The diagram is in Dutch.
- "used to reduce yield losses to pests"
- "avoid economic losses to ensure economical survival"
- "increase supply market and reduce market prices"
- "ignorance of sustainable use"
- "integral part of commercially grow high yielding varieties so without use, high yields may not be sustained"
- "damage to agriculture land from the use occurs over long period of time so costs may not look serious short term, but reduces economic welfare in long term"
- "environmental damage: pollutes rivers and groundwater, destroys beneficial predators and interferes with ecosystem overall"
- "health risks underestimated"
- "chemical companies selling it have incentive to push their use by advertising and promotion" (1,9).
The complex model reflects the COVID-19 outbreak in Burnie, Tasmania. The model explains how the COVID-19 outbreak will influence the government policies and economic impacts. The infected population will be based on how many susceptible, infected, and recovered individuals in Burnie. It influences the probability of infected population meeting with susceptible individuals.
The fatality rate will be influenced by the elderly population and pre-existing medical conditions. Even though individuals can recover from COVID-19 disease, some of them will have immunity loss and become part of the susceptible individuals, or they will be diagnosed with long term illnesses (mental and physical). Thus, these variables influence the number of confirmed cases in Burnie and the implementation of government policies.
The government policies depend on the confirmed COVID-19 cases. The government policies include business restrictions, lock down, vaccination and testing rate. These variables have negative impacts on the infection of COVID-19 disease. However, these policies have some negative effects on commercial industry and positive effects on e-commerce and medical industry. These businesses growth rate can influence the economic growth of Burnie with the economic
Most of the variables are adjustable with the slider provided below. They can be adjusted from 0 to 1, which illustrates the percentages associated with the specific variables. They can also be adjusted to three decimal points, i.e., from 0.1 to 0.001.
Assumptions
- The maximum
population of Burnie is 20000.
- The maximum
number of infected individuals is 100.
- Government
policies are triggered when the COVID-19 cases reach 10 or above.
- The government
policies include business restrictions, lock down, vaccination and testing
rates only. Other policies are not being considered under this model.
- The vaccination
policy implemented by the government is compulsory.
- The testing
rate is set by the government. The slider should not be changed unless the testing
rate is adjusted by the government.
- The
fatality rate is influenced by the elderly population and pre-existing medical
conditions only. Other factors are not being considered under this model.
- People who
recovered from COVID-19 disease will definitely suffer form immunity loss or any
other long term illnesses.
- Long term
illnesses include mental illnesses and physical illnesses only. Other illnesses
are not being considered under this model.
- Economic activities
are provided with an assumption value of 1000.
- The higher
the number of COVID-19 cases, the more negative impact they have on the economy
of Burnie.
Interesting Insights
A higher recovery rate can decrease the number of COVID-19 cases as well as the probability of infected population meeting with susceptible persons, but it takes longer for the economy to recover compared to a lower recovery rate. A higher recovery rate can generate a larger number of people diagnosed with long term illnesses.
Testing rate triggers multiple variables, such as government policies, positive cases, susceptible and infected individuals. A lower testing rate can decrease the COVID-19 confirmed cases, but it can increase the number of susceptible people. And a higher testing rate can trigger the implementation of government policies, thus decreasing the infection rate. As the testing rate has a strong correlation with the government policies, it can also influence the economy of Burnie.
The COVID‑19 pandemic represents a complex, ill‑structured problem characterized by uncertainty, rapidly changing conditions, and conflicting stakeholder perspectives. As El‑Taliawi and Hartley emphasize, COVID‑19 is not merely a biomedical crisis but a socio‑technical system failure involving public health, governance, economics, social behavior, and global interdependence. There was no single agreed‑upon definition of “the problem.” For some actors, the problem was viral transmission and mortality; for others, it was economic collapse, civil liberties, misinformation, or institutional trust.
Key features of the unstructured problem include:
High uncertainty about the virus’s behavior, transmission, and long‑term effects.
Multiple stakeholders with competing values and priorities (health vs. economy, freedom vs. safety).
Nonlinear dynamics, where interventions (lockdowns, travel bans, vaccination campaigns) produced unintended consequences.
Fragmented governance, with responses varying across nations, states, and institutions.
Information overload and misinformation, complicating sense‑making and public compliance.
This ambiguity and plurality make COVID‑19 unsuitable for purely “hard” systems approaches and well suited for Soft Systems Methodology (SSM), which focuses on learning, interpretation, and accommodation rather than optimization.
2) Root Definition (What–How–Why)A system to coordinate societal responses to the COVID‑19 pandemic (X), by integrating public health expertise, policy decision‑making, communication, and stakeholder engagement under conditions of uncertainty (Y), in order to reduce harm to human life and societal functioning while maintaining legitimacy, trust, and resilience (Z).
What (X) — Coordinating societal responses to COVID‑19.
How (Y) — Through adaptive governance, expert input, communication, and stakeholder engagement.
Why (Z) — To minimize health, social, and economic harm while sustaining trust and resilience.
This root definition reflects SSM’s emphasis on purposeful human activity systems, not technical control systems.
3) Perspectives (CATWOE Analysis)Customers — General public, vulnerable populations, healthcare workers, businesses, future generations affected by long‑term consequences.
Actors — Governments, public health agencies (e.g., WHO, CDC), healthcare providers, scientists, media organizations, community leaders.
Transformation — A society facing uncontrolled viral spread and systemic disruption is transformed into one that manages risk, adapts behavior, and mitigates impacts.
Worldview (Weltanschauung) — COVID‑19 is a complex, evolving crisis requiring learning, adaptation, and pluralistic decision‑making rather than linear control.
Owners — National governments, international bodies, and political authorities with the power to authorize or terminate interventions.
Environmental Constraints — Scientific uncertainty, political polarization, economic limitations, cultural norms, global interdependence, time pressure.
CATWOE highlights how different worldviews lead to different “valid” problem definitions, reinforcing the need for SSM.
4) Systemigram / Rich Picture (Narrative Description)The rich picture would depict COVID‑19 at the center as a disruptive force interacting with multiple subsystems. Public health institutions generate evolving scientific knowledge, feeding into government decision‑making. Governments issue policies (lockdowns, mandates, economic relief), which influence public behavior. Public response is shaped by trust, media narratives, misinformation, and social norms. Economic systems react to restrictions, feeding back political pressure on leaders. Healthcare systems experience strain, influencing policy urgency and public fear.
Feedback loops dominate the picture:
Policy decisions affect public behavior, which affects transmission rates.
Media narratives influence trust, which affects compliance.
Economic impacts influence political decisions, sometimes undermining health goals.
The systemigram emphasizes learning loops, delays, conflicts, and unintended consequences rather than linear cause‑effect chains.
If you want, I can translate this directly into a Word‑ready format, tighten it to a specific page limit, or sketch a labeled rich‑picture layout you can redraw by hand or digitally for submission.
Based on El‑Taliawi and Hartley
IntroductionThe COVID‑19 pandemic represents one of the most complex global crises of the modern era. Traditional “hard” systems approaches, which assume clearly defined problems and measurable objectives, proved insufficient for addressing the pandemic’s intertwined health, social, political, and economic dimensions. El‑Taliawi and Hartley argue that COVID‑19 is best understood as a messy, ill‑structured problem situation, making it well suited for analysis using Soft Systems Methodology (SSM).
SSM does not attempt to “solve” the problem in a technical sense. Instead, it provides a structured learning process to explore multiple perspectives, clarify assumptions, and identify purposeful human activity systems that can improve the situation. This document follows the core SSM steps required in the assignment: (1) describing the unstructured problem, (2) developing a root definition, (3) identifying perspectives using CATWOE, and (4) developing a systemigram / rich picture narrative.
1. Description of the Problem Situation (Unstructured)The COVID‑19 pandemic emerged rapidly and evolved unpredictably, creating a situation characterized by ambiguity, disagreement, and uncertainty. At the outset, there was no shared understanding of the nature or scale of the threat. Scientific knowledge about transmission, severity, and long‑term effects developed incrementally, often changing public guidance and policy decisions. This uncertainty undermined confidence and complicated coordinated action.
The problem situation extended far beyond public health. Governments faced competing pressures to protect lives, preserve economic stability, and maintain civil liberties. Healthcare systems experienced surges in demand, shortages of personnel and equipment, and moral distress among frontline workers. Businesses and workers faced closures, unemployment, and financial insecurity. Social isolation measures disrupted education, mental health, and community cohesion.
Multiple stakeholders framed the “problem” differently. For public health officials, the primary concern was reducing transmission and mortality. For political leaders, the challenge included maintaining legitimacy and public compliance. For citizens, the problem often centered on personal risk, economic survival, and trust in institutions. Media organizations and social platforms amplified both accurate information and misinformation, shaping public perception and behavior.
Clone of Wagdy Samir Macroeconomics work in progress IM-901 Additions and deletions based on Robert Skidelsky's description of Keynes general THeory from his Biography Vol2 p 549 -571
