Yes, Keep Wearing Masks. Here鈥檚 Why

This model shows just how effective they are.

3 MIN READ

Jul 2, 2020

With the advent of an infectious disease outbreak, epidemiologists and public health officials quickly try to forecast deaths and infections using complex computer models. But with a brand-new virus such as the one that causes COVID-19, these estimates are complicated by a on symptoms, contagion, and those who are most at risk.

My team at the Goldenson Center for Actuarial Research has developed a free, user-friendly computer model with a different goal. It demonstrates how infections and deaths progress daily over a three-month period depending on how people behave in the outbreak. This model allows the public to input data that demonstrate how changes in safety measures in their communities, including wearing face covering and social distancing, can significantly impact the spread of this virus and mortality rates.

Our uses a hypothetical 1,000-person population and calculates outcomes using three types of information: the initial number of infections, social distancing, and personal protection measures that include wearing masks, frequent hand-washing, and staying quarantined if one is exhibiting COVID-19 symptoms. Our model then uses this initial information to project daily the cumulative infections and deaths over a three-month period. It鈥檚 not based on actual disease data and is designed to demonstrate the effects of safety measures, rather than make specific predictions.

This simple actuarial model uses general guidelines, rather than data and assumptions about COVID-19 specifically, to simulate the effect of safety protocols. Here, a hypothetical group of 100 infected people out of a population of 1,000, with 10% observing good safety protocols, leads to hundreds of infections and deaths after three months.

This simulation shows the effect on the same hypothetical group of 100 infected people out of a group of 1,000 where 80% of people wear masks and practice social distancing, which slows the infection rate to almost zero after two months. ,

Why it matters

By inputting different assumptions, people can see how their community鈥檚 personal actions can change the course of this pandemic鈥攁nd how poor protocols can trigger of the virus.

For example, let鈥檚 assume that 100 people are infected out of a population of 1,000, with 1 in 10 wearing masks, keeping appropriate distance, and quarantining if necessary. The model shows that 30 days later, the virus would have killed 156 people. After three months, the death toll reaches 460鈥攚ith 510 now infected.

However, our model shows that if half the population practices safe protocols, infections after 90 days drop to 293 and deaths drop even more dramatically, to 149鈥攁bout one-third of the lives lost under looser measures.

The main takeaway is that safety measures that are within our control have significant impact鈥攁nd ignoring those protocols can have dire consequences.

If a state opens up and maintains safety measures for at least three months, the virus will be contained and possibly eliminated. On the other hand, if a state opens up too soon and its residents ignore safety protocols, COVID-19 deaths could increase exponentially within months. It鈥檚 important for the public to realize that spread of the virus is affected only by personal behavior.

What鈥檚 next?

Our model shows that there must be continued emphasis on maintaining necessary safety measures as we relax shelter-in-place rules and get people back to work. Practicing common-sense social distancing, wearing masks in public, and quarantining when necessary is a small inconvenience for a limited amount of time鈥攁nd will contain the devastation of this virus and ensure that our economy is restored.

This article was originally published by . It has been published here with permission.

Jeyaraj Vadiveloo is a professor and director of the Goldenson Center for Actuarial Research at the University of Connecticut. With over 30 years of experience in industry and academia, Dr. Vadiveloo now focuses on applied actuarial research projects from industry using teams of highly talented graduate students to come up with practical, implementable solutions.