Introduction:        This model demonstrates the COVID-19 outbreak in Bernie, Tasmania, and shows the relationship between coVID-19 outbreaks, government policy and the local economy. The spread of pandemics is influenced by many factors, such as infection rates, mortality rates, recovery rates a

Introduction:

This model demonstrates the COVID-19 outbreak in Bernie, Tasmania, and shows the relationship between coVID-19 outbreaks, government policy and the local economy. The spread of pandemics is influenced by many factors, such as infection rates, mortality rates, recovery rates and government policies. Although government policy has brought the Covid-19 outbreak under control, it has had a negative impact on the financial system, and the increase in COVID-19 cases has had a negative impact on economic growth.

 

Assumptions:

The model is based on different infection rates, including infection rate, mortality rate, detection rate and recovery rate. There is a difference between a real case and a model. Since the model setup will only be initiated when 10 cases are reported, the impact on infection rates and economic growth will be reduced.

 

Interesting insights:

Even as infection rates fall, mortality rates continue to rise. However, the rise in testing rates and government health policies contribute to the stability of mortality. The model thinks that COVID-19 has a negative impact on offline industry and has a positive impact on online industry.

This model shows the COVID-19 outbreaks in Burnie and the Government intervention to alleviate the crisis and also how is the intervention affect the economy.    It is assumed that the Government intervention is triggered when the COVID-19 case is equal to or more than 10.      Government interventi
This model shows the COVID-19 outbreaks in Burnie and the Government intervention to alleviate the crisis and also how is the intervention affect the economy.

It is assumed that the Government intervention is triggered when the COVID-19 case is equal to or more than 10. 

Government intervention - lock down the state, suppress the development of COVID-19 effectively. It is related to most of people stay at home to reduce the exposure in public area.
On the other hand, it also bring the economy of Burnie in the recession, as no tourists, no dining out activities and decrease in money spending in the city.
[The Model of COVID-19 Pandemic Outbreak in Burnie, TAS]   A model of COVID-19 outbreaks and responses from the government with the impact on the local economy and medical supply.      It is assumed that the government policy is triggered and rely on reported COVID-19 cases when the confirmed cases
[The Model of COVID-19 Pandemic Outbreak in Burnie, TAS]

A model of COVID-19 outbreaks and responses from the government with the impact on the local economy and medical supply. 

It is assumed that the government policy is triggered and rely on reported COVID-19 cases when the confirmed cases are 10 or less. 

Interesting insights
The infection rate will decline if the government increase the testing ranges, meanwhile,  the more confirmed cases will increase the pressure on hospital capacity and generate more demand for medical resources, which will promote government policy intervention to narrow the demand gap and  affect economic performance by increasing hospital construction with financial investment.

 Simple epidemiological model for Burnie, Tasmania   SIR: Susceptible to infection - Infected - Recovery, Government responses and Economic impacts           Government policy is activated when there are 10 or fewer reported cases of COVID-19. The more people tested, the fewer people became infected
Simple epidemiological model for Burnie, Tasmania
SIR: Susceptible to infection - Infected - Recovery, Government responses and Economic impacts  

Government policy is activated when there are 10 or fewer reported cases of COVID-19. The more people tested, the fewer people became infected. So the government's policy is to reduce infections by increasing the number of people tested and starting early. At the same time, it has slowed the economic growth (which, according to the model,  will stop for next 52 weeks).
Initial data from: Italian data [ link ], as of Mar 28  Incubation estimation [ link ]      Model focuses on outbreak dynamics and control, this version ignores symptom onset to hospital admission and the rest of recovery dynamics.
Initial data from:
Italian data [link], as of Mar 28
Incubation estimation [link

Model focuses on outbreak dynamics and control, this version ignores symptom onset to hospital admission and the rest of recovery dynamics.
This model is developed to simulate how Burnie can deal with a new outbreak of COVID-19 considering health and economic outcomes. The time limit of the simulation is 100 days when a stable circumstance is reached.      Stocks   There are four stocks involved in this model. Susceptible represents the
This model is developed to simulate how Burnie can deal with a new outbreak of COVID-19 considering health and economic outcomes. The time limit of the simulation is 100 days when a stable circumstance is reached. 

Stocks
There are four stocks involved in this model. Susceptible represents the number of people that potentially could be infected. Infected refers to the number of people infected at the moment. Recovered means the number of people that has been cured, but it could turn into susceptible given a specific period of time since the immunity does not seem everlasting. Death case refers to the total number of death since the beginning of outbreak. The sum of these four stocks add up to the initial population of the town.

Variables
There are four variables in grey colour that indicate rates or factors of infection, recovery, death or economic outcomes. They usually cannot be accurately identified until it happen, therefore they can be modified by the user to adjust for a better simulation outcome.

Immunity loss rate seems to be less relevant in this case because it is usually unsure and varies for individuals, therefore it is fixed in this model.

The most interesting variable in green represents the government policy, which in this situation should be shifting the financial resources to medical resources to control infection rate, reduce death rate and increase recovery rate. It is limited from 0 to 0.8 since a government cannot shift all of the resources. Bigger scale means more resources are shifted. The change of government policy will be well reflected in the economic outcome, users are encouraged to adjust it to see the change.

The economic outcome is the variable that roughly reflects the daily income of the whole town, which cannot be accurate but it does indicate the trend.

Assumptions:
The recovery of the infected won't happen until 30 days later since it is usually a long process. And the start of death will be delayed for 14 days considering the characteristic of the virus.
Economic outcome will be affected by the number of infected since the infected cannot normally perform financial activities.
Immunity effect is fixed at 30 days after recovery.

Interesting Insights:
 In this model it is not hard to find that extreme government policy does not result in the best economic outcome, but the values in-between around 0.5 seems to reach the best financial outcome while the health issues are not compromised. That is why usually the government need to balance health and economic according to the circumstance. 
 

An SD model formulated to present the trend of COVID-19 infection and death rate at Puerto Princesa City, PALAWAN using the CESU-PPC file last June 3, 2021.
An SD model formulated to present the trend of COVID-19 infection and death rate at Puerto Princesa City, PALAWAN using the CESU-PPC file last June 3, 2021.