Simple model of Paramecium with constrained growth.

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

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.

This is the base stock and flow diagram I will use to develop a larger system of influencing factors, from health, agri-food systems, and environmental models. Data was taken from UNICEF and UNFPA. Time = 0 starts at 1987.

SIR model with waning immunity - Metrics by Guy Lakeman

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

SIR model with waning immunity - Metrics by Guy Lakeman

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

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

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.

Hepatitis A merupakan penyakit infeksi virus pada hati melalui makanan atau minuman

This insight is about infection propagation and  population migration influence on this propagation. For this, we defined a world population size and a percentage of it who’s infected. Then, we created an agent where we simulated possible states of an individual. So, he can be healthy, infected (with an infection rate) or immunized ( with a certain rate of immunization). If the individual is infected, he can be alive or dead. Then, we simulated different continents (North-America, Asia and Europe) with a migration between these with a certain rate of migration (we tried to approach reality). Then, thanks to our move action which represents a circular permutation between the different continents with a random probability, the agent will be applied to every individual of the world population.

 How does the program work ?

In order to use this insight, we need to define a size of world population and a probability of every individual to reproduce himself. Every individual of this population can have three different state (healthy, infected or immunized) and infected people can be alive or dead. We need to define a percentage of infection for healthy people and a percentage of death for infected people and also a percentage of immunization.
Finally, there is Migration Part of the program, in this one, we need to define three different continents, states or whatever you want. We also need to define a migration probability between each continent to move these person. With this moving people, we can study the influence of migration on the propagation of a disease.

Vincent Cochet, Julien Platel, Jordan Béguet

Multiple Cause Diagrams (MCDs) can be used to find solutions to systemic problems. This diagram tries to explore treatment options that could theoretically be available to a person who has been diagnosed with a particular type of blepharitis (inflammation of eye lids). This type of blepharitis often leads to 'pink eye' and  'dry eye syndrome'. It  is caused by rosacea of the eye lids, a systemic disease which can only be controlled but not cured.  The MCD also assumes that the patient's tear glands do not produce enough tears, which  further complicates his eye condition.  The broken green lines indicate treatment options.Their aim is to weaken or disrupt links that keep the malignant process going.

Our Economy is all about making air filters using factories that make the air worse, causing more people to buy air filters.

This is the base stock and flow diagram I will use to develop a larger system of influencing factors, from health, agri-food systems, and environmental models. Data was taken from UNICEF and UNFPA. Time = 0 starts at 1987.

RMIT Assignment MATH2220

SARS Modelling with SEIR Model.

This insight is about infection propagation and population migration influence on this propagation.

For this, we defined a world population size and a percentage of it who’s infected. Then, we created an agent where we simulated possible states of an individual.

So, he can be healthy, infected (with an infection rate) or immunized ( with a certain rate of immunization). If the individual is infected, he can be alive or dead. Then, we simulated different continents (North-America, Asia and Europe) with a migration between theses with a certain rate of migration (we tried to approach reality).

Then, thanks to our our move action which represent a circular permutation between the different continents with a random probability the agent will be applied to every individual of the world population.

How the program works ?

In order to use this insight needs to define a size of world population and a probability of every individual to reproduce himself.

Every individual of this population can have three different state (healthy, infected or immunized) and infected people can be alive or dead.

We need to define a percentage of infection to healthy people and a percentage of death for infected people and also a percentage of immunization.

Finally there is le migration part of the program, in this one we need to define three different continents, states or whatever you want. We also need to define a migration probability between each continent to move these person.

With this moving people we can study the influence of migration on the propagation of a disease.

This insight is about infection propagation and  population migration influence on this propagation. For this, we defined a world population size and a percentage of it who’s infected. Then, we created an agent where we simulated possible states of an individual. So, he can be healthy, infected (with an infection rate) or immunized ( with a certain rate of immunization). If the individual is infected, he can be alive or dead. Then, we simulated different continents (North-America, Asia and Europe) with a migration between these with a certain rate of migration (we tried to approach reality). Then, thanks to our move action which represents a circular permutation between the different continents with a random probability, the agent will be applied to every individual of the world population.

 How does the program work ?

In order to use this insight, we need to define a size of world population and a probability of every individual to reproduce himself. Every individual of this population can have three different state (healthy, infected or immunized) and infected people can be alive or dead. We need to define a percentage of infection to healthy people and a percentage of death for infected people and also a percentage of immunization.
Finally there is Migration Part of the program, in this one, we need to define three different continents, states or whatever you want. We also need to define a migration probability between each continent to move these person. With this moving people, we can study the influence of migration on the propagation of a disease.

Vincent Cochet, Julien Platel, Jordan Béguet

This is a model on how a virus may spread in a population. It is a model that can relatively easily built by students in upper secondary education

RMIT Assignment MATH2220