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Ocean/atmosphere/biosphere model tuned for interactive economics-based simulations from Y2k on.
Lab 13 Base Model
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The Logistic Map is a polynomial mapping (equivalently, recurrence relation) of degree 2, often cited as an archetypal example of how complex, chaotic behaviour can arise from very simple non-linear dynamical equations. The map was popularized in a seminal 1976 paper by the biologist Robert May, in part as a discrete-time demographic model analogous to the logistic equation first created by Pierre François Verhulst

Mathematically, the logistic map is written

where:

 is a number between zero and one, and represents the ratio of existing population to the maximum possible population at year n, and hence x0 represents the initial ratio of population to max. population (at year 0)r is a positive number, and represents a combined rate for reproduction and starvation.
For approximate Continuous Behavior set 'R Base' to a small number like 0.125To generate a bifurcation diagram, set 'r base' to 2 and 'r ramp' to 1
To demonstrate sensitivity to initial conditions, try two runs with 'r base' set to 3 and 'Initial X' of 0.5 and 0.501, then look at first ~20 time steps

The Logistic Map
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Extended from Im-628 Supply and demand by adding control folder.
See also Managing Health Services Use IM-17566
Based on JHPPL 2015 article Note here the framing is an economic exchange rather than a public service (needs-services-resources) or capabilities
Neoliberalism and health policy
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Initial Stock & Flow of Energy Infrastructure Development, Climate Change Impacts, and Economic Activity
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Model based on chapter 10 (opportunity cost) of the book Modeling Dynamic Economic Systems
Opportunity cost
310
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This model indicate indicates the modeling COVID-19 outbreaks and responses from government policies with the effect on the local economy. Model was occurred at Burnie, Tasmania. The model mainly contains three parts: COVID-19 pandemic outbreak, four differences government policies and what the impact on economy from those policies.

 

Assumptions:

(1) Various variables influence the model, which can result in varied outcomes. The following values are based on an estimate and may differ from actual values. Government initiatives are focused at reducing Covid-19 infections and, as a result, affecting (both positive and negative) economic growth.

 

(2) 42% of infected people will recovery. 10% of people who are infected will die and the rate relatively higher due to the much old people living in Burnie, Tasmania.

78% of cases get tested.

 

(3) Government policy will only be implemented when there are ten or more recorded cases. Four government policies have had influences on infection.  

 

(4) The rising number of instances will have a negative impact on Burnie's economic growth.

 

Insights:

1. As a result of the government's covid 19 rules, fewer people will be vulnerable. Less people going to be susceptible.

 

2. After the government policy intervention, there is a effectively reduce of infected people.

 

3. Overall, there is no big differences of economic performance from the graph, might due to the positive and negative effect of economy. And after two weeks, the economy maintained a level of development without much decline.

BMA708 Yanglin Hu
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This model simulates the economics of buying a home. It was created to compare buying a home against using investment returns to pay for rent.

Try cloning this insight, setting the parameter values for real-world scenarios, and then running sensitivity analysis (see tools) to determine the likely wealth outcomes. Compare buying a home to renting. Note that each run will keep the parameters the same while simulating market volatility.

version 1.8
Home buying simulation 1.8
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This model shows the simulation of COVID-19 outbreaks when it hit Burnie, Tasmania. This model will show how government intervention will impact the total number in COVID 19 cases and the overall economic activity.

 

Assumptions

1.   The current Burnie population in 19550. Therefore, the susceptible population is equal to the current Burnie population.

2.       Since Burnie is just a regional city, the virus infection rate is 25% as 5000 people in Burnie went into quarantine during the outbreak last year.

3.       50% of people who are infected will recover.

4.       20% of people who are infected will die because Burnie population average is old.

5.       Government intervention and policy will reduce the Infection

6.       COVID-19 is only countable as a case if the infected people have been tested, and the percentage of testing depends on how many infected people have been tested.

7.       Following a recovery, there is a chance that people could lose their immunity, and also the immunity loss rate measures this.

8.       Government intervention will reduce the infection rate by 15%.

9.       Lockdown will cause tourism industry to shut down and affect the overall economic activity.

10.   Lockdown is one of the most effective way to prevent infection.

11.   Strict health protocol also contributes to reduce the infection.

12.   Vaccination will not make people fully immune to the virus. However, vaccinated people will reduce the immunity loss percentage.

13.   Economic growth rate percentage is based on year 2020.

Findings

1.       COVID-19 could be significantly reduced in number and the spread of the vaccine could make a significant impact on the epidemic.

2.       Economic activity will drop during the first phase of government intervention, However, it will steadily increase overtime

3.       Less people going to be susceptible as government imposed covid 19 rules.

BMA708 Michael Sunjaya Jurenang ID:547923
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State Goverment Fiscal Policy model
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Socio-economic factors (kaya)
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My Insight - Housing and Social Cohesion
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My Insight_ENVS8019 report 5 exercise
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Causal loop structure of system dynamics models of the business cycle and the Kondratieff long wave from Gene Bellinger's AI gemini prompts mc and mr Jan2026 From MIT Sloan school work esp Forrester and Sterman
Short and Long Business and Economic Cycles
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Decarbonization Stories
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My InsightPublic Opinion Toward Immigration Reform: The Role of Economic Motivations
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Biodiversity-Habitat Loss
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An initial study of the economics of single use coffee pods.
Coffee Pods ISD Humanities - Anouk D 10.4
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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 is an evolving attempt to illustrate the interconnected nature of the economic assets of Roswell - Chaves County
RCC economic model 1.1
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Explanation of the Model
This is a Model of COVID-19 outbreak in Burnie, Tasmania which shows the government actions in response to the pandemic COVID-19 and its affects on the Economy. The government health policy changes depending on the reported cases, which is a dependent upon the testing rate. 

Assumptions
Lockdown and travel ban were the main factor in government policy. It negatively impacts on the Economic growth as individuals are not going out which is directly affects the business around the world, in this insight 'Burnie'. This reduces the economic growth and the factors positively effecting economic growth such as Tourism.

Government policies has a negative impact on Exposer of individuals. Moreover, it also has a negative impact on chances of infection when exposed as well as other general infection rate.
 

Interesting Insight 
There is a significant impact of test rating on COVID-19 outbreak. Higher rates increases the government involvement, which decreases cases as well as the total death. 
In contrast, lower testing rates increase the death rate and cases. 

Tourism which plays a avital role in Tasmanian Economy greatly affects the Economic Growth. The decline of Tourism in parts of Tasmania such as Burnie, would directly decrease the economy of Tasmania.


  
BMA 708, Assessment Tast 3: Complex System, Burnie COVID-19 outbreak, Diprina Shakya-519673
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From Neil WIlson and Steve Keen's double entry accounting view of the money circuit model

Bank money flows
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This model is based on the article Dynamic modeling of Infectious Diseases, An application to Economic Evaluation of Influenza Vaccination Farmacoeconomics 2008, 26(1): 45-56 .

And EBOLA


Dynamic Modeling of Infectious Diseases
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Clone of IM-91683 from jacqui and vincy Summary of paper map produced by participants at the compelling case for prevention workshop 6 june 2017. 

Current premier version containing Story Steps and text for vincy to update.
This is clone of 97129 via Vincy.
FINAL Clone of Concept Map produced by CCP Workshop 1