Model description:     This model is designed to simulate the Covid-19 outbreak in Burnie, Tasmania by estimating several factors such as exposed population, infection rate, testing rate, recovery rate, death rate and immunity loss. The model also simulates the measures implemented by the governm

Model description: 

This model is designed to simulate the Covid-19 outbreak in Burnie, Tasmania by estimating several factors such as exposed population, infection rate, testing rate, recovery rate, death rate and immunity loss. The model also simulates the measures implemented by the government which will impact on the local infection and economy. 

 

Assumption:

Government policies will reduce the mobility of the population as well as the infection. In addition, economic activities in the tourism and hospitality industry will suffer negative influences from the government measures. However, essential businesses like supermarkets will benefit from the health policies on the contrary.

 

Variables:

Infection rate, recovery rate, death rate, testing rate are the variables to the cases of Covid-19. On the other hand, the number of cases is also a variable to the government policies, which directly influences the number of exposed. 

 

The GDP is dependent on the variables of economic activities. Nonetheless, the government’s lockdown measure has also become the variable to the economic activities. 

 

Interesting insights:

Government policies are effective to curb infection by reducing the number of exposed when the case number is greater than 10. The economy becomes stagnant when the case spikes up but it climbs up again when the number of cases is under control. 

Ocean/atmosphere/biosphere model tuned for interactive economics-based simulations from Y2k on.
Ocean/atmosphere/biosphere model tuned for interactive economics-based simulations from Y2k on.
 
 Adapted from Fig 12.1 p.476 of the Book James A. Forte ( 2007), Human Behavior and The Social Environment: Models, Metaphors and Maps for Applying Theoretical Perspectives to Practice; Thomson Brooks/Cole Belmont ISBN 0-495-00659-9

Adapted from Fig 12.1 p.476 of the Book James A. Forte ( 2007), Human Behavior and The Social Environment: Models, Metaphors and Maps for Applying Theoretical Perspectives to Practice; Thomson Brooks/Cole Belmont ISBN 0-495-00659-9

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 Bo
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)
 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

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.

A single resource is used​ with a constant rate and converted into products in use. After a while, these products become unusable because of aging. The recycling of these unusable products is imperfect, thus the amount of not recyclable resource grows (until a better recycling process is invented).
A single resource is used​ with a constant rate and converted into products in use. After a while, these products become unusable because of aging. The recycling of these unusable products is imperfect, thus the amount of not recyclable resource grows (until a better recycling process is invented).
 MODERN MONETARY THEORY SHOWS HOW FULL EMPLOYMENT CAN BE ACHIEVED!  POTENTIAL GDP is a level of overall spending - by the government and the non-government sector - at which there is full employment. If the economy is not operating at
its potential, then the  private sector
has failed to invested or

MODERN MONETARY THEORY SHOWS HOW FULL EMPLOYMENT CAN BE ACHIEVED!

POTENTIAL GDP is a level of overall spending - by the government and the non-government sector - at which there is full employment. If the economy is not operating at its potential, then the  private sector has failed to invested or spend enough to generate the necessary growth nor has income  from net exports contributed enough. This only leaves the government to close the spending gap. Conceptually, a government disposing of its own freely floating currency could act using two powerful tools -  spending in excess of tax revenue, and taxation - to ensure that the gap between the actual economic activity and potential GDP is quickly closed. Achieving the  full employment that prevailed for 30 years between 1945 and 1975 in western economies is definitely possible! 

This is Figure 6 from Lancastle, N. (2012) 'Circuit Theory Extended: The Role of Speculation in Crises' based on Keen, S. (2010). Solving the Paradox of Monetary Profits.   http://www.economics-ejournal.org/economics/journalarticles/2012-34      Banks expand their lending, which in this model leads
This is Figure 6 from Lancastle, N. (2012) 'Circuit Theory Extended: The Role of Speculation in Crises' based on Keen, S. (2010). Solving the Paradox of Monetary Profits.

http://www.economics-ejournal.org/economics/journalarticles/2012-34

Banks expand their lending, which in this model leads to higher production, wages and spending. The result is an increase in total spending.  
This model was proposed in a regulatory framework in Brazil. Its main idea is the obtainment of a dynamic control model to avoid the related parties issues on regulated public services over contract extensions. As the terminal condition of these contract extensions is NPV=0, the firms would have an
This model was proposed in a regulatory framework in Brazil. Its main idea is the obtainment of a dynamic control model to avoid the related parties issues on regulated public services over contract extensions. As the terminal condition of these contract extensions is NPV=0, the firms would have an incentive to contract related parties to inflate costs, and diminish their profits, in order to request a larger time extension. So, this system creates a stable "shadow" based on the 5 years before these extensions, where the company did not have such incentives.
Simulation of MTBF with controls   F(t) = 1 - e ^ -λt   Where    • F(t) is the probability of failure    • λ is the failure rate in 1/time unit (1/h, for example)   • t is the observed service life (h, for example)  The inverse curve is the trust time On the right the increase in failures brings its
Simulation of MTBF with controls

F(t) = 1 - e ^ -λt 
Where  
• F(t) is the probability of failure  
• λ is the failure rate in 1/time unit (1/h, for example) 
• t is the observed service life (h, for example)

The inverse curve is the trust time
On the right the increase in failures brings its inverse which is loss of trust and move into suspicion and lack of confidence.
This can be seen in strategic social applications with those who put economy before providing the priorities of the basic living infrastructures for all.

This applies to policies and strategic decisions as well as physical equipment.
A) Equipment wears out through friction and preventive maintenance can increase the useful lifetime, 
B) Policies/working practices/guidelines have to be updated to reflect changes in the external environment and eventually be replaced when for instance a population rises too large (constitutional changes are required to keep pace with evolution, e.g. the concepts of the ancient Greeks, 3000 years ago, who based their thoughts on a small population cannot be applied in 2013 except where populations can be contained into productive working communities with balanced profit and loss centers to ensure sustainability)

Early Life
If we follow the slope from the leftmost start to where it begins to flatten out this can be considered the first period. The first period is characterized by a decreasing failure rate. It is what occurs during the “early life” of a population of units. The weaker units fail leaving a population that is more rigorous.

Useful Life
The next period is the flat bottom portion of the graph. It is called the “useful life” period. Failures occur more in a random sequence during this time. It is difficult to predict which failure mode will occur, but the rate of failures is predictable. Notice the constant slope.  

Wearout
The third period begins at the point where the slope begins to increase and extends to the rightmost end of the graph. This is what happens when units become old and begin to fail at an increasing rate. It is called the “wearout” period. 
Ocean/atmosphere/biosphere model tuned for interactive economics-based simulations from Y2k on.
Ocean/atmosphere/biosphere model tuned for interactive economics-based simulations from Y2k on.
I made this model to simulate how a companies revenue will change depending on the lifetime of the appliances it manufactures, in combination with the ratio of repair costs and price. It also shows the accumulation of e-waste.
I made this model to simulate how a companies revenue will change depending on the lifetime of the appliances it manufactures, in combination with the ratio of repair costs and price. It also shows the accumulation of e-waste.