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
This model is comparing healthy and sick residents in Burnie, Tasmania after the Covid-19 Outbreak in 2020. It will also show how the Burnie economy is effected by the disease, how the Government Health Policies are implemented and how they are enforced.
This model is based on the SIR, Susceptible, Infection, Recovery (or
Removed) These are the three possible states related to the members of
the Burnie population when a contagious decease spreads.
The Government/Government Health Policy, played a big part in the successful decrease in Covid-19 infections. The Government enforced the following. - No travel (interstate or international) - Isolation within the residents homes - Social distancing by 1.5m - Quarantine - Non essential companies to be temporarily closed - Limitations on public gatherings - And limits on time and kilometers aloud to travel from ones home within a local community
This resulted in lower reported infection rates of Covid-19 and higher recovery rates. In my opinion: When the first case was reported the Government could have been even faster to enforce these rules to decrease the fatality rates further for the Burnie, population.
Assumption: Government policies were only triggered when 10 cases were recorded. Also, more cases that had been recorded effected the economic growth during this time.
Interesting Findings: In the simulation it shows as the death rates increases towards the end of the week, the rate of testing goes down. You would think that the government would have enforced a higher testing rate over the duration of this time to decrease the number of infections, exposed which would increase the recovery rates faster and more efficiently.
Figures have been determined by the population of Burnie being 19,380 at the time of assignment.
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 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 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
This model simulates the COVID-19 outbreaks in Burnie, the government reactions, as well as the economic impact. The government's strategy is based on the number of COVID-19 cases reported and testing rates and recovered.
Assumptions
In the same trend that government policy decreases infection, it also reduces economic growth.
When there are ten or fewer COVID-19 cases reported, government policy is triggered.
The economy suffers as a result of an increase in COVID-19 cases.
Interesting insights
The higher testing rates appear to result in a more quick government response, resulting in fewer infectious cases. However, it has a negative influence on the economy.
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.
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).
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.
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 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.
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.
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.
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 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.
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 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 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 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 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.
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.
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 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.
![[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](https://insightmakercloud-files.storage.googleapis.com/44b61667-a1e2-4b2a-ade5-e63899744c9d/images/cover.jpg?X-Goog-Algorithm=GOOG4-RSA-SHA256&X-Goog-Credential=insightmakercloud-file-access%40insightmakercloud.iam.gserviceaccount.com%2F20240426%2Fauto%2Fstorage%2Fgoog4_request&X-Goog-Date=20240426T010728Z&X-Goog-Expires=3601&X-Goog-SignedHeaders=host&X-Goog-Signature=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)
