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Ocean/atmosphere/biosphere model tuned for interactive economics-based simulations from Y2k on.
Lab 13 Start
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Stage 4 Project
Stage 4
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This model is comparing healthy and sick residents in Burnie, Tasmania after the Covid-19 Outbreak in 2020. It will also show how the Burnie economy is effected by the disease, how the Government Health Policies are implemented and how they are enforced.

This model is based on the SIR, Susceptible, Infection, Recovery (or Removed) These are the three possible states related to the members of the Burnie population when a contagious decease spreads.

The Government/Government Health Policy, played a big part in the successful decrease in Covid-19 infections. The Government enforced the following.
- No travel (interstate or international)
- Isolation within the residents homes
- Social distancing by 1.5m
- Quarantine
- Non essential companies to be temporarily closed
- Limitations on public gatherings
- And limits on time and kilometers aloud to travel from ones home within a local community

This resulted in lower reported infection rates of Covid-19 and higher recovery rates.

In my opinion:
When the first case was reported the Government could have been even faster to enforce these rules to decrease the fatality rates further for the Burnie, population.  

Assumption: Government policies were only triggered when 10 cases were recorded.
Also, more cases that had been recorded effected the economic growth during this time.

Interesting Findings: In the simulation it shows as the death rates increases towards the end of the week, the rate of testing goes down. You would think that the government would have enforced a higher testing rate over the duration of this time to decrease the number of infections, exposed which would increase the recovery rates faster and more efficiently.  

Figures have been determined by the population of Burnie being 19,380 at the time of assignment.

Complex Systems How Burnie Tasmania dealt with Covid-19 Outbreak BMA708
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Deforestation and Economic Development in an Underdeveloped County
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Economic Effect
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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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241004_economic growth model structure_SFD
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Overview of Part G Ch 27 to 30 of Mitchell Wray and Watts Textbook see IM-164967 for book overview
History of Macroeconomic Thought
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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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From a March 2016 blog entry by Ari Andricopoulos
The economy simply explained
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This causal loop diagram illustrates the interconnected factors affecting the economic empowerment of Congolese refugee women in Rwanda, with economic dependency as the central problem reinforced by limited access to vocational training, employment opportunities, and financial services. The diagram shows two key reinforcing loops: one where vocational training leads to employment and income generation, which reduces dependency and improves access to further training (R1), and another where income generation builds self-confidence and skills recognition, leading to better employment opportunities (R2), while language barriers and cultural constraints act as inhibiting factors throughout the system.

Causal Loop Diagram: Economic Empowerment of Congolese refugee women in Rwanda.
9 months ago
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COVID Systemigram
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Economic Model
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Implementação do modelo Handy.

Referência:

Motesharrei, S.; Rivas, J.; Kalnay, E. "Human and nature dynamics (HANDY): Modelling inequality and use of resources in the collapse or sustainability of societies". Ecological Economics 101 (2014) 90-102

http://www.sciencedirect.com/science/article/pii/S0921800914000615
HANDY
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MONEY_People, Experts. Knowledge IPN_Model2_Oscillations_0.1.7
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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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Farming_small vs large
10 months ago
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ESI6550 Group 6 (Model 2)
10 months ago
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Laying out and testing before coupling to main model (which is Final Project)
Socio-Economic Factors
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An initial study of the economics of single use coffee pods.
Nina Coffee Company Model *
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WIP Dynamic map from Steve Keen's Minsky at 100 Lecture video and slides and later Emergent Macroeconomics papers
Minsky Instability from Macrodefinitions Keen
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THE NEW SCIENCE OF PLEASURE Daniel L. McFadden NBER Working Paper 18687

From Extended Neoclassical to Behavioral Choice Models