A sample model for class discussion modeling COVID-19 outbreaks and responses from government with the effect on the local economy.  Govt policy is dependent on reported COVID-19 cases, which in turn depend on testing rates less those who recover       Assumptions   Govt policy reduces infection and
A sample model for class discussion modeling COVID-19 outbreaks and responses from government with the effect on the local economy.  Govt policy is dependent on reported COVID-19 cases, which in turn depend on testing rates less those who recover

Assumptions
Govt policy reduces infection and economic growth in the same way.

Govt policy is trigger when reported COVID-19 case are 10 or less.

A greater number of COVID-19 cases has a negative effect on the economy.  This is due to economic signalling that all is not well.

Interesting insights

Higher testing rates seem to trigger more rapid government intervention, which reduces infectious cases.  The impact on the economy though of higher detected cases though is negative. 




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 r
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.
This model is to show the status of numbers of infected people, recovered people and deaths during COVID-19 in Burnie Australia. It also shows impact on the growth of economy.       Variables    The infection rate and the percentage of people washing their hands are influencing the infected number o
This model is to show the status of numbers of infected people, recovered people and deaths during COVID-19 in Burnie Australia. It also shows impact on the growth of economy. 

Variables
The infection rate and the percentage of people washing their hands are influencing the infected number of people. Also, there are death rate and recovery rate and immunity lost rate determining the numbers of deaths, recovered and infected-again people.  
for the economy growth, there are several factors, including unemployment rate, infection rate, economic growth rate and government health policy. 

Perspective
After some time, people will recovered, also the economic activities. 
 This Model was developed from the SEIR model (Susceptible, Enposed, Infected, Recovered). It was designed to explore relationships between the government policies regarding the COVID-19 and its impact upon the economy as well as well-being of residents.    Assumptions:   Government policies will be

This Model was developed from the SEIR model (Susceptible, Enposed, Infected, Recovered). It was designed to explore relationships between the government policies regarding the COVID-19 and its impact upon the economy as well as well-being of residents. 

Assumptions:

Government policies will be triggered when reported COVID-19 case are 10 or less;


Government Policies affect the economy and the COV-19 infection negatively at the same time;


Government Policies can be divided as 4 categories, which are Social Distancing, Business Restrictions, Lock Down, Travel Ban, and Hygiene Level, and they represented strength of different aspects;

 

Parameters:

Policies like Social Distancing, Business Restrictions, Lock Down, Travel Ban all have different weights and caps, and they add up to 1 in total;

 

There are 4 cases on March 9th; 

Ro= 5.7  Ro is the reproduction number, here it means one person with COVID-19 can potentially transmit the coronavirus to 5 to 6 people;


Interesting Insights:

Economy will grow at the beginning few weeks then becoming stagnant for a very long time;

Exposed people are significant, which requires early policies intervention such as social distancing.

Description:   This is a system dynamics model of COVID-19 outbreak in Burnie which shows the process of infections and how  government responses, impact on the local economy.       First part is outbreak model, we can know that when people is infected, there are two situations. One is that he recov
Description:

This is a system dynamics model of COVID-19 outbreak in Burnie which shows the process of infections and how  government responses, impact on the local economy.  

First part is outbreak model, we can know that when people is infected, there are two situations. One is that he recovers from  treatment, but even if he recovered, the immunity loss rate increase, makes him to become infected again. The other situation is death. In this outbreak, the government's health policies (ban on non-essential trips, closure of non-essential retailers, limits on public gatherings and quarantine )  help to reduce the spread of the COVID-19 new cases. Moreover,  government legislation is dependent on  number of COVID-19 cases and testing rates. 

 Second part: the model of Govt legislation and economic impact. Gov policy can help to reduce infection rate and local economy at same way. The increase of number of COVID-19 cases has a negative impact on local Tourism industry and economic growth rate. On the other hand, Govt legislation also can be change when reported COVID-19 case are less or equal to 10.






 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 

corona virus model for spread.   correlated to US and Italy
corona virus model for spread.
correlated to US and Italy
 This Agent-based Model was an idea of Christopher DICarlo "Disease Transmission with Agent Based Model' aims to present the COVID cases in Puerto Princesa City as of June 3, 2021     Insight author: Pia Mae M. Palay
This Agent-based Model was an idea of Christopher DICarlo "Disease Transmission with Agent Based Model' aims to present the COVID cases in Puerto Princesa City as of June 3, 2021

Insight author: Pia Mae M. Palay

 Here we have a basic SEIR model and we will investigate what changes would be appropriate for modelling the 2019 Coronavirus.  The initial parametrization is based on the suggested current data. The initial population is set for Catalonia.

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

The initial parametrization is based on the suggested current data. The initial population is set for Catalonia.

 This insight began as a March 22nd Clone of "Italian COVID 19 outbreak control"; thanks to  Gabo HN  for the original insight. The following links are theirs:      Initial data from:  Italian data [ link ] (Mar 4)  Incubation estimation [ link ]        Andy Long   Northern Kentucky University  May

Initial data from:
Italian data [link] (Mar 4)
Incubation estimation [link]

Northern Kentucky University
May 2nd, 2020

This is an update of our model from April 9th, 2020. As we prepare for our final exam, I read a story in The Guardian about Italy's struggle to return to normalcy. The final paragraphs:

During the debate in the Senate on Thursday, the opposition parties grilled Conte. Ex-prime minister Matteo Renzi, who has called for less restraint in the reopening, remarked, “The people in Bergamo and Brescia who are gone, those who died of the virus, if they could speak, they’d tell us to relaunch the country for them, in their honour.”

Renzi’s controversial statement was harshly criticised by doctors who warned that the spread of the disease, which, as of Thursday, had killed almost 30,000 people in the country and infected more than 205,000 [ael: my emphasis], was not over and that a misstep could take the entire country back to mid-March coronavirus levels.

“We risk a new wave of infections and outbreaks if we’re not careful,” said Tullio Prestileo, an infectious diseases specialist at Palermo’s Benefratelli Hospital. “If we don’t realise this, we could easily find ourselves back where we started. In that case, we may not have the strength to get back up again.”

I have since updated the dataset, to include total cases from February 24th to May 2nd. I went to Harvard's Covid-19 website for Italy  and and then to their daily updates, available at github. I downloaded the regional csv file for May 2nd,  which had regional totals (21 regions); I grabbed the column "totale_casi" and did some processing to get the daily totals from the 24th of February to the 2nd of May.

The cases I obtained in this way matched those used by Gabo HN.

The initial data they used started on March 3rd (that's the 0 point in this Insight).

You can get a good fit to the data through April 9th by choosing the following (and notice that I've short-circuited the process from the Infectious to the Dead and Recovered). I've also added the Infectious to the Total cases.

The question is: how well did we do at modeling this epidemic through May 2nd (day 60)? And how can we change the model to do a better job of capturing the outbreak from March 3rd until May 2nd?

Incubation Rate:  .025
R0: 3
First Lockdown: IfThenElse(Days() == 5, 16000000, 0)
Total Lockdown: IfThenElse(Days() >= 7, 0.7,0)

(I didn't want to assume that the "Total Lockdown" wasn't leaky! So it gets successively tighter, but people are sloppy, so it simply goes to 0 exponentially, rather than completely all at once.)

deathrate: .01
recoveryrate: .03

"Death flow": [deathrate]*[Infectious]
"Recovery flow": [recoveryrate]*[Infectious]

Total Reported Cases: [Dead]+[Surviving / Survived]+[Infectious]



Resources:
 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

   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.

  INTRODUCTION
  

  COVID-19  

 Coronavirus which was named COVID-19 is a
respiratory disease which affects the lungs of the infected person and thus
making such people vulnerable to other diseases such as pneumonia. It was first
discovered in Wuhan China in December 2019 and since then has spread

INTRODUCTION

COVID-19

Coronavirus which was named COVID-19 is a respiratory disease which affects the lungs of the infected person and thus making such people vulnerable to other diseases such as pneumonia. It was first discovered in Wuhan China in December 2019 and since then has spread across the world affecting more than 40 million people from which over one million have died.

In the early discovery of the COVID-19, there were measures that were put in place with the help World Health Organization (WHO). They recommended a social distance of 1.5 meters to 2 meters to curb the spread since the scientist warned that COVID-19 can be carried in the droplets when someone breathes or cough. Another measure which was advised by WHO was wearing of mask, especially when people are in group. Wearing of mask would ensure that someone’s droplets do not leave their mouth or nose when they breathe or cough. It also help one from breathing in the virus which believed to be contagious and airborne.

The World Health Organization also advised on washing of the hand and avoiding frequent touching of the face. People mostly use their hand to touch surfaces which mad their hand the greatest harbor of the disease. Therefore, washing hands with soap will kill and wash away the virus from the hands. Avoiding touching of face also will prevent people from contracting the disease since the virus is believed to enter the body through openings such as eye, nose and mouth.

Another measure as a precaution from contracting the disease was to avoid hand shaking, hugging, kissing and any other thing which would bring people together. These were measures put to ensure that COVID-19 do not move from one person to another because of its airborne nature and the fact that it can be carried from the mouth or nose droplets.

Healthcare workers, in most of the countries, were provided with Personal Protective Equipment (PPEs) which helped them to protect themselves from contracting the virus. Healthcare workers were at the forefront in combating the disease since they were the people receiving the sick, including the ones with the virus. This exposed them to COVID-19 more than anyone hence more care was needed for them. Their PPEs comprised of white overall covering the whole body from head to toes. It also includes face mask and googles worn to prevent anything getting in their eyes. Their hands also were covered with gloves which were removed occasionally to avoid concentration of the virus on one glove.

COVID-19 affected many economies across the world as it greatly affected the human economic activities across the world. Due to the nature and how it spread, COVID-19 lead many countries to lockdown the country as we know it. Travelling was stopped as many countries feared the surge of the virus due to many people travelling form the countries which are already greatly affected. Another reason which travelling was hampered was due to the fact that the virus could spread among the travelers in an airplane. There were no proper measures to ensure social distance in the airplane and many people feared travelling from fear of contracting the disease.

This greatly affected the economy of many countries including great economies like USA. Tourism industry was the one affected the most as many country mostly depend on foreign travelers as their tourist. Many countries do not have proper domestic tourism structure and therefore depend on visitors who travels from foreign countries. Such countries have their economies greatly affected since the earnings from tourism either gone down or was not there at all.

Apart from locking down the country from foreigners, many major cities across the world were under lockdown. This means that even the citizens of the country were neither allowed in or out of the city. This restricted movement of people affecting greatly the human economic activities as many businesses were closed down especially transport businesses. The movement of goods from one places to another was affected making business difficult to carry out. Many people who dealt in perishable agricultural products count losses as their farm produced were destroyed because of lack of wider market. Some countries banned some businesses such as importing second hand clothes since it was believed that they could harbor the virus. Most of the meeting places such as sporting events and pubs were closed down affecting greatly the people who were involved in such businesses.

Across the world, schools were closed. Schools contain students in large numbers which could affect many students across the world. Learning was temporary stopped as different countries were finding ways of curbing the virus.

Scientist are busy like bees across the world to find the vaccine for the diseases that have ravage many countries and above all, they are trying to find the cure. Many countries have carried out their trial of vaccines with the hope to find an effective vaccine for the virus.

Meanwhile it is necessary to find ways by which the virus can be controlled so that it doesn’t spread to a point where it come out of control. Some of the measures put by the WHO has been highlighted above, but these measures need to be studied to ensure that measures which are more effective are affected at great heights. I therefore, have created a model in Insight Maker to check how these measures prove their effectiveness over time.