Tugas Permo

A simple feedback loop of the COVID-19 pandemic.

Tugas Permo

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

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.

Here we have a basic SEIR model and we will investigate what changes would be appropriate for modelling the 2019 Coronavirus 

Италиядағы COVID-19 экосистемасы

ABOUT THE MODEL

This is a dynamic model that shows the correlation between the health-related policies implemented by the Government in response to COVID-19 outbreak in Burnie, Tasmania, and the policies’ impact on the Economic activity of the area.

 ASSUMPTIONS

The increase in the number of COVID-19 cases is directly proportional to the increase in the Government policies in the infected region. The Government policies negatively impact the economy of Burnie, Tasmania.

INTERESTING INSIGHTS

1. When the borders are closed by the government, the economy is severely affected by the decrease of revenue generated by the Civil aviation/Migration rate. As the number of COVID-19 cases increase, the number of people allowed to enter Australian borders will also decrease by the government. 

2. The Economic activity sharply increases and stays in uniformity. 

3. The death rate drastically decreased as we increased test rate by 90%.

Model di samping adalah model SEIR yang telah dimodifikasi sehingga dapat digunakan untuk menyimulasikan perkembangan penyebaran COVID-19.

Initial data from:

Model di samping adalah model SEIR yang telah dimodifikasi sehingga dapat digunakan untuk menyimulasikan perkembangan penyebaran COVID-19.

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

If no attempt is made to eradicate SARS-CoV-2 it will eventually become endemic, ineradicable, at a high never-ending cost to world in terms of economic growth, human health and lives. The current strategy adopted by most governments is to impose  restrictive measures when the virus threatens to overwhelm hospital services and to relax these restrictions as this danger recedes. This is short-sighted. It cannot eliminate the highly infectious delta variant, which has an estimated R0-value of between 6 & 9. Periodic lockdowns will be hard to avoid in the future.

However, eradication is possible, herd immunity can be achieved quickly worldwide, reducing the R0 permanently to below 1, which will lead to the disappearance of the virus. Critical in achieving this is Ivermectin, a medicine that is cheap,  readily available and can be manufactured by most countries. A recent meta study has shown that Ivermectin, prophylactically employed, can prevent infection with the virus  by 86 % on average – very similar to the efficacy of vaccines. Eradication will require employment of all the instruments shown in the graph: future generations do not have to live with this plague. 

This model demonstrates the relationship between the covid-19 outbreak, government policy, and economic impacts. This model was developed based on SIR model (Susceptible, Infection, Recovery). The model also outlines the policies been implemented by the government to cope with Covid-19 pandemic and it also indicate its economic impact. 

This model calculates and demonstrates the possible spread of COVID-19 through an agent-based map. It shows the timeline of a healthy individual being infected to recovery.