As Death Toll Mounts, Governments Point Fingers Over Coronavirus - NYTimes 2020

First U.S. Colleges Close Classrooms as Virus Spreads. More Could Follow - NYTimes 2020

Measles spreads to 4 more states as 2019 outbreak grows – NYTimes 2019
 
Ebola spread in the Democratic Republic of Congo, causing the second-largest outbreak in history – BuzzFeed 2018
 
Norovirus cases at Winter Olympics rise to 261; two Swiss skiers infected – LA Times 2018
 
Monkeypox: healthcare worker is third UK case of disease – BBC 2018
 
 
What do all of these headlines have in common? Not only are they are all from recent newspaper stories, each of them refers to similar events from around the globe.

As this activity is being written, our world is experiencing the beginnings of an outbreak COVID-19, a flu-like disease caused by the virus SARS-CoV-2. The more we can understand about how disease outbreaks like COVID-19 are similar, the better we will be at managing and mitigating the impacts of infectious disease in a world of ever increasing population.
 
It is a principle of systems thinking to assume that there is always more to an event than what meets the eye. Like an iceberg, there is often a huge amount of unseen pattern and structure lying beneath the surface of any event.
 
The news stories associated with all of these headlines follow a pattern of cause and effect. In all cases multiple individuals suffer from a disease, and in all cases the disease turns up in groups that share a common living space and undergo continual contact with others of the same group. Each case is referred to as an “outbreak,” barely noticeable at first and suddenly rising to the level of an epidemic in a short period of time.
 
Could it be that these similar events, all showing similar patterns, are linked by common systemic structures that drive their behavior? And if they are, could knowledge of those structures prove useful when designing policies that could help prevent and manage similar outbreaks in the future? These are the kinds of questions that system models can help to answer.

Open the model and get acquainted with its structure and function.
https://sagemodeler.concord.org/#shared=97218

Investigate the model by experimenting. As you do, use what you discover to answer the following questions.

Click once on the SIMULATE arrow at the top of the workspace, then use the model to answer the following questions.

As useful as this model is in helping us understand some of the complexity around epidemics, it is limited in its ability to address many of the more nuanced and detailed aspects of a spreading epidemic. Time is often a critical variable when battling the spread of a disease within a population. By their very nature, epidemics are at first barely noticeable but quickly erupt to become a crisis. When is it best to intervene? Is it possible to respond late and still control an epidemic? Can an epidemic be stopped before a majority of the population has contracted the disease? Questions like these require that we consider more than just the events in an epidemic crisis and look more deeply into their patterns of change in behavior as time goes on. For this we need to move to dynamic modeling.