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How Data Can Help Identify Ways to Flatten the Curve of the COVID-19 Outbreak

The coronavirus (COVID-19) pandemic continues to threaten the welfare of individuals, markets, and governmental systems around the world. In conversations relating to this virus, one of the most pressing tactics experts encourage is that of flattening the curve. By taking measures to do so, it is believed that the spread of the virus will be […]

The coronavirus (COVID-19) pandemic continues to threaten the welfare of individuals, markets, and governmental systems around the world. In conversations relating to this virus, one of the most pressing tactics experts encourage is that of flattening the curve. By taking measures to do so, it is believed that the spread of the virus will be better contained, and this belief is supported by existing data and expert opinions.

What Does it Mean to Flatten the Curve?

Put simply, flattening the curve refers to the process of limiting the number of developing cases of a given disease in order to lessen the burden on existing systems, most specifically healthcare. In the case of COVID-19, flattening the curve can be achieved most effectively through social distancing on an individual level and government-endorsed closings and cancellations of gathering spaces and large events. 

Simulations of the Spread

In a recent article, the Washington Post’s Harry Stevens provides a few randomized simulations that reflect the various outcomes pertaining to the coronavirus outbreak. These simulations demonstrate how the spread of the virus could be affected through different practices such as mandated quarantines and social distancing. Presented in the article are four simulations, the results of which are different for each independent viewer of the piece, that represent the following responses to this pandemic: forced quarantine, moderate social distancing, extreme social distancing, and a “free-for-all.”

The function of these simulations is not to provide a solution to the rapid spread of COVID-19 but rather to highlight why flattening the curve should be a priority as well as the best ways to accomplish that goal. While the article’s author acknowledges that the simulations oversimplify the spread of the virus, they are still effective in illustrating how extensive social distancing can slow the contagion, providing a visual collection of data to support the notion.

Mathematical Explanations

Presuming that an infected person will easily infect multiple individuals (if there are not cautionary or isolatory measures in place), each generation of the virus grows at an exponential rate, resulting in rapid growth that cannot be managed by the current healthcare systems anywhere in the world. As of March 16, mathematicians determined that the number of COVID-19 cases worldwide was doubling every six days.

Eventually, the number will begin to decline simply because there will be fewer susceptible individuals than there are infected individuals, resulting in a gradual decrease of cases. However, until that point, the risk of the virus spreading and exceeding the capacity of healthcare systems continues to be high. Because of the existing data that has been gathered in regards to the pandemic, researchers and mathematicians urge individuals to practice social distancing in order to flatter the curve, limit the spread of the disease, and reduce the strain on healthcare systems.

Making Decisions Without Data

At present, there are too many unknowns surrounding the spread of COVID-19. The number of infected individuals and how the virus spreads is unclear, and the data to support decisions being made by governments around the world are not supported by sufficient data. What this means is that there is considerable uncertainty regarding the virus as well as the measures being taken to prevent its spread; determining when the curve of infection will peak and what tactics will help flatter the curve becomes challenging without accurate data to determine a course of action. 

Originally published on RobinBlackburn.com.

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