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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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Healthcare

Visualizing Global Attitudes Towards the COVID-19 Vaccines

This graphic visualizes global attitudes to vaccines categorized into five segments including anti-vaxxers and COVID cautious.

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Visualizing Global Attitudes Towards COVID-19 Vaccines

View the high-resolution of the infographic by clicking here.

To vaccinate, or not to vaccinate? That is the question.

In order to achieve herd immunity against COVID-19, some experts believe that between 70% to 80% of a population must be vaccinated.

But attitudes towards these vaccines are undoubtedly mixed. In fact, it’s estimated that one-third of people globally have some major concerns.

Using survey data from eight different countries, Global Web Index created five archetypes to help illustrate how typical attitudes towards vaccines differ depending on a range of factors, such as age, income, lifestyle, and values.

SegmentBreakdownAge SkewGender SkewIncomeVaccine Concerns
Vaccine Supporter66%18-34NoneHigh incomePotential side-effects, availability, and logistics of vaccine distribution.
Vaccines Hesitant12%38-56FemaleLow/Middle incomePotential side-effects specifically due to no long-term testing, cost of vaccine, and more transparency around science required.
Vaccine Obligated11%16-24MaleLow incomePotential side-effects, not sure COVID-19 vaccine is necessary to combat the virus.
Vaccine Skeptical11%45-64FemaleLow incomePotential side-effects, don’t believe vaccines can curtail the pandemic.
Anti-vaxxer1.4% (13% of the Vaccine Skeptical segment)16-24, 55-64MaleLow incomePotential side-effects, don’t believe vaccines in general are safe.

Countries surveyed: United States, Germany, United Kingdom, Brazil, China, India, Japan, and Italy.

Which segment are you most likely to fall under, according to these segments?

Vaccine Supporters

[People who say they will get the COVID-19 vaccine.]

Out of all participants surveyed, 66% of them support the idea of getting a COVID-19 vaccine. Within this group, there is a skew towards younger people (aged 18-34) who are likely working professionals earning a high income and living in a city.

Despite their optimism towards COVID-19 vaccines, however, one-third of vaccine supporters say they will wait to get one, due to lingering concerns regarding issues with vaccine distribution and any potential side-effects.

Interestingly, this procrastination mindset has been seen before during the H1N1 (swine flu) pandemic when both members of the general public and healthcare workers showed low levels of vaccine acceptance due to safety concerns.

Vaccine Hesitant

[People who are not sure if they will get the COVID-19 vaccine.]

The vaccine hesitant group, which is more common among cautious suburban parents, makes up 12% of the total study. They are more likely to be female, and feel anxious about the length of time spent testing vaccines and therefore require more transparency around the science.

With that being said, this group could be easily swayed, as they are more receptive to word-of-mouth and messaging boards to get advice from their peers over any other medium.

Vaccine Obligated

[People who will only get the vaccine if it’s necessary for travel, school, work etc.]

The vaccine obligated group makes up 11% of the total, and has a skew towards males aged between 16 and 24 years old.

While this group is also concerned with potential side-effects, their responses suggesting that a vaccine may not be necessary to combat COVID-19 was above average compared to other segments in the study. They also index above average when it comes to viewing themselves as traditionalists.

Vaccine Skeptical

[People who won’t get the COVID-19 vaccine.]

The vaccine skeptical group makes up another 11% of the total. However, this group is mostly female, who are aged between 45-64 and earn a lower-than-average income. They are less likely to have a college degree, and are more likely to live in a rural area.

Along with the worry of potential side-effects, this group is generally more pessimistic about containing COVID-19 at all. Therefore a small percentage do not believe a vaccine will help tackle the global health crisis.

With notably low trust levels, this group is one of the hardest to reach and potentially persuade. What makes them unique however, is their lack of faith in the scientific process.

Anti-Vaxxers

[People who will not get the vaccine, because they are against vaccines in general.]

It is important to note that those who choose not to get a COVID-19 vaccine should not be confused with anti-vaxxers.

Anti-vaxxers are a sub-segment of the vaccine skeptical group that makes up 1.4% of the total population. The difference is, anti-vaxxers do not believe in getting any vaccine due to safety concerns, not just not a vaccine for COVID-19.

According to the study, anti-vaxxers tend to fall into one of two age brackets, between 16-24 years or 55-64 years old, and are typically males with lower incomes.

Another Tool in the Arsenal Against COVID-19

The study demonstrates that broad segments of society—regardless of their demographic or views—are at least somewhat concerned about COVID-19 vaccines becoming widely available.

While scientists are not quite sure if the current vaccines on the market can stop infection or transmission of the virus, they are an important part of our global defenses against COVID-19, along with other safety restrictions like wearing masks and keeping a distance.

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Money

Mapping Global Income Support During COVID-19

The need for income support during COVID-19 has been vast. This map visualizes different levels of income support around the world.

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income support during COVID-19

Mapping Global Income Support During COVID-19

Income loss has impacted many during the COVID-19 pandemic. Unemployment, reduced hours, office closures, and business shutdowns have prompted the need for mass income support.

Globally, income from work fell $3.5 trillion in the first nine months of 2020, a change of -10.7% compared to the same period in 2019.

In the above map, Our World in Data reveals the different levels of income support provided by governments across the globe.

Income support, in this case, is defined as governments broadly covering lost salaries, or providing universal basic income or direct payments to people who have lost their jobs or cannot work. Levels of income support are changing over time.

Small Government

Many world governments have provided no support when it comes to a universally applicable scheme to cover lost income in their countries.

Examples: (as of January 25th, 2021)

  • 🇻🇪 Venezuela
  • 🇸🇾 Syria
  • 🇧🇾 Belarus
  • 🇧🇩 Bangladesh
  • 🇰🇭 Cambodia

The majority of the governments providing no support are in low to lower-middle income countries. Based on a recent report from the International Labour Organization (ILO), lower-middle income countries have also seen the highest income losses, reaching 15.1% since 2019.

Developing countries tend to experience a significant fiscal stimulus gap, in which they do not have the capacity to cushion lost income or lost jobs. In fact, it’s estimated by the ILO that low and lower-middle income countries would need to inject an additional $982 billion into their economies to reach the same level of fiscal stimulus as high income countries.

A Helping Hand

There are other governments that are giving out some help on a wide-scale basis, providing citizens less than 50% of their lost salaries:

Examples: (as of January 25th, 2021)

  • 🇿🇦 South Africa
  • 🇨🇳 China
  • 🇷🇺 Russia
  • 🇹🇭 Thailand
  • 🇦🇺 Australia

South Africa’s unemployment rate was the highest in the world at 37.0% in 2020, an increase from 28.7% in 2019. Despite having one of the strictest lockdowns, the country has not been able to slow rising case counts or job losses. Now, South Africa is facing another threat, as a new strain of the novel coronavirus has taken hold in the nation.

The Most Supportive Governments

Finally, many world governments have offered higher amounts of income support, providing citizens with more than 50% of lost income:

Examples: (as of January 25th, 2021)

  • 🇨🇦 Canada
  • 🇺🇸 United States
  • 🇬🇧 United Kingdom
  • 🇪🇸 Spain
  • 🇸🇦 Saudi Arabia

Regionally, it’s the Americas that have been hit the hardest, according to the ILO. The region experienced a 12.1% drop in labor income in 2020 compared to 2019, revealing the need for broad-based income support.

U.S. unemployment went from 3.7% to 8.9% between 2019 and 2020. While the American government initially provided support in the form of the CARES Act, the policy response was recently extended through the more recent $900 billion relief deal.

Income Support Post COVID-19

While some countries have not been in extreme need of income support, others have been and haven’t received it. When looking at demographics, the hardest hit workers have been temporary workers, migrant workers, care workers, and self-employed vendors who have no labor contracts or employment insurance.

As a result, some critics have used this as an opportunity to call for universal basic income (UBI). A three-year study is already being implemented in Germany, for example, to test out how effective this kind of income support would be in the post-pandemic period.

Today, however, income is not a guarantee, and while in 2021 things may be returning to ‘normal,’ that does not mean that income levels will go back to normal.

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