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.

CLD exposition of Goodwin01 from Steve Keen's August 2019 course on Introduction to Economic Dynamics and Minsky software See video and powerpoint slides. Based on IM-2011 Minsky FIH and IM-168865 MacroEconomics CLDs. SeeIM-172005 for Simulation

A sample model for class discussion modeling COVID-19 outbreaks and responses from government with the effect on the local economy.  Govt policy is dependent on reported COVID-19 cases, which in turn depend on testing rates less those who recover

WIP Social determinants of health from Michael Marmot's  ABC 2016 Boyer Lectures on Social Justice and the Health Gap See US Data website for data and AIHW website for concepts. See also IM-83417 Marmot Essay 2017

Clone of general Multiscale Innovation Dynamics Insight   to be applied to the specifics of health WIP

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

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

Overview:

The COVID-19 Outbreak in Burnie Tasmania shows the process of COVID-19 outbreak, the impacts of government policy on both the COVID-19 outbreak and the GDP growth in Burnie.

Assumptions:

We set some variables at fix rates, including the immunity loss rate, recovery rate, death rate, infection rate and case impact rate, as they usually depend on the individual health conditions and social activities.

It should be noticed that we set the rate of recovery, which is 0.7, is higher than that of immunity loss rate, which is 0.5, so, the number of susceptible could be reduced over time.

Adjustments: (please compare the numbers at week 52)

Step 1: Set all the variables at minimum values and simulate

results: Number of Infected – 135; Recovered – 218; Cases – 597; Death – 18,175; GDP – 10,879.

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

results: Number of Infected – 166 (up); Recovered – 249 (up); Cases – 554 (down); Death – 18,077 (down); GDP – 824 (down).

So, the increase of health policy, quarantine and travel restriction will help increase recovery, decrease confirmed cases, decrease death, but also decrease GDP.

Step 3: Increase the variables of Testing Rate to 0.4, others keep the same as step 2, and simulate

results: Number of Infected – 152 (down); Recovered – 243 (down); Cases – 1022 (up); Death – 17,625 (down); GDP – 824 (same).

So, the increase of testing rate will help to increase the confirmed cases.

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

results: Number of Infected – 152 (same); Recovered – 243 (same); Cases – 1022 (same); Death – 17,625 (same); GDP – 6,632 (up).

So, the increase of GDP growth rate and tourism growth rate will helps to improve the GDP in Burnie.

Modern industrial civilisation has created massive interdependencies which define it and without which it could not function. We all depend on industrial farming to produce the food we eat, we depend on gasoline being available at the gas station,  on the availability of electricity and even on the bread supplied by the local baker. Naturally, we tend to support the institutions that supply the amenities and goods to which we have become accustomed: if we get our food from the local supermarket, it is likely that we would be opposed to it’s closure. This means that the economic system that relies on continuous growth enjoys implicit societal support and that nothing short of environmental disaster or a shortage of essential raw materials will impede it’s growing indefinitely. It is not hard to work out the consequences of this situation!

WIP Summary of MIchael Hudson's Book Killing the Host: How Financial Parasites and Debt destroy the Global Economy 

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

This model is designed for the local government of Burnie, Tasmania, aiming to help with balancing COIVD-19 and economic impacts during a possible outbreak. 

The model has been developed based upon the SIR model (Susceptible, Infected, Recovered) model used in epidemiology. 

It lists several possible actions that can be taken by the government during a COVID-19 outbreak and provide the economic impact simulation. 

The model allow users to Change the government policies factors (Strength of Policies) and simulate the total economic impact.

Interestingly, the government plicies largely help with controlling the COVID outbreak. However, the stronger the policies are, the larger impact on local economy

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.