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The Math Behind Social Distancing

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The math behind social distancing

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The Math Behind Social Distancing

As we wait for scientists and healthcare professionals to develop a vaccine for COVID-19, there is another, more readily available tool at our disposal.

Social distancing, defined as measures taken to reduce physical contact, is the first line of defense for containing an infectious disease like COVID-19. That’s because these infections spread when people cough, sneeze, or touch surfaces on which the virus resides.

To help us grasp the impact these measures can actually have, today’s infographic illustrates how a reduction in social exposure can theoretically contain the spread of infection.

Theoretical Potential

The calculations used to create today’s infographic come from Signer Laboratory, a stem cell research lab located in the Moores Cancer Center at the University of California San Diego.

Using a summation formula makes it possible to estimate the number of new infections over a 30 day period, across three scenarios.

Scenario5 Day Period30 Day Period
No social distancing practiced1 person infects 2.5* others406 people infected as a result
50% reduction in social exposure1 person infects 1.25* others15 people infected as a result
75% reduction in social exposure1 person infects 0.625* others2.5 people infected as a result

*For estimations only. It is not possible to infect only a fraction of another person.

To arrive at the figures reported above, Robert A.J. Signer, Ph.D., and his team made a number of key assumptions.

First, they estimated the basic reproduction number (R0) of COVID-19 to be 2.5, a figure supported by recent research. This means that, on average, an infected individual will spread the disease to 2.5 other people.

Next, they assumed that an infected individual will unknowingly spread COVID-19 over the median five day incubation period. After this period, the individual will begin to develop symptoms, immediately self quarantine, and no longer pose a threat.

Finally, they assumed a direct linear correlation between social interactions and R0. This means that when an infected person reduces their physical contact with others by 50%, they also spread the disease by an amount 50% less.

Timing is Everything

While the figures above are the results of mathematical estimations, researchers have actually studied social distancing from a variety of angles.

One study used simulations to determine the magnitude and timing of social distancing measures required to prevent a pandemic. The distancing measures simulated were:

MeasureDetails
School closureTeachers and students spent weekday daytime cycles at home, rather than at school.
Increased case isolationUpon becoming symptomatic, adults (90%) and children (100%) would self quarantine for the duration of the infection.
Workplace non-attendanceEach day, a person had a 50% chance of staying home instead of attending their workplace.
Community contact reductionIndividuals reduced their physical contact with community members by half, each day.
Combination of all fourAll four measures combined. 

The results, for a community of 30,000 people and an epidemic with R=2.5, are charted below. We can define the final illness attack rate as the share of people from an at risk population who ultimately catch the disease.

power of early social distancing

Results showed that when no action was taken, 65% of the population contracted the disease. However, if a combination of all four distancing measures were implemented instead, the attack rates were:

  • 45% (distancing begins after a 4 week delay)
  • 21% (distancing begins after a 3 week delay)
  • 7% (distancing begins after a 2 week delay)

What’s clear is that social distancing was significantly more effective when implemented with minimal delay—the final illness attack rate rose quickest beyond the third week. These findings draw a parallel to the visualizations in today’s infographic, which showed us just how quickly a disease can spread.

Social distancing interventions are important as they represent the only … measure guaranteed to be available against a novel strain of influenza in the early phases of a pandemic.

Kelso, J.K., Milne, G.J. & Kelly, H., BMC Public Health 9, 117 (2009)

We arrive at a similar conclusion when it comes to the types of distancing measures implemented. In the simulations, none of the four measures taken on their own were able to have a similar effect as when they were combined.

We All Have a Part to Play

With the global number of COVID-19 cases still rising, many governments have issued quarantine orders and travel bans.

The math supports these decisions—reducing our physical contact with others, even when we aren’t experiencing any symptoms, is crucial. Studies like the one summarized above also prove that taking action sooner, rather than later, can go a long way in reducing the spread of infection.

The key takeaway from all of this? Social distancing is a powerful disease control tool, but only if we all participate.

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Markets

Charted: The Gen Z Unemployment Rate, Compared to Older Generations

COVID-19 has impacted everyone, but one generation is taking it harder than the others. This graphic reveals the Gen Z unemployment rate.

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gen z unemployment

Putting the Gen Z Unemployment Rate in Perspective

There are more than 2 billion people in the Generation Z age range globally. These individuals, born between 1997 and 2009, represent about 30% of the total global population—and it’s predicted that by 2025, Gen Z will make up about 27% of the workforce.

Due to the global pandemic, unemployment has been on the rise across the board—but Gen Z has been hit the hardest. This chart, using data from the OECD, displays the difference between the unemployment rate for Gen Zers and the rate for older generations.

Note: The OECD defines the ‘unemployed’ as people of legal working age who don’t have work, are available to work, and have taken steps to find a job. The final figure is the number of unemployed people as a share of the total labor force.

The Generation Gap: Gen Z Unemployment

Compared to their older working-age counterparts, Baby Boomers, Gen X, and Millennials (Gen Y)—the most recent 2020 data shows that Gen Z has an unemployment rate of nearly 2x more in almost every OECD country.

CountryUnemployment Rate (Gen Z)Unemployment Rate (Millennial, Gen X, Boomer)
🇦🇺 Australia14.3%5.0%
🇦🇹 Austria10.5%4.7%
🇧🇪 Belgium15.3%4.8%
🇨🇦 Canada20.0%7.9%
🇨🇱 Chile24.8%9.6%
🇨🇴 Colombia27.5%13.9%
🇨🇿 Czech Republic8.0%2.3%
🇩🇰 Denmark11.5%4.7%
🇪🇪 Estonia17.7%5.9%
🇫🇮 Finland21.0%6.0%
🇫🇷 France20.1%6.8%
🇩🇪 Germany6.2%4.0%
🇭🇺 Hungary12.4%3.5%
🇮🇸 Iceland11.9%5.5%
🇮🇪 Ireland15.2%4.4%
🇮🇱 Israel7.9%3.7%
🇮🇹 Italy29.1%-
🇯🇵 Japan4.5%2.6%
🇰🇷 South Korea10.5%3.6%
🇱🇻 Latvia14.8%7.7%
🇱🇹 Lithuania19.5%7.7%
🇱🇺 Luxembourg22.4%5.6%
🇲🇽 Mexico8.0%3.8%
🇳🇱 Netherlands9.1%2.8%
🇳🇿 New Zealand12.4%3.3%
🇵🇱 Poland10.9%2.6%
🇵🇹 Portugal22.9%5.9%
🇸🇰 Slovakia19.3%6.0%
🇸🇮 Slovenia14.2%4.3%
🇪🇸 Spain38.3%14.0%
🇸🇪 Sweden23.8%6.4%
🇨🇭 Switzerland8.6%4.3%
🇬🇧 United Kingdom13.5%3.2%
🇺🇸 United States15.1%7.1%

Note: For the purposes of this article, we are only considering the Gen Zers of legal working age—those born 1997-2006. The rest—Baby Boomers, Gen X, and Millennials—are those born between 1946–1996.

The timing for the youngest working generation could not be worse. Gen Z is just beginning to graduate college and high school, and are beginning to search for work and careers.

Gen Z is also an age group that is overrepresented in service industries like restaurants and travel–industries that were equally hard hit by the pandemic. In the U.S., for example, around 25% of young people work in the hospitality and leisure sectors. Between February and May 2020 alone, employment in these sectors decreased by 41%.

Countries like Spain are facing some of the biggest headwinds among OECD countries. The country already has a high unemployment rate for those aged 25-74, at 14%. But the unemployment rate for Gen Z is more than double that, at over 38%.

Implications For the Future

While it may be true throughout history that this age group is often less employed than older cohorts, the share of labor held by those aged 15-24 dropped significantly in 2020.

labor share gen z

Note: This chart represents the data from G7 countries.

In terms of their future employment prospects, some economists are anticipating what they call ‘scarring’. Due to longer periods of unemployment, Gen Z will miss out on formative years gaining experience and training. This may impact them later in life, as their ability to climb the career ladder will be affected.

Starting out slower can also hit earnings. One study found that long periods of youth unemployment can reduce lifetime income by 2%. Finally, it is also postulated that with the current economic situation, Gen Zers may accept lower paying jobs setting them on a track of comparatively lower earnings over their lifetime.

Overall, there are many future implications associated with the current unemployment rate for Gen Zers. Often getting your foot in the door after college or high school is one of the hardest steps in starting a career. Once you’re in, you gain knowledge, skills, and the oh-so-coveted experience needed to get ahead.

The Kids are Alright?

One positive for Gen Z is that they have been found to be more risk averse and financially conscious than other generations, and were so even prior to COVID-19. Many of them were children during the 2008 Recession and became very cautious as a result.

They are also the first digital generation— the first to grow up without any memory of a time before the internet. Additionally, they have been called the first global generation. This could mean that they pioneer location-independent careers, create innovative revenue streams, and find new ways to define work.

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Healthcare

Explained: The 3 Major COVID-19 Variants

New variants of COVID-19 are spreading fast around the world. Here’s a look at the 3 major ones and how they differ from one another.

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3 Major COVID variants

Explained: The 3 Major COVID-19 Variants

As billions of people gear up for widespread vaccination against COVID-19, another issue has reared its head. Three major COVID-19 variants have emerged across the globe—and preliminary research suggests these variants may be cause for concern.

But what makes them different from the original strain?

The following visualizations answer some key questions, including when these variants were first discovered, how far they’ve spread worldwide, and most importantly, their potential impact on the population.

Some Context: What is a Variant?

Before diving in, it’s important to understand why viruses mutate in the first place.

To infect someone, a virus takes over a host cell and uses it to replicate itself. But nature isn’t perfect, and sometimes, mistakes are made during the replication process—those mistakes are called mutations.

A virus with one or more mutations is referred to as a variant. Most of the time, variants do not affect a virus’s physical structure, and in those instances, they eventually disappear. However, there are certain cases when a mutation impacts part of a virus’s genetic makeup that does change its behavior.

According to the U.S. Centers for Disease Control (CDC) a change in behavior can alter:

  • Rate of transmission
  • Deadliness
  • Ability to potentially infect someone with natural or vaccine-induced immunity

Preliminary research has detected some of these changes in the three major COVID-19 variants—B.1.1.7, B.1.351, and P.1.

The 3 Major COVID-19 Variants

The three major variants emerged at different times, and in different parts of the world. Here’s an overview of each variant, when they were discovered, and how far they’ve spread so far.

B.1.1.7

The B.1.1.7 variant was detected in the UK in the fall of 2020. By December 2020, it had spread across the globe, with cases emerging across Europe, North America, and Asia.

B117 COVID Variant

Currently, the variant has been reported in roughly 94 countries.

Early research suggests it’s 50% more transmissible than other variants, and potentially 35% more deadly than the standard virus. Luckily, studies suggest that some of the existing vaccines work well against it.

B.1.351

In October 2020, the second major variant was discovered—B.1.351. It was first identified in South Africa, but by end of the year, it had spread to the UK, Switzerland, Australia, and Japan.

B1351 COVID variant

There are approximately 48 countries with reported cases, and research suggests several of the existing COVID-19 vaccines may not be as effective against this variant.

P.1

The P.1 variant was the last to arrive on the scene.

It was first discovered in January 2021, when Japan reported four cases of the variant, which was found in travelers who had arrived from Brazil.

P1 COVID variant

Approximately 25 countries have reported cases of the P.1 variant, and early research suggests this variant is not only more contagious, but could also have the ability to infect people with natural immunity who had already recovered from the original strain.

Still Early Days

While there have been preliminary studies showing a dip in vaccine effectiveness, some experts emphasize that it’s too early to tell for certain. More data is needed to gain a deeper and more accurate understanding.

In the meantime, experts are emphasizing the importance of following our current public health strategies, which include physical distancing, vaccination, washing your hands, and using masks.

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