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This model is based on the article Dynamic modeling of Infectious Diseases, An application to Economic Evaluation of Influenza Vaccination Farmacoeconomics 2008, 26(1): 45-56 .

And EBOLA


Dynamic Modeling of Infectious Diseases
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This high-level simulation model presented by Jay Forrester in his book World Dynamics, simulates socio-economic-environmental world system. The world Model was created in a time where pollution and other negative effects of industrialization and economic growth started to become recognized in 1970. For this exam purpose, we have rebuilt the model to do some experiments and analyze the results. 
World Model1
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​In a recent report, the World Economic Forum considered that the use of robots in economic activity will cause far more job losses in the near future than there will be new ones created. Every economic sector will be affected. The CLD tries to illustrate the dynamic effects of replacing human workers with robots. This  dynamic  indicates that if there is no replacement of the  income forgone by the laid off workers, then the economy will soon grind to a halt. To avoid disaster, there must be enough money in circulation, not parked in off-shore investments, to permit the purchase of all the goods and services produced by robots. The challenge for the government is to make sure that this is  case.  

ROBOTS AND A DISATROUS ECONOMIC DYNAMIC
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Solow model without external factors.
Solow Model
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This model also shows the operation of a simple economy. It differs from Model 1 primarily in the representation of all goods in the economy by units of measure of a higher level of abstraction. Thus, the same model can represent economies at different levels.

The simulation demonstrates how differing rates of consumption affect Savings.
Simple Economy: Model 2
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This model is an attempt to simulate what is commonly referred to as the “pesticide treadmill” in agriculture and how it played out in the cotton industry in Central America after the Second World War until around the 1990s.

The cotton industry expanded dramatically in Central America after WW2, increasing from 20,000 hectares to 463,000 in the late 1970s. This expansion was accompanied by a huge increase in industrial pesticide application which would eventually become the downfall of the industry.

The primary pest for cotton production, bol weevil, became increasingly resistant to chemical pesticides as they were applied each year. The application of pesticides also caused new pests to appear, such as leafworms, cotton aphids and whitefly, which in turn further fuelled increased application of pesticides.

The treadmill resulted in massive increases in pesticide applications: in the early years they were only applied a few times per season, but this application rose to up to 40 applications per season by the 1970s; accounting for over 50% of the costs of production in some regions.

The skyrocketing costs associated with increasing pesticide use were one of the key factors that led to the dramatic decline of the cotton industry in Central America: decreasing from its peak in the 1970s to less than 100,000 hectares in the 1990s. “In its wake, economic ruin and environmental devastation were left” as once thriving towns became ghost towns, and once fertile soils were wasted, eroded and abandoned (Lappe, 1998).

Sources: Douglas L. Murray (1994), Cultivating Crisis: The Human Cost of Pesticides in Latin America, pp35-41; Francis Moore Lappe et al (1998), World Hunger: 12 Myths, 2nd Edition, pp54-55.

Pesticide Use in Central America Model
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Cornerstore Economic Model
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This high-level simulation model presented by Jay Forrester in his book World Dynamics, simulates socio-economic-environmental world system. The world Model was created in a time where pollution and other negative effects of industrialization and economic growth started to become recognized in 1970. For this exam purpose, we have rebuilt the model to do some experiments and analyze the results. 
World Model2
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The housing market is heavily dependent on two main factors; supply and demand. Both play a major role in determining an equilibrium price for both sellers and buyers in the real estate market. 

Residents, or the general population of individuals, place significant reliance on financial institutions to provide sources of capital i.e mortgages, to fund their purchases of homes. The rate of interest charged by these organisations in turn gives buyers (consumers) purchasing power, creating demand. 

Supply is made up of the number of houses in the market, and consequently, of these, the number of houses which are up for sale. As the prices of houses for sale increases, the demand for purchase of these properties decreases. Conversely, the lower price, the higher the demand. Once the market reaches an equilibrium point, to which buyers and sellers form an agreement, houses are sold accordingly. An underlying factor to consider is the cost of construction, which impacts producers, or suppliers in this instance, and thus the number of homes for sale, and the expected profit sellers hope to achieve. 

The simulated graph highlights the common scenario within the housing market, to which we see that as price increases, the total number for houses for sale decreases, generating an opposite slope to the price. As the price for houses increases, the demand for the houses decreases and vice versa. The equilibrium is evident at time 14 whereby the price of houses and the number of houses for sale overlaps which in turn creates a market to which both buyers and sellers are happy.
The effect of Supply and Demand on the Housing Market Assignment 3 (43323871)
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ECONOMIC GROWTH feeds on itself, provided the growth engine is fed with materials and finance. In this highly simplified representation  some of the factors that influence economic growth are show in the incircled green fields. Governments can influence economic growth positively via investments  and payouts. The most obvious tool which governments can use to slow an overheated economy is taxation.

Economic Growth Engine
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Simple model of the global economy, the global carbon cycle, and planetary energy balance.

The planetary energy balance model is a two-box model, with shallow and deep ocean heat reservoirs. The carbon cycle model is a 4-box model, with the atmosphere, shallow ocean, deep ocean, and terrestrial carbon. 

The economic model is based on the Kaya identity, which decomposes CO2 emissions into population, GDP/capita, energy intensity of GDP, and carbon intensity of energy. It allows for temperature-related climate damages to both GDP and the growth rate of GDP.

This model was originally created by Bob Kopp (Rutgers University) in support of the SESYNC Climate Learning Project.
Simple Climate-Carbon-Economic Model
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NATIONAL DEBT MODEL
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During the Biden administration (2021–2024), the U.S. immigration system was under a lot of pressure. There was a record-high asylum backlog, not enough detention space, and policy changes that made more people eligible to apply, all while the system struggled to keep up. This model reflects those challenges. It shows how more and more asylum seekers were entering an already overwhelmed system, while slow processing times and uneven funding made it hard to move cases forward. As a result, detention numbers kept rising, but deportations stayed relatively low. Instead of resolving cases efficiently, the system settled into a kind of uneasy balance, leaving many people stuck in limbo, neither fully processed nor removed.
GSGS 4610 Migration Project Attempt 2
21 hours ago
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Simple model of the global economy, the global carbon cycle, and planetary energy balance.

The planetary energy balance model is a two-box model, with shallow and deep ocean heat reservoirs. The carbon cycle model is a 4-box model, with the atmosphere, shallow ocean, deep ocean, and terrestrial carbon. 

The economic model is based on the Kaya identity, which decomposes CO2 emissions into population, GDP/capita, energy intensity of GDP, and carbon intensity of energy. It allows for temperature-related climate damages to both GDP and the growth rate of GDP.

This model was originally created by Bob Kopp - https://insightmaker.com/user/16029 (Rutgers University) in support of the SESYNC Climate Learning Project.

Steve Conrad (Simon Fraser University) modified the model to include emission/development/and carbon targets for the use by ENV 221.
REM 221 Simple Climate-Carbon-Economic Model with Targets
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This Insight Maker model illustrates the complex relationships involved in the destruction of rainforests. The reinforcing loop emphasizes the destructive cycle where economic development leads to increased deforestation, while the balancing loop highlights the negative consequences on biodiversity, climate, and economic activities, attempting to counteract the destructive forces. The model serves as a simplified representation to better understand the interconnected factors contributing to rainforest destruction and the importance of considering feedback loops in addressing environmental issues.
Destruction of Rainforests
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Wealth can be seen as the factories, infrastructure, goods and services the population of a nation dispose of. According to Tim Garrett,  a scientist who looks at the economy from the perspective of physics, it is existing wealth that generates economic activity and growth. This growth demands the use of energy as no activity can take place without its use. He also points out that the use of this energy unavoidably  leads to concentrations of CO2 in the atmosphere.  All this, Tim Garrett says,  follows from the second law of thermodynamics.  If wealth decreases then so does economic activity and growth. The CLD tries to illustrate how wealth, ironically, now generates the conditions and feedback loops  that  may cause it to decline. The consequences are  inevitably economic  stagnation (or secular recession?). 

You can read about the connection Tim Garrett makes between 'Wealth, Economic Growth, Energy and CO2  Emissions' simply by Googling 'Tim Garrett and Economy'.

ECONOMIC GROWTH WILL MAKE EVERYTHING WORSE
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Clone of Pesticide Use in Central America for Lab work


This model is an attempt to simulate what is commonly referred to as the “pesticide treadmill” in agriculture and how it played out in the cotton industry in Central America after the Second World War until around the 1990s.

The cotton industry expanded dramatically in Central America after WW2, increasing from 20,000 hectares to 463,000 in the late 1970s. This expansion was accompanied by a huge increase in industrial pesticide application which would eventually become the downfall of the industry.

The primary pest for cotton production, bol weevil, became increasingly resistant to chemical pesticides as they were applied each year. The application of pesticides also caused new pests to appear, such as leafworms, cotton aphids and whitefly, which in turn further fuelled increased application of pesticides. 

The treadmill resulted in massive increases in pesticide applications: in the early years they were only applied a few times per season, but this application rose to up to 40 applications per season by the 1970s; accounting for over 50% of the costs of production in some regions. 

The skyrocketing costs associated with increasing pesticide use were one of the key factors that led to the dramatic decline of the cotton industry in Central America: decreasing from its peak in the 1970s to less than 100,000 hectares in the 1990s. “In its wake, economic ruin and environmental devastation were left” as once thriving towns became ghost towns, and once fertile soils were wasted, eroded and abandoned (Lappe, 1998). 

Sources: Douglas L. Murray (1994), Cultivating Crisis: The Human Cost of Pesticides in Latin America, pp35-41; Francis Moore Lappe et al (1998), World Hunger: 12 Myths, 2nd Edition, pp54-55.

REM 221 - Causal Loop diagramming
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Ocean/atmosphere/biosphere model tuned for interactive economics-based simulations from Y2k on.
Lab 13_affluence
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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.

2018 OVERPOPULATION LEADS TO POLLUTION based on Weather & Climate Extreme Loss of Arable Land and Ocean Fertility by Guy Lakeman - The World3+ Model: Forecaster
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Ocean/atmosphere/biosphere model tuned for interactive economics-based simulations from Y2k on.
Final Project w/ socio-economic
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This model shows the structure and operation of a simple economy. It can represent economic systems at different levels of abstraction (e.g. a single good, a group of goods, multiple groups, & an "economy.")

This model has one significant difference from Model 4. The fractional consumption rate table serves the purpose of demonstrating the effects of changes in the fractional consumption rate (or the converse the fractional rate of saving) from 100% to less-than 100% to more-than 100%.

It demonstrates dramatically the effects of significant changes in consumption rates.
Simple Economy: Model 5
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Like Model 6 this model shows the operation of a simple economy. It demonstrates the effect of changes in the fractional rate of consumption (or the converse the fractional rate of saving.)

In summary, government "spending" tends to slow growth of production and consumption.
Simple Economy: Model 7
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Ocean/atmosphere/biosphere model tuned for interactive economics-based simulations from Y2k on.
Lab 13: Future C Emissions Benchmark