COVID-19: Activity in Public Spaces as a Metric for Social Distancing

How do levels of social distancing in select US cities compare to Italy and South Korea?

Background

Experts agree that social distancing is critical to delay and reduce the spread of Covid-19. Models predict various outcomes based on scenarios with varying levels of social distancing assumed. Researchers want to regularly run models in order to make informed decisions about social distancing policy. 

In running these models, a number of assumptions must be made in regard to social distancing. Notably, it is unclear how much any given policy actually influences real-world behavior. When a government strongly urges social distancing, does the population comply and to what extent?

South Korea’s response to COVID-19 was an “informed” social distancing strategy. Officials asked South Koreans to practice social distancing and participate in drive-through testing facilities that have the ability “to test up to 20,000 people a day at 633 testing sites nationwide, including drive-through clinics… an army of around 1,200 medical professionals analyze results¹.” As people began to self-isolate, they were informed with the results of readily available test results.

Researchers have agreed that “it’s much better to test and then quarantine a specific person than to do a citywide or province wide lockdown, which in certain ways prevents the virus from leaving the province but actually doesn’t make the province any less likely to have high infection rates,” says Eric Feigl-Ding, a senior fellow at the Federation of American Scientists in Washington, D.C., and an epidemiologist at the Harvard Chan School of Public Health².

Italy’s response, on the other hand, seems to be heavily influenced by “individuals’ behavior, lifestyles, civic responsibilities, and relationships with public institutions. In Italy, as in much of the Western world, citizens tend to believe that things will turn out for the best…³” While the risk of COVID-19 was imminent, Italian citizens were less proactive in terms of social distancing.  

Objective

Our objective is to use mobile data to quantify actual behavior by measuring the GPS positioning of devices before and after a social distancing policy is enacted. This quantification can be correlated to the increase in new cases in order to improve models, evaluate the effectiveness of policy and inform future policy.

Analysis

Measure social distancing

In order to measure social distancing, you first have to define the public spaces social distancing is meant to avoid. For example, if you are practicing social distancing then you are likely not visiting restaurants, markets, churches, bars, offices, transit centers, museums, universities, and airports at the same rate you did prior to social distancing. 

Once public spaces are defined, you can identify the number of devices in those spaces day over day during the social distancing period and compare that to the average. This chart shows visitation to public spaces in Los Angeles county for the first few months in 2020, as expressed as a foot traffic index. 

Social distancing (or the act of not visiting public spaces) did not begin until the end of February, almost a month after the first confirmed case of COVID-19 in Los Angeles County on January 26, 2020⁴.

Plot the Social Distancing of High-Profile COVID-19 Pandemics

Once public spaces in two high-profile COVID-19 Pandemic locations – South Korea and Italy – were identified, the number of devices in those locations (by country) were plotted by days since the first confirmed case. 

We’ve aligned the South Korea and Italy visitation to public spaces changes side by side so you can really compare how visitation changes as COVID-19 events unravel. 

Compare Social Distancing to Amount of Reported COVID-19 Cases

If we add the amount of confirmed COVID-19 cases by days since the first confirmed case, we can start to look at some patterns. 

South Korea has been an area that has had a decent amount of success in keeping the curve of reported cases low, meaning that after the initial increase in cases, fewer cases have been reported day over day. New cases reported in South Korea are represented by the dark blue line. 

Unfortunately in Italy, there has been a significant increase in cases over time, as represented by the dark orange line. 

South Korea’s total foot traffic in public spaces (in light blue) begins decreasing at the end of January when global reports of COVID-19 increase and a few COVID-19 cases are confirmed in South Korea. Foot traffic then decreases rapidly in the middle of February as more cases are reported and stay low throughout the course of the outbreak (in dark blue). 

Italy, on the other hand, maintained the usual amount of public activity (in orange) through the middle of February and only declined at the beginning of its increases in reported cases (in dark orange). 

Between the two countries, South Korea took a more immediate and aggressive approach to public health and has experienced a significantly smaller outbreak than Italy. 

Insight #1: Gradual, but immediate distancing might slow the spread

In the first 30 days after the first confirmed case in the region, South Korea saw a gradual decrease in foot traffic to public spaces whereas Italy saw a rise in foot traffic in the first 20 days but then fell off sharply. By comparing the amount of visitation to public places in the first 30 days, South Korea showed about 10% more social distancing than Italy.  

Insight #2: Timing of distancing might matter more than the intensity of distancing  

South Korea showed nearly a 65% decrease in foot traffic before the number of cases began to rise whereas Italy showed only a 24% decrease in foot traffic before the cases began to rise. In fact, Italy distanced more over time, but they did it more slowly than South Korea. 

Comparing Emerging US Trends Against Known Pandemics

By using South Korea and Italy as two early examples of social distancing and comparing those to places where COVID-19 is still emerging, it provides a useful baseline for determining what to expect in communities based on their adoption of social distancing. 

This is the same data but visualized in a different way, allowing you to compare different communities’ trends against advanced outbreaks. 

To use Florida as an example, you can focus on its curves and how it compares to other communities in order to better inform public policies and communications with citizens.  

Conclusion

South Korea and Italy can be used as baselines for communities to better understand what they should expect when confronting COVID-19 in their own regions. This type of analysis can be applied to any other regions, simply by defining public spaces in that region, analyzing the data, layering in publicly available COVID-19 outbreak data, and comparing the curves between social distancing and increase in COVID-19 cases. 

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Sources

1. South Korea’s coronavirus success story underscores how the U.S. initially failed https://www.washingtonpost.com/world/2020/03/17/south-koreas-coronavirus-success-story-underscores-how-us-initially-failed/ 
2. Uncharted territory: Italy’s response to the coronavirus https://www.ecfr.eu/article/commentary_uncharted_territory_italys_response_to_the_coronavirus