The SEIRS(D) model for the purpose of experimenting with the phenomena of viral spread. I use it for COVID-19 simulation.
COVID-19 Coronavirus
The SEIRS(D) model for the purpose of experimenting with the phenomena of viral spread. I use it for COVID-19 simulation.
Clone of SEIR - COVID-19 (v.1)
Ashutosh Bansal
The System Dynamics Model presents the the COVID-19 status in Puerto Princesa City
System Modeling Covid-19
The System Dynamics Model presents the the COVID-19 status in Puerto Princesa City
Clone of Ph_Covid19SDM_AngelKateCacayan
Zhenis
11 months ago
The System Dynamics Model presents the the COVID-19 status in Germany
System Modeling Covid-19 germany
The System Dynamics Model presents the the COVID-19 status in Germany
Өзіндік жұмыс соңғы
Qqq zzz
6 months ago
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
Dinamica De Sistemas Modelo SIR Coronavirus COVID-19 Epidemiología
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.
Clone of Modelo SIR simples - Covid 19
Michel Nieto
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/
Disease Corona Coronavirus COVID-19 Infection Pandemic SARS-CoV-19 Virus

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/


CORONAVIRUS EL SALVADOR
Moises Panama Pino
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
Economy COVID-19 Burnie Tasmania BMA708

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%.


COVID-19 Outbreak in Burnie Tasmania (Rajaa Sajjad, 538837)
Rajaa Sajjad
Model di samping adalah model SEIR yang telah dimodifikasi sehingga dapat digunakan untuk menyimulasikan perkembangan penyebaran COVID-19. Modified by Rio dan Pras
Coronavirus COVID-19
Model di samping adalah model SEIR yang telah dimodifikasi sehingga dapat digunakan untuk menyimulasikan perkembangan penyebaran COVID-19.

Modified by Rio dan Pras
Clone of SEIR Model for COVID-19 in Indonesia - case study SLEMAN
Rio Swarawan Putra
If no attempt is made to eradicate SARS-CoV-2 it will eventually become endemic, ineradicable, at a high never-ending cost to world in terms of economic growth, human health and lives. The current strategy adopted by most governments is to impose  restrictive measures when the virus threatens to ov
Vaccines COVID-19 Eradiation Herd Immunity SARS-Cov-2 Strategy

If no attempt is made to eradicate SARS-CoV-2 it will eventually become endemic, ineradicable, at a high never-ending cost to world in terms of economic growth, human health and lives. The current strategy adopted by most governments is to impose  restrictive measures when the virus threatens to overwhelm hospital services and to relax these restrictions as this danger recedes. This is short-sighted. It cannot eliminate the highly infectious delta variant, which has an estimated R0-value of between 6 & 9. Periodic lockdowns will be hard to avoid in the future.

However, eradication is possible, herd immunity can be achieved quickly worldwide, reducing the R0 permanently to below 1, which will lead to the disappearance of the virus. Critical in achieving this is Ivermectin, a medicine that is cheap,  readily available and can be manufactured by most countries. A recent meta study has shown that Ivermectin, prophylactically employed, can prevent infection with the virus  by 86 % on average – very similar to the efficacy of vaccines. Eradication will require employment of all the instruments shown in the graph: future generations do not have to live with this plague. 

SarsCov 2: Countering its Dynamic
Hanns-Jürgen Hodann
Modelo epidemiológico simples SIR: Susceptíveis -Infectados - Recuperados Ajuste os PARÂMETROS abaixo. Clique em SIMULATE no menu superior para simular. Dados iniciais de 04 Abr 2020 Fonte:  https://www.worldometers.info/coronavirus/country/brazil/
COVID-19 Coronavirus SIR Epidemiología
Modelo epidemiológico simples
SIR: Susceptíveis -Infectados - Recuperados

Ajuste os PARÂMETROS abaixo.
Clique em SIMULATE no menu superior para simular.
Dados iniciais de 04 Abr 2020
Clone of Modelo SIR simples para Covid-19 - Brasil
Barbara Scoralick Villela
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.
Coronavirus COVID 19
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.
Clone of Italian COVID 19 outbreak control V2
Jingting REN
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
COVID-19 Virus Coronavirus SARS-CoV-19 Disease Pandemic Corona Infection
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
Clone of SARS-CoV-19 model
Carlos Andres Calvo Garcia
Tugas Permo
COVID-19
Tugas Permo
Clone of Tugas Permo_Corona
Yopy Anjas
This stock-flow simulation model is to show Covid-19 virus spread rate, sources of spreading and safety measures followed by all the countries affected around the world. The simulation also aims at predicting for how much more period of time the virus will persist, how many people could recover at w
Infected COVID-19 Corona Rate Virus Disease Death
This stock-flow simulation model is to show Covid-19 virus spread rate, sources of spreading and safety measures followed by all the countries affected around the world.
The simulation also aims at predicting for how much more period of time the virus will persist, how many people could recover at what kind of rate and also about the virus toughness dependence based on its excessive speed, giving rise to bigger numbers day-by-day.
Week-12-Practice
Sai Nagavelli
10
Modelling the demand for health and care resources resulting from the Covid-19 outbreak using an SEIR model.
COVID-19 Health And Social Care Infectious Disease SARS-Cov-2
Modelling the demand for health and care resources resulting from the Covid-19 outbreak using an SEIR model.

Infectious Disease Model (Version 4.0)
Eleanor Jeram
8
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
Disease Coronavirus Infection Corona Virus COVID-19 SARS-CoV-19 Pandemic
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
Clone of SARS-CoV-19 model
Albatross Cena
COVID-19 outbreak in Burnie Tasmania Simulation Model Introduction This model simulates how COVID-19 outbreak in Burnie and how the government responses influence the economic community.  Government responses are based on the reported COVID-19 cases amount, whcih is considered to be
Burnie Tasmania Government Policy Economic COVID-19
COVID-19 outbreak in Burnie Tasmania Simulation Model

Introduction

This model simulates how COVID-19 outbreak in Burnie and how the government responses influence the economic community.  Government responses are based on the reported COVID-19 cases amount, whcih is considered to be based on testing rate times number of people who are infected minus those recovered from COVID-19 and dead.
Government interventions include the implement of healthy polcy, border surveillance, quarantine and travel restriction. After outbreak, economic activities are positively affected by the ecommerce channel development and normal economic grwoth, while the unemployement rate unfortunately increases as well. 

Assumption
  • Enforcing government policies reduce both infection and economica growth.                        
  • When there are 10 or greater COVID-19 cases reported, the governmwnt policies are triggered.                                                          
  • Greater COVID-19 cases have negatively influenced the economic activities.                    
  • Government policies restict people's activities socially and economically, leading to negative effects on economy.                                          
  • Opportunities for jobs are cut down too, making umemployment rate increased.           
  • During the outbreak period, ecommerce has increased accordingly because people are restricted from going out.                                  
Interesting insights

An increase in vaccination rate will make difference on reduing the infection. People who get vaccinated are seen to have higher immunity index to fight with COVID-19. Further research is needed.

Testing rate is considered as critical issue to reflect the necessity of government intervention. Higher testing rate seems to boost immediate intervention. Reinforced policies can then reduce the spread of coronvirus but absoluately have negative impacts on economy too.
Clone of Mengling Xue 561743 BMA708_Marketing insights into Big Data
Mengling Xue
This model shows the COVID-19 outbreaks in Burnie and the Government intervention to alleviate the crisis and also how is the intervention affect the economy. It is assumed that the Government intervention is triggered when the COVID-19 case is equal to or more than 10.  Government interventi
BMA708 COVID-19 Burnie Economic Impacts
This model shows the COVID-19 outbreaks in Burnie and the Government intervention to alleviate the crisis and also how is the intervention affect the economy.

It is assumed that the Government intervention is triggered when the COVID-19 case is equal to or more than 10. 

Government intervention - lock down the state, suppress the development of COVID-19 effectively. It is related to most of people stay at home to reduce the exposure in public area.
On the other hand, it also bring the economy of Burnie in the recession, as no tourists, no dining out activities and decrease in money spending in the city.
Burnie COVID-19 outbreaks and economic impacts_Pui Chu Daisy Cheung 524767
Pui Chu Daisy Cheung
7
Modelling the demand for health and care resources resulting from the Covid-19 outbreak using an SEIR model.
SARS-Cov-2 Health And Social Care Infectious Disease COVID-19
Modelling the demand for health and care resources resulting from the Covid-19 outbreak using an SEIR model.

Clone of Infectious Disease Model (Version 3.0)
Chris Skelly
Modelling the demand for health and care resources resulting from the Covid-19 outbreak using an SEIR model.
COVID-19 Infectious Disease SARS-Cov-2 Health And Social Care
Modelling the demand for health and care resources resulting from the Covid-19 outbreak using an SEIR model.

Clone of Infectious Disease Model (Version 3.0)
Chris Skelly
Model of Covid-19 outbreak in Burnie, Tasmania This model was designed from SIR model(susceptible, infected, revovered) to find out the effect of covid-19 outbreak into economic outcomes via government policy. Assumptions The government policy is triggered when number of infected is mor
Economic BMA708 COVID-19
Model of Covid-19 outbreak in Burnie, Tasmania

This model was designed from SIR model(susceptible, infected, revovered) to find out the effect of covid-19 outbreak into economic outcomes via government policy.

Assumptions

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

The government policies will take negative effect into Covid-19 outbreaks and financial system

Parameters

We set some fixed and adjusted variables.
Covid-19 outbreak's parameter
Fixed parameters: Infection rate, Background disease, recovery rate.
Adjusted parameter: Immunity loss rate can be change 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

Increase vaccination rate and testing rate will decrease the number amount of infected case and a little bit more negative effect to economic system. However economic system still need a long time to recover in both cases.
BMA708_Assignment 3_ndkvo_520272_COVID-19 outbreak and Burnie economy
KV
Modelo epidemiológico simples SIR: Susceptíveis - Infectados - Recuperados Dados iniciais do Brasil em 04 Abr 2020 Fonte: https://www.worldometers.info/coronavirus/country/brazil/
SIR COVID-19 Epidemiología Coronavirus
Modelo epidemiológico simples
SIR: Susceptíveis - Infectados - Recuperados

Dados iniciais do Brasil em 04 Abr 2020
Clone of Modelo SIR simples - Covid-19
Waner Miranda
This model calculates and demonstrates the possible spread of COVID-19 through an agent-based map. It shows the timeline of a healthy individual being infected to recovery.
Health COVID-19 Pandemic PSU
This model calculates and demonstrates the possible spread of COVID-19 through an agent-based map. It shows the timeline of a healthy individual being infected to recovery.
COVID Model
Justine Grace Jumawan
Insight diagram
SIR COVID-19 Coronavirus India
Индия короновирус, 2021 жыл
Ersultan
6 months ago
Insight diagram
Coronavirus COVID-19
Coronavirus, COVID-19
Yusriyadi