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 W

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.

  INTRODUCTION
  

  COVID-19  

 Coronavirus which was named COVID-19 is a
respiratory disease which affects the lungs of the infected person and thus
making such people vulnerable to other diseases such as pneumonia. It was first
discovered in Wuhan China in December 2019 and since then has spread

INTRODUCTION

COVID-19

Coronavirus which was named COVID-19 is a respiratory disease which affects the lungs of the infected person and thus making such people vulnerable to other diseases such as pneumonia. It was first discovered in Wuhan China in December 2019 and since then has spread across the world affecting more than 40 million people from which over one million have died.

In the early discovery of the COVID-19, there were measures that were put in place with the help World Health Organization (WHO). They recommended a social distance of 1.5 meters to 2 meters to curb the spread since the scientist warned that COVID-19 can be carried in the droplets when someone breathes or cough. Another measure which was advised by WHO was wearing of mask, especially when people are in group. Wearing of mask would ensure that someone’s droplets do not leave their mouth or nose when they breathe or cough. It also help one from breathing in the virus which believed to be contagious and airborne.

The World Health Organization also advised on washing of the hand and avoiding frequent touching of the face. People mostly use their hand to touch surfaces which mad their hand the greatest harbor of the disease. Therefore, washing hands with soap will kill and wash away the virus from the hands. Avoiding touching of face also will prevent people from contracting the disease since the virus is believed to enter the body through openings such as eye, nose and mouth.

Another measure as a precaution from contracting the disease was to avoid hand shaking, hugging, kissing and any other thing which would bring people together. These were measures put to ensure that COVID-19 do not move from one person to another because of its airborne nature and the fact that it can be carried from the mouth or nose droplets.

Healthcare workers, in most of the countries, were provided with Personal Protective Equipment (PPEs) which helped them to protect themselves from contracting the virus. Healthcare workers were at the forefront in combating the disease since they were the people receiving the sick, including the ones with the virus. This exposed them to COVID-19 more than anyone hence more care was needed for them. Their PPEs comprised of white overall covering the whole body from head to toes. It also includes face mask and googles worn to prevent anything getting in their eyes. Their hands also were covered with gloves which were removed occasionally to avoid concentration of the virus on one glove.

COVID-19 affected many economies across the world as it greatly affected the human economic activities across the world. Due to the nature and how it spread, COVID-19 lead many countries to lockdown the country as we know it. Travelling was stopped as many countries feared the surge of the virus due to many people travelling form the countries which are already greatly affected. Another reason which travelling was hampered was due to the fact that the virus could spread among the travelers in an airplane. There were no proper measures to ensure social distance in the airplane and many people feared travelling from fear of contracting the disease.

This greatly affected the economy of many countries including great economies like USA. Tourism industry was the one affected the most as many country mostly depend on foreign travelers as their tourist. Many countries do not have proper domestic tourism structure and therefore depend on visitors who travels from foreign countries. Such countries have their economies greatly affected since the earnings from tourism either gone down or was not there at all.

Apart from locking down the country from foreigners, many major cities across the world were under lockdown. This means that even the citizens of the country were neither allowed in or out of the city. This restricted movement of people affecting greatly the human economic activities as many businesses were closed down especially transport businesses. The movement of goods from one places to another was affected making business difficult to carry out. Many people who dealt in perishable agricultural products count losses as their farm produced were destroyed because of lack of wider market. Some countries banned some businesses such as importing second hand clothes since it was believed that they could harbor the virus. Most of the meeting places such as sporting events and pubs were closed down affecting greatly the people who were involved in such businesses.

Across the world, schools were closed. Schools contain students in large numbers which could affect many students across the world. Learning was temporary stopped as different countries were finding ways of curbing the virus.

Scientist are busy like bees across the world to find the vaccine for the diseases that have ravage many countries and above all, they are trying to find the cure. Many countries have carried out their trial of vaccines with the hope to find an effective vaccine for the virus.

Meanwhile it is necessary to find ways by which the virus can be controlled so that it doesn’t spread to a point where it come out of control. Some of the measures put by the WHO has been highlighted above, but these measures need to be studied to ensure that measures which are more effective are affected at great heights. I therefore, have created a model in Insight Maker to check how these measures prove their effectiveness over time.

Agent based Modeling Simulation for Pandemic COVID-19 Disease
Agent based Modeling Simulation for Pandemic COVID-19 Disease
THE BROKEN LINK BETWEEN SUPPLY AND DEMAND CREATES TURBULENT CHAOTIC DESTRUCTION  The existing global capitalistic growth paradigm is totally flawed  Growth in supply and productivity is a summation of variables as is demand ... when the link between them is broken by catastrophic failure in a compon
THE BROKEN LINK BETWEEN SUPPLY AND DEMAND CREATES TURBULENT CHAOTIC DESTRUCTION

The existing global capitalistic growth paradigm is totally flawed

Growth in supply and productivity is a summation of variables as is demand ... when the link between them is broken by catastrophic failure in a component the creation of unpredictable chaotic turbulence puts the controls ito a situation that will never return the system to its initial conditions as it is STIC system (Lorenz)

The chaotic turbulence is the result of the concept of infinite bigness this has been the destructive influence on all empires and now shown up by Feigenbaum numbers and Dunbar numbers for neural netwoirks

See Guy Lakeman Bubble Theory for more details on keeping systems within finite working containers (villages communities)

This three loop goal-seeking structure identifies the three key influences on managing blood glucose for people with diabetes - insulin injections reduce blood glucose levels, exercise reduces blood glucose levels, and food increases blood glucose levels.  The balance of all three is necessary to ma
This three loop goal-seeking structure identifies the three key influences on managing blood glucose for people with diabetes - insulin injections reduce blood glucose levels, exercise reduces blood glucose levels, and food increases blood glucose levels.  The balance of all three is necessary to manage diabetes.
This insight shows the relation between a healthy set of people and an infected set using the primitive infection rate variable as the "rate" that defines how many people get into the infected set at which rate. The second part of the insight shows how many people get recovered and move into Immune
This insight shows the relation between a healthy set of people and an infected set using the primitive infection rate variable as the "rate" that defines how many people get into the infected set at which rate. The second part of the insight shows how many people get recovered and move into Immune set by the rate defined through Recovery Rate variable.
Agent based Modeling Simulation for Pandemic COVID-19 Disease
Agent based Modeling Simulation for Pandemic COVID-19 Disease
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
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. 
Agent based Modeling Simulation for Pandemic COVID-19 Disease
Agent based Modeling Simulation for Pandemic COVID-19 Disease
This two loop goal-seeking structure identifies two factors to manage blood glucose for people with diabetes - insulin injections and exercise.
This two loop goal-seeking structure identifies two factors to manage blood glucose for people with diabetes - insulin injections and exercise.
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.
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
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
Simple goal seeking loop for type 1 diabetes, describing relationship between blood glucose level, insulin injections, and food consumption, seeking to achieve healthy balanced blood glucose levels in the body.
Simple goal seeking loop for type 1 diabetes, describing relationship between blood glucose level, insulin injections, and food consumption, seeking to achieve healthy balanced blood glucose levels in the body.
Relationship between weight and eating patterns
Relationship between weight and eating patterns
 A Susceptible-Infected-Recovered (SIR) disease model with waning immunity

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

21 last week
OVERSHOOT GROWTH GOES INTO TURBULENT CHAOTIC DESTRUCTION  The existing global capitalistic growth paradigm is totally flawed  The chaotic turbulence is the result of the concept of infinite bigness this has been the destructive influence on all empires and now shown up by Feigenbaum numbers and Dunb
OVERSHOOT GROWTH GOES INTO TURBULENT CHAOTIC DESTRUCTION

The existing global capitalistic growth paradigm is totally flawed

The chaotic turbulence is the result of the concept of infinite bigness this has been the destructive influence on all empires and now shown up by Feigenbaum numbers and Dunbar numbers for neural netwoirks

See Guy Lakeman Bubble Theory for more details on keeping systems within finite limited size working capacity containers (villages communities)

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.
modelo ejemplo tutorial con agregado de variación estocastica en tasa de contagio
modelo ejemplo tutorial con agregado de variación estocastica en tasa de contagio
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. Compare with WHO NCD Framework picture and IHI Whole system measures 2.0 (Added Nov 2016) See CLD conversion  insight
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. Compare with WHO NCD Framework picture and IHI Whole system measures 2.0 (Added Nov 2016) See CLD conversion insight