To learn about what Facebook Data for Good is doing in response to the COVID19 pandemic, click here.

Our Work on COVID-19

Facebook Data for Good has a number of tools and initiatives that can help organizations respond to the COVID-19 pandemic. This includes:

COVID-19 Symptom Map

This symptom map is designed to help policymakers and health researchers better monitor and forecast the spread of COVID-19 and improve their response to the pandemic. In partnership with Carnegie Mellon University and University of Maryland, Facebook users are invited to take a survey conducted by the universities to self-report how they’re feeling and any symptoms they may be experiencing. To ensure that the survey sample more accurately reflects the characteristics of the population represented in the data, Facebook shares a single statistic known as a weight value that doesn’t identify a person but helps researchers correct for any sample bias. Facebook doesn’t share who took the survey with our academic partners, and they don’t share individual survey responses with us.  


Aggregated data are publicly available through CMU’s API for the US survey and UMD’s API for the global survey. Non-aggregated data from these partners are only available to eligible researchers with signed Data Use Agreements. The data available are not received, collected or stored by Facebook. Interested academic and nonprofit researchers can submit a request here.


  • All publicly available information is aggregated and privacy preserving measures are applied. 
  • Facebook does not receive, collect or store individual survey responses. 
  • CMU and UMD do not learn who took a survey. 

Publicly Available Tools

You can learn more about our High Resolution Population Density Maps and CrowdTangle Displays by watching this video.

High Resolution Population Density Maps

These are the most accurate population datasets in the world. They are available to download for 169 countries, right now, by anyone, on UN OCHA’s Humanitarian Data Exchange here or Amazon AWS Open Data Sets here. You can find a tutorial video here for how to work with Population Density Maps in QGIS, a mapping software. 

This map shows the distribution of people over the age of 60 in Mexico.


The World Bank used these High Resolution Population Density Maps to plan for better COVID resource allocation in Spain. Read more here


These maps are built using census data and satellite imagery, and do not use any Facebook data. The methodology is here

CrowdTangle COVID-19 Live Displays

CrowdTangle COVID-19 Live Displays are very useful for monitoring trending public posts on Facebook and Instagram related to COVID-19. You can find many countries here; others can be added by request.


  • CrowdTangle is focused entirely on public data.
  • The easiest way to think about CrowdTangle is this: if you can see it natively on the platform without any special permissions to the page or account, we can show it to you in our tool.
  • CrowdTangle gathers information that is publicly available on Facebook, Instagram, and Reddit. That information is aggregated, benchmarked, and served to you in an easy to read visual format.
  • Read more about how these displays were built here.

Tools for Nonprofits & Universities

Disease Prevention Maps

Facebook Disease Prevention Maps are designed to help public health organizations close gaps in understanding where people live, how people are moving, and the state of their cellular connectivity, in order to improve the effectiveness of health campaigns and epidemic response. These maps were launched in May 2019 and have been used for other health crises including the cholera outbreak in Mozambique. 


There are four map types that sit under Disease Prevention Maps that can provide insights during public health crises:

  • Co-location Maps (launched for COVID-19): Reveal the probability that people in one area will come in contact with people in another, helping illuminate where COVID-19 cases may appear next
  • Trends on Staying Near Home (launched for COVID-19): Trends showing whether, at a regional or county level, people are generally staying near home, which can provide insights into whether preventive measures are headed in the right direction
  • Movement Maps: Aggregated information showing movement between two points from people using Facebook on their mobile phones 
  • Network Coverage Maps: Aggregated information show where people on Facebook have cellular connectivity


The Institute for Disease Modeling recently used Movement Maps for the State of Washington to determine the rates at which mixing among workforces had been disrupted to inform transmission forecasts.


  • All information is aggregated and privacy preserving measures are applied. The highest resolution are tiles that are six American football fields on a side. This allows nonprofits and researchers to analyze patterns at scale while preventing re-identification.
  • We also only generate mobility datasets during natural disasters and public health emergencies for specific windows of time and share them with nonprofits and universities that have signed data license agreements. These partners are then onboarded to our tools for which access is administered at a user level.
  • Trends on Staying Near Home show trends only at a county or regional level. These data are aggregated and do not answer questions about specific households. 
  • Movement Maps aggregate information only from people using Facebook on their mobile phones with Location History enabled. The methodology can be found here.
  • Network Coverage Maps are visualized as a polygon of network coverage by speed. The methodology can be found here.

Social Connectedness Index

The Social Connectedness Index measures the strength of connectedness between two geographic areas as measured by Facebook friendship ties. These connections can reveal important insights about economic opportunities, social mobility, trade and more. In the context of COVID-19, this serves as another helpful input for disease modeling, and helps researchers understand where areas hit hardest by COVID-19 might seek support. 


This tool is only available to nonprofits and researchers. Interested researchers are invited to email to work with the Social Connectedness Index data. If you are a researcher who is already working with the Data for Good team, feel free to connect with your standing contacts to start working with this data.


Researchers at NYU used the Social Connectedness Index to show that areas with stronger social ties to two early COVID-19 “hotspots” (Westchester County, NY, in the U.S. and Lodi province in Italy) generally have more confirmed COVID-19 cases as of March 30, 2020. Read more here.


  • We use aggregated friendship connections on Facebook to measure social connectedness between geographies.
  • Locations are assigned to users based on information they provide, connection information, and location services they have opted into (to learn more about how Facebook uses location data and how to control location privacy see Location Privacy Basics).
  • We use these friendships to estimate the probability a pair of users in these geographies are Facebook friends (we rescale based on the population of two geographies) and map this to an index score called the Social Connectedness Index (SCI).
  • If the SCI is twice as large between two pairs of geographies, it means the users in the first geography-pair are about twice as likely to be connected than the second geography-pair.
  • More details on the methodology can be found on our website here, or in the paper Social Connectedness: Measurement, Determinants, and Effects published in the Journal of Economic Perspectives.

COVID-19 Mobility Data Network

The COVID-19 Mobility Data Network is a network of infectious disease epidemiologists at universities around the world working with technology companies to use aggregated mobility data to support the COV-19 response. To connect with the COVID-19 Mobility Data Network, email


We’re piloting this approach with Direct Relief, a non-profit working with the California Governor’s office to provide insights. Read more here.


  • All information is aggregated, and privacy-preserving measures are applied. For example, information shared on mobility is aggregated up to either a county-level or a tile leve, which are 0.6 km (or six American football fields) on a side.
  • These insights do not answer questions related to contact tracing, but they do provide valuable insights into whether public sector interventions are headed in the right direction.
  • Read more about the Mobility Data Network’s Data Use Policy here.

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