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The model is built to demonstrates how Burnie Tasmania can deal with a new COVID-19 outbreaks, taking government policies and economic effects into account.

The susceptible people are the local Burnie residents. If residents were infected, they would either recovered or dead. However, even they do recover, there is a chance that they will get infected again if immunity loss occurs.

From the simulation result we can see that with the implementation of local government policies including travel ban and social distancing, the number of infected people will decrease. The number of recovered people will increase in the first 5 weeks but then experience a decrease.

In addition, with the implementation of local government policy, the economic environment in Burnie will be relatively stable when the number of COVID-19 cases is stable.

How Burnie, Tasmania can deal with a new outbreak of COVID-19

Jie Sun

3

Model di samping adalah model SEIR yang telah dimodifikasi sehingga dapat digunakan untuk menyimulasikan perkembangan penyebaran COVID-19.

SEIR Model for COVID-19 in Indonesia (Revised)

Firly Feisal

3

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

Modelo Epidemiológico para os Casos de Covid-19

Insigh Authors:

Luis Felipe (UFSM)

Carlos Heitor (UFSM)

Paulo Vilella (UFJF)

Modelo UFSM - COVID-19

Luis Felipe Dias Lopes

Simulation of how a virus infects after entering the body, how it replicates inside living cells, and how the body's immune system responds towards the virus

System Dynamic Model 1b (Previously-infected individual)

Hazwan Hafiz

3

AT-3

Xuanze Liang

4

Италиядағы COVID-19 экосистемасы

Жаңа идея

Таир Аубакиров

3

Covid-19 Pandemic

Kaushal Reddy

Pada Tugas 3 mata kuliah Pemodelan Transportasi Laut, ditugaskan untuk membuat pemodelan penyebaran COVID-19 di negara yang dipilih, dan pada simulasi ini merupakan negara Indonesia

Dosen Pengampu : Dr.-Ing Ir Setyo Nugroho

Clone of Clone of Clone of Simulasi Pemodelan Penyebaran COVID-19 di Indonesia

Putro Bee

3

3 бөлім өзіндік жұмыс

Nurdaulet Abilkasym

Sike Liu's model on COVID-19 & Burnie Economy

This model contains three parts, the first part stimulates the COVID-19 pandemic outbreak in Burnie; the second part describes possible government policies on pandemic control; and the third part examines the possible negative impact on economy growth from those policies.

Assumptions:

1. The state boarder has already been closed and all new arrivals in Burnie need to enter a fixed period of quarantine. And the quarantine rate measures the strength of the government policy on quarantine (such as length and method).

2. Patient zero refers to the initial number of undetected virus carriers in the community.

3. Government policies such as social distancing, compulsory mask and lock down could effectively reduce community’s exposure to the virus.

4. Social distancing and compulsory mask will be triggered when COVID-19 cases reach and beyond 10 and lock down will be triggered when cases reach and beyond 1000.

4. High vaccine rate, on the other hand, could effectively reduce the exposed people’s chance of getting infected.

5. Only when vaccine rate reaches 0.6 and beyond, then the spread of COVID-19 will be significantly slowed.

6. Vaccine can’t 100% prevent the infection of the virus.

7.The infected people will need to be tested so that they could be counted as COVID-19 cases and the test rate decides the percentage of infected people being tested.

8. After people recover, there are chances of them losing immunity and the immunity lost rate measures that.

9. The COVID-19 cases could also be detected at quarantine facilities, and the quarantine process will effectively reduce the Infection and exposure rate.

10. Social distancing and compulsory mask wearing are considered as light restrictions in this model and will have less impact on both supply and demand side, and lockdown is considered as heavy restriction which will have strong negative impact on economy growth in this model.

11. In this model, light restrictions will have more negative impacts on the demand side compared to the supply side.

12. In this model, both supply side and demand side will power the economy growth.

Interest hints:

The vaccine could significantly reduce the spread of COVID-19 and effectively reduce the number of COVID-19 cases.

The number of the COVID-19 cases will eventually be stabilized when the number of susceptible is running out in a community (reached community immunity).

Quarantine could slightly reduce the cases numbers, but the most effective way is to reduce the number of new arrivals.

BMA708_Assignment 3_Sike Liu_567871_COVID-19 outbreak and Burnie economy

Sike Liu

Pemodelan Covid-19 di Indonesia

Jihan Widya Candra

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

COVID-19_SIR_MODEL_No_Quarantine

Abhijith N

Model di samping adalah model SEIR yang telah dimodifikasi sehingga dapat digunakan untuk menyimulasikan perkembangan penyebaran COVID-19.

SEIR Model for COVID-19 in Indonesia - v2

Ngaliman Abu Ibrahim

Simulation of the spread of COVID-19 in Wuhan.

COVID-19

Chris Hitchin

Using the reading assignment from El-Taliawi and Hartley on using a SSM for COVID-19 follow the steps for SSM to include:

1) Describe the Problem (unstructured).

2) Develop a Root Definition for the COVID-19 problem space by identifying the three elements: what, how, why. A System to do X, by (means of) Y, in order to achieve Z.

X - What the system does

Y - How it does it

Z - Why is it being done

(see slide 33 in the Systems Thinking Workshop reading)

3) Identify the Perspectives (CATWOE)

4) Develop a basic Systemigram / Rich Picture to tell the story.

Submit your assignment as a Word document or PDF that addresses #1-4. You can use InsightMaker to create your systemigram or use the Systemitool which you can access at SERC hereLinks to an external site..

If you use InsightMaker, try presenting your results as a Story using the Storytelling capabilityLinks to an external site..

You will have TWO WEEKS to complete this assignment (due on March 7th).

Systemigram Model Building Exercise Luis Vega

Luis Vega

COVID-19

Аяулым Халыктай

covid-19

Maria Camila Ramirez

This model bases on the SIR model aims to indicate the relationship between the lockdown policy of the government for combating with COVID-19 and the economic activity in Burnie Tasmania during the pandemic.

This model assumes that more COVID-19 cases will lead to the more serious lockdown policy of the local government, which indirectly affect the economic activities and economic growth. The primary reason is that the lockdown policy force people to stay at home and reduce the chance to work and consume.

The simulation trend of the model is that the economy will keep a steady increase when the serious government policy reduces the COVID-19 spreading speed rate.

COVID-19 outbreak in Burnie model by LUJIN 517217

LU JIN

Covid-19

Luis Felipe Dias Lopes

14

COVID-19 Kazakstan Abdrakhman

Abdrakhman

This stock-flow simulation model is to show Covid-19 virus spread rate, sources of spreading and safety measures followed by all the countries affected around the world.

The simulation also aims at predicting for how much more period of time the virus will persist, how many people could recover at what kind of rate and also about the virus toughness dependence based on its excessive speed, giving rise to bigger numbers day-by-day.

covid-19 in France

Егор Саяпин

3 months ago

Model description:

This model is designed to simulate the Covid-19 outbreak in Burnie, Tasmania by estimating several factors such as exposed population, infection rate, testing rate, recovery rate, death rate and immunity loss. The model also simulates the measures implemented by the government which will impact on the local infection and economy.

Assumption:

Government policies will reduce the mobility of the population as well as the infection. In addition, economic activities in the tourism and hospitality industry will suffer negative influences from the government measures. However, essential businesses like supermarkets will benefit from the health policies on the contrary.

Variables:

Infection rate, recovery rate, death rate, testing rate are the variables to the cases of Covid-19. On the other hand, the number of cases is also a variable to the government policies, which directly influences the number of exposed.

The GDP is dependent on the variables of economic activities. Nonetheless, the government’s lockdown measure has also become the variable to the economic activities.

Interesting insights:

Government policies are effective to curb infection by reducing the number of exposed when the case number is greater than 10. The economy becomes stagnant when the case spikes up but it climbs up again when the number of cases is under control.

Sample Model of COVID-19 outbreak in Burnie Tasmania by Yim Fong Ng (544885)

Chrissie Ng

Somulacion clase 2, retroalimentación + y - , primer versión

Modelo Covid-19 Co

brow