Model tentang penyebaran SARS
Clone of Spread of SARS
A simple Susceptible - Infected - Recovered disease model.
Clone of SIR Model
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
A Susceptible-Infected-Recovered (SIR) disease model with isolation policies.
Clone of SIR model with isolation
A Susceptible-Infected-Recovered (SIR) disease model with waning immunity
Clone of SIR model with waning immunity
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.
Clone of Clone of Week-12-Practice
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).
Clone of Spatially Aware SIR Diseasse Model
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
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
A simple Susceptible - Infected - Aids Patient disease model.
Clone of HIV model - Vinicius Carius and Cesar Conopoima
This Epidemic model illustrates an model for more understanding of the spread and impact of diseases in Human populations. To recovered from disease.
Epidemic Model
Tutorial model of disease dynamics using ABM
Clone of Agent-Based Disease Dynamics
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
Tugas Pemodelan Transportasi Laut
Memodelkan persebaran pandemik covid-19 menggunakan insightmaker
Dosen pembimbing : Dr-Ing Ir. Setyo Nugroho
Pandemic Covid-19 Simulation
This is reproduction of the tutorial exercise 1, Disease Dynamics.
Tut1-diseaseDynamics
A Susceptible-Infected-Recovered (SIR) disease model with herd immunity and isolation policies.
Clone of SIR model with herd immunity and isolation
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).
Clone of CS558 Agent-Based Spatially Aware Disease Model
A simple Susceptible - Infected - Recovered disease model.
System Dynamics Disease Model
Interactive Yellow Fever Outbreak model
Yellow Fever larvacide
SIR Model - Metrics by Guy Lakeman
A simple Susceptible - Infected - Recovered disease model.
SIR Model - Metrics by Guy Lakeman
A Susceptible-Infected-Recovered (SIR) disease model with herd immunity and isolation policies.
Clone of Clone of SIR model with herd immunity and isolation
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).
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Clone of Spatially Aware SIR Disease Model
