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Socioeconomic Factors Section
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An initial study of the economics of single use coffee pods.
Claire - Coffee Pods ISD Humanities v 1.02
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Business Economic Sustainability
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Fig 17.15 p700 Causal structure of commercial real estate markets of Case Study from John Sterman's 2000 Business Dynamics Book 
Boom and bust in Commercial Real Estate
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Overview:

Overall, this analysis showed a COVID-19 outbreak in Burnie, the government policies to curtail that, and some of the impacts it is having on the Burnie economy.


Variables

The simulation made use of the variables such as; Covid-19: (1): Infection rate. (2): Recovery rate. (3): Death rate. (4): Immunity loss rate etc. 


Assumptions:

From the model, it is apparent that government health policies directly affect the economic output of Burnie. A better health policy has proven to have a better economic condition for Burnie and verse versa.


In the COVID-19 model, some variables are set at fixed rates, including the immunity loss rate, recovery rate, death rate, infection rate, and case impact rate, as this is normally influenced by the individual health conditions and social activities.

Moving forward, we decided to set the recovery rate to 0.7, which is a rate above the immunity loss rate of 0.5, so, the number of susceptible could be diminished over time.


Step 1: Try to set all value variables at their lowest point and then stimulate. 

 

Outcome: the number of those Infected are– 135; Recovered – 218; Cases – 597; Death – 18,175; GDP – 10,879.


Step 2: Try to increase the variables of Health Policy, Quarantine, and Travel Restriction to 0.03, others keep the same as step 1, and simulate


Outcome: The number of those Infected – 166 (up); Recovered – 249 (up); Cases – 554 (down); Death – 18,077 (down); GDP – 824 (down).


With this analysis, it is obvious that the increase of health policy, quarantine, and travel restriction will assist in increase recovery rate, a decrease in confirmed cases, a reduction in death cases or fatality rate, but a decrease in Burnie GDP.


Step 3: Enlarge the Testing Rate to 0.4, variable, others, maintain the same as step 2, and simulate


Outcome: It can be seen that the number of Infected is down to – 152; those recovered down to – 243; overall cases up to – 1022; those that died down to–17,625; while the GDP remains – 824.


In this step, it is apparent that the increase of testing rate will assist to increase the confirmed cases.


Step 4: Try to change the GDP Growth Rate to 0.14, then Tourism Growth Rate to 0.02, others keep the same as step 3, and then simulate the model


Outcome: what happens is that the Infected number – 152 remains the same; Recovered rate– 243 the same; Number of Cases – 1022 (same); Death – 17,625 (same); but the GDP goes up to– 6,632. 


This final step made it obvious that the increase of GDP growth rate and tourism growth rate will help to improve the overall GDP performance of Burnie's economy.

The Recent COVID-19 Outbreak in Burnie Tasmania - Buchi Okafor 546792
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lab 13 Social and economic
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Vicious economic circle of Aboriginal people
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WIP Summary of MIchael Hudson's Book Killing the Host: How Financial Parasites and Debt destroy the Global Economy 
Killing the Host
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Systemigram Model Building Exercise
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DPSIR Framework to Analyze EcoPeace Middle East's Good Water Neighbours Strategy
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The World3 model is a detailed simulation of human population growth from 1900 into the future. It includes many environmental and demographic factors.

Use the sliders to experiment with the initial amount of non-renewable resources to see how these affect the simulation. Does increasing the amount of non-renewable resources (which could occur through the development of better exploration technologies) improve our future? Also, experiment with the start date of a more environmentally focused policy.

ECM-Training - World3 Model (clone) : Classic World Simulation
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economic inequality
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Social determinants of health are economic and social conditions that influence the health of people and communities. These conditions are shaped by the amount of money, power, and resources that people have, all of which are influenced by policy choices. Social determinants of health affect factors that are related to health outcomes. Factors related to health outcomes include:
  • How a person develops during the first few years of life (early childhood development)
  • How much education a persons obtains
  • Being able to get and keep a job
  • What kind of work a person does
  • Having food or being able to get food (food security)
  • Having access to health services and the quality of those services
  • Housing status
  • How much money a person earns
  • Discrimination and social support
Determinates of a healthy population
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Ocean/atmosphere/biosphere model tuned for interactive economics-based simulations from Y2k on.
Utopia!!!!!!!
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Rating Matrix of S&P
Rating Matrix
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Barangay IRAWAN Systems Model
Biophysical, Socio-cultural & Economic Data of Bgy. IRAWAN
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Bourke is a remote town in NSW with a population of 2634 people.  In 2013 crime figures from Bourke showed the highest assault, break-ins and car theft rates in NSW with crime spikes mostly occurring during nights and school holidays.  Over the past five years, the Aboriginal Community has come together to trial a model for change, called Just Reinvest.

This  model illustrates the relationship between Community Factors (which includes social disadvantage, economic issues, family trauma) on Disengaged Youth, Crime and the impact of the Just Reinvest Program.  This model particularly illustrates the complexity of factors on outcomes and how factors are interrelated making crime a wicked problem that is not easily viewed in isolation from the socio-economic and social causes.

Stocks
Youth in Burke is set based on Australian Bureau of Statistics levels but is easily modified to track population changes on modelling
Disengaged Youth are those with problematic behaviour 
Crime Levels are those Disengaged Youth who go on to commit a crime
Early Intervention Programs are those run through Just Reinvest as part of the community program - the quantity of these can be adjusted.

Data of Note
- Economic Impact is five times cost of running the program
- Justice Impacts are roughly 66% and Non-Justice Impacts make up the remaining 33%.

Assumptions
While the UN defines "Youth" as 15 - 24 year olds, the KPMG report outlines programs for 10 - 24 year olds therefore in the context of Bourke the 10 - 24 year old age bracket is considered "Youths".  This has been rounded to 700 people (ABS 2016 Census).

- It is estmated 70% of Bourke Youths will have problematic behaviour with 50% of those going on to commit a crime and be caught
- Cost of Early Intervention Youth Program is estimated at $100 per person per crime

Conclusion

While this model shows the impacts and benefits of additional funding on early intervention programs and the flow on affects this has on crime, it does not take into account the underlying cultural and social disadvantage issues that are often motivators for crime nor does this model take into account issues such as cultural prejudice and bias, over-policing or additional early intervention methods.
Relationship between Youth Alienation, Police and Community Development in Bourke
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Introduction:

This model demonstrates the COVID-19 outbreak in Bernie, Tasmania, and shows the relationship between coVID-19 outbreaks, government policy and the local economy. The spread of pandemics is influenced by many factors, such as infection rates, mortality rates, recovery rates and government policies. Although government policy has brought the Covid-19 outbreak under control, it has had a negative impact on the financial system, and the increase in COVID-19 cases has had a negative impact on economic growth.

 

Assumptions:

The model is based on different infection rates, including infection rate, mortality rate, detection rate and recovery rate. There is a difference between a real case and a model. Since the model setup will only be initiated when 10 cases are reported, the impact on infection rates and economic growth will be reduced.

 

Interesting insights:

Even as infection rates fall, mortality rates continue to rise. However, the rise in testing rates and government health policies contribute to the stability of mortality. The model thinks that COVID-19 has a negative impact on offline industry and has a positive impact on online industry.

Model of COVID-19 outbreak in Burnie, Tasmania
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Ocean/atmosphere/biosphere model tuned for interactive economics-based simulations from Y2k on.
normL
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Overview
The model simulates how logging in with tourism(mountain biking) in Derby Tasmania.
How the model works.
Trees grow, loggers cut them in order to sell them because of demand for Timber.
Mountain cyclist depends on satisfaction and expectation.  Satisfaction and Expectation depends on Scenery number of trees compared to visitor and Adventure number of trees and users.  Park capacity limits the number of users.  Local Business is influenced by the timber and number of Mountain Cyclist. Employment is influenced by the number of mountain cyclist and logging activity.

Simulation of Mountain Cyclist vs logging
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COVID-19 Outbreak in Burnie Tasmania Simulation Model

Introduction:

This model simulates the COVID-19 outbreak situation in Burnie and how the government responses impact local economy. The COVID-19 pandemic spread is influenced by several factors including infection rate, recovery rate, death rate and government's intervention policies.Government's policies reduce the infection spread and also impact economic activities in Burnie, especially its tourism and local businesses.   

Assumptions: 

- This model was built based on different rates, including infection rate, recovery rate, death rate, testing rate and economic growth rate. There can be difference between 
this model and reality.

- This model considers tourism and local business are the main industries influencing local economy in Burnie.

- Government's intervention policies will positive influence on local COVID-19 spread but also negative impact on local economic activity.

- When there are more than 10 COVID-19 cases confirmed, the government policies will be triggered, which will brings effects both restricting the virus spread and reducing local economic growth.

- Greater COVID-19 cases will negatively influence local economic activities.

Interesting Insights:

Government's vaccination policy will make a important difference on restricting the infection spread. When vaccination rate increase, the number of deaths, infected people and susceptible people all decrease. This may show the importance of the role of government's vaccination policy.

When confirmed cases is more than 10, government's intervention policies are effective on reducing the infections, meanwhile local economic activities will be reduced.

BMA708-Tian Liang-586868-Model of COVID-19 Outbreak in Burnie, Tasmania
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ECONOMIC INEQUALITY IN SOUTH DAKOTA