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.
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.
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
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


How do drugs affect us on individual and popular levels? Let's take a look at drug addiction as a system and pick it apart based on its biological, financial, mental, and communal effects.
How do drugs affect us on individual and popular levels? Let's take a look at drug addiction as a system and pick it apart based on its biological, financial, mental, and communal effects.
Bugs have a life cycle. The population of the bugs can be controlled by destroying the stocks of eggs/nymphs/adults or by controlling the rate at which they lay eggs, the rate of hatching of the eggs and the rate at which the nymphs become adults. The growth also depends on the time taken for eggs t
Bugs have a life cycle. The population of the bugs can be controlled by destroying the stocks of eggs/nymphs/adults or by controlling the rate at which they lay eggs, the rate of hatching of the eggs and the rate at which the nymphs become adults. The growth also depends on the time taken for eggs to hatch and for the nymphs to become adults. Some of the control strategies could also be to increase this time. The effectiveness of these strategies differs and the model lets you evaluate them
8 months ago
This is reproduction of the tutorial exercise 1, Disease Dynamics.
This is reproduction of the tutorial exercise 1, Disease Dynamics.
SARS Modelling with SEIR Model. Author: Aulia Nur Fajriyah & Lutfi Andriyanto
SARS Modelling with SEIR Model.
Author: Aulia Nur Fajriyah & Lutfi Andriyanto
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.
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.
Our Economy is all about making air filters using factories that make the air worse, causing more people to buy air filters.
Our Economy is all about making air filters using factories that make the air worse, causing more people to buy air filters.
The Bioresource Model is circular in its nature, and can be divided into two halves, or arcs, within the circle: 1) Primary bioresources = the food and fiber system, and  2) Secondary bioresources = organic waste that is manufactured into secondary bioproducts, e.g. soil amendments (like compost), a
The Bioresource Model is circular in its nature, and can be divided into two halves, or arcs, within the circle:
1) Primary bioresources = the food and fiber system, and
2) Secondary bioresources = organic waste that is manufactured into secondary bioproducts, e.g. soil amendments (like compost), animal feed, materials & chemicals, and energy (fuels, electricity, and CHP)
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 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.
From NAP Toward Quality Measures for Population Health and the Leading Health Indicators  Report  with detailed Maternal  Infant and Child Health Example Fig.3-5
From NAP Toward Quality Measures for Population Health and the Leading Health Indicators Report with detailed Maternal  Infant and Child Health Example Fig.3-5
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 (wi
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
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
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
 A Susceptible-Infected-Recovered (SIR) disease model with herd immunity and isolation policies.

A Susceptible-Infected-Recovered (SIR) disease model with herd immunity and isolation policies.

This model shows the relationship between placement to Bourke Hospital and Infection Rate, Recovery rate and release from Bourke Hospital.       Assumptions   This model assumes that:  upper value for Sensitive to get infected is 50 people  upper value for Placed into Bourke hospital is 50 people  u
This model shows the relationship between placement to Bourke Hospital and Infection Rate, Recovery rate and release from Bourke Hospital.  

Assumptions
This model assumes that:
upper value for Sensitive to get infected is 50 people
upper value for Placed into Bourke hospital is 50 people
upper value for Released from Bourke hospital is 50 people

Variables
Infection Rate - can be adjusted upwards or downwards to stimulate infection rate.
Infection Factor - can be adjusted upwards or downwards to stimulate infection rate.
Recovery Rate - can be adjusted upwards or downwards to stimulate infection rate.
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 (wi
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
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 (wi
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
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.
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.
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, infecte
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.