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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

Assumptions
Govt policy reduces infection and economic growth in the same way.

Govt policy is trigger when reported COVID-19 case are 10 or less.

Interesting insights

Higher testing rates seem to trigger more rapid government intervention, which reduces infectious cases.  





Clone of Burnie COVID-19 outbreak demo model
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This Model was developed from the SEIR Model (Susceptible, Exposed, Infected, Recovered) and it predicts the COVID-19 outbreak in Burnie, Tasmania. This pandemic outbreak contributes to diverse rates including infection rate, death rates and recovery rate, government policies and its economic impacts.    

Assumptions:

 This model is driven by its determined rates, e.g., incubation rate, morality rate, test rate and immunity loss rate and its recovery rate.

Government policies are involved in fully vaccination rate, social distance, national border closure, travel, and business restriction which effect Burnie’s economy.

There are three economic entities dimensions in Burnie Island, we can tell that the pandemic has negative impact on Brick-and-Mortar enterprises and tourism business to some extent, whereas, e commercial business plays a crucial role to stimulate the regional economic activities during the COVID-19 period.

 

Interesting Insights:

 The figure of susceptible changes significantly during the initial 3 weeks because of low recovery rate and high infection rate. On the other hand, the implementation and interventions of government policies is effective, because the number of patients who tested negative is increased and the majority of them release and go back home after medical follow-up. 

Xueli Huang 501514, BMA708 Model of COVID-19 Outbreak in Burnie, Tasmania
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The model represents the interaction between influenza and SARS-CoV-2. The data used is for Catalonia region.
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This model estimates the deaths due to COVID19 in Bangalore City. 
Assumptions:
City has a population = 8 Million
Initial infected population = 10
Probability of infection = 8%
Contact rate in population = 6
Average duration of recovery = 10 days
Death rate = 1%
Quarantine rate = 80%
Delay in quarantine = 5 days
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  • tingkat interaksi fisik : 1-10 orang per hari
  • penerapan prokes 0%-100%
  • penanganan pemerintah : minim (<40%) cukup (40%-70%) baik (>70%)


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Explanation of the Model

The sample model demonstrate the COVID-19 outbreak in Burnie, Tasmania appearing how the government reacts by executing important health approaches and the impacts on the economy of the region

Assumptions

The economic growth rate is subordinate on the extent of the populace who can be exposed. The number of COVID-19 cases adversely impacts the economy. The government arrangement is activated when the COVID-19 cases are 10 or above

Interesting Insights

1. There is a positive relationship between exposure to COVID- 19 and economic growth rate. Since the more individuals go out, the more trade activity takes place and that ultimately results economic growth

2. Expanding the testing rate results
- Higher cases being recognized
- Strict  government intervention
- Less deaths

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