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COVID-19 outbreak in Burnie Tasmania Simulation Model

Introduction

This model simulates how COVID-19 outbreak in Burnie and how the government responses influence the economic community. Government responses are based on the reported COVID-19 cases amount, whcih is considered to be based on testing rate times number of people who are infected minus those recovered from COVID-19 and dead.

Government interventions include the implement of healthy policy, border surveillance, quarantine and travel restriction. After outbreak, economic activities are positively affected by the ecommerce channel development and normal economic grwoth, while the unemployement rate unfortunately increases as well.

Assumption

Enforcing government policies reduce both infection and economica growth.
When there are 10 or greater COVID-19 cases reported, the governmwnt policies are triggered.
Greater COVID-19 cases have negatively influenced the economic activities.
Government policies restict people's activities socially and economically, leading to negative effects on economy.
Opportunities for jobs are cut down too, making umemployment rate increased.
During the outbreak period, ecommerce has increased accordingly because people are restricted from going out.

Interesting insights

An increase in vaccination rate will make difference on reduing the infection. People who get vaccinated are seen to have higher immunity index to fight with COVID-19. Further research is needed.

Testing rate is considered as critical issue to reflect the necessity of government intervention. Higher testing rate seems to boost immediate intervention. Reinforced policies can then reduce the spread of coronvirus but absoluately have negative impacts on economy too.

Mengling Xue 561743 BMA708_Marketing insights into Big Data

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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%.

COVID-19 Outbreak in Burnie Tasmania (Rajaa Sajjad, 538837)

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The cotton industry expanded dramatically in Central America after WW2, increasing from 20,000 hectares to 463,000 in the late 1970s. This expansion was accompanied by a huge increase in industrial pesticide application which would eventually become the downfall of the industry.

The primary pest for cotton production, bol weevil, became increasingly resistant to chemical pesticides as they were applied each year. The application of pesticides also caused new pests to appear, such as leafworms, cotton aphids and whitefly, which in turn further fuelled increased application of pesticides.

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Model description:

This model is designed to simulate the outbreak of Covid-19 in Burnie in Tasmania. It also tell us the impact of economic policies on outbreak models and economic growth.

Variables:

The simulation takes into account the following variables and its adjusting range:

On the left of the model, the variables are: infection rate( from 0 to 0.25), recovery rate( from 0 to 1), death rate( from 0 to 1), immunity loss rate( from 0 to 1), test rate ( from 0 to 1), which are related to Covid-19.

In the middle of the model, the variables are: social distancing( from 0 to 0.018), lock down( from 0 to 0.015), quarantine( from 0 to 0.015), vaccination promotion( from 0 to 0.019), border restriction( from 0 to 0.03), which are related to governmental policies.

On the right of the model, the variables are: economic growth rate( from 0 to 0.3), which are related to economic growth.

Assumptions:

(1) The model is influenced by various variables and can produce different results. The following values based on the estimation, which differ from actual values in reality.

(2) Here are just five government policies that have had an impact on infection rates in epidemic models. On the other hand, these policies will also have an impact on economic growth, which may be positive or negative.

(3) Governmental policy will only be applied when reported cases are 10 or more.

(4) This model lists two typical economic activities, namely e-commerce and physical stores. Government policies affect these two types of economic activity separately. They together with economic growth rate have an impact on economic growth.

Enlightening insights:

(1) In the first two weeks, the number of susceptible people will be significantly reduced due to the high infection rate, and low recovery rate as well as government policies. The number of susceptible people fall slightly two weeks later. Almost all declines have a fluctuating downward trend.

(2) Government policies have clearly controlled the number of deaths, suspected cases and COVID-19 cases.

(3) The government's restrictive policies had a negative impact on economic growth, but e-commerce economy, physical stores and economic growth rate all played a positive role in economic growth, which enabled the economy to stay in a relatively stable state during the epidemic.

Model of COVID-19 Outbreak in Burnie, Tasmania

LILI LIU

Based on the SIR (Susceptible, Infected, Recovered) model of disease, this is an upgraded model with more specifc vaeriables.

Insights:

When the growth rate and the number of the recovered is much larger than deaths, the economic activity remain steady growing.

Model of COVID-19 outbreak in Burnie Tasmania

Yini Song

3

Eastern oyster growth model calibrated for Long Island Sound
Developed and implemented by Joao G. Ferreira and Camille Saurel; growth data from Eva Galimany, Gary Wickfors, and Julie Rose; driver data from Julie Rose and Suzanne Bricker; Culture practice from the REServ team and Tessa Getchis. This model is a workbench for combining ecological and economic components for REServ. Economic component added by Trina Wellman.

This is a one box model for an idealized farm with one million oysters seeded (one hectare @ a stocking density of 100 oysters per square meter)

1. Run WinShell individual growth model for one year with Long Island Sound growth drivers;

2. Determine the scope for growth (in dry tissue weight per day) for oysters centered on the five weight classes)

3. Apply a classic population dynamics equation:

dn(s,t)/dt = -d[n(s,t)g(s,t)]/ds - u(s)n(s,t)

s: Weight (g)
t: Time
n: Number of individuals of weight s
g: Scope for growth (g day-1)
u: Mortality rate (day-1)

4. Set mortality at 30% per year, slider allows scenarios from 30% to 80% per year

5. Determine harvestable biomass, i.e. weight class 5, 40-50 g (roughly three inches length)

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Joao G. Ferreira

VA - socio-economic

Baihua

Storytelling of My Investigating Insight Theme

Ana Cristina Beja

Introduction:

This model aims to show that how the Tasmania government's COVID-19 policy can address the spread of the pandemic and in what way these policies can damage the economy.

Assumption:

Variables such as infection rate, death rate and the recovery rate are influenced by the actual situation.

The government will implement stricter travel bans and social distant policies as there are more cases.

Government policies reduce infection and limit economic growth at the same time.

A greater number of COVID-19 cases has a negative effect on the economy.

Interesting insights:

A higher testing rate will make the infection increase and the infection rate will slightly increase as well.

Government policies are effective to lower the infection, however, they will damage the local economy. While the higher number of COVID-19 cases also influences economic activities.

Model of COVID-19 outbreak in Burnie_Guoyu Shen

Guoyu Shen