CDC Used Phone Location Data to Track Schools, Churches to See if Americans Followed COVID Lockdown Orders    HFL

CDC tracked “patterns of those visiting K-12 schools” as well as “visits to parks, gyms, or weight management businesses,” according to CDC documents obtained via Freedom of Information Act request.

By Jon Fleetwood – May 3, 2022


  • The Centers for Disease Control and Prevention (CDC) paid for access to location data collected from tens of millions of phones in the United States to track COVID-19 protocol compliance among citizens, Vice’s Motherboard reports.
  • Documents obtained by Motherboard via a Freedom of Information Act (FIOA) request show that the CDC used COVID-19 as a reason to buy access to the data more quickly, but also that the agency intended to use the data for other purposes.
  • The CDC looked at location data, which is information regarding a device’s location, which in turn can then show where a person lives, works, and where they traveled.
  • The health agency also used the data to “Track patterns of those visiting K-12 schools by the school and compare to 2019.”
  • The documents reveal how the CDC paid $420,000 for access to one year of data from the data broker SafeGraph, whose investors include Peter Thiel and the former head of Saudi intelligence among its investors. SafeGraph was banned from the Play Store in June.

C.6 Potential CDC Use Cases for Data:

  1. Implementation and cancellation of community mitigation measures and its impact on case and fatality rates.
  2. Impact of state limitations on close person-to-person contacts outside the household: comparing gathering density in 2019 and 2020.
  3. The effect of large-scale anti-contagion policies on the COVID-19 pandemic
  4. Analysis of bar and restaurant closure dataset compared to COVID-19 incidence and death rates.
  5. Examination of volume of mobile phones grouped in proximity each month and compare 2019 to 2020 data to see the impact of these orders. Project how much worse things would have been without the bans.
  6. Developing a clearer picture if IHE openings on mobility and COVID-19 case incidence, e.g. comparing areas with and without college campuses before and after re-openings.
  7. Follow shifts in school decisions over time and its potential on student mobility and potential illness.
  8. Track pattern for those visiting K-12 schools by the school and compare to 2019; compare the epi metrics if possible.
  9. Hot spot detection – counties with more mobile residents more likely to be detected as hsotspot counties
  10. Prediction of hot spot counties due to influx of persons from nearby hot spots
  11. Monitoring adherence to state-level policies to quarantine after arrival from another state
  12. Examination of the effectiveness of public policy on Navajo nation.
  13. Examination of COVID-19 vaccination rates, mobility, and incidence/seroprevalence/% positivity, etc. at the county and sub-county level (this could also be applied to flu and mask use).
  14. Examination of the correlation of mobility patterns data and rise in COVID-19 cses;
    1. Schools (K-12) opening/closing/re-opening
    2. Shelter in Place Orders
    3. Social distancing measures (local/regional)
    4. Mass gatherings (Concerts, Games, Places of worship etc.)
    5. Public transit stations
    6. Major destinations (retail, grocery stores, parks etc) correlated with COVID infection waves (2nd, 3rd, etc.)
    7. National Shelter Data for disasters
    8. Movement restrictions (Border closures, inter-regional and nigh curfews) and patterns
    9. Movement restrictions (Border closures, inter-regional and nigh curfews) to show compliance
  15. Examination of mobility data for tracking school closures such as school bus routes and cell phone data around institutes of higher education around events like spring break.
    1. County weekly number of visits to K to 12 schools as a dataset that could feed into other reports
    2. Compare with previous year as baseline
    3. Could help supplement the situation awareness data for K-12 and IHE
  16. Assess movement in and out of counties during periods of natural disasters to assist with planning and distribution of COVID resources to evacuation areas
  17. Research points of interest such as visits to pharmacies in a vaccine distribution plan or grocery stores
  18. Exposure to place based environmental exposures, like places with high air pollution and area-level incidence of pollution-related outcome like asthma
  19. Research points of interest for physical activity and chronic disease prevention such as visits to parks, gyms, or weight management business
  20. Creation of user-defined queries and metrics fo population mobility such as inferring mode of transport (e.g. walking, biking)
  21. Exposure to certain building ty]es, urban areas, and violence.

C.5 IT Security and Privacy Considerations:

  1. Baseline Security Requirements

Copy of document obtained by Motherboard


Cybersecurity researcher Zach Edwards said after reviewing the documents that the CDC “seems to have purposefully created an open-ended list of use cases, which included monitoring curfews, neighbor to neighbor visits, visits to churches, schools and pharmacies, and also a variety of analysis with this data specifically focused on ‘violence.’”


  • “The sort of data the CDC bought was aggregated—meaning it was designed to follow trends that emerge from the movements of groups of people—but researchers have repeatedly raised concerns with how location data can be deanonymized and used to track specific people,” Motherboard reported.
  • Some of the data use cases conducted by the CDC were not explicitly linked to COVID-19, one reading, “Research points of interest for physical activity and chronic disease prevention such as visits to parks, gyms, or weight management businesses.”

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