Insight diagram
SARS-CoV-19 COVID-19 Corona Coronavirus Virus Disease Pandemic Infection
Clone of SARS-CoV-19 model
CarInTheLake
Insight diagram
Agent Base Modeling Disease
Clone of Agent Based Disease
Tarcisio Costa Brum
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) Germany
Coronavirus Virus Corona Disease COVID-19 SARS-CoV-19 Infection 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)

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)

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

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
  • practicing preventive measures (ie. washing hands regularly, not touching your face etc.): 0.1 (nobody does anything) - 1 (very strictly)
  • government elucidation: 0.1 (very bad) - 1 (highly transparent and educating)
  • Immunity rate (due to lacking data): 0 (you can't get immune) - 1 (once you had it you'll never get it again)

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
Clone of SARS-CoV-19 model
Mark Dav
Ohhigladyoudecidedtolookatthisrightnowinsteadoflikeaweekagoorsomething. Iamfeelingextremelypassiveaggressiverightnow. Emilyisstressedlol Nateisstealingmycomputer LoveyouMitchell<3 HateyousomuchFIXTHISMODEL
Disease Epidemiology Mitchellneedstolookatthisnow Whyisn'tmitchelllookingatthisrightnow Mitchellyousuck Mitchellwhyareyouthebestpartnernotreally
Ohhigladyoudecidedtolookatthisrightnowinsteadoflikeaweekagoorsomething.
Iamfeelingextremelypassiveaggressiverightnow.
Emilyisstressedlol
Nateisstealingmycomputer
LoveyouMitchell<3
HateyousomuchFIXTHISMODEL
So NOW you decide to look at this.
Mitchell Lee
This systems model will help students understand the different systems that make up our body and how choices we make can impact how those systems work. Factors are based on daily choices.
Health Disease Human Body Systems
This systems model will help students understand the different systems that make up our body and how choices we make can impact how those systems work.
Factors are based on daily choices.
Clone of Human Body Systems Efficiency
Marc-André Beaulieu
This is reproduction of the tutorial exercise 1, Disease Dynamics.
Health Disease
This is reproduction of the tutorial exercise 1, Disease Dynamics.
Tut1-diseaseDynamics
Samundra Singh
4
Insight diagram
Agent Base Modeling Disease
Clone of Agent Based Disease
TomG
This systems model will help students understand the different systems that make up our body and how choices we make can impact how those systems work. Factors are based on daily choices.
Disease Health Human Body Systems
This systems model will help students understand the different systems that make up our body and how choices we make can impact how those systems work.
Factors are based on daily choices.
Clone of Human Body Systems Efficiency
Youssef
This systems model will help students understand the different systems that make up our body and how choices we make can impact how those systems work. Factors are based on daily choices.
Disease Health Human Body Systems
This systems model will help students understand the different systems that make up our body and how choices we make can impact how those systems work.
Factors are based on daily choices.
Clone of Clone of Human Body Systems Efficiency
Marcela Denisse Magaña Marroquín
Hepatitis A merupakan penyakit infeksi virus pada hati melalui makanan atau minuman
Health Care Disease Health
Hepatitis A merupakan penyakit infeksi virus pada hati melalui makanan atau minuman
Hepatitis A Model dan Simulasi
DEVI LUTHFITANINGRUM LUTHFITANINGRUM
SARS-CoV-19 spread  in different countries - please  adjust variables accordingly Italy elderly population (&gt;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
Tisa Monita
A simple Susceptible - Infected - Recovered disease model.
KeLE ABM Disease
A simple Susceptible - Infected - Recovered disease model.
Clone of SIR Model
Tatiana Costache
Simple Basic Model as suggested in the manual (in German)
Disease Biology Immunology
Simple Basic Model as suggested in the manual (in German)
Clone of Modellierung einer einfachen Infektionskrankheit
Wolfgang Käppeli
A simple Susceptible - Infected - Recovered disease model.
KeLE ABM Disease
A simple Susceptible - Infected - Recovered disease model.
Clone of SIR Model
Mariam Mohamed
A simple Susceptible - Infected - Recovered disease model.
Disease KeLE ABM
A simple Susceptible - Infected - Recovered disease model.
SIR Model
Steven D'Alessandro
SARS-CoV-19 spread  in different countries - please  adjust variables accordingly Italy elderly population (&gt;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 Coronavirus Corona COVID-19 Infection Disease Pandemic Virus
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
Tony Zambito
Insight diagram
Disease Agent Base Modeling
Clone of Agent Based Disease
Jeb Eddy
Um modelo simples de modelo de difusão de doenças.
Disease
Um modelo simples de modelo de difusão de doenças.
Difusão de Doença
Simulação Computacional
Semestrální projekt na operační a systémovou analýzu
Disease
Semestrální projekt na operační a systémovou analýzu
Operacni a systemova analyza
Tomáš Kaufman
Insight diagram
Agent Base Modeling Disease
Clone of Clone of Agent Based Disease
max
Simple Basic Model as suggested in the manual (in German)
Immunology Disease Biology
Simple Basic Model as suggested in the manual (in German)
Modellierung einfache Infektionskrankheit
Steffen Schaal
SARS-CoV-19 spread  in different countries - please  adjust variables accordingly Italy elderly population (&gt;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
Pandemic Infection Disease Virus Coronavirus Corona COVID-19 SARS-CoV-19
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
Holger Huette
SIR model with waning immunity - Metrics by Guy Lakeman A Susceptible-Infected-Recovered (SIR) disease model with waning immunity
Disease Ebola Health Health Care

SIR model with waning immunity - Metrics by Guy Lakeman

A Susceptible-Infected-Recovered (SIR) disease model with waning immunity


Clone of SIR model with waning immunity - Metrics by Guy Lakeman
Greg King
Insight diagram
SIR Disease Agent-Based Model
Clone of SIR Model
Evandro Dias Gaio