Some of these models are simple, governed by a single mathematical equation, and some are complex in which the relationships between system components are intertwined, resulting in a series of interrelated mathematical equations with hard to predict outcomes. Here comes the need for simulation. Simulating them requires using numerical solutions with iterative nature to be able to display their outputs in a clear visual format that enables understanding of these relationships and their implications. The simulation tool becomes handy when the system is exposed to sudden changes. Some of these modeling and simulation methods come down to the individual level like Agent-Based Modeling (ABM) and go into the analysis of social networks. Some rise to a higher level where they focus on explicitly delineating the feedback dynamics of the phenomena within the system of interest like System Dynamics (SD). Some simulate the sequence of operations in systems like Discrete Event Simulation (DES). Most of these methods, and others, incorporate statistical and stochastic models at different levels and each method has its own power and limitations.

The idea of models and the multiple ways of simulating them emerged historically from engineering applications in design and control of mechanical, electronic, chemical and industrial systems. They were also used to demonstrate phenomena in physics and astrophysics. Modeling and simulation also penetrated the management and economic systems. Later they entered the biological and medical fields, where they are used in studying the human body, assessing therapeutic interventions, and designing healthcare delivery and public health policy.

One of the most important advantages of modeling and simulation is their ability to represent possible scenarios based on certain variables that help scientists, practitioners, consultants, managers, decision-makers, and organizational members and societies to communicate more clearly to reach a more profound understanding of what is happening around them in an effort to improve the quality and efficacy of their decisions that may reflect on their personal and family safety or their organization’s health. Their societies would also be able to maximize their chances of prosperity and reduce their risk of deterioration.

These models remain as attempts to simplify the complex reality to improve our perception despite their inherent limitations. They are based on assumptions which both their validity and accuracy can be debatable by many across the spectrum. Models undoubtedly provide an unprecedented means to communicate and clarify concepts to deal with the present and imagine the potential future and how to prepare for it.

What mankind is currently experiencing in the crisis of the COVID-19 pandemic has led to a plethora of scientific reports, interactive simulations, and explanatory presentations, insightful blogs, and informative podcasts. They are all based on these models that illustrate the path of the pandemic over time and strongly influence the formation of public policies, international coordination, and the research path to its containment and treatment. This clearly confirms the prominent power of modeling and simulation particularly during times of crisis.

The System Dynamics Society has curated an excellent COVID-19 resources page that includes links to an assortment of simulation models, learning material, current articles, and demonstration videos, and analysis blogs. All are invited to submit their relevant work to office@systemdynamics.org to be added to the page and enrich the accessible content to the membership and the world at large.