Tasmania Models

These models and simulations have been tagged “Tasmania”.

Related tagsCOVID-19EconomyBurnie

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. 




This model demonstrate how the exisitng tested COVID cases effects economic recovery via goverment intervenes. Assumption:Goverment intervenes positively contribute on transmission, patients recovery, and death elimination. When existing cases equal or lower than 10 cases, economic growth will be so
This model demonstrate how the exisitng tested COVID cases effects economic recovery via goverment intervenes.
Assumption:Goverment intervenes positively contribute on transmission, patients recovery, and death elimination. When existing cases equal or lower than 10 cases, economic growth will be soaring with helps of influencial elements.
Interesting points: even though there are certain amount of unknow cases, enhancing social restriction and increasing test rate ould still reduce amount of cases
 Simple epidemiological model for Burnie, Tasmania   SIR: Susceptible to infection - Infected - Recovery, Government responses and Economic impacts           Government policy is activated when there are 10 or fewer reported cases of COVID-19. The more people tested, the fewer people became infected
Simple epidemiological model for Burnie, Tasmania
SIR: Susceptible to infection - Infected - Recovery, Government responses and Economic impacts  

Government policy is activated when there are 10 or fewer reported cases of COVID-19. The more people tested, the fewer people became infected. So the government's policy is to reduce infections by increasing the number of people tested and starting early. At the same time, it has slowed the economic growth (which, according to the model,  will stop for next 52 weeks).
  Overview     This model simulates logging and mountain biking competition in Derby, Tasmania. The Simulation is referenced to simulate Derby mountain biking with logging.      Model   W  ork     The tourism industry is represented on the model's left side, and the logging industry is on the right

Overview

This model simulates logging and mountain biking competition in Derby, Tasmania. The Simulation is referenced to simulate Derby mountain biking with logging.

 

Model Work

The tourism industry is represented on the model's left side, and the logging industry is on the right side. Interactions between these two industries generate tax revenues. Logging and tourism have different growth rates regarding people working/consuming. The initial values of these two industries in the model are not fixed but increase yearly due to inflation or economic growth.

 

Detail Insights

From the perspective of tourism, as the number of tourists keeps growing, the number of people who choose to ride in Derby City also gradually increases. And the people who ride rate the ride. The negative feedback feeds back into the cycling population. Similarly, positive cycling reviews lead to more customer visits. And all the customers will create a revenue through tourism, and a certain proportion of the income will become tourism tax.

From a logging perspective, it is very similar to the tourism industry. As the number of people working in the industry is forecast to increase, the industry's overall size is predicted to grow. And as the industry's size continues to rise, the taxes on the logging industry will also continue to rise. Since logging is an industry, the tax contribution will be more significant than the tourism excise tax.

 

This model assumption is illustrated below:

1. The amount of tax reflects the level of industrial development.

2. The goal of reducing carbon emissions lets us always pay attention to the environmental damage caused by the logging industry.

3. The government's regulatory goal is to increase overall income while ensuring the environment.

4. Logging will lead to environmental damage, which will decrease the number of tourists.

 

This model is based on tourism tax revenue versus logging tax revenue. Tourism tax revenue is more incredible than logging tax revenue, indicating a better environment. As a result of government policy, the logging industry will be heavily developed in the short term. Growth in the logging industry will increase by 40%. A growth rate of 0.8 and 0.6 of the original is obtained when logging taxes are 2 and 4 times higher than tourism taxes.

 

Furthermore, tourism tax and logging tax also act on the positive rate, which is the probability that customers give a positive evaluation. The over-development of the logging industry will lead to the destruction of environmental resources and further affect the tourism industry. The logging tax will also affect the tourism Ride Rate, which is the probability that all tourism customers will choose Derby city.

 

This model more accurately reflects logging and tourism's natural growth and ties the two industries together environmentally. Two ways of development are evident in the two industries. Compared to tourism, logging shows an upward spiral influenced by government policies. Government attitudes also affect tourism revenue, but more by the logging industry. 

Overview This model is a working simulation of the competition between the mountain biking tourism industry versus the forestry logging within Derby Tasmania.    How the model works  The left side of the model highlights the mountain bike flow beginning with demand for the forest that leads to incre
Overview
This model is a working simulation of the competition between the mountain biking tourism industry versus the forestry logging within Derby Tasmania.

How the model works
The left side of the model highlights the mountain bike flow beginning with demand for the forest that leads to increased visitors using the forest of mountain biking. Accompanying variables effect the tourism income that flows from use of the bike trails.
On the right side, the forest flow begins with tree growth then a demand for timber leading to the logging production. The sales from the logging then lead to the forestry income.
The model works by identifying how the different variables interact with both mountain biking and logging. As illustrated there are variables that have a shared effect such as scenery and adventure and entertainment.

Variables
The variables are essential in understanding what drives the flow within the model. For example mountain biking demand is dependent on positive word mouth which in turn is dependent on scenery. This is an important factor as logging has a negative impact on how the scenery changes as logging deteriorates the landscape and therefore effects positive word of mouth.
By establishing variables and their relationships with each other, the model highlights exactly how mountain biking and forestry logging effect each other and the income it supports.

Interesting Insights
The model suggests that though there is some impact from logging, tourism still prospers in spite of negative impacts to the scenery with tourism increasing substantially over forestry income. There is also a point at which the visitor population increases exponentially at which most other variables including adventure and entertainment also increase in result. The model suggests that it may be possible for logging and mountain biking to happen simultaneously without negatively impacting on the tourism income.
 Overview 

 A model which simulates the competition between logging versus adventure
tourism (mountain bike ridding) in Derby Tasmania.  

  
How the model works: 

 Trees grow, and we cut them down because of the demand for Timber and
sell the logs. Mountain bikers and holiday visitors will come t

Overview

A model which simulates the competition between logging versus adventure tourism (mountain bike ridding) in Derby Tasmania. 


How the model works:

Trees grow, and we cut them down because of the demand for Timber and sell the logs. Mountain bikers and holiday visitors will come to the park and this depends on experience and recommendations.  Past experience and recommendations depend on the Scenery, number of trees compared to the visitor and Adventure number of trees and users.  Park capacity limits the number of users.  To utilize highest park capacity, they need to promote to the holiday visitor segment as well. Again, the visit depends on the scenery. So, both mountain biking and forestry (logging) businesses need to contribute a significant amount of revenue to CSR for faster regrowth of trees.


Interesting insights

It looks like a lot of logging doesn't stop people from mountain biking. 

Faster replantation of the tree will balance out the impact created by logging which will give the visitor a positive experience and the number of visitors is both improved. 

To keep the park's popularity in check, the price of wood needs to be high. 

Also, it looks like mountain biking only needs a narrow path.

CSR contribution to nature can be a crucial factor. 

  Overview  A model which simulates the competition between logging versus adventure tourism (mountain bike ridding) in Derby Tasmania.  Simulation borrowed from the Easter Island simulation.     How the model works.   Trees grow, we cut them down because of demand for Timber amd sell the logs.  Wit
Overview
A model which simulates the competition between logging versus adventure tourism (mountain bike ridding) in Derby Tasmania.  Simulation borrowed from the Easter Island simulation.

How the model works.
Trees grow, we cut them down because of demand for Timber amd sell the logs.
With mountain bkie visits.  This depends on past experience and recommendations.  Past experience and recommendations depends on Scenery number of trees compared to visitor and Adventure number of trees and users.  Park capacity limits the number of users.  
Interesting insights
It seems that high logging does not deter mountain biking.  By reducing park capacity, visitor experience and numbers are improved.  A major problem is that any success with the mountain bike park leads to an explosion in visitor numbers.  Also a high price of timber is needed to balance popularity of the park. It seems also that only a narrow corridor is needed for mountain biking
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. 




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. 




This Model described the outbreak simulation under government policy and impacts on Economics.     Assumptions    The social distance policy can reduce 80% of infection.        Interesting Insights   The story tell the difference when social distance applied or not        Click on View story to star
This Model described the outbreak simulation under government policy and impacts on Economics.

Assumptions 
The social distance policy can reduce 80% of infection.

Interesting Insights
The story tell the difference when social distance applied or not

Click on View story to start simulations

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. 




 Simple epidemiological model for Burnie, Tasmania   SIR: Susceptible to infection - Infected - Recovery, Government responses and Economic impacts           Government policy is activated when there are 10 or fewer reported cases of COVID-19. The more people tested, the fewer people became infected
Simple epidemiological model for Burnie, Tasmania
SIR: Susceptible to infection - Infected - Recovery, Government responses and Economic impacts  

Government policy is activated when there are 10 or fewer reported cases of COVID-19. The more people tested, the fewer people became infected. So the government's policy is to reduce infections by increasing the number of people tested and starting early. At the same time, it has slowed the economic growth (which, according to the model,  will stop for next 52 weeks).
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. 




   Explanation of the Model    This is a Model of COVID-19 outbreak in Burnie, Tasmania which shows the government actions in response to the pandemic COVID-19 and its affects on the Economy. The government health policy changes depending on the reported cases, which is a dependent upon the testing
Explanation of the Model
This is a Model of COVID-19 outbreak in Burnie, Tasmania which shows the government actions in response to the pandemic COVID-19 and its affects on the Economy. The government health policy changes depending on the reported cases, which is a dependent upon the testing rate. 

Assumptions
Lockdown and travel ban were the main factor in government policy. It negatively impacts on the Economic growth as individuals are not going out which is directly affects the business around the world, in this insight 'Burnie'. This reduces the economic growth and the factors positively effecting economic growth such as Tourism.

Government policies has a negative impact on Exposer of individuals. Moreover, it also has a negative impact on chances of infection when exposed as well as other general infection rate.
 

Interesting Insight 
There is a significant impact of test rating on COVID-19 outbreak. Higher rates increases the government involvement, which decreases cases as well as the total death. 
In contrast, lower testing rates increase the death rate and cases. 

Tourism which plays a avital role in Tasmanian Economy greatly affects the Economic Growth. The decline of Tourism in parts of Tasmania such as Burnie, would directly decrease the economy of Tasmania.


  
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. 




 This Model was first developed from the SIR model (Susceptible, Infected, Recovered). It was designed to explore relationship between the government policies regarding the COVID-19 and its influences on the economy as well as well-being of local residents.       Assumptions:   Government policies w

This Model was first developed from the SIR model (Susceptible, Infected, Recovered). It was designed to explore relationship between the government policies regarding the COVID-19 and its influences on the economy as well as well-being of local residents. 

 

Assumptions:

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

Government policies reduces the infection and economic growth at the same time.

 


Interesting Insights:

In the first two weeks, the infected people showed an exponential growth, in another word, that’s the most important period to control the number of people who got affected. 

 

  Overview  A model which simulates the competition between logging versus adventure tourism (mountain bike ridding) in Derby Tasmania.  Simulation borrowed from the Easter Island simulation.     How the model works.   Trees grow, we cut them down because of demand for Timber amd sell the logs.  Wit
Overview
A model which simulates the competition between logging versus adventure tourism (mountain bike ridding) in Derby Tasmania.  Simulation borrowed from the Easter Island simulation.

How the model works.
Trees grow, we cut them down because of demand for Timber amd sell the logs.
With mountain bkie visits.  This depends on past experience and recommendations.  Past experience and recommendations depends on Scenery number of trees compared to visitor and Adventure number of trees and users.  Park capacity limits the number of users.  
Interesting insights
It seems that high logging does not deter mountain biking.  By reducing park capacity, visitor experience and numbers are improved.  A major problem is that any success with the mountain bike park leads to an explosion in visitor numbers.  Also a high price of timber is needed to balance popularity of the park. It seems also that only a narrow corridor is needed for mountain biking
  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.

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. 




  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 num

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%.


 This Model was first developed from the SIR model (Susceptible, Infected, Recovered). It was designed to explore relationship between the government policies regarding the COVID-19 and its influences on the economy as well as well-being of local residents.       Assumptions:   Government policies w

This Model was first developed from the SIR model (Susceptible, Infected, Recovered). It was designed to explore relationship between the government policies regarding the COVID-19 and its influences on the economy as well as well-being of local residents. 

 

Assumptions:

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

Government policies reduces the infection and economic growth at the same time.

 


Interesting Insights:

In the first two weeks, the infected people showed an exponential growth, in another word, that’s the most important period to control the number of people who got affected. 

 

[The Model of COVID-19 Pandemic Outbreak in Burnie, TAS]   A model of COVID-19 outbreaks and responses from the government with the impact on the local economy and medical supply.      It is assumed that the government policy is triggered and rely on reported COVID-19 cases when the confirmed cases
[The Model of COVID-19 Pandemic Outbreak in Burnie, TAS]

A model of COVID-19 outbreaks and responses from the government with the impact on the local economy and medical supply. 

It is assumed that the government policy is triggered and rely on reported COVID-19 cases when the confirmed cases are 10 or less. 

Interesting insights
The infection rate will decline if the government increase the testing ranges, meanwhile,  the more confirmed cases will increase the pressure on hospital capacity and generate more demand for medical resources, which will promote government policy intervention to narrow the demand gap and  affect economic performance by increasing hospital construction with financial investment.

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. 




 This Model was first developed from the SIR model (Susceptible, Infected, Recovered). It was designed to explore relationship between the government policies regarding the COVID-19 and its influences on the economy as well as well-being of local residents.       Assumptions:   Government policies w

This Model was first developed from the SIR model (Susceptible, Infected, Recovered). It was designed to explore relationship between the government policies regarding the COVID-19 and its influences on the economy as well as well-being of local residents. 

 

Assumptions:

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

Government policies reduces the infection and economic growth at the same time.

 


Interesting Insights:

In the first two weeks, the infected people showed an exponential growth, in another word, that’s the most important period to control the number of people who got affected.