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 i
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
 Here we have a basic SEIR model and we will investigate what changes would be appropriate for modelling the 2019 Coronavirus 

Here we have a basic SEIR model and we will investigate what changes would be appropriate for modelling the 2019 Coronavirus 

6 7 months ago
   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 .
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.

 Based on this particular model created by Lutfi Andriyanto and Aulia Nur Fajriyah: https://insightmaker.com/insight/2wxxIeiWJsHNFGNH6cf6ke/SEIR     Updated by (Kelompok 2):  Daffa Muhammad Romero	20/456363/TK/50493  Iskan Mustamir			20/456367/TK/50497  Tasya Nafisah Kamal		20/460569/TK/51158  Hervi

Based on this particular model created by Lutfi Andriyanto and Aulia Nur Fajriyah: https://insightmaker.com/insight/2wxxIeiWJsHNFGNH6cf6ke/SEIR


Updated by (Kelompok 2):

Daffa Muhammad Romero 20/456363/TK/50493

Iskan Mustamir 20/456367/TK/50497

Tasya Nafisah Kamal 20/460569/TK/51158

Hervi Nur Rahmadien 20/463601/TK/51593

 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 pol
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.

        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 ra

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.

A simple ABM example illustrating how the SEIR model works. It can be a basis for experimenting with learning the impact of human behavior on the spread of a virus, e.g. COVID-19.
A simple ABM example illustrating how the SEIR model works. It can be a basis for experimenting with learning the impact of human behavior on the spread of a virus, e.g. COVID-19.
 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,

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).

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