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Overview:

Overall, this analysis showed a COVID-19 outbreak in Burnie, the government policies to curtail that, and some of the impacts it is having on the Burnie economy.


Variables

The simulation made use of the variables such as; Covid-19: (1): Infection rate. (2): Recovery rate. (3): Death rate. (4): Immunity loss rate etc. 


Assumptions:

From the model, it is apparent that government health policies directly affect the economic output of Burnie. A better health policy has proven to have a better economic condition for Burnie and verse versa.


In the COVID-19 model, some variables are set at fixed rates, including the immunity loss rate, recovery rate, death rate, infection rate, and case impact rate, as this is normally influenced by the individual health conditions and social activities.

Moving forward, we decided to set the recovery rate to 0.7, which is a rate above the immunity loss rate of 0.5, so, the number of susceptible could be diminished over time.


Step 1: Try to set all value variables at their lowest point and then stimulate. 

 

Outcome: the number of those Infected are– 135; Recovered – 218; Cases – 597; Death – 18,175; GDP – 10,879.


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


Outcome: The number of those Infected – 166 (up); Recovered – 249 (up); Cases – 554 (down); Death – 18,077 (down); GDP – 824 (down).


With this analysis, it is obvious that the increase of health policy, quarantine, and travel restriction will assist in increase recovery rate, a decrease in confirmed cases, a reduction in death cases or fatality rate, but a decrease in Burnie GDP.


Step 3: Enlarge the Testing Rate to 0.4, variable, others, maintain the same as step 2, and simulate


Outcome: It can be seen that the number of Infected is down to – 152; those recovered down to – 243; overall cases up to – 1022; those that died down to–17,625; while the GDP remains – 824.


In this step, it is apparent that the increase of testing rate will assist to increase the confirmed cases.


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


Outcome: what happens is that the Infected number – 152 remains the same; Recovered rate– 243 the same; Number of Cases – 1022 (same); Death – 17,625 (same); but the GDP goes up to– 6,632. 


This final step made it obvious that the increase of GDP growth rate and tourism growth rate will help to improve the overall GDP performance of Burnie's economy.

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COVID-19 Outbreak in Burnie Tasmania Simulation Model

Introduction:

This model simulates the COVID-19 outbreak situation in Burnie and how the government responses impact local economy. The COVID-19 pandemic spread is influenced by several factors including infection rate, recovery rate, death rate and government's intervention policies.Government's policies reduce the infection spread and also impact economic activities in Burnie, especially its tourism and local businesses.   

Assumptions: 

- This model was built based on different rates, including infection rate, recovery rate, death rate, testing rate and economic growth rate. There can be difference between 
this model and reality.

- This model considers tourism and local business are the main industries influencing local economy in Burnie.

- Government's intervention policies will positive influence on local COVID-19 spread but also negative impact on local economic activity.

- When there are more than 10 COVID-19 cases confirmed, the government policies will be triggered, which will brings effects both restricting the virus spread and reducing local economic growth.

- Greater COVID-19 cases will negatively influence local economic activities.

Interesting Insights:

Government's vaccination policy will make a important difference on restricting the infection spread. When vaccination rate increase, the number of deaths, infected people and susceptible people all decrease. This may show the importance of the role of government's vaccination policy.

When confirmed cases is more than 10, government's intervention policies are effective on reducing the infections, meanwhile local economic activities will be reduced.

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SARS-CoV-19 spread in different countries
- please adjust variables accordingly

Italy
  • elderly population (>65): 0.228
  • estimated undetected cases factor: 4-11
  • starting population size: 60 000 000
  • high blood pressure: 0.32 (gbe-bund)
  • heart disease: 0.04 (statista)
  • free intensive care units: 3 100

Germany
  • elderly population (>65): 0.195 (bpb)
  • estimated undetected cases factor: 2-3 (deutschlandfunk)
  • starting population size: 83 000 000
  • high blood pressure: 0.26 (gbe-bund)
  • heart disease: 0.2-0.28 (herzstiftung)
  • free intensive care units: 5 880

France
  • elderly population (>65): 0.183 (statista)
  • estimated undetected cases factor: 3-5
  • starting population size: 67 000 000
  • high blood pressure: 0.3 (fondation-recherche-cardio-vasculaire)
  • heart disease: 0.1-0.2 (oecd)
  • free intensive care units: 3 000

As you wish
  • numbers of encounters/day: 1 = quarantine, 2-3 = practicing social distancing, 4-6 = heavy social life, 7-9 = not caring at all // default 2
  • practicing preventive measures (ie. washing hands regularly, not touching your face etc.): 0.1 (nobody does anything) - 1 (very strictly) // default 0.8
  • government elucidation: 0.1 (very bad) - 1 (highly transparent and educating) // default 0.9
  • Immunity rate (due to lacking data): 0 (you can't get immune) - 1 (once you had it you'll never get it again) // default 0.4

Key
  • Healthy: People are not infected with SARS-CoV-19 but could still get it
  • Infected: People have been infected and developed the disease COVID-19
  • Recovered: People just have recovered from COVID-19 and can't get it again in this stage
  • Dead: People died because of COVID-19
  • Immune: People got immune and can't get the disease again
  • Critical recovery percentage: Chance of survival with no special medical treatment
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COVID-19 outbreak model brief description

The model stimulated the COVID-19 outbreak at Burnie in Tasmania. The pandemic spread was driven by infection rate, death rate, recovery rate, and government policy.

The government policy reduces the infection in some way, but it also decreases the physical industry. Online industry plays a vital role during the pandemic and brings more opportunities to the world economy. 

The vaccination directly reduces the infection rate. The national border will open as long as residents have been fully vaccinated. 

Assumption: 
The model was created based on different rates, including infection rate, death rate, testing rate and recovered rate. There will be difference between the real cases and the model. 

The model only list five elements of government policies embracing vaccination rate, national border and state border restrictions, public health orders, and business restrictions. Public health order includes social distance and residents should wear masks in high spread regions. 

This model only consider two industries which are physical industry, like manufacturer, retailers, or hospitality industries, and online industry. During the pandemic, employees star to work from home and students can have online class. Therefore, the model consider the COVID-19 has positive impact on online industry. 

Interesting insights:
The susceptible will decrease dramatically in first two weeks due to high infection rate and low recovery rate and government policy. After that, the number of susceptible will have a slight decline. 

The death toll and recovery rate was increased significantly in the first two weeks due to insufficient healthy response. And the trend will become mild as government policy works.