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
  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
   Overview   The model shows the industry connection and conflict between Forestry and Mountain Tourism in Derby, Tasmania. The objective of this simulation is to find out the balance point for co-exist.      How Does the Model Work?   Both industries can provide economic contribution to Tasmania.

Overview

The model shows the industry connection and conflict between Forestry and Mountain Tourism in Derby, Tasmania. The objective of this simulation is to find out the balance point for co-exist.

 

How Does the Model Work?

Both industries can provide economic contribution to Tasmania. Firstly, selling timbers through logging would generate income. Also, spendings from mountain bike riders would generate incomes. However, low tree regrowth rate can not cover up logging, which influences the beautiful vistas and riders' experiences. While satisfaction and expectation depend on vistas and experience, the demand of mountain biking would be influenced through repeat visits and world of mouth as well.

 

Interesting Insights

Although forestry can provide a great amount of economic contribution to Tasmania, over logging goes against ESG framework as well as creating conflict with mountain tourism. As long as the number of rider visits is stable, tourism can always provide a greater economic contribution compared to forestry. Therefore, the government should consider the balance point between two industries.

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. 




  Overview  

 It is a model simulating
logging and adventure tourism (mountain bike riding) competition in Derby,
Tasmania. It is a chance for northeast Tasmania to become an exciting, new, world-class
product for the mountain bike tourism industry, which drives local economic
development. 

 Simul

Overview

It is a model simulating logging and adventure tourism (mountain bike riding) competition in Derby, Tasmania. It is a chance for northeast Tasmania to become an exciting, new, world-class product for the mountain bike tourism industry, which drives local economic development.

Simulation borrowed from the Easter Island simulation.

How the model works

l  Trees grow; we cut them down because of demand for Timber and sell the logs.

l  The mountain bike visits depend on previous experience and suggestions.

l  Previous experience and suggestions depend on the number of trees compared to visitors and adventure number of trees and users. Park capacity limits the number of mountain bike trail users.

l  The employment opportunity depends on the mountain bike demand and demand for Timber.

Interesting Insights

Mountain biking appears to be unaffected by heavy logging. The visitor experience and numbers are improved by reducing park capacity. The main issue is that any success with the mountain bike park increases visitor numbers. A high timber price is also required to balance the park's popularity. Mountain biking appears to require only a narrow corridor; that is, single-track mountain bike trails are enough. The employment is a measure of the economic acting, a recession or growth trends.

This insight suggests a relationship between the mountain biking industry (which occurs in nature and is motivated by a desire to exercise, connect with nature and be satisfied) and the forestry industry (which relies on logging of forests to yield timber and revenue). This insight analyses this rel
This insight suggests a relationship between the mountain biking industry (which occurs in nature and is motivated by a desire to exercise, connect with nature and be satisfied) and the forestry industry (which relies on logging of forests to yield timber and revenue). This insight analyses this relationship, within the context of Derby, Tasmania. Some 38,823 Tasmania received visitor cyclists, while Tourism accounts for $2.25B of Tasmanias GSP and 33,600 jobs. 

Northern Foresty accounts for 35% of regional employment derived from Tasmania's 3.35M hectares of forests. The industry (valued at $1.2B) received $212M in 2022 in Federal support and provides over 5700 jobs and $115M to 673 Tasmanian business. This money derived from both logging and mountain biking is often reinvested in local accommodation and flows into the local economy. The two industries can coexist. Both profitable industries rely on Tasmanian trees to attract tourists and source Timber. The size of the forests impacts satisfaction and positive referrals, which in turn affect how many people go mountain biking. In order to construct new accommodation, trees must be cut to benefit the Derby population. 


  Sike Liu's model on COVID-19 & Burnie Economy       This model contains three parts, the first part stimulates the COVID-19 pandemic outbreak in Burnie; the second part describes possible government policies on pandemic control; and the third part examines the possible negative impact on econo
Sike Liu's model on COVID-19 & Burnie Economy

 

This model contains three parts, the first part stimulates the COVID-19 pandemic outbreak in Burnie; the second part describes possible government policies on pandemic control; and the third part examines the possible negative impact on economy growth from those policies.


Assumptions:

1. The state boarder has already been closed and all new arrivals in Burnie need to enter a fixed period of quarantine. And the quarantine rate measures the strength of the government policy on quarantine (such as length and method).

2. Patient zero refers to the initial number of undetected virus carriers in the community.

3. Government policies such as social distancing, compulsory mask and lock down could effectively reduce community’s exposure to the virus.

4. Social distancing and compulsory mask will be triggered when COVID-19 cases reach and beyond 10 and lock down will be triggered when cases reach and beyond 1000.

4. High vaccine rate, on the other hand, could effectively reduce the exposed people’s chance of getting infected.

5. Only when vaccine rate reaches 0.6 and beyond, then the spread of COVID-19 will be significantly slowed.

6. Vaccine can’t 100% prevent the infection of the virus.

7.The infected people will need to be tested so that they could be counted as COVID-19 cases and the test rate decides the percentage of infected people being tested.

8. After people recover, there are chances of them losing immunity and the immunity lost rate measures that.

9. The COVID-19 cases could also be detected at quarantine facilities, and the quarantine process will effectively reduce the Infection and exposure rate.

10. Social distancing and compulsory mask wearing are considered as light restrictions in this model and will have less impact on both supply and demand side, and lockdown is considered as heavy restriction which will have strong negative impact on economy growth in this model.

11. In this model, light restrictions will have more negative impacts on the demand side compared to the supply side.

12. In this model, both supply side and demand side will power the economy growth.

 

Interest hints:

The vaccine could significantly reduce the spread of COVID-19 and effectively reduce the number of COVID-19 cases.

The number of the COVID-19 cases will eventually be stabilized when the number of susceptible is running out in a community (reached community immunity).

Quarantine could slightly reduce the cases numbers, but the most effective way is to reduce the number of new arrivals.

A balanced loop model of managing target inventory with demand.  We did this on Wednesday 2-4.
A balanced loop model of managing target inventory with demand.  We did this on Wednesday 2-4.
There is a concern that Logging has an adverse effect on the experience of tourist mountain bikers looking for nature experiences in Derby, Tasmaina.    This model helps give more insight on the relationship between the forest industry and mountain tourism, showing that despite the changes and incre
There is a concern that Logging has an adverse effect on the experience of tourist mountain bikers looking for nature experiences in Derby, Tasmaina.

This model helps give more insight on the relationship between the forest industry and mountain tourism, showing that despite the changes and increase in logging activities with the aim of generating more income from timber, there can be a balance between mountain tourism and the forest industry.
Simple bass model which shows the diffusion of the innovation
Simple bass model which shows the diffusion of the innovation
 Overview:   The model shows the industry competition and relationship between Forrestry and Mountain Bike Trip in Derby, Tasmania. The aim of the simulation is to find a balance between the co-existence of these two industry.      How Does the Model Work?       Both industries will generate incomes
Overview: 
The model shows the industry competition and relationship between Forrestry and Mountain Bike Trip in Derby, Tasmania. The aim of the simulation is to find a balance between the co-existence of these two industry.

How Does the Model Work?

Both industries will generate incomes. Firstly, income is generated from the sale of timber through logging. In addition, income is also generated from the consumption of mountain bike riders. Regarding to the Forrestry industry, people cut down trees because there is a market demand for timber. The timber is sold for profits. However, the experience of mountain biking tourism is largely affected by the low regeneration rate of trees and the degradation of the environment and landscape due to tree felling. People have better riding experiences when trees are abundant and the scenery is beautiful. People's satisfaction and expectations depend on the scenery and experience. Recommendations of past riders will also impact the tourists amount.

Interesting Insights

The income generated by logging can provide a significant economic contribution to Tasmania, but excessive logging can lead to environmental problems and a reduction in visitors. Excessive logging can lead to a decline in tourism in the mountains, which will affect tourism. Despite the importance of forestry, tourism can also provide a significant economic contribution to Tasmania. The government should find a balance between the two industries while maintaining the number of tourists. 



  Overview:     

 This model displays the
conflict between the tourism and timber industry in Derby, Tasmania. It becomes
a problem for the government officials when choosing the future policy direction.
Our aim is to construct a model for simulation and find a equilibrium point to
maximize the sta

Overview: 

This model displays the conflict between the tourism and timber industry in Derby, Tasmania. It becomes a problem for the government officials when choosing the future policy direction. Our aim is to construct a model for simulation and find a equilibrium point to maximize the state benefit.

 

How Does the Model Work?

The key factor of the model is the value of the policy variable. It can take values between -1 and +1. The more it is close to +1 means that the policy government takes is more tourism-friendly. The more it is close to -1 means that the policy government takes is more timber-friendly.

Other than the policy variable, there are three sections for the model.

Section 1: The tourism

       We assume that there exist a population which contains the whole potential customers. The potential customers will make bike trips to Derby at a relatively stable rate. The input policy value will affect the satisfaction rate for the tourists. Some of them will provide positive feedbacks and become our potential customers again. On the other hand, those had bad experience will no longer make trips to Derby. All the tourists make consumption every month and part of the expense will become the tourism revenue. The average expense variable is also provided in this section.

Section 2: The timber industry

      The input policy variable will also affect the employment in the timber industry. It will partially determine the industry growth rate. Like the tourism, the sales/industry scale will generate monthly revenue for the industry at a given rate.

Section 3: The state benefit

      The revenue from the two industries will be added up. Our aim is to adjust the policy value to maximize the state benefit.

 

Interesting Insights

       Excessive logging may lead to environmental problems and it isn’t the best option for the whole state benefit. Based on the pre-set parameters and the model, we can see that the revenue contribution from the tourism is also considerable. According to our results, the policy value should be around 0.31, which represents the tourism-friendly policy.

  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
  Overview   This model is an amalgamation of the Easter Island and Steven D'Alessandro's Derby mountain biking versus logging simulations. It shows the variables that comprise both Sustainable Timber Tasmania and mountain bike tourism in Derby, Tasmania. Plus, it demonstrates their potential effect
Overview
This model is an amalgamation of the Easter Island and Steven D'Alessandro's Derby mountain biking versus logging simulations. It shows the variables that comprise both Sustainable Timber Tasmania and mountain bike tourism in Derby, Tasmania. Plus, it demonstrates their potential effect on each others' revenue streams.
How the Model Works
The model works by showing the processes for each industry, the points at which they interact, and their resulting impact on each others performance over time.This ideally provides a way to optimise performance in both.
Interesting Insights
It appears that it is possible for the two industries to coexist. The amount of forest stock required to be left over to create a scenic forest fringe is negligible to forestry production efficiency. However, it contributes greatly to mountain biker perceptions of scenery and adventure. Knowing this can help promote profit in both industries, moving forward.
This model shows the changing happened in forest industry and mountain tourism in Derby Tasmania. Logging will degrade mountain tourism while benefit the forestry industry. Simulation borrowed from the Easter Island simulation.    According to the analysis, logging does not reduce tourism income. Wi
This model shows the changing happened in forest industry and mountain tourism in Derby Tasmania. Logging will degrade mountain tourism while benefit the forestry industry. Simulation borrowed from the Easter Island simulation.

According to the analysis, logging does not reduce tourism income. With the increase of number of bike guide, tourism income will increase as well. Also, in forest industry, timber income is higher than the harvest spending which means the industry always gain profits from logging. Therefore, the main concern is that the logging should be balanced between the Mountain Tourism and the forest industry.
A model situmalte the relationship between moutain bikes and logging industry in Derby, Tasmania, It explains more when the number of visitors increases or decreses.    How the model works  The left side shows when the number of travellers increase, the income from travellers rental of bike and stay
A model situmalte the relationship between moutain bikes and logging industry in Derby, Tasmania, It explains more when the number of visitors increases or decreses. 

How the model works
The left side shows when the number of travellers increase, the income from travellers rental of bike and stay of hotel increase simultaneously. However, there is a capacity for both parking lots and hotel venues, which means that the top ability of hospitality of Derby. The right side shows the logging industry of Derby and income from logging. It has a impact on how travellers would value Derby moutain.

Insights
As the number of travellers increase, it increases the total income of Derby, and in return, the local government will re-revest in Derby Moutain and will also maintain the forrestry logging industry. 
  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. 

 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.

A model than matches production with demand and a target inventory level
A model than matches production with demand and a target inventory level
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.






  Explanation   This model shows the COVID-19 outbreak in Burnie and how the government policy impacts the economy. The possible phases when the infectious disease spreads in Burnie can be labelled as Susceptible, Infection and Recovery, which are main factors in the model. It is concluded that the
Explanation
This model shows the COVID-19 outbreak in Burnie and how the government policy impacts the economy. The possible phases when the infectious disease spreads in Burnie can be labelled as Susceptible, Infection and Recovery, which are main factors in the model. It is concluded that the government policy can reduce the infectious disease and also the impact in the overall economy.

Assumption
The Government Healthy Policy will affect the decrease in the infection and economy growth rate at the same time.

The Government Health Policy is only triggered when there are more than 10 cases

The increase in number of COVID-19 cases can affect negatively towards the economic growth.

Interesting Insights:
The Government's vaccination promote will reduce the possibility of spreading the infectious disease. 

When vaccination rate increase, the dead, infected people and susceptible group will all decrease. This reveals that the crucial role in government's vaccination promote program.

When there is more than 10 confirmed cases, the government policies can effectively reduce the infections and the overall economic activities.


 The model simulates the comparison between mountain biking industry and forestry/logging in Derby Tasmania.     How the model works  On the left-hand side, Derby Mountain biking, tourists visit the mountain according to reviews and recommendation of mountain scenery and entertainment activities. Th
The model simulates the comparison between mountain biking industry and forestry/logging in Derby Tasmania.

How the model works
On the left-hand side, Derby Mountain biking, tourists visit the mountain according to reviews and recommendation of mountain scenery and entertainment activities. The number of people who hire bikes and who choose to dine on the mountain are limited by bike availability. Both bike hiring and biker dining contribute to tourist revenue in Derby. On the right-hand side, forest trees grow at certain rates, but are negatively affected by timber demand. Timber logging generate revenue, which depends on sale price and associated cost.

Interesting insights
Although forestry contributes more revenue in a certain time, it seems that Derby Mountain bike generate more tourist revenue from dining services and bike hiring in a long term.

 Mountain Bike riding versus logging in Derby, Tasmania.      This is a model that shows logging vs adventure tourism in Derby.  Derby is on the north-east of Tasmania and is a small town that is known for it's beautiful forestry, scenery and more recently it's mountain bike trials. Due to dense for
Mountain Bike riding versus logging in Derby, Tasmania. 

This is a model that shows logging vs adventure tourism in Derby.
Derby is on the north-east of Tasmania and is a small town that is known for it's beautiful forestry, scenery and more recently it's mountain bike trials. Due to dense forestry it also means the Derby is known for logging within the same area. 
This has meant competing priorities have emerged between mountain bike riding on their world famous mountain bike trails and logging on the same trials impacting both sides. The impact of noise from machinery and interrupted views has meant some dissatisfaction in tourism and will decrease tourism numbers in the area. An increase in adventure tourism can detract from logging as well, which until more trails opened in Derby Forestry had the most impact the local economy. Most of the logging goes towards high-quality products such as tas oak furniture which also has a high demand. 
This model shows that logging and mountain bike riding in Derby can co-exist. As the demand for the mountain bike Derby and park capacity increases the adventure tourism decreases as less people will want to visit Derby for mountain biking if over crowded. As both create revenue for the economy it is important that they co-exist and logging can be contained to certain areas away from mountain biking.  

        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.