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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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Economy

When Will Your Country Recover from the Pandemic?

The path to COVID-19 recovery varies worldwide—some countries have already recovered, while others will not be back to normal for years.

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covid-19 recovery

What started as a novel virus in China quickly became a sweeping disease that shut down the world and put a 1.5 year halt on the global economy.

But while some countries’ economies are already back to normal, others are lagging far behind.

COVID-19 Recovery Timelines, by OECD Country

This chart using data from the OECD anticipates when countries will economically recover from the global pandemic, based on getting back to pre-pandemic levels of GDP per capita.

Note: The categorization of ‘advanced’ or ‘emerging’ economy was determined by OECD standards.

covid-19 recovery time by country

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The Leaders of the Pack

At the top, China and the U.S. are recovering at breakneck speed. In fact, recovering is the wrong word for China, as they reached pre-pandemic GDP per capita levels just after Q2’2020.

On the other end, some countries are looking at years—not months—when it comes to their recovery date. Saudi Arabia isn’t expected to recover until after Q1’2024, and Argentina is estimated to have an even slower recovery, occurring only after Q2’2026.

CountryRecoveryEconomy
🇧🇪 BelgiumAfter Q4 2022Advanced
🇸🇪 SwedenAfter Q4 2021Advanced
🇸🇰 SlovakiaAfter Q4 2021Advanced
🇳🇿 New ZealandAfter Q4 2021Advanced
🇩🇪 GermanyAfter Q4 2021Advanced
🇪🇪 EstoniaAfter Q4 2021Advanced
🇩🇰 DenmarkAfter Q4 2021Advanced
🇮🇸 IcelandAfter Q3 2023Advanced
🇸🇮 SloveniaAfter Q3 2022Advanced
🇵🇹 PortugalAfter Q3 2022Advanced
🇫🇷 FranceAfter Q3 2022Advanced
🇦🇹 AustriaAfter Q3 2022Advanced
🇵🇱 PolandAfter Q3 2021Advanced
🇳🇴 NorwayAfter Q3 2021Advanced
🇱🇺 LuxembourgAfter Q3 2021Advanced
🇱🇻 LatviaAfter Q3 2021Advanced
🇯🇵 JapanAfter Q3 2021Advanced
🇫🇮 FinlandAfter Q3 2021Advanced
🇪🇸 SpainAfter Q2 2023Advanced
🇬🇧 United KingdomAfter Q2 2022Advanced
🇳🇱 NetherlandsAfter Q2 2022Advanced
🇮🇹 ItalyAfter Q2 2022Advanced
🇬🇷 GreeceAfter Q2 2022Advanced
🇨🇿 Czech RepublicAfter Q2 2022Advanced
🇨🇦 CanadaAfter Q2 2022Advanced
🇺🇸 United StatesAfter Q2 2021Advanced
🇰🇷 South KoreaAfter Q2 2021Advanced
🇮🇪 IrelandAfter Q2 2021Advanced
🇨🇭 SwitzerlandAfter Q1 2022Advanced
🇮🇱 IsraelAfter Q1 2022Advanced
🇭🇺 HungaryAfter Q1 2022Advanced
🇦🇺 AustraliaAfter Q1 2022Advanced
🇱🇹 LithuaniaAfter Q1 2021Advanced
🇿🇦 South AfricaAfter Q4 2022Emerging
🇮🇩 IndonesiaAfter Q4 2021Emerging
🇮🇳 IndiaAfter Q4 2021Emerging
🇲🇽 MexicoAfter Q3 2023Emerging
🇨🇴 ColombiaAfter Q3 2022Emerging
🇧🇷 BrazilAfter Q3 2022Emerging
🇨🇱 ChileAfter Q3 2021Emerging
🇹🇷 TurkeyAfter Q3 2020Emerging
🇦🇷 ArgentinaAfter Q2 2026Emerging
🇨🇷 Costa RicaAfter Q2 2023Emerging
🇷🇺 RussiaAfter Q2 2021Emerging
🇨🇳 ChinaAfter Q2 2020Emerging
🇸🇦 Saudi ArabiaAfter Q1 2024Emerging

Most countries will hit pre-pandemic levels of GDP per capita by the end of 2022. The slowest recovering advanced economies—Iceland and Spain—aren’t expected to bounce back until 2023.

Four emerging economies are speeding ahead, and are predicted to get back on their feet by the end of this year or slightly later (if they haven’t already):

  • 🇷🇺 Russia: after Q2’2021
  • 🇨🇱 Chile: after Q3’2021
  • 🇮🇳 India: after Q4’2021
  • 🇮🇩 Indonesia: after Q4’2021

However, no recovery is guaranteed, and many countries will continue face setbacks as waves of COVID-19 variants hit—India, for example, was battling its biggest wave as recently as May 2021.

Trailing Behind

Why are some countries recovering faster than others? One factor seems to be vaccination rates.

CountryDoses Administered per 100 PeopleTotal Doses AdministeredPercent of Population Fully Vaccinated
World473,573,004,544
🇦🇪 U.A.E.16616,194,52669%
🇲🇹 Malta143718,41871%
🇧🇭 Bahrain1362,224,91663%
🇮🇸 Iceland129466,43470%
🇺🇾 Uruguay1294,458,39458%
🇨🇱 Chile12824,248,54560%
🇦🇼 Aruba125133,42159%
🇶🇦 Qatar1233,474,94456%
🇬🇧 United Kingdom12281,438,89253%
Mongolia1213,912,99656%
Israel12110,959,63358%
Canada11844,293,65948%
Singapore1136,440,73542%
Belgium11112,700,51346%
Curaçao108170,85751%
Denmark1086,266,89243%
Maldives106561,74846%
Netherlands10518,273,23843%
Spain10549,585,19749%
Hungary10410,155,46654%
Portugal10310,579,25944%
Luxembourg102633,97441%
Germany10284,989,85045%
China1021,426,347,000
United States101336,054,95348%
Ireland1014,995,71944%
Austria1008,866,47444%
Italy9959,966,90841%
Switzerland958,133,48642%
France9362,321,35540%
Sweden939,536,16436%
Finland904,951,92526%
Norway894,785,93731%
Greece899,560,59242%
Lithuania882,459,60542%
Czech Republic889,346,39738%
Poland8532,413,19942%
Dominican Rep.849,066,15134%
Estonia791,049,41634%
Serbia785,415,43438%
Slovenia781,626,07236%
Cyprus76916,81935%
Turkey7461,747,39923%
Slovakia734,003,63933%
Mauritius71901,53024%
Croatia712,870,86632%
Macau69434,72627%
Cuba697,767,60117%
Latvia661,264,43333%
Bhutan64487,0600.02%
Saudi Arabia6321,556,3149.2%
Hong Kong624,638,90826%
Barbados59168,95525%
Argentina5826,134,81511%
Brazil57120,726,75216%
Kuwait562,375,45522%
Morocco5620,584,81226%
Cambodia56924292524%
El Salvador533,422,21420%
Japan5366,714,52820%
Costa Rica522,606,79116%
French Polynesia51141,52324%
Montenegro49304,65523%
Fiji47419,9988%
Romania479,092,14124%
Guyana46363,44216%
Colombia4522,624,56819%
Jordan454,498,74818%
Azerbaijan424,242,72717%
Panama421,781,54215%
Mexico4152,704,96017%
Malaysia4113,107,68113%
South Korea4121,157,61212%
New Caledonia40115,21819%
Ecuador406,890,87610%
Kazakhstan397,303,18014%
Suriname38222,3778%
Australia389,631,80710%
Belize38147,08010%
Albania371,052,10816%
Russia3550,383,63814%
Oman351,728,6186%
North Macedonia34713,11413%
Samoa3262,1614.7%
Moldova31834,52713%
Grenada3135,07213%
Peru319,954,42912%
Saint Lucia3054,36113%
Sri Lanka296,431,1007.3%
India29391,340,4916%
New Zealand291,404,34311%
Brunei28121,2414.3%
Tonga2728,667
Bulgaria271,896,57412%
Bolivia273,117,5217%
Trinidad and Tobago27375,92411%
Bahamas2597,99210%
Lebanon251,693,1649%
Laos241,708,9819%
Saint Vincent and the Grenadines2325,509
Cape Verde23124,9583%
Timor-Leste22281,2833%
Indonesia2155,819,7816%
Equatorial Guinea21279,1129%
West Bank & Gaza20958,5199%
Thailand1913,533,7175%
Taiwan194,603,6391%
Tunisia192,206,9806%
São Tomé and Príncipe1837,7165%
Bosnia and Herzegovina14470,2185%
Venezuela144,000,0004%
Nepal133,730,3444%
Philippines1314,074,5144%
Botswana12284,6765%
Honduras121,172,8301%
Paraguay12826,6422%
Belarus
Zimbabwe111,575,5394%
Comoros1190,880
Uzbekistan113,541,4424%
Pakistan102,166,06502%
Jamaica9.8290,3824%
Armenia8.8260,8132%
Ukraine8.83,899,8903%
Iran7.96,530,1243%
Georgia7.8289,3993%
South Africa7.74,535,2223%
Guatemala6.91,146,4771%
Namibia6.7166,6161%
Myanmar6.5*3,500,000
Libya6.3425,119
Bangladesh6.210,108,2243%
Guinea6770,6882%
Algeria
Eswatini5.260,0692%
Rwanda5.1646,9092%
Senegal5.1823,6102%
Angola4.91,558,2012%
Egypt4.84,851,3491%
Vanuatu4.714,026
Vietnam4.34,185,6230.3%
Togo
Tajikistan4.3397,6940.2%
Ghana4.21,265,3061%
Mauritania4182,6420.3%
Solomon Islands3.825,6281%
Ivory Coast3.3861,278
Gabon3.372,3511%
Republic of the Congo3163,742
Kenya2.91,550,3891%
Sierra Leone2.9225,3800.2%
Iraq2.81,087,8661%
Djibouti2.826,796
Afghanistan2.71,024,1681%
Kyrgyzstan2.7173,7001.%
Lesotho2.756,3221%
Nicaragua
Uganda2.41,079,943
Malawi2.3428,4070.2%
Nigeria23,938,9451%
Liberia1.995,4230.2%
Ethiopia1.92,090,997
Gambia1.943,5571%
Niger1.8423,3350.3%
Mozambique1.7508,1841%
Central African Republic1.778,685
Somalia1.6249,7901%
Sudan1.6677,9570.3%
Zambia1.4243,8180.3%
Guinea-Bissau1.325,0120.1%
Yemen1297,405<0.1%
Mali1196,8620.3%
Syria0.8131,2210.1%
Madagascar0.7197,001
Turkmenistan
Cameroon0.6163,9210.1%
Papua New Guinea0.651,170<0.1%
South Sudan0.555,915<0.1%
Benin0.452,5630.1%
Burkina Faso0.233,960<0.1%
Chad0.224,459<0.1%
Congo0.173,764<0.1%

As of July 16th, 2021.

The higher the rate of vaccination, the harder it is for COVID-19 to spread. This gives countries a chance to loosen restrictions, let people get back to work and regular life, and fuel the economy. Additionally, the quicker vaccines are rolled out, the less time there is for variants to mutate.

Another factor is the overall strength of a country’s healthcare infrastructure. More advanced economies often have more ICU capacity, more efficient dissemination of public health information, and, simply, more hospital staff. These traits help better handle the pandemic, with reduced cases, less restrictions, and a speedy recovery.

Finally, the level of government support and fiscal stimulus injected into different economies has determined how swiftly they’ve recovered. Similar to the disparity in vaccine rollouts, there was a significant fiscal stimulus gap, especially during the heat of the pandemic.

Recovering to Normal?

Many experts and government leaders are now advocating for funneling more money into healthcare infrastructure and disease research preventatively. The increased funding now would help stop worldwide shut downs and needless loss of life in future.

Time will tell when we return to “normal” everywhere, however, normal will likely never be the same. Many impacts of the global pandemic will stay with us over the long term.

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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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