A simple Susceptible - Infected - Recovered disease model.
A simple Susceptible - Infected - Recovered disease model.
A simple Susceptible - Infected - Aids Patient disease model.
A simple Susceptible - Infected - Aids Patient disease model.
5 months ago
A simple Susceptible - Infected - Aids Patient disease model.
A simple Susceptible - Infected - Aids Patient disease model.
5 months ago
Model
sloužící k analýze dynamiky šíření epidemie v populaci a k testování různých
scénářů řízení, jako je zvýšení vakcinace nebo zavedení karanténních opatření.
Model sloužící k analýze dynamiky šíření epidemie v populaci a k testování různých scénářů řízení, jako je zvýšení vakcinace nebo zavedení karanténních opatření.
9 months ago
A simple Susceptible - Infected - Recovered disease model.
A simple Susceptible - Infected - Recovered disease model.
12 months ago
A simple Susceptible - Infected - Recovered disease model.
A simple Susceptible - Infected - Recovered disease model.
10 months ago
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
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.
3 weeks ago
A simple Susceptible - Infected - Recovered disease model.
A simple Susceptible - Infected - Recovered disease model.
11 months ago
 SIR model with herd immunity - Metrics by Guy Laekman   A Susceptible-Infected-Recovered (SIR) disease model with herd immunity

SIR model with herd immunity - Metrics by Guy Laekman

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

6 months ago
A simple Susceptible - Infected - Recovered disease model.
A simple Susceptible - Infected - Recovered disease model.
6 months ago
A simple Susceptible - Infected - Recovered disease model.
A simple Susceptible - Infected - Recovered disease model.
 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).

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).

6 months ago
 SIR model with herd immunity - Metrics by Guy Laekman   A Susceptible-Infected-Recovered (SIR) disease model with herd immunity

SIR model with herd immunity - Metrics by Guy Laekman

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

6 months ago
A simple Susceptible - Infected - Recovered disease model.
A simple Susceptible - Infected - Recovered disease model.
6 months ago
A simple Susceptible - Infected - Recovered disease model.
A simple Susceptible - Infected - Recovered disease model.
6 months ago
 A spatially aware, agent based model of disease spread. There are four classes of sheep: susceptible (healthy), infected (sick and infectious),  recovered (healthy and temporarily immune), and death

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


4 months ago
 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