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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.

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Explanation:

Explanation:

This model presents the COVID-19 outbreak in Burnie and how the government reacts to it. Moreover, the model also illustrates how the economy in Burnie is impacted by the pandemic. The possible stages of residents when the infectious disease spreads in Burnie can be concluded as Susceptible, Infection and Recovery, which are used as the main data in this model. However, the improvement of decreasing of reported infection rates of this infectious disease and increasing of recovery rates are contributed by the implementation of the Government Health Policy.

Assumption

The decrease of both infection rate and economic growth are all influenced by the Government Health Policy simultaneously. The Government Health Policy is only triggered when there are 10 cases reported. However, the increase in reporting COVID-19 cases affects economic growth negatively.

Interesting Insights:

There are two interesting insights that have been revealed from the simulation. First, the death rate continuously increased even though the infection rate goes down. However, the increase in testing rates contributed to the stability of the death rate towards the end of the week. Moreover, higher testing rates also trigger faster government intervention, which can reduce infectious cases. Second, as the Government Health Policy limited the chance of going out and shopping, the economic growth is negative due to the higher cases.

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