, with infection rate 1/2, recovery rate 1/3, and initial infectious population I_0=1.27x10-4, we reproduce their figure

With a death rate of .005 (one two-hundredth of the infected per day), an infectivity rate of 0.5, and a recovery rate of .145 or so (takes about a week to recover), we get some pretty significant losses -- about 3.2% of the total population.

Resources:
Summary of Ray Pawson's Book The Science of Evaluation: A Realist Manifesto See also  lse review
Summary of Ray Pawson's Book The Science of Evaluation: A Realist Manifesto See also lse review
Overview of Part E Ch 20 to 24 of Mitchell Wray and Watts Textbook see  IM-164967  for book overview
Overview of Part E Ch 20 to 24 of Mitchell Wray and Watts Textbook see IM-164967 for book overview