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Model of Covid-19 outbreak in Burnie, Tasmania

This model was designed from SIR model(susceptible, infected, revovered) to find out the effect of covid-19 outbreak into economic outcomes via government policy.

Assumptions

The government policy is triggered when number of infected is more than ten.

The government policies will take negative effect into Covid-19 outbreaks and financial system

Parameters

We set some fixed and adjusted variables.
Covid-19 outbreak's parameter
Fixed parameters: Infection rate, Background disease, recovery rate.
Adjusted parameter: Immunity loss rate can be change from vaccination rate.

Government policy's parameters
Adjusted parameters: Testing rate(from 0.15 to 0.95), vaccination rate(from 0.3 to 1), travel ban(from 0 to 0.9), social distancing(from 0.1 to 0.8), Quarantine(from 0.1 to 0.9)

Economic's parameters
Fixed parameter: Tourism
Adjusted parameter: Economic growth rate(from 0.3 to 0.5)

Interesting insight

Increase vaccination rate and testing rate will decrease the number amount of infected case and a little bit more negative effect to economic system. However economic system still need a long time to recover in both cases.
BMA708_Assignment 3_ndkvo_520272_COVID-19 outbreak and Burnie economy
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Michael Marmot's Eur J Epidemiol Essay 2017 See also IM-62760  Social determinants of health from Michael Marmot's  ABC 2016 Boyer Lectures on Social Justice and the Health Gap
Social Justice, Epidemiology and Health Inequalities
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This insight includes a Limits to Success archetype. (Bubbles colored with a darker blue)
Economical Factor
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Model-SIM from chapter 3 of Wynn Godley and Marc Lavoie's Monetary Economics, but with household debt added into the model.
Model-SIM-HHD
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Clone of Economics Fast Fashion
12 11 months ago
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Air pollution in Bangladesh
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Model Explanation:

This system dynamics model visualises the impact on investment into policing and community engagement resources on the crime rates within the youth population of Bourke, NSW. 
The model also adds in the variable of funding for safe houses. With a high rate of domestic violence, unfavorable home conditions and other socio-economic factors, many youth roam the streets with no safe place to go, which may lead to negative behaviour patterns.


Assumptions

Youth Population: 700
Total youth population in 2016 for Bourke LGA was 646 (ages 10-29). (Census, 2016) Figures rounded to 700 for purposes of this model simulation. 

Constants:
70% registration and engagement rates for Community funded programs
30% attendance rate for Safe Houses
50% crime conviction rate


Variables

Positive and Negative Influences

The model shows a number of key variables that lead youth to become more vunerable to commit a crime (such as alienation, coming from households with domestic violence, boredom and socio-economic disadvantages such as low income), as well as the variables that enhance the youth's likelihood to be a contributing member of the community (developing trusted relationships and connections with others, and having a sense of self worth, purpose and pride in the community). These factors (positive and negative) are aggregated to a single rate of 50% each for the purposes of the simulation, however each individual situation would be unique.  

Police Funding / Resources

Police funding and resources means the number of active police officers attending to criminal activities, as well as prevention tactics and education programs to reduce negative behaviour. The slider can be moved to increase or decrease policing levels to view the impact on conviction rates. Current policing levels are approx 40 police to a population of under 3000 in Bourke.

Crime Rate

Youth crime rates in Australia were 3.33% (2016). Acknowledging Bourke crime rates are much higher than average, a crime rate of 40% is set initially for this model, but can be varied using the sliders. 


Community Program Funding / Resources

Community Program Funding and Resources means money, facilities and people to develop and support the running of programs such as enhancing employability through mentorship and training, recreational sports and clubs, and volunteering opportunities to give back to the community. As engagement levels in the community programs increase, the levels of crime decrease. The slider can be moved to increase or decrease funding levels to view the impact on youth registrations into the community programs.

Observations

Ideally the simulations should show that an increase in police funding reduces crime rates over time, allowing for more youth committing crimes to be convicted and subsequently rehabilitated, therefore decreasing the overall levels of youth at risk.

A portion of those youth still at risk will move to the youth not at risk category through increased funding of safe houses (allowing a space for them to get out of the negative behaviour loop and away), whom them may consider registering into the community engagement programs. An increase in funding in community engagement programs will see more youth become more constructive members of the community, and that may in turn encourage youth at risk to seek out these programs as well by way of social and sub-cultural influences.

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Justice & Community Support Investment and the Impacts on Bourke Youth Population
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Unfortunately, this model only produces the illusion of functioning, but I did manage to get it to give me the graph. However, because of the use of flows, if you change the time step to and the simulation length to anything other than the same numbers, you'll find the graph showing something that looks more exponential. This is due to the function referencing itself in regards to time, so inevitably each time consumption grows it changes the outcome on the other side of the equation. Still, this is a convincing mock up. I added a "45 degree" line so that one could conceivably see (and also change) the difference made by altering the level of autonomous consumption.
Keynesian Macroeconomics
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Circular equations WIP for Runy.

Added several versions of the model. Added a flow to make C increase. Added a factor to be able to change the value 0.5. 
Circularity in Economic models 1
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Calculating EOQ using classical inventory model
Clone of Economic Order Quantity
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I propose we grow this sim model (or similar) over time to help ourselves better understand the opposing investment and austerity strategies now being advocated for the U.S. government. The hope is to build as simple a model as possible that subsumes the major underlying feedback loops that probably exist in the mental models of proponents of each of these positions. Starting this model was inspired by this Investment vs. Austerity discussion http://www.linkedin.com/groups/Investment-vs-Austerity-How-can-4582801.S.157876413

20120908a_InvestmentVsAusterity
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Economic model
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Model-SIM from Chapter 3 of Wynn Godley and Marc Lavoie's Monetary Economics, adapted for an open economy. The model is stock-flow consistent with only government money--no bills or bonds. No central bank and interest rates do not change. Government spends buying output from the production sector. The production sector is passive turning over all revenue over to households. Households save out of income and spend partially spend out of wealth. Imports and exports pass through the production sector illustrating the idea that consumer households buy from domestic businesses that which they have imported. The model also tracks the sectoral balance flows and changes in equity. Sectoral flows and equity balances match each other dollar for dollar to satisfy the sectoral balances accounting identity (Household Saving - Consumption) + (Business Saving - Expenditure) + (Taxes - Government Spending) - (Exports - Imports) = 0. Since business investment occurs internally to the Business Sector, 
SFC_Model-SIM_open_economy
5 months ago
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Unfolding causal loop diagram story described in Rios-Ocampo and Gary 2025 article  based on Sydney Australia urban planning documents since 1968
Urban growth strategy in Greater Sydney
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A framework exploring flood risk management in a developing city, under the old paradigm of control - characterised by narrowly defined goals and an over-reliance on hard-engineered structural solutions.
Urban flood risk (control paradigm)
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Verano, Mary Ann -Economic Data
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Marine Tourism Task III - Great Blue Hole
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System Dynamics - Ludhiana
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Map of SD work on Samuelson's 1939 model of the business cycle. See also D-memo D-2311-2 Gilbert Low 1976 and IM-165713. An alernative to the Ch 26 Macroeconomics textbook exposition.  From Gil Low's Multiplier Accelerator Model of Business Cycles, Ch 4 of Elements of the System Dynamics Method Book edited by Jorgen Randers 1976 (MIT Press) and 1980 (Productivity Press)
Samuelson multiplier accelerator model
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An initial study of the economics of single use coffee pods.
Real Coffee Pods ISD Humanities v 1.02
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This page provides a structural analysis of POTUS Candidate Rick Perry's economic policy based on the information at: https://rickperry.org/issues/​ The method used is Integrative Propositional Analysis (IPA) available: ​ http://scipolicy.org/uploads/3/4/6/9/3469675/wallis_white_paper_-_the_ipa_answer_2014.12.11.pdf
DRAFT IPA of Rick Perry economic policy
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HANDY Model of Societal Collapse from Ecological Economics Paper 
see also D Cunha's model at IM-15085 (Spanish)
Human and Nature Dynamics of Societal Inequality
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 Goodwin cycle IM-2010 with debt and taxes added, modified from Steve Keen. THis can be extended by adding the Ponzi effect of borrowing for speculative investment.

Minsky Financial Instability Model