Insight diagram
SIR Economy Disease
SIR model
NangManCat
4 weeks ago
SIR model with herd immunity - Metrics by Suresh Vunnam A Susceptible-Infected-Recovered (SIR) disease model with herd immunity
Health Disease Health Care

SIR model with herd immunity - Metrics by Suresh Vunnam

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

SIR model with herd immunity - Metrics by suresh vunnam
suresh vunnam
A simple Susceptible - Infected - Recovered disease model.
Disease KeLE ABM
A simple Susceptible - Infected - Recovered disease model.
Clone of SIR Model
Jacob Hagen
A simple Susceptible - Infected - Recovered disease model.
Disease KeLE ABM
A simple Susceptible - Infected - Recovered disease model.
Clone of SIR Model
Daphné Daoust
A simple Susceptible - Infected - Recovered disease model.
Disease KeLE ABM
A simple Susceptible - Infected - Recovered disease model.
Clone of SIR Model
Bilal Koussayer
A simple Susceptible - Infected - Recovered disease model.
KeLE ABM Disease
A simple Susceptible - Infected - Recovered disease model.
Clone of SIR Model
Katie Kelly
A spatially aware, agent based model of disease spread. There are three classes of people: susceptible (healthy), infected (sick and infectious), and recovered (healthy and temporarily immune). @ LinkedIn ,  Twitter ,  YouTube
ABM Disease SIR Roam

A spatially aware, agent based model of disease spread. There are three classes of people: susceptible (healthy), infected (sick and infectious), and recovered (healthy and temporarily immune).

@LinkedIn, Twitter, YouTube

Clone of Spatially Aware SIR Disease Model
Cindy Diaz
A model of an infectious disease and control
Pandemic Environment Health Care Finance Disease
A model of an infectious disease and control

Clone of Disease Dynamics (Agent Based Modeling) Guy Lakeman
Tom Foale
A simple Susceptible - Infected - Recovered disease model.
Disease KeLE ABM
A simple Susceptible - Infected - Recovered disease model.
Clone of SIR Model
hansolo
A simple Susceptible - Infected - Recovered disease model.
KeLE ABM Disease
A simple Susceptible - Infected - Recovered disease model.
Clone of Clone of SIR Model
Tatiana Costache
A simple Susceptible - Infected - Recovered disease model.
Disease KeLE ABM
A simple Susceptible - Infected - Recovered disease model.
Clone of SIR Model
joseph Assouad
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
Corona SARS-CoV-19 COVID-19 Coronavirus Virus Disease 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)
  • 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
Jonathon Sevy
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
Virus Coronavirus SARS-CoV-19 Corona COVID-19 Infection Pandemic Disease
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
Lohitha Meduri
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
Virus Coronavirus Corona Pandemic COVID-19 Infection SARS-CoV-19 Disease
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
lululala
A Susceptible-Infected-Recovered (SIR) disease model with waning immunity
Health Health Care Disease

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

Clone of SIR model with waning immunity
David Nifong
A simple Susceptible - Infected - Recovered disease model.
KeLE ABM Disease
A simple Susceptible - Infected - Recovered disease model.
Clone of SIR Model
José Eduardo Henriques da Silva
This is reproduction of the tutorial exercise 1, Disease Dynamics.
Health Disease
This is reproduction of the tutorial exercise 1, Disease Dynamics.
Clone of Tut1-diseaseDynamics
Bilal Koussayer
A simple Susceptible - Infected - Recovered disease model.
Disease KeLE ABM
A simple Susceptible - Infected - Recovered disease model.
Clone of SIR Model
Jonathan Nocenti
Dosage per day, Doses per day, Every ? hours, Medicine in Intestines, Drug absorption, Plasma level, Blood volume, Plasma concentration, ​Toxic level, Medicinal level, Drug excretion, Excretion rate, Half-Life
Health Biomedical Food Biogeochemistry Disease Health Care
Dosage per day, Doses per day, Every ? hours, Medicine in Intestines, Drug absorption, Plasma level, Blood volume, Plasma concentration, ​Toxic level, Medicinal level, Drug excretion, Excretion rate, Half-Life
Clone of Pharmacokinetics
Fiorenza Celestyn
This model simulates a waterborne illness spread from a central reservoir. It illustrates the combination of System Dynamics (modeling pathogen levels in the reservoir) and Agent Based Modeling. Make sure to check out the Map display to see the geographic clustering of disease incidence around th
Disease Agent Based Modeling
This model simulates a waterborne illness spread from a central reservoir. It illustrates the combination of System Dynamics (modeling pathogen levels in the reservoir) and Agent Based Modeling.

Make sure to check out the Map display to see the geographic clustering of disease incidence around the reservoir.
Clone of Reservoir Disease Spread
J
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 Corona Coronavirus COVID-19 Virus Disease 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)
  • 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
Gnana K Bharathy
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 SARS-CoV-19 Corona Coronavirus Virus Disease 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)
  • 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
sub cribed
A Susceptible-Infected-Recovered (SIR) disease model with waning immunity
Health Health Care Disease

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

Clone of SIR model with waning immunity
Jordan C Argrett
A spatially aware, agent based model of disease spread. There are three classes of people: susceptible (healthy), infected (sick and infectious), and recovered (healthy and temporarily immune).
Disease ABM

A spatially aware, agent based model of disease spread. There are three classes of people: susceptible (healthy), infected (sick and infectious), and recovered (healthy and temporarily immune).

Agent-Based Spatially Aware Disease Model
Ray Madachy
6