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.

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. 

This page provides a structural analysis of POTUS Candidate Chris Christi's economic policy based on the information at: https://d70h9a36p82zs.cloudfront.net/Ccpres2016/base/assets/1-0-1/production/Chris-Christie-TheEconomy.pdf   The method used is Integrative Propositional Analysis (IPA) available: ​ http://scipolicy.org/uploads/3/4/6/9/3469675/wallis_white_paper_-_the_ipa_answer_2014.12.11.pdf

An initial study of the economics of single use coffee pods.

Archetype:  Success to the successful

Ocean/atmosphere/biosphere model tuned for interactive economics-based simulations from Y2k on.

I made this as an illustration of a piece of text I read in Regenerative Economics, household economics.

A government deficit means that more money has been transferred in the form of payments or investments from the government sector to the private sector than the government has received in taxes. As shown in the drawing,  GOVERNMENT DEFICIT = INCOME AND SAVING for the private sector. Not all the income transferred from the government to the private sector will be employed and some of it will be saved in bank accounts. It is therefore correct to say that Government Deficits lead to Private Sector Saving. It is equally true to say that Investment  leads to Saving. This is important because in the current recession one of the major problems is the massive amount of private debt. In these circumstances a cumulative government deficit is necessary to help the private sector save and repay some of its debt. Note: I have not taken into account the foreign sector here which can also contribute to private sector income and saving.

Causal loop diagram illustrating a variety of feedback loops influencing the price of oil.

The simulation integrates or sums (INTEG) the Nj population, with a change of Delta N in each generation, starting with an initial value of 5.Nj+1 = Nj  + mu (1- Nj / Nmax ) Nj

Delta Nj: is the “change in number of items” as we go from the present generation into the next generation. This is just the number of items born minus the number of items who have died.

mu: is the growth or birth rate parameter, similar to that in the exponential growth and decay model. However, as we extend our model it will no longer be the actual growth rate, but rather just a constant that tends to control the actual growth rate without being directly proportional to it.

F(Nj) = mu(1‐Nj/Nmax): is our model for the effective “growth rate”, a rate that decreases as the number of items approaches the maximum allowed by external factors such as food supply, disease or predation. (You can think of mu as the growth or birth rate in the absence of population pressure from other items.) We write this rate as F(Nj), which is a mathematical way of saying F is affected by the number of items, i.e., “F is a function of Nj”. It combines both growth and all the various environmental constraints on growth into a single function. This is a good approach to modeling; start with something that works (exponential growth) and then modify it incrementally, while still incorporating the working model.

Nj+1 = Nj + Delta Nj : This is a mathematical way to say, “The new number of items equals the old number of items plus the change in number of items”.

Nj/Nmax: is what fraction a population has reached of the maximum "carrying capacity" allowed by the external environment. We use this fraction to change the overall growth rate of the population. In the real world, as well as in our model, it is possible for a population to be greater than the maximum population (which is usually an average of many years), at least for a short period of time. This means that we can expect fluctuations in which Nj/Nmax is greater than 1.

Ocean/atmosphere/biosphere model tuned for interactive economics-based simulations from Y2k on.

Description:

Simulation of MTBF with controls


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
Useful Life

Wearout

Ocean/atmosphere/biosphere model tuned for interactive economics-based simulations from Y2k on.

Problem statement : “The world's out-of-school population has only fallen by just 1% in almost 10 years despite decades of progress”