Wenn kein Versuch unternommen wird, SARS-CoV-2 auszurotten, wird es
schließlich endemisch und unausrottbar werden, mit hohen, nicht endenden Kosten
für die Welt in Bezug auf Wirtschaftswachstum, menschliche Gesundheit und
Menschenleben. Die derzeitige Strategie der meisten Regierungen besteht darin

Wenn kein Versuch unternommen wird, SARS-CoV-2 auszurotten, wird es schließlich endemisch und unausrottbar werden, mit hohen, nicht endenden Kosten für die Welt in Bezug auf Wirtschaftswachstum, menschliche Gesundheit und Menschenleben. Die derzeitige Strategie der meisten Regierungen besteht darin, restriktive Maßnahmen zu ergreifen, wenn das Virus die Krankenhäuser zu überschwemmen droht und diese Beschränkungen wieder zu lockern, wenn diese Gefahr zurückgeht. Diese Strategie kann die hochinfektiöse Delta-Variante, die einen geschätzten R0-Wert von 6 bis 9 hat, nicht eliminieren. Regelmäßige Sperrungen werden sich in Zukunft kaum vermeiden lassen.

Eine Ausrottung ist jedoch möglich, ebenso wie eine weltweit schnell erreichte Herdenimmunität, die den R0-Wert dauerhaft auf unter 1 senkt und somit zum Verschwinden des Virus führen wird. Entscheidend dafür ist Ivermectin, ein Medikament, das billig und leicht verfügbar ist und in den meisten Ländern hergestellt werden kann. Eine kürzlich durchgeführte Metastudie hat gezeigt, dass die prophylaktische Anwendung von Ivermectin eine Infektion mit dem Virus im Durchschnitt um 86 % verhindern kann, was der Wirksamkeit von Impfstoffen sehr ähnlich ist. Die, die nicht geimpft wurden und nicht immun sind, weil sie Covid-19 überstanden haben, könnten sich mit Ivermectin sehr effektiv vor einer Infektion schützen.  Die Ausrottung erfordert den Einsatz aller in der Grafik gezeigten Instrumente: künftige Generationen könnte es erspart bleiben mit dieser Plage leben zu müssen.  

     El Salvador     Tamaño población inicial: 6,400,000  Unidad de cuidados intensivos disponibles: 2000  Casos confirmados hasta 13/10/2020: 30,480  Casos fallecidos hasta 13/10/2020: 899   Fuente: https://covid19.gob.sv/

El Salvador
  • Tamaño población inicial: 6,400,000
  • Unidad de cuidados intensivos disponibles: 2000
  • Casos confirmados hasta 13/10/2020: 30,480
  • Casos fallecidos hasta 13/10/2020: 899
Fuente: https://covid19.gob.sv/


Simulation einer Pandemie (Corona) am Beispiel der Bevölkerungssituation in Hamburg (1,9mio Einwohner, variabel)
Simulation einer Pandemie (Corona) am Beispiel der Bevölkerungssituation in Hamburg (1,9mio Einwohner, variabel)
 SARS-CoV-19 spread  in different countries - please  adjust variables accordingly        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
SARS-CoV-19 spread in different countries
- please adjust variables accordingly

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
Modèle simple de causalité entre mesures et impact
Modèle simple de causalité entre mesures et impact
  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
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. 



    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 loo

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. 





The model represents the interaction between influenza and SARS-CoV-2. The data used is for Catalonia region.
The model represents the interaction between influenza and SARS-CoV-2. The data used is for Catalonia region.
5 2 weeks ago
 لطفا برای بزرگنمایی و مشاهده مدل بر روی دکمه     [Explore The Model]   کلیک کنید      شگفتی سازهای تاثیر گذار بر محورمقاومت در جهان پساکرونا چه خواهند بود؟    لطفا نظرات خود را با من در میان بگذارید:  motealle@gmail.com
لطفا برای بزرگنمایی و مشاهده مدل بر روی دکمه
کلیک کنید

شگفتی سازهای تاثیر گذار بر محورمقاومت در جهان پساکرونا چه خواهند بود؟
لطفا نظرات خود را با من در میان بگذارید:
motealle@gmail.com
  Overview:   Overall, this analysis showed a COVID-19 outbreak in Burnie, the government policies to curtail that, and some of the impacts it is having on the Burnie economy.      Variables   The simulation made use of the variables such as; Covid-19: (1): Infection rate. (2): Recovery rate. (3): D

Overview:

Overall, this analysis showed a COVID-19 outbreak in Burnie, the government policies to curtail that, and some of the impacts it is having on the Burnie economy.


Variables

The simulation made use of the variables such as; Covid-19: (1): Infection rate. (2): Recovery rate. (3): Death rate. (4): Immunity loss rate etc. 


Assumptions:

From the model, it is apparent that government health policies directly affect the economic output of Burnie. A better health policy has proven to have a better economic condition for Burnie and verse versa.


In the COVID-19 model, some variables are set at fixed rates, including the immunity loss rate, recovery rate, death rate, infection rate, and case impact rate, as this is normally influenced by the individual health conditions and social activities.

Moving forward, we decided to set the recovery rate to 0.7, which is a rate above the immunity loss rate of 0.5, so, the number of susceptible could be diminished over time.


Step 1: Try to set all value variables at their lowest point and then stimulate. 

 

Outcome: the number of those Infected are– 135; Recovered – 218; Cases – 597; Death – 18,175; GDP – 10,879.


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


Outcome: The number of those Infected – 166 (up); Recovered – 249 (up); Cases – 554 (down); Death – 18,077 (down); GDP – 824 (down).


With this analysis, it is obvious that the increase of health policy, quarantine, and travel restriction will assist in increase recovery rate, a decrease in confirmed cases, a reduction in death cases or fatality rate, but a decrease in Burnie GDP.


Step 3: Enlarge the Testing Rate to 0.4, variable, others, maintain the same as step 2, and simulate


Outcome: It can be seen that the number of Infected is down to – 152; those recovered down to – 243; overall cases up to – 1022; those that died down to–17,625; while the GDP remains – 824.


In this step, it is apparent that the increase of testing rate will assist to increase the confirmed cases.


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


Outcome: what happens is that the Infected number – 152 remains the same; Recovered rate– 243 the same; Number of Cases – 1022 (same); Death – 17,625 (same); but the GDP goes up to– 6,632. 


This final step made it obvious that the increase of GDP growth rate and tourism growth rate will help to improve the overall GDP performance of Burnie's economy.

 This is the third in a series of models that explore the dynamics of infectious diseases. This model looks at the impact of two types of suppression policies.      Press the simulate button to run the model with no policy.  Then explore what happens when you set up a lockdown and quarantining polic
This is the third in a series of models that explore the dynamics of infectious diseases. This model looks at the impact of two types of suppression policies. 

Press the simulate button to run the model with no policy.  Then explore what happens when you set up a lockdown and quarantining policy by changing the settings below.  First explore changing the start date with a policy duration of 60 days.
 Simple epidemiological model for Burnie, Tasmania   SIR: Susceptible to infection - Infected - Recovery, Government responses and Economic impacts           Government policy is activated when there are 10 or fewer reported cases of COVID-19. The more people tested, the fewer people became infected
Simple epidemiological model for Burnie, Tasmania
SIR: Susceptible to infection - Infected - Recovery, Government responses and Economic impacts  

Government policy is activated when there are 10 or fewer reported cases of COVID-19. The more people tested, the fewer people became infected. So the government's policy is to reduce infections by increasing the number of people tested and starting early. At the same time, it has slowed the economic growth (which, according to the model,  will stop for next 52 weeks).
This model demonstrates the relationship between the covid-19 outbreak, government policy, and economic impacts. This model was developed based on SIR model (Susceptible, Infection, Recovery). The model also outlines the policies been implemented by the government to cope with Covid-19 pandemic and
This model demonstrates the relationship between the covid-19 outbreak, government policy, and economic impacts. This model was developed based on SIR model (Susceptible, Infection, Recovery). The model also outlines the policies been implemented by the government to cope with Covid-19 pandemic and it also indicate its economic impact. 
Interesting insights
This model indicates the government policies have had positive influence on economic impact and it reduce its negative effects on the economy.
   Description         The model shows Covid-19 situations in Burnie, Tasmania. Under such circumstances, how the state government deals with the pandemic and how economy changes will be illustrated. The relationship between government policy and economic activities under Covid-19 outbreaks will be

Description

 

The model shows Covid-19 situations in Burnie, Tasmania. Under such circumstances, how the state government deals with the pandemic and how economy changes will be illustrated. The relationship between government policy and economic activities under Covid-19 outbreaks will be explained through different variables.


Assumptions

 

Government policy negatively affects Covid-19 outbreaks and economic activities.

Covid-19 outbreaks also has negative effects on economic growth.

 

Parameters

 

There are several fixed and adjusted variables.

 

1.     COVID-19 Outbreaks

Fixed variables: infection rate, recovery rate

Adjusted variables: immunity loss rate

 

2.     Government Policy

Adjusted variables: lockdown, social distancing, testing, vaccination

3.     Economic impact

Fixed variables: tourism

Adjusted variables: economic growth rate

 

Interesting Insights

 

Tourism seems to be the most effective way to bring back economic growth in Tasmania, and it takes time to recover from Covid-19.

 

Government policies tend to have negative influences on economic growth.

  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
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.

 SARS-CoV-19 spread  in different countries - please  adjust variables accordingly        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
SARS-CoV-19 spread in different countries
- please adjust variables accordingly

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
 SARS-CoV-19 spread  in different countries - please  adjust variables accordingly        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
SARS-CoV-19 spread in different countries
- please adjust variables accordingly

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 can be used to investigate how government interventions affect transmission and mortality associated with COVID-19 during an outbreak, and how these interventions impact on the economic activities in Burnie, Tasmania.     Assumptions can be made that effective government intervention can
This model can be used to investigate how government interventions affect transmission and mortality associated with COVID-19 during an outbreak, and how these interventions impact on the economic activities in Burnie, Tasmania.

Assumptions can be made that effective government intervention can reduce the number of people infected, whereas the local economy is severely impacted.

Insights:
1. When COVID-19 case are more than 10, government policy will be triggered.

2. Testing rate is very crucial to understanding the spread of the pandemic and responding appropriately.


  ABOUT THE MODEL   This is a dynamic model that shows the correlation between the
health-related policies implemented by the Government in response to COVID-19 outbreak
in Burnie, Tasmania, and the policies’ impact on the Economic activity of the
area.   

   ASSUMPTIONS  

 The increase in the num

ABOUT THE MODEL

This is a dynamic model that shows the correlation between the health-related policies implemented by the Government in response to COVID-19 outbreak in Burnie, Tasmania, and the policies’ impact on the Economic activity of the area.

 ASSUMPTIONS

The increase in the number of COVID-19 cases is directly proportional to the increase in the Government policies in the infected region. The Government policies negatively impact the economy of Burnie, Tasmania.

INTERESTING INSIGHTS

1. When the borders are closed by the government, the economy is severely affected by the decrease of revenue generated by the Civil aviation/Migration rate. As the number of COVID-19 cases increase, the number of people allowed to enter Australian borders will also decrease by the government. 

2. The Economic activity sharply increases and stays in uniformity. 

3. The death rate drastically decreased as we increased test rate by 90%.


   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
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. 

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 th
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?  
 Modelling the demand for health and care resources resulting from the Covid-19 outbreak using an SEIR model.
Modelling the demand for health and care resources resulting from the Covid-19 outbreak using an SEIR model.