Health | Insight Maker

Agent Based

Disease Dynamic basic

Luay Assidmi

This model has been constructed from the model published in the following article:

Jack B. Homer, "Worker burnout: a dynamic model with implications for prevention and control".

System Dynamics Review 1 (no. 1, Summer 1985): 42-62. ISSN 0883-7066. 0 1985 by the Svstem Dynamics Society.

Clone of Burnout

Hoa Nguyen

Simulation of MTBF with controls

F(t) = 1 - e ^ -λt

Where

• F(t) is the probability of failure

• λ is the failure rate in 1/time unit (1/h, for example)

• t is the observed service life (h, for example)

The inverse curve is the trust time
On the right the increase in failures brings its inverse which is loss of trust and move into suspicion and lack of confidence.
This can be seen in strategic social applications with those who put economy before providing the priorities of the basic living infrastructures for all.

This applies to policies and strategic decisions as well as physical equipment.
A) Equipment wears out through friction and preventive maintenance can increase the useful lifetime,
B) Policies/working practices/guidelines have to be updated to reflect changes in the external environment and eventually be replaced when for instance a population rises too large (constitutional changes are required to keep pace with evolution, e.g. the concepts of the ancient Greeks, 3000 years ago, who based their thoughts on a small population cannot be applied in 2013 except where populations can be contained into productive working communities with balanced profit and loss centers to ensure sustainability)

Early Life

If we follow the slope from the leftmost start to where it begins to flatten out this can be considered the first period. The first period is characterized by a decreasing failure rate. It is what occurs during the “early life” of a population of units. The weaker units fail leaving a population that is more rigorous.

Useful Life

The next period is the flat bottom portion of the graph. It is called the “useful life” period. Failures occur more in a random sequence during this time. It is difficult to predict which failure mode will occur, but the rate of failures is predictable. Notice the constant slope.

Wearout

The third period begins at the point where the slope begins to increase and extends to the rightmost end of the graph. This is what happens when units become old and begin to fail at an increasing rate. It is called the “wearout” period.

Clone of Clone of BATHTUB MEAN TIME BETWEEN FAILURE (MTBF) RISK

Ivan Stamenkovic

This model has been constructed from the model published in the following article:

Jack B. Homer, "Worker burnout: a dynamic model with implications for prevention and control".

System Dynamics Review 1 (no. 1, Summer 1985): 42-62. ISSN 0883-7066. 0 1985 by the Svstem Dynamics Society.

Clone of Burnout

Gagandeep Singh

This model was developed as part of the curriculum development for a short introductory course on systems dynamics modelling for health system analysts.
This is the fourth and final developmental component of Module 2. The population progression through health states is complete

Final CVD Prevention Model

Lynne Vinten

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

Clone of SIR model with waning immunity

Racquel Figueroa

This model has been constructed from the model published in the following article:

Jack B. Homer, "Worker burnout: a dynamic model with implications for prevention and control".

System Dynamics Review 1 (no. 1, Summer 1985): 42-62. ISSN 0883-7066. 0 1985 by the Svstem Dynamics Society.

Clone of Burnout

RichardS

This model has been constructed from the model published in the following article:

Jack B. Homer, "Worker burnout: a dynamic model with implications for prevention and control".

System Dynamics Review 1 (no. 1, Summer 1985): 42-62. ISSN 0883-7066. 0 1985 by the Svstem Dynamics Society.

Clone of Clone of Burnout

RichardS

Module 2 model on Healthy Population model

CVD Disease Progression Model

Lee Robertson

Model description:

This model is designed to simulate the outbreak of Covid-19 in Burnie in Tasmania, death cases, the governmental responses and Burnie local economy.

More importantly, the impact of governmental responses to both Covid-19 infection and to local economy, the impact of death cases to local economy are illustrated.

The model is based on SIR (Susceptible, Infected and recovered) model.

Variables:

The simulation takes into account the following variables:

Variables related to Covid-19: (1): Infection rate. (2): Recovery rate. (3): Death rate. (4): Immunity loss rate.

Variables related to Governmental policies: (1): Vaccination mandate. (2): Travel restriction to Burnie. (3): Economic support. (4): Gathering restriction.

Variables related to economic growth: Economic growth rate.

Adjustable variables are listed in the part below, together with the adjusting range.

Assumptions:

(1): Governmental policies are aimed to control(reduce) Covid-19 infections and affect (both reduce and increase) economic growth accordingly.

(2) Governmental policy will only be applied when reported cases are 10 or more.

(3) The increasing cases will negatively influence Burnie economic growth.

Enlightening insights:

(1) Vaccination mandate, when changing from 80% to 100%, doesn't seem to affect the number of death cases.

(2) Governmental policies are effectively control the growing death cases and limit it to 195.

Burnie Tasmania Covid - 19 outbreak simulation Model by Yankang Huang 541 277

Yankang Huang

Example of Configurable Conveyor Pattern (vectorized conveyor with multiple 'conveyor speeds')

See Taking The Pill

https://getsatisfaction.com/insightmaker/topics/delay-in-taking-the-pill for the problem statement

Clone of Configurable Conveyor Pattern

Paulo Villela

This model has been constructed from the model published in the following article:

Jack B. Homer, "Worker burnout: a dynamic model with implications for prevention and control".

System Dynamics Review 1 (no. 1, Summer 1985): 42-62. ISSN 0883-7066. 0 1985 by the Svstem Dynamics Society.

Clone of Burnout

Hoa Nguyen

Amlodipine

Evan Ananda Jati

3

This is reproduction of the tutorial exercise 1, Disease Dynamics.

Clone of Tut1-diseaseDynamics

Bilal Koussayer

This model has been constructed from the model published in the following article:

Jack B. Homer, "Worker burnout: a dynamic model with implications for prevention and control".

System Dynamics Review 1 (no. 1, Summer 1985): 42-62. ISSN 0883-7066. 0 1985 by the Svstem Dynamics Society.

Clone of Burnout

RJC

The World3 model is a detailed simulation of human population growth from 1900 into the future. It includes many environmental and demographic factors.

THIS MODEL BY GUY LAKEMAN, FROM METRICS OBTAINED USING A MORE COMPREHENSIVE VENSIM SOFTWARE MODEL, SHOWS CURRENT CONDITIONS CREATED BY THE LATEST WEATHER EXTREMES AND LOSS OF ARABLE LAND BY THE ALBEDO EFECT MELTING THE POLAR CAPS TOGETHER WITH NORTHERN JETSTREAM SHIFT NORTHWARDS, AND A NECESSITY TO ACT BEFORE THERE IS HUGE SUFFERING.

BY SETTING THE NEW ECOLOGICAL POLICIES TO 2015 WE CAN SEE THAT SOME POPULATIONS CAN BE SAVED BUT CITIES WILL SUFFER MOST.

CURRENT MARKET SATURATION PLATEAU OF SOLID PRODUCTS AND BEHAVIORAL SINK FACTORS ARE ALSO ADDED

Use the sliders to experiment with the initial amount of non-renewable resources to see how these affect the simulation. Does increasing the amount of non-renewable resources (which could occur through the development of better exploration technologies) improve our future? Also, experiment with the start date of a low birth-rate, environmentally focused policy.

Clone of 2014 Weather & Climate Extreme Loss of Arable Land and Ocean Fertility - The World3+ Model: Forecaster

Kyra Evers

9 months ago

Simulation of MTBF with controls

F(t) = 1 - e ^ -λt

Where

• F(t) is the probability of failure

• λ is the failure rate in 1/time unit (1/h, for example)

• t is the observed service life (h, for example)

The inverse curve is the trust time
On the right the increase in failures brings its inverse which is loss of trust and move into suspicion and lack of confidence.
This can be seen in strategic social applications with those who put economy before providing the priorities of the basic living infrastructures for all.

This applies to policies and strategic decisions as well as physical equipment.
A) Equipment wears out through friction and preventive maintenance can increase the useful lifetime,
B) Policies/working practices/guidelines have to be updated to reflect changes in the external environment and eventually be replaced when for instance a population rises too large (constitutional changes are required to keep pace with evolution, e.g. the concepts of the ancient Greeks, 3000 years ago, who based their thoughts on a small population cannot be applied in 2013 except where populations can be contained into productive working communities with balanced profit and loss centers to ensure sustainability)

Early Life

If we follow the slope from the leftmost start to where it begins to flatten out this can be considered the first period. The first period is characterized by a decreasing failure rate. It is what occurs during the “early life” of a population of units. The weaker units fail leaving a population that is more rigorous.

Useful Life

The next period is the flat bottom portion of the graph. It is called the “useful life” period. Failures occur more in a random sequence during this time. It is difficult to predict which failure mode will occur, but the rate of failures is predictable. Notice the constant slope.

Wearout

The third period begins at the point where the slope begins to increase and extends to the rightmost end of the graph. This is what happens when units become old and begin to fail at an increasing rate. It is called the “wearout” period.

Clone of BATHTUB MEAN TIME BETWEEN FAILURE (MTBF) RISK

Ariel Ortiz Gomes

THE 2018 MODEL (BY GUY LAKEMAN) EMPHASIZES THE PEAK IN POLLUTION BEING CREATED BY OVERPOPULATION.
WITH THE CARRYING CAPACITY OF ARABLE LAND NOW BEING 1.5 TIMES OVER A SUSTAINABLE FUTURE (PASSED IN 1990) AND NOW INCREASING IN LOSS OF HUMAN SUSTAINABILITY DUE TO SEA RISE AND EXTREME GLOBAL WATER RELOCATION IN WEATHER CHANGES IN FLOODS AND DROUGHTS AND EXTENDED TROPICAL AND HORSE LATTITUDE CYCLONE ACTIVITY AROUND HADLEY CELLS

The World3 model is a detailed simulation of human population growth from 1900 into the future. It includes many environmental and demographic factors.

THIS MODEL BY GUY LAKEMAN, FROM METRICS OBTAINED USING A MORE COMPREHENSIVE VENSIM SOFTWARE MODEL, SHOWS CURRENT CONDITIONS CREATED BY THE LATEST WEATHER EXTREMES AND LOSS OF ARABLE LAND BY THE ALBEDO EFECT MELTING THE POLAR CAPS TOGETHER WITH NORTHERN JETSTREAM SHIFT NORTHWARDS, AND A NECESSITY TO ACT BEFORE THERE IS HUGE SUFFERING.

BY SETTING THE NEW ECOLOGICAL POLICIES TO 2015 WE CAN SEE THAT SOME POPULATIONS CAN BE SAVED BUT CITIES WILL SUFFER MOST.

CURRENT MARKET SATURATION PLATEAU OF SOLID PRODUCTS AND BEHAVIORAL SINK FACTORS ARE ALSO ADDED

Use the sliders to experiment with the initial amount of non-renewable resources to see how these affect the simulation. Does increasing the amount of non-renewable resources (which could occur through the development of better exploration technologies) improve our future? Also, experiment with the start date of a low birth-rate, environmentally focused policy.

Clone of 2018 OVERPOPULATION LEADS TO POLLUTION based on Weather & Climate Extreme Loss of Arable Land and Ocean Fertility by Guy Lakeman - The World3+ Model: Forecaster

Ilandor@Ynev

This model has been constructed from the model published in the following article:

Jack B. Homer, "Worker burnout: a dynamic model with implications for prevention and control".

System Dynamics Review 1 (no. 1, Summer 1985): 42-62. ISSN 0883-7066. 0 1985 by the Svstem Dynamics Society.

Clone of Burnout

Hoa Nguyen

This model has been constructed from the model published in the following article:

Jack B. Homer, "Worker burnout: a dynamic model with implications for prevention and control".

System Dynamics Review 1 (no. 1, Summer 1985): 42-62. ISSN 0883-7066. 0 1985 by the Svstem Dynamics Society.

Clone of Burnout

Dave Small

STI

Mel Smith

This model has been constructed from the model published in the following article:

Jack B. Homer, "Worker burnout: a dynamic model with implications for prevention and control".

System Dynamics Review 1 (no. 1, Summer 1985): 42-62. ISSN 0883-7066. 0 1985 by the Svstem Dynamics Society.

Clone of Burnout

Gagandeep Singh

This model has been constructed from the model published in the following article:

Jack B. Homer, "Worker burnout: a dynamic model with implications for prevention and control".

System Dynamics Review 1 (no. 1, Summer 1985): 42-62. ISSN 0883-7066. 0 1985 by the Svstem Dynamics Society.

Clone of Burnout

Gagandeep Singh

MEE460-04

Caleb Hemmelgarn

Sarah Hollis

Carson Kizer

Scott Koney

McKenzie Warman

A Team-Community Cooking Classes and Garden

Caleb Hemmelgarn

Health Models