Social Distancing Scoreboard

According to the World Health Organization and the CDC, social distancing is currently the most effective way to slow the spread of COVID-19. We created this interactive Scoreboard, updated daily, to empower organizations to measure and understand the efficacy of social distancing initiatives at the local level.

Please scroll down and explore the data — the more we all understand, the more lives we can save together.

Compare your community's social distancing activity to its activity prior to COVID-19

Methodology: driven by data science for actionability

Real World Graph® — Unacast's core asset that provides a range of perspectives and critical context for how people relate to physical locations.The COVID-19 toolkit empowers organizations in unprecedented times, to make quality decisions quickly.

The toolkit is powered by Unacast's robust team of data scientists and PhDs focuses on data accuracy to ensure that our partners and clients get high-quality insights that reflect real-world events.

  • For counties:

    - Before March 22: Corona Data Scraper
    - Starting March 22 (incl): John Hopkins github repository started publishing complete data on each county in USA (with FIPS for each county) on March 22

    For states:

    All data is only from John Hopkins github repository:
    - Before March 22: Archived data
    - Starting March 22 (incl): Current data

  • To ensure a full picture of activities, we wait for three days after an event day for all the data for that given event date to come in. Processing takes another day and therefore, the existing and default delay is four days from a given event date.
    Since we know time is of the essence in the fight against COVID19, our team is figuring out if we can reduce the lag, use less data, and still provide strong signals. At the same time, we will further enhance our score to make it more robust and explain different facets of social distancing.

  • Our first underlying metrics uses change in average distance traveled from pre-COVID-19 days as one proxy: 
    • A: >70% decrease
    • B: 55-70% decrease
    • C: 40-55% decrease
    • D: 25-40% decrease
    • F: <25% decrease or increase

    Our second metric uses change in non-essential visitation as an additional proxy:
    • A: >70% decrease
    • B: 65-70% decrease
    • C: 60-65% decrease
    • D: 55-60% decrease
    • F: <55% decrease or increase

    These two metrics are then combined:
    A & B = round( (5 + 4) / 2)  = 4.5 =  A-
    A & C
    = round( (5 + 3) / 2 )  = 4 =  B
    F & D
    = round( (1 + 2) / 2 )  = 1.5 =  D-

  • For a deeper dive into our methodology, please see stay tuned for a blogpost on our exciting updates!


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Venue Impact Tracker

For any given place of interest (such as airports, stadiums, and retail stores), compare traffic patterns to news cycles to determine which fluctuations are the result of COVID-19.

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Origin-Destination Flux

Measure changes in the human mobility patterns of larger areas, such as movement within neighborhoods or between states.

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Custom Data Analysis & Curated Data Sets

Pre-defined correlations and insights for organizations that need fast, user-friendly solutions tailored to their businesses.

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  • 1

    Get in touch to discover how location data can help your organization measure the impact of the virus.

  • 2

    Chat with our team to determine data strategies to tackle your particular challenges.

  • 3

    Use high-quality, curated data and human mobility insights to create reaction strategies and identify recovery signals.

What can human mobility insights do to combat COVID-19?

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