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Ocean/atmosphere/biosphere model tuned for interactive economics-based simulations from Y2k on.

Final Project 1 W/ Socio-Economic Factors

Geoffrey Alan Chapman

3

VA - socio-economic

Baihua

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

Steve Conrad

371

Mental Health Platform Post-Covid June 2021 including revisiting Wiser Health Decisions

Mental Health Platform

Geoff McDonnell

4 9 months ago

This model shows the operation of a simple economy with two modifications made to Model 2 -- 1) feedback from production rate to consumption rate and 2) the use of a fractional rate input for calculating consumption rate.

In summary, lower fractional rates of consumption (based on production) result in higher levels of Savings.

Simple Economy: Model 3

Jim Berger

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

Ocean/atmosphere/biosphere model tuned for interactive economics-based simulations from Y2k on.

Q2 Final Project w/ socio-economic

Claire Murley

Based on chapter 14 of Modeling Dynamic Economic Systems

Quasi-competitive equilibrium model

Martín López Ramírez

213

Challenge p.212 Business Dynamics, Sterman

Oil Shortage 1979 Iran Revolution

Roland Kofler

3

Buying and storing electricity when it is cheap, and selling it when it is expensive. What are the benefits, both public and private?

Smart Grid: Electricity storage and variable energy pricing

Carlos

14

Eastern oyster growth model calibrated for Long Island Sound
Developed and implemented by Joao G. Ferreira and Camille Saurel; growth data from Eva Galimany, Gary Wickfors, and Julie Rose; driver data from Julie Rose and Suzanne Bricker; Culture practice from the REServ team and Tessa Getchis. This model is a workbench for combining ecological and economic components for REServ. Economic component added by Trina Wellman.

This is a one box model for an idealized farm with one million oysters seeded (one hectare @ a stocking density of 100 oysters per square meter)

1. Run WinShell individual growth model for one year with Long Island Sound growth drivers;

2. Determine the scope for growth (in dry tissue weight per day) for oysters centered on the five weight classes)

3. Apply a classic population dynamics equation:

dn(s,t)/dt = -d[n(s,t)g(s,t)]/ds - u(s)n(s,t)

s: Weight (g)
t: Time
n: Number of individuals of weight s
g: Scope for growth (g day-1)
u: Mortality rate (day-1)

4. Set mortality at 30% per year, slider allows scenarios from 30% to 80% per year

5. Determine harvestable biomass, i.e. weight class 5, 40-50 g (roughly three inches length)

REServ Eastern oyster ecology and economics Long Island Sound

Joao G. Ferreira

COVID-19 outbreak in Burnie Tasmania Simulation Model

Introduction

This model simulates how COVID-19 outbreak in Burnie and how the government responses influence the economic community. Government responses are based on the reported COVID-19 cases amount, whcih is considered to be based on testing rate times number of people who are infected minus those recovered from COVID-19 and dead.

Government interventions include the implement of healthy policy, border surveillance, quarantine and travel restriction. After outbreak, economic activities are positively affected by the ecommerce channel development and normal economic grwoth, while the unemployement rate unfortunately increases as well.

Assumption

Enforcing government policies reduce both infection and economica growth.
When there are 10 or greater COVID-19 cases reported, the governmwnt policies are triggered.
Greater COVID-19 cases have negatively influenced the economic activities.
Government policies restict people's activities socially and economically, leading to negative effects on economy.
Opportunities for jobs are cut down too, making umemployment rate increased.
During the outbreak period, ecommerce has increased accordingly because people are restricted from going out.

Interesting insights

An increase in vaccination rate will make difference on reduing the infection. People who get vaccinated are seen to have higher immunity index to fight with COVID-19. Further research is needed.

Testing rate is considered as critical issue to reflect the necessity of government intervention. Higher testing rate seems to boost immediate intervention. Reinforced policies can then reduce the spread of coronvirus but absoluately have negative impacts on economy too.

Mengling Xue 561743 BMA708_Marketing insights into Big Data

Mengling Xue

Causal loop diagram capturing the interactions, trade-offs, and synergies between agriculture (SDG 2), water availability (SDG 6), economic growth (SDG 8), and life on land (SDG 15). Positive feedback linkages are shown as a positive sign (+), whereas negative feedback linkages are shown with a negative sign (−). The purple arrows indicate the enviro-biophysical linkages. The green arrows indicate the socio-economic linkages. The SDG icons are courtesy of the UN SDG communications material.

Reference - Bandari, Reihaneh, et al. "Participatory Modeling for Analyzing Interactions Between High‐Priority Sustainable Development Goals to Promote Local Sustainability." Earth's Future 11.12 (2023): e2023EF003948.

The Story of Interactions of SDGs

Steve Conrad

Any activity requires the use of energy. Economic activity is not possible without energy, especially fossil fuels. An increase in economic activity necessarily leads to an increase in the use fossil fuels and greenhouse gas emissions. In addition there will be a commensurate increase in waste products, pollution and heat. This is dictated by the laws of physics and unavoidable. A problem arise when the cost of this degeneration caused by continual economic growth surpasses the benefit society derives from it. The ecological economist Professor Herman Daly (2014) explained that when the impact on the ecosystem is correctly measured, global growth has reached a point where the total private and social costs of economic growth outweigh the private and social benefits. In other words, more economic growth is making global society worse off overall - growth has become uneconomic! The model shows that eventually pressures will build up that counteract the perennial belief that all social ills can be solved with economic growth.

The dynamic of UNECONOMIC growth

Hanns-Jürgen Hodann

Marine tourism and snorkeling in the maldives

Anna

5

Introduction:

This simulation model demonstrates the outbreak of Covid-19 in Burnie, Tasmania and how the corresponding government’s responses affect the spreading of Covid-19. Meanwhile, this model also shows how the economy in Burnie is influenced by the impacts of both Covid-19 and government policies.

Variables:

This simulation contains some relevant variables as follow:

Variables in Covid-19 outbreaks: (1) Infection rate, (2) Recovery rate, (3) Death rate, (4) Immunity loss rate

Variables in Government policies: (1) Vaccination rate, (2) Lockdown, (3) Travel ban, (4)Quarantine

Variables in Economy: (1) E-commerce business, (2) Unemployment rate, (3) Economic growth rate.

Assumption:

Government responses would be triggered when reported Covid-19 cases are at least 10.

The government policies reduce the spreading of Covid-19, but they would also limit economic development at the same time due to the negative impact of the policies on the economy is greater than the positive impact.

The increase in reported Covid-19 cases would negatively affect economic growth.

Interesting Insights:

The first finding is that the death number would keep increasing even though the infection rate has decreased, but with stronger government policies (such as implementing a coefficient over 25%), no more death numbers will occur caused by Covid-19.

The second finding is that as government policies limit business activities, with the increasing number of reported Covid-19 cases, economic growth will suffer a severe blow even if e-commerce grows, it can’t make up for this economic loss.

BMA 708 assignment 3 - simulation model of Covid-19 Outbreak in Burnie, Tasmania

Xuanze Liang

Summary of US apa2017 report pdf link

Stress and Health Disparities

Geoff McDonnell

Multiscale view of Combined PH and Economic Views IM 70763 in preparation for integrating with Prevention Investment Framework (private) IM

Multiscale Zoomable Prevention Model View

Geoff McDonnell

Tourism Flow

Robert Luetkemeier

Based on the SIR (Susceptible, Infected, Recovered) model of disease, this is an upgraded model with more specifc vaeriables.

Insights:

When the growth rate and the number of the recovered is much larger than deaths, the economic activity remain steady growing.

Model of COVID-19 outbreak in Burnie Tasmania

Yini Song

3

The recent moratorium on deep-sea drilling will reduce the supply of oil. But the world-wide trend is an ever increasing demand for it. This simple CLD tries to illustrate the dampening effect on demand and on economic activity of diminishing oil supplies and of rising prices: oil prices affect virtually all products and especially agricultural production. As it becomes more and more difficult to extract oil, prices must rise. At the moment the global recession counteracts this effect, but the recession will not last forever. Is it too early to speak of Peak Oil?

Economy and Oil

Hanns-Jürgen Hodann

3

Storytelling of My Investigating Insight Theme

Ana Cristina Beja

Extended from Im-628 Supply and demand by adding control folder.

See also Managing Health Services Use IM-17566

Based on JHPPL 2015 article Note here the framing is an economic exchange rather than a public service (needs-services-resources) or capabilities

Neoliberalism and health policy

Geoff McDonnell

ABOUT THE MODEL

This is a dynamic model that shows the correlation between the health-related policies implemented by the Government in response to COVID-19 outbreak in Burnie, Tasmania, and the policies’ impact on the Economic activity of the area.

ASSUMPTIONS

The increase in the number of COVID-19 cases is directly proportional to the increase in the Government policies in the infected region. The Government policies negatively impact the economy of Burnie, Tasmania.

INTERESTING INSIGHTS

1. When the borders are closed by the government, the economy is severely affected by the decrease of revenue generated by the Civil aviation/Migration rate. As the number of COVID-19 cases increase, the number of people allowed to enter Australian borders will also decrease by the government.

2. The Economic activity sharply increases and stays in uniformity.

3. The death rate drastically decreased as we increased test rate by 90%.

COVID-19 Outbreak in Burnie Tasmania (Rajaa Sajjad, 538837)

Rajaa Sajjad

3