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Introduction:
This model demonstrates the COVID-19 outbreak in Burnie, Tasmania. It shows how the government policy tries to reduce the spread of COVID-19 whilst also impacting the local economy.

Assumptions:
This model has four variables that influence the number of COVID-19 cases: infection rate, immunity loss rate, recovery rate and death rate.

In order to reduce the pandemic spread, in this model, assume the government released six policies when Burnie COVID-19 cases are equal or over 10 cases. Policies are vaccination promotion, travel restriction to Burnie, quarantine, social distance, lockdown and testing rate.

Government policies would reduce the pandemic. However, it decreases economic growth at the same time. In this model, only list three variable that influence local economic activities. 
Travel restrictions and quarantine will reduce Burnie tourism and decrease the local economy. On the other hand, quarantine, social distance, lockdown allow people to stay at home, increasing E-commerce business.
As a result, policies that cause fewer COVID-19 cases also cause more considerable negative damage to the economy.

Interesting insights:
One of the interesting findings is that the government policy would reduce the COVID-19 spread significantly if I adjust the total government policies are over 20% (vaccine promotion, travel restriction, quarantine, social distance, lockdown), 3560 people will die, then no more people get COVID-19.
However, if I change the total government policy to less than 5%, the whole Burnie people will die according to the model. Therefore, we need to follow the polices, which saves our lives.
BMA708 assignment3 - Model of COVID-19 outbreak in Burnie
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Community Economic Impact
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Template to start Assignment 1.  Includes a solution to Worksheet 4.
MV ISCI 360 Assignment 1 (1)
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Capitalism is in crisis and climate change disruption is now beginning to hit the bottom line. Insurance companies know this well. According to a report by the Bank of England, insured losses have risen from $10 000 million in 1985 to $50 000 million in 2015. Climate change cannot be reversed, and extreme weather events  will undoubtedly get worse in the future strengthening the disruptive effects shown in the CLD.  Another dynamic is that companies will continue to automate and, as The Economic Policy Institute has shown, fail to reflect  productivity gains in workers' salaries. The result, stagnating salaries is disastrous for demand, given that capitalism needs endlessly rising demand and consumption. A further serious problem is that as climate change gets worse there will be increasing demands for companies to assume their responsibility and bear the costs of negative externalities.  The CLD shows these factors which are likely to lead to the collapse of the system: when capitalism can no longer generate 'capital' it has stopped to serves any useful purpose. 

DOES THIS DYNAMIC SPELL THE END OF CAPITALISM
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From Jay Forrester 1988 killian lectures youtube video describing system dynamics at MIT. For Concepts See IM-185226. For more detailed biography See Jay Forrester memorial webpage For MIT HIstory see IM-184930
System Dynamics Applications
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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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Base_economics
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To compete with cheap price and convenience,
Community Economy must provide the distinct merits; human connection, belief in person, unique quality enable citizens willing to pay for fair price.
Community Values Change the Spending Choice of Citizens for Economic Equity
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From Walrave ISDC2014 paper Counteracting the success trap in publically owned corporations. Similar to the ordinary (efficiency focussed) and dynamic capabilities (explore) insight described by David Teece
See also evolution and brain control insight
Explore or Exploit
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Verano, Mary Ann (Economic Data)
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This paper aims at describing a case where system dynamics modeling was used to evaluate the effects of information and material supply lead-time variation on sales contributions margins and operating cash conversion cycle of a commodity export business.  An empirical dynamic model, loaded with econometric theory of price effect on competitive demand, was used to describe the input data.  The model simulation outputs proved themselves relevant in analyzing the complex interconnections of multiple variables affecting  the profitability in a commercial routine, supporting the decision process among sales managers.

SDR Case study System dynamic modelling
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Simulating Hyperinflation for 3650 days.

If private bond holdings are going down and the government is running a big deficit then the central bank has to monetize bonds equal to the deficit plus the decrease in private bond holdings.  We don't show the details of the central bank buying bonds here, just the net results.

See blog at http://howfiatdies.blogspot.com for more on hyperinflation, including a hyperinflation FAQ.
Hyperinflation Simulation
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System Zoo Z409 Fishery dynamics from Hartmut Bossel (2007) System Zoo 2 Simulation Models. Climate, Ecosystems, Resources

Fishing is a classic example for use of a renewable resource. Unless overfished, fish populations If is hardly by fishing, then the fish population will persist at a constant size corresponding to its specific ecological envi­ ronment If the stock is overfished, the juvenile generation becomes too small to fully replace the adult generation. If overfishing continues. the population cannot recover and will collapse in short time. Even if fish catch stops now/, it could take decades until the fish population recovers to its original size if it hasn't become extinct meanwhile. In many of the world overtlshing has led, and still leads, to the complete collapse of formerly huge tlsh populations: herring in the North Sea, codtlsh in the Northern Atlantic. tuna, whales to name only a few. With the collapse of fish stocks came the collapse of the t1shing industry in many regions. Employment and
incomes disappeared: whole regions (like Newfoundland) lost their economic base.​
REM 221 - Z409 Fishery dynamics
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This Model was developed from the SEIR model (Susceptible, Enposed, Infected, Recovered). It was designed to explore relationships between the government policies regarding the COVID-19 and its impact upon the economy as well as well-being of residents. 

Assumptions:

Government policies will be triggered when reported COVID-19 case are 10 or less;


Government Policies affect the economy and the COV-19 infection negatively at the same time;


Government Policies can be divided as 4 categories, which are Social Distancing, Business Restrictions, Lock Down, Travel Ban, and Hygiene Level, and they represented strength of different aspects;

 

Parameters:

Policies like Social Distancing, Business Restrictions, Lock Down, Travel Ban all have different weights and caps, and they add up to 1 in total;

 

There are 4 cases on March 9th; 

Ro= 5.7  Ro is the reproduction number, here it means one person with COVID-19 can potentially transmit the coronavirus to 5 to 6 people;


Interesting Insights:

Economy will grow at the beginning few weeks then becoming stagnant for a very long time;

Exposed people are significant, which requires early policies intervention such as social distancing.

Model of COVID-19 Outbreak in Burnie, Tasmania
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The World Socio-Economics model is computer model to simulate the consequence of interactions between the earth and human systems based on the World3 model by the work of Club of Rome, The Limits to Growth[1].

The World3 model builds by system dynamics theory that is has an approach to understanding the nonlinear behaviour of complex systems over time using stocks, flows, feedback loops, table functions and time delays.

The Limits to Growth concludes that, without substantial changes in resource consumption, "the most probable result will be a rather sudden and uncontrollable decline in both population and industrial capacity". 

Since the World3 model was originally created, it has had minor tweaks to get to the World3-91 model used in the book Beyond the Limits[2], later improved to get the World3-03 model used in the book Limits to Growth: the 30 year update[3].

References;
[1] Meadows, Donella H., Meadows, Dennis L., Randers, Jørgen., Behrens III, William W (1972). The Limits to Growth. 

[2] Meadows, Donella H., Dennis L. Meadows, Randers, Jørgen., (1992). Beyond the limits: global collapse or a sustainable future.

[3] Meadows, Dennis., Randers, Jørgen., (2004). The limits to growth: the 30-year update.
World Socio-Economics model 2000-2100
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Goodwin cycle IM-2010 with debt and taxes added, modified from Steve Keen's illustration of Hyman Minsky's Financial Instability Hypothesis "stability begets instability". This can be extended by adding the Ponzi effect of borrowing for speculative investment.

Minsky Financial Instability Model
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Final Project Socio-Economic Model
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Lakon_Energy Economics Fossil Fuel
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Difficulties with formulae and links
Problems with formulae and links
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The macroeconomic ruel: SPENDING = INCOME = OUTPUT, WHICH DRIVES EMPLOYMENT is presented here in a schematic form. Output can be taken to be equivalent to  GDP. In order to maintain output it is necessary for all the income earned to be spent. If this is not the case, then companies find they have excess unsold stock on their hands and will cut back on production. This, in time, will lead to an increase in unemployment as companies need fewer employees. The shortfall in spending can be made up by any of the three sectors that contribute to total output. However, in cases where  a country has a trade deficit and where the private sector is not spending or investing enough, the only option is for the government to Net Spend i.e. to spend more than it collected in taxes causing a fiscal deficit.

Investment and Output 1
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Clone of Pesticide Use in Central America for Lab work


This model is an attempt to simulate what is commonly referred to as the “pesticide treadmill” in agriculture and how it played out in the cotton industry in Central America after the Second World War until around the 1990s.

The cotton industry expanded dramatically in Central America after WW2, increasing from 20,000 hectares to 463,000 in the late 1970s. This expansion was accompanied by a huge increase in industrial pesticide application which would eventually become the downfall of the industry.

The primary pest for cotton production, bol weevil, became increasingly resistant to chemical pesticides as they were applied each year. The application of pesticides also caused new pests to appear, such as leafworms, cotton aphids and whitefly, which in turn further fuelled increased application of pesticides. 

The treadmill resulted in massive increases in pesticide applications: in the early years they were only applied a few times per season, but this application rose to up to 40 applications per season by the 1970s; accounting for over 50% of the costs of production in some regions. 

The skyrocketing costs associated with increasing pesticide use were one of the key factors that led to the dramatic decline of the cotton industry in Central America: decreasing from its peak in the 1970s to less than 100,000 hectares in the 1990s. “In its wake, economic ruin and environmental devastation were left” as once thriving towns became ghost towns, and once fertile soils were wasted, eroded and abandoned (Lappe, 1998). 

Sources: Douglas L. Murray (1994), Cultivating Crisis: The Human Cost of Pesticides in Latin America, pp35-41; Francis Moore Lappe et al (1998), World Hunger: 12 Myths, 2nd Edition, pp54-55.

Clone of REM 221 - Causal Loop diagramming
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Goodwin Model:
This is a basic version of the Goodwin Model based on Kaoru Yamagushi (2013), Money and Macroeconomic Dynamics, Chapter 4.5 (link)

Equilibrium conditions:
  • Labor Supply = 100
Devation from the equilibrium conditions generates growth cycles.
Goodwin Model
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Explanation of the Model

This is a sample model of Covid-19 outbreak in Burnie, Tasmania showing how the Government responds by implementing relevant health policy and the effects on the Economy of the area. 
 
Assumptions

Economic growth rate is dependent on the proportion of the population who can be exposed. Number of COVID cases negatively impacts the economy. Govt policy is triggered when COVID-19 cases are 10 or more.

Interesting Insights

1) Exposure to the disease has a positive relationship with economic growth rate because the more people goes out, more business activity takes place, resulting in Economic Growth.

2) Increasing the Testing rate results in:

- Higher cases being detected

- Stricter Govt Policy

- Less Deaths


 


Covid-19 outbreak in Burnie Tasmania
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Socio-economic Cycle - Final Porjecy