# COVID-19 Models

These models and simulations have been tagged “COVID-19”.

Overview:

The COVID-19 Outbreak in Burnie Tasmania shows the process of COVID-19 outbreak, the impacts of government policy on both the COVID-19 outbreak and the GDP growth in Burnie.

Assumptions:

We set some variables at fix rates, including the immunity loss rate, recovery rate, death rate, infection rate and case impact rate, as they usually depend on the individual health conditions and social activities.

It should be noticed that we set the rate of recovery, which is 0.7, is higher than that of immunity loss rate, which is 0.5, so, the number of susceptible could be reduced over time.

Step 1: Set all the variables at minimum values and simulate

results: Number of Infected – 135; Recovered – 218; Cases – 597; Death – 18,175; GDP – 10,879.

Step 2: Increase the variables of Health Policy, Quarantine, and Travel Restriction to 0.03, others keep the same as step 1, and simulate

results: Number of Infected – 166 (up); Recovered – 249 (up); Cases – 554 (down); Death – 18,077 (down); GDP – 824 (down).

So, the increase of health policy, quarantine and travel restriction will help increase recovery, decrease confirmed cases, decrease death, but also decrease GDP.

Step 3: Increase the variables of Testing Rate to 0.4, others keep the same as step 2, and simulate

results: Number of Infected – 152 (down); Recovered – 243 (down); Cases – 1022 (up); Death – 17,625 (down); GDP – 824 (same).

So, the increase of testing rate will help to increase the confirmed cases.

Step 4: Change GDP Growth Rate to 0.14, Tourism Growth Rate to 0.02, others keep the same as step 3, and simulate

results: Number of Infected – 152 (same); Recovered – 243 (same); Cases – 1022 (same); Death – 17,625 (same); GDP – 6,632 (up).

So, the increase of GDP growth rate and tourism growth rate will helps to improve the GDP in Burnie.

9 months ago

Description:

Model of Covid-19 outbreak in Burnie, Tasmania

This model was designed from the SIR model(susceptible, infected, recovered) to determine the effect of the covid-19 outbreak on economic outcomes via government policy.

Assumptions:

The government policy is triggered when the number of infected is more than ten.

The government policies will take a negative effect on Covid-19 outbreaks and the financial system.

Parameters:

We set some fixed and adjusted variables.

Covid-19 outbreak's parameter

Fixed parameter: Background disease.

Adjusted parameters: Infection rate, recovery rate. Immunity loss rate can be changed from vaccination rate.

Government policy's parameters

Adjusted parameters: Testing rate(from 0.15 to 0.95), vaccination rate(from 0.3 to 1), travel ban(from 0 to 0.9), social distancing(from 0.1 to 0.8), Quarantine(from 0.1 to 0.9)

Economic's parameters

Fixed parameter: Tourism

Adjusted parameter: Economic growth rate(from 0.3 to 0.5)

Interesting insight

An increased vaccination rate and testing rate will decrease the number of infected cases and have a little more negative effect on the economic system. However, the financial system still needs a long time to recover in both cases.

9 months ago
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.

Italy
• elderly population (>65): 0.228
• estimated undetected cases factor: 4-11
• starting population size: 60 000 000
• high blood pressure: 0.32 (gbe-bund)
• heart disease: 0.04 (statista)
• free intensive care units: 3 100

Germany
• elderly population (>65): 0.195 (bpb)
• estimated undetected cases factor: 2-3 (deutschlandfunk)
• starting population size: 83 000 000
• high blood pressure: 0.26 (gbe-bund)
• heart disease: 0.2-0.28 (herzstiftung)
• free intensive care units: 5 880

France
• elderly population (>65): 0.183 (statista)
• estimated undetected cases factor: 3-5
• starting population size: 67 000 000
• high blood pressure: 0.3 (fondation-recherche-cardio-vasculaire)
• heart disease: 0.1-0.2 (oecd)
• free intensive care units: 3 000

As you wish
• numbers of encounters/day: 1 = quarantine, 2-3 = practicing social distancing, 4-6 = heavy social life, 7-9 = not caring at all // default 2
• practicing preventive measures (ie. washing hands regularly, not touching your face etc.): 0.1 (nobody does anything) - 1 (very strictly) // default 0.8
• government elucidation: 0.1 (very bad) - 1 (highly transparent and educating) // default 0.9
• Immunity rate (due to lacking data): 0 (you can't get immune) - 1 (once you had it you'll never get it again) // default 0.4

Key
• Healthy: People are not infected with SARS-CoV-19 but could still get it
• Infected: People have been infected and developed the disease COVID-19
• Recovered: People just have recovered from COVID-19 and can't get it again in this stage
• Dead: People died because of COVID-19
• Immune: People got immune and can't get the disease again
• Critical recovery percentage: Chance of survival with no special medical treatment
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.

9 months ago

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

INTRODUCTION

This is a balanced loop model that demonstrates how COVID 19 outbreak in Burnie and the response of the government (e.g. by enforcing health policies: Lockdown; quarantine, non-necessary business closure; border closure) affect the local economy.  This model has 13 positive loops and seven negative loops.  Government response is dependent on the number of reported COVID-19 cases which in turn thought to be dependent on the testing rates less those who recovered from COVID 19 and dead. Economic activity is dependent on the economic growth rate, increased in online shopping, increased in unemployment, number of people who do not obey the rules, COVID 19 cases and health policies.

ASSUMPTIONS

· Both infection and economic growth is reduced by enforcing government policies

· However, the negative effect of government policies is reduced by the number of people who do not obey government health policies

· Govt policies are enforced when the reported COVID-19 case are 10 or greater.

·     Number of COVID cases reported is dependent on the testing rates less those who recovered and dead.

·   The higher number of COVID-19 cases have a negative effect on local economy. This phenomena is known as negative signalling.

·   Government policies have a negative effect on economic activity because health policies limit both social and economic activities which directly or indirectly affect the economy in Burnie .

·  This negative effect is somewhat reduced by the increase in online shopping and the number of people who do not obey heath rules.

INTERESTING INSIGHTS

The test ratings seem to play a vital role in controlling COVID-19 outbreak. Higher Rates of COVID testings decrease the number of COVID 19 deaths and number of infected. This is because higher rates of testing accelerate the government involvement (as the government intervention is triggered earlier, 10 COVID cases mark is reached earlier). Delaying the government intervention by reducing the COVID testing rates increases the death rates and number of infected.

Increased testing rates allow the figures (deaths, susceptible, infected) to reach a plateau quickly.

9 months ago
Evolution of Covid-19 in Brazil:
A System Dynamics Approach

Villela, Paulo (2020)
paulo.villela@engenharia.ufjf.br

This model is based on Crokidakis, Nuno. (2020). Data analysis and modeling of the evolution of COVID-19 in Brazil. For more details see full paper here.

This model aims to show that how Tasmania government's Covid-19 policy can address the spread of the pandemic and in what way these policy can damage the economy.

This model assumes that if the COVID-19 cases are more than 10, the government will take action such as quarantine and lockdown at the area. These policy can indirectly affect the local economy in many different way. At the same time, strict policy may be essential for combating Covid-19.

From the simulation of the model, we can clearly see that the economy of Burine will be steady increase when government successfully reduces the COVID-19 cased and make it spreading slower.

Interesting finding: In this pandemic, the testing rate and the recovery rate are important to stop Covid-19 spreading. Once the cases of Covid-19 less than 10, the government might stop intervention and the economy of Burnie will back to normal.

9 months ago

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%.

Simulation einer Pandemie (Corona) am Beispiel der Bevölkerungssituation in Hamburg (1,9mio Einwohner, variabel)
5 months ago
This System Model presents the cases of COVID-19 in Puerto Princesa City as of June 3, 2021

Insight Author: Pia Mae M. Palay

Introduction;

This model shows COVID-19 outbreak in Burnie have some impact for local economy situation and government policy. The main government policy is lockdown during the spreading period which can help reduce the infected rate, and also increase the test scale to help susceptible confirm their situation.

Variables;

Infection rate, Death rate, Recovery rate, test rate, susceptible, immunity rate, economy growth rate

These variables are influenced by different situation.

When cases over 10, government will implement lockdown policy.

Conclusion;

When cases increase too much , they will influence the economic situation.

Interesting insights:

If the recover rate is higher, more people will recover from the disease. It seems to be a positive sign. However, it would lead to a higher number of recovered people and more susceptible. As a result, there would be more cases, and would have a negative impact on the economic growth.

9 months ago
Model description:
This model is designed to simulate the outbreak of Covid-19 in Burnie in Tasmania, death cases, the governmental responses and Burnie local economy.

More importantly, the impact of governmental responses to both Covid-19 infection and to local economy, the impact of death cases to local economy are illustrated.

The model is based on SIR (Susceptible, Infected and recovered) model.

Variables:
The simulation takes into account the following variables:

Variables related to Covid-19: (1): Infection rate. (2): Recovery rate. (3): Death rate. (4): Immunity loss rate.

Variables related to Governmental policies: (1): Vaccination mandate. (2): Travel restriction to Burnie. (3): Economic support. (4): Gathering restriction.

Variables related to economic growth: Economic growth rate.

Adjustable variables are listed in the part below, together with the adjusting range.

Assumptions:
(1): Governmental policies are aimed to control(reduce) Covid-19 infections and affect (both reduce and increase) economic growth accordingly.

(2) Governmental policy will only be applied when reported cases are 10 or more.

(3) The increasing cases will negatively influence Burnie economic growth.

Enlightening insights:
(1) Vaccination mandate, when changing from 80% to 100%, doesn't seem to affect the number of death cases.

(2) Governmental policies are effectively control the growing death cases and limit it to 195.

9 months ago
COVID-19 outbreak model brief description

The model stimulated the COVID-19 outbreak at Burnie in Tasmania. The pandemic spread was driven by infection rate, death rate, recovery rate, and government policy.

The government policy reduces the infection in some way, but it also decreases the physical industry. Online industry plays a vital role during the pandemic and brings more opportunities to the world economy.

The vaccination directly reduces the infection rate. The national border will open as long as residents have been fully vaccinated.

Assumption:
The model was created based on different rates, including infection rate, death rate, testing rate and recovered rate. There will be difference between the real cases and the model.

The model only list five elements of government policies embracing vaccination rate, national border and state border restrictions, public health orders, and business restrictions. Public health order includes social distance and residents should wear masks in high spread regions.

This model only consider two industries which are physical industry, like manufacturer, retailers, or hospitality industries, and online industry. During the pandemic, employees star to work from home and students can have online class. Therefore, the model consider the COVID-19 has positive impact on online industry.

Interesting insights:
The susceptible will decrease dramatically in first two weeks due to high infection rate and low recovery rate and government policy. After that, the number of susceptible will have a slight decline.

The death toll and recovery rate was increased significantly in the first two weeks due to insufficient healthy response. And the trend will become mild as government policy works.

9 months ago
This is the second in a series of models that explore the dynamics of and policy impacts on infectious diseases. This basic SIR model explores the impact of a simple test and isolate policy. The first model can be found here.

Collapse of the economy, not just recession, is now very likely. To give just one possible cause, in the U.S. the fracking industry is in deep trouble. It is not only that most fracking companies have never achieved a free cash flow (made a profit) since the fracking boom started in 2008, but that  an already very weak  and unprofitable oil industry cannot cope with extremely low oil prices. The result will be the imminent collapse of the industry. However, when the fracking industry collapses in the US, so will the American economy – and by extension, probably, the rest of the world economy. To grasp a second and far more serious threat it is vital to understand the phenomenon of ‘Global Dimming’. Industrial activity not only produces greenhouse gases, but emits also sulphur dioxide which converts to reflective sulphate aerosols in the atmosphere. Sulphate aerosols act like little mirrors that reflect sunlight back into space, cooling the atmosphere. But when economic activity stops, these aerosols (unlike carbon dioxide) drop out of the atmosphere, adding perhaps as much as 1° C to global average temperatures. This can happen in a very short period time, and when it does mankind will be bereft of any means to mitigate the furious onslaught of an out-of-control and merciless climate. The data and the unrelenting dynamic of the viral pandemic paint bleak picture.  As events unfold in the next few months,  we may discover that it is too late to act,  that our reign on this planet has, indeed,  come to an abrupt end?

Dieses Causal Loop Diagramm (CLD) versucht in vereinfachter Weisse die Wesentliche Dynamik des Mars-CoV-2 zu veranschaulichen. Der Motor hinter den Infektionen ist offensichtlich eine selbstverstärkende Rückkopplungsschleife, und ausschlaggebend in diesem Bezug ist der R-Wert. Wenn der R-Wert unter 1 liegt, dann heisst das, dass eine infizierte Person während des Zeitraums, in dem sie infektiös ist, weniger als eine andere Person infiziert.  Liegt der Wert über 1, dann steckt die Infizierte mehr als eine andere Person an, und das Virus verbreitet sich exponentiell. Die Schleifen, die blaue Pfeile enthalten, sind negative Rückkopplungsschleifen – sie bremsen die Verbreitung des Virus. Das Diagramm suggeriert, dass der R-Wert als Schlüssel zur Kontrolle der Verbreitung des Virus dienen könnte. Sollte der Wert über 1 steigen, so müssten  Schutzmassnahem eingeführt werden. Ist der Wert unter 1, dann sind die negativen Schleifen dominierend und einige Massnahmen könnten gelockert werden.

A simple ABM example illustrating how the SEIR model works. It can be a basis for experimenting with learning the impact of human behavior on the spread of a virus, e.g. COVID-19.
Introduction:
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.
9 months ago

Model introduction

This is an SIR model that simulates the potential COVID outbreak that can happen in Burnie, Tasmania after the positive case reported on October 2nd 2021, which incorporates three parts: Susceptible – Infectious – Recovered Looping model, government’s health policy that will affect each phase of the SIR process, and the potential economy that will affect people’s behaviours and thus influence the effectiveness of government’s public policy.

For instance, the values of variables deciding the inflection rate are influenced by actions taken to control the situation, such as through the quarantine of those infected, social distancing, travel bans, and personal isolation and protection strategies. Conversely, the magnitude of the problem at various points in time will also influence the magnitude of the response to control the situation.

Assumptions

1. The population is assumed to be homogeneous and well-mixed. And there is no significant change on the total population due to births and deaths.

2. Once lockdown is lifted, no further imported cases are assumed to occur.

3. Super spreader events are not explicitly considered.

4. The interaction among states is assumed to be implicit.

5. All confirmed cases would go to quarantine, and 90% of their contacts can be traced.

6. Contact tracing and testing capacity is sufficient.

Insights

Ideally, both one-way scenario analysis and two-way scenario analysis (amount change in one/two variables each time) will be conducted to find out the variable that has the greatest impact on getting new cases. Insights below can be gained:

1.What happens if people are more/less likely to pass on infection, through washing their hands and sneeze into their elbows (infection rate affected by people’s behaviours that will further induced by government’s policies)

2. How vaccination rate will affect the development of positive cases

3. What if the structure of the contact network changes (extent to which school, workplace and restaurants is shut down)

4. How growth rate is sensitive to the duration of illness and probability of infection

9 months ago

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

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.

9 months ago