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The System Dynamics Model presents the the COVID-19 status in Puerto Princesa City

самостоятельная

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

Covid-19 Pandemic

Kaushal Reddy

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

3 бөлім өзіндік жұмыс

Nurdaulet Abilkasym

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

COVID-19 modelling with SEIR(D) Model method to predict transmission of COVID-19.

SEIR(D) Model COVID-19

pemsim kelompok 3

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

Evolution of Covid-19 in Brazil:

A System Dynamics Approach

Villela, Paulo (2020)
villela.paulo@gmail.com

This model is based on Crokidakis, Nuno. (2020). Data analysis and modeling of the evolution of COVID-19 in Brazil. For more details see full paper here.

Evolution of Covid-19 in Brazil: A System Dynamics Approach

Paulo Villela

3

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

6 months ago

Италиядағы COVID-19 экосистемасы

Жаңа идея

Таир Аубакиров

3

Pemodelan Covid-19 di Indonesia

Jihan Widya Candra

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

COVID-19

Аяулым Халыктай

COVID-19 Kazakstan Abdrakhman

Abdrakhman

Өзіндік жұмыс агент

Алтынай Садир

5

Covid-19

Luis Felipe Dias Lopes

14

Системная динамика COVID-19 в Казахстане в 2020 году

Эрметов Диёрбек Нодирбекович

Somulacion clase 2, retroalimentación + y - , primer versión

Modelo Covid-19 Co

brow

Evolution of Covid-19 in Brazil:

A System Dynamics Approach

Villela, Paulo (2020)
paulo.villela@engenharia.ufjf.br

This model is based on Crokidakis, Nuno. (2020). Data analysis and modeling of the evolution of COVID-19 in Brazil. For more details see full paper here.

Evolução da Covid-19 no Brasil

Paulo Villela

covid-19

Maria Camila Ramirez

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

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