Modelo epidemiológico simples   SIR: Susceptíveis - Infectados - Recuperados         Clique aqui  para ver um vídeo com a apresentação sobre a construção e uso deste modelo.  É recomendável ver o vídeo num computador de mesa para se poder ver os detalhes do modelo.          Dados iniciais de  infec
Modelo epidemiológico simples
SIR: Susceptíveis - Infectados - Recuperados

Clique aqui para ver um vídeo com a apresentação sobre a construção e uso deste modelo.  É recomendável ver o vídeo num computador de mesa para se poder ver os detalhes do modelo.


Dados iniciais de infectados, recuperados e óbitos para diversos países (incluindo o Brasil) podem ser obtidos aqui neste site.
Initial data from: Italian data [ link ], as of Mar 28  Incubation estimation [ link ]      Model focuses on outbreak dynamics and control, this version ignores symptom onset to hospital admission and the rest of recovery dynamics.
Initial data from:
Italian data [link], as of Mar 28
Incubation estimation [link

Model focuses on outbreak dynamics and control, this version ignores symptom onset to hospital admission and the rest of recovery dynamics.
 Modelo epidemiológico simples   SIR: Susceptíveis - Infectados - Recuperados         Clique aqui  para ver um vídeo com a apresentação sobre a construção e uso deste modelo.  É recomendável ver o vídeo num computador de mesa para se poder ver os detalhes do modelo.          Dados iniciais de  infec
Modelo epidemiológico simples
SIR: Susceptíveis - Infectados - Recuperados

Clique aqui para ver um vídeo com a apresentação sobre a construção e uso deste modelo.  É recomendável ver o vídeo num computador de mesa para se poder ver os detalhes do modelo.


Dados iniciais de infectados, recuperados e óbitos para diversos países (incluindo o Brasil) podem ser obtidos aqui neste site.
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.
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.
8 months ago
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  The government has reduced both the e
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
The government has reduced both the epidemic and economic development by controlling immigration.
The impact of social activities on the economy is enormous.
The impact of immigration on the economy is huge, but the government's move is effective in controlling covid-19.

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.

 Spring, 2020: in the midst of on-line courses, due to the pandemic of Covid-19.      With the onset of the Covid-19 coronavirus crisis, we focus on SIRD models, which might realistically model the course of the disease.     We start with an SIR model, such as that featured in the MAA model featured
Spring, 2020: in the midst of on-line courses, due to the pandemic of Covid-19.

With the onset of the Covid-19 coronavirus crisis, we focus on SIRD models, which might realistically model the course of the disease.

We start with an SIR model, such as that featured in the MAA model featured in

Without mortality, with time measured in days, with infection rate 1/2, recovery rate 1/3, and initial infectious population I_0=1.27x10-4, we reproduce their figure

With a death rate of .005 (one two-hundredth of the infected per day), an infectivity rate of 0.5, and a recovery rate of .145 or so (takes about a week to recover), we get some pretty significant losses -- about 3.2% of the total population.

Resources:
 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.  

   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. 

 Modelo epidemiológico simples   SIR: Susceptíveis - Infectados - Recuperados         Clique aqui  para ver um vídeo com a apresentação sobre a construção e uso deste modelo.  É recomendável ver o vídeo num computador de mesa para se poder ver os detalhes do modelo.          Dados iniciais de  infec
Modelo epidemiológico simples
SIR: Susceptíveis - Infectados - Recuperados

Clique aqui para ver um vídeo com a apresentação sobre a construção e uso deste modelo.  É recomendável ver o vídeo num computador de mesa para se poder ver os detalhes do modelo.


Dados iniciais de infectados, recuperados e óbitos para diversos países (incluindo o Brasil) podem ser obtidos aqui neste site.
 This Model was first developed from the SIR model (Susceptible, Infected, Recovered). It was designed to explore relationship between the government policies regarding the COVID-19 and its influences on the economy as well as well-being of local residents.       Assumptions:   Government policies w

This Model was first developed from the SIR model (Susceptible, Infected, Recovered). It was designed to explore relationship between the government policies regarding the COVID-19 and its influences on the economy as well as well-being of local residents. 

 

Assumptions:

Government policies will be triggered when reported COVID-19 case are 10 or less;

Government policies reduces the infection and economic growth at the same time.

 


Interesting Insights:

In the first two weeks, the infected people showed an exponential growth, in another word, that’s the most important period to control the number of people who got affected. 

 

 Spring, 2020: in the midst of on-line courses, due to the pandemic of Covid-19.      With the onset of the Covid-19 coronavirus crisis, we focus on SIRD models, which might realistically model the course of the disease.     We start with an SIR model, such as that featured in the MAA model featured
Spring, 2020: in the midst of on-line courses, due to the pandemic of Covid-19.

With the onset of the Covid-19 coronavirus crisis, we focus on SIRD models, which might realistically model the course of the disease.

We start with an SIR model, such as that featured in the MAA model featured in

Without mortality, with time measured in days, with infection rate 1/2, recovery rate 1/3, and initial infectious population I_0=1.27x10-4, we reproduce their figure

With a death rate of .005 (one two-hundredth of the infected per day), an infectivity rate of 0.5, and a recovery rate of .145 or so (takes about a week to recover), we get some pretty significant losses -- about 3.2% of the total population.

Resources:
 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.

 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 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. 




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

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