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.
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).
When reported COVID-19 cases begin to show a rapid increase, the government will initiate control policies to deal with the spread.As the number of people tested increases and measures such as isolation and medical assistance are implemented, the number of people infected will decline rapidly.Therefore, the government's policy is to reduce and eliminate sources of transmission by increasing the number of tests and initiating control measures.At the same time, it also shows the negative impact of economic growth, which according to the model will stop in the next 20 weeks.
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
[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.
This model which simulates the competition of Logging with Mountain Tourism in Derby, Tasmania. This main reason of this simulation is to find if logging will affect the mountain tourism and by any chance they can co-exist.
How the model works.
Both Timber harvesting and mountain tourism can bring the economic contribution to Tasmania. In the Logging industry, it helps increase the need of employment and at the same time logging generate the profit through selling those timbers. In the Mountain Tourism industry, it can get the revenue through couple of ways which include accommodation (approximately 3 days find in paper), Restaurant and parking fee. However, the low growth rate of the trees is not keeping up with the rate of logging, if the trees getting less in Derby mountain, it will affect the sights and the riding experience for tourists, which will affect the satisfaction and expectation as it depends on the sights and experience. The satisfaction and expectation will influence the number of visitors, if they satisfied, they can come again or tell others about the great experience, if not, more and more people will not come again.
Interesting insights
It seems like logging has no significant negative effect to the mountain tourism, compare the forestry income with the tourism income, tourism income gradually higher than the forestry income at last, which means tourism is in a very important position, as long as the visitors are stable, tourism industry can provide greater economic contribution, stakeholders and governments can find the balance by maintain the status or better slightly reduce logging in order to make them co-exist.
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 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 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 economic growth in the same way.
Govt policy is trigger when reported COVID-19 case are 10 or less.
Interesting insights
Higher testing rates seem to trigger more rapid government intervention, which reduces infectious cases.
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
Create a simulation model which demonstrates how well these competing industries can co-exist, and under what conditions would one adversely affect the other
This model demonstrates the COVID-19 outbreak in Bernie, Tasmania, and shows the relationship between coVID-19 outbreaks, government policy and the local economy. The spread of pandemics is influenced by many factors, such as infection rates, mortality rates, recovery rates and government policies. Although government policy has brought the Covid-19 outbreak under control, it has had a negative impact on the financial system, and the increase in COVID-19 cases has had a negative impact on economic growth.
Assumptions:
The model is based on different infection rates, including infection rate, mortality rate, detection rate and recovery rate. There is a difference between a real case and a model. Since the model setup will only be initiated when 10 cases are reported, the impact on infection rates and economic growth will be reduced.
Interesting insights:
Even as infection rates fall, mortality rates continue to rise. However, the rise in testing rates and government health policies contribute to the stability of mortality. The model thinks that COVID-19 has a negative impact on offline industry and has a positive impact on online industry.
This is a model that simulates the competition between logging versus adventure tourism (mountain bike riding) in Derby Tasmania. The simulation is borrowed from the Easter island simulation
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 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.
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](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%2F20241121%2Fauto%2Fstorage%2Fgoog4_request&X-Goog-Date=20241121T173616Z&X-Goog-Expires=3601&X-Goog-SignedHeaders=host&X-Goog-Signature=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)
