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. Here’s how you can make use of these tools:

More About Each Tool

High Resolution Population Density Maps

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About

  • These are the most accurate population datasets in the world.
  • You can watch a video explaining how these maps were made here
  • You can watch a tutorial video here for how to work with Population Density Maps in QGIS, a geospatial software. 
  • Check out this tutorial which will walk you through the creation of a map and dataset which identifies potential problem areas for COVID-19 vulnerable populations using High Resolution Population Density Maps and Movement Range Maps.
  • In addition to releasing a map of the total population density for each country, we also release demographic data showing populations of (1) men (2) women (3) children (ages 0-5), (4) youth (ages 15-24) (5) women of reproductive age (ages 15-49) and elderly (ages 60+).

Privacy

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

Case Studies

  • The World Bank used these High Resolution Population Density Maps to plan for better COVID resource allocation in Spain. Read more here
  • For a list of all Case Studies using High Resolution Population Density Maps, go here

COVID-19 Symptom Survey



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About

  • This symptom survey 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. 

Privacy

  • 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. 
  • 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.  

Case Studies

  • The Institute for Health Metrics and Evaluation used these surveys to evaluate mask use in the United States. Read more here

Movement Range Maps

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About

  • Movement Range Maps inform researchers and public health experts about how populations are responding to physical distancing measures.
  • These datasets have two different metrics: Change in Movement and Stay Put.
    • The Change in Movement metric looks at how much people are moving around and compares it to a baseline period that predates most social distancing measures.
    • The Stay Put metric looks at the fraction of the population that appears to stay within a small area surrounding their home for an entire day.
  • Check out this tutorial which will walk you through the creation of a map and dataset which identifies potential problem areas for COVID-19 vulnerable populations using Movement Range Maps and High Resolution Population Density Maps.

Privacy

  • A differential privacy framework is applied to this dataset. Read more here

Case Studies

  • Governor Gavin Newsom praised Movement Range data in a press conference regarding the State of California’s COVID19 response efforts. 

COVID-19 Preventive Health Survey

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About

  • The COVID-19 Preventive Health Survey is designed to help policymakers and health communities better understand the effectiveness of and adherence to COVID-19 policies, such as stay-at-home orders and wearing masks, as well as inform future policies and communications in response to the pandemic.
  • In partnership with MIT and JHU, Facebook users are invited to take a survey, conducted by MIT, to self-report their adherence to preventive measures, such as washing hands and wearing masks, and what they know about COVID-19, including symptoms of the disease, risk factors and how their community is handling the pandemic. 

Privacy

  • All publicly available information is aggregated.
  • Facebook does not receive, collect or store individual survey responses. 
  • MIT does not learn who took a survey. 

Case Studies

Coming soon!

Social Connectedness Index

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About

  • 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. 

Privacy

Case Studies

  • 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.

Survey on Gender Equality at Home

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About

  • Facebook’s Survey on Gender Equality at Home generates a global snapshot of women and men’s access to resources, their time spent on unpaid care work, and their attitudes about equality.

Privacy

  • Read about the methodology here.

Case Studies

  • Read the Survey on Gender Equality at Home full report here.

COVID-19 Forecasts

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About

Facebook AI builds adaptive models and collaborates with experts to help the world better understand the spread of the virus. The COVID-19 Forecasts produced by the models gives researchers and public health experts information that can help them with resource planning and allocation and early outbreak detection. These forecasts are developed using public, non-Facebook data, and serve as a tool to support our global efforts to keep people informed as the pandemic evolves. Our data-driven methods achieve strong performance when compared to other state of the art forecasts.

Privacy

  • Read about the methodology here.

Case Studies

  • Direct Relief used COVID-19 Forecasts to predict that the United States would see 1 million new infections between October 26th and November 8th. You can read more here. 

Disease Prevention Maps

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About

Facebook Disease Prevention Maps are designed to help public health organizations close gaps in understanding how people are moving or 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 under Disease Prevention Maps:

  • Travel Patterns (launched for COVID19): Show comparisons of the number of Facebook users moving large distances, like air or train travel. We are initially looking at international travel.
  • Co-location Maps (launched for COVID19): 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. These maps look at two locations and measure the rate at which Randomly Chosen Person A and Randomly Chosen Person B are colocated in the same place over a certain period. As a concrete example: if you choose a random person from Los Angeles County and a random person from San Francisco County, what is the probability that they spent at least 15 minutes in the same level 14 Bing tile anywhere in the world during the week 2019-10-25 to 2019-10-31? 
  • Movement Maps: Aggregated information showing movement between two points from people using Facebook on their mobile phones 
  • Network Coverage Maps: Network Coverage Maps: Aggregated information show where people on Facebook have cellular connectivity

Privacy

  • 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.
  • 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.

Case Studies

  • Researchers summarize the initial impact of the lockdown in India for a representative sample of mostly poor and non-migrants workers in Delhi. Using Facebook mobility data, they show that intra-city movement dropped 80 percent following the announcement. 
  • More Disease Prevention Maps case studies can be found here. 

CrowdTangle COVID-19 Live Displays

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About

  • CrowdTangle COVID-19 Live Displays are very useful for monitoring trending public posts on Facebook and Instagram related to COVID-19. 

Privacy

  • 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.

Case Studies

  • Coming soon!

COVID-19 Mobility Data Network

 

Access

  • Join the COVID19 Mobility Data Network by emailing contact@covid19mobility.org, if you are a qualifying nonprofit or university researcher
  • Public sector officials interested in being connected with COVID19 Mobility Data Network researchers can email diseaseprevmaps@fb.com 

About

  • The COVID19 Mobility Data Network is a network of infectious disease epidemiologists at universities around the world working with technology companies (like Facebook) to use aggregated mobility data to support the COVID19 response. 

Privacy

The participants in the COVID19 Mobility Data Network share a deep commitment to privacy values and data protection as well as best practice principles related to data governance and ethics. The following principles guide the Network’s effort:

  • The use of data, including data sharing, aggregation, and analysis, for Covid19 response must speak to a clear need articulated by public health authorities, and for no other purpose.
  • The use of data must both be in compliance with existing laws and adhere to best practice principles of data governance.
  • Data should be aggregated to the lowest feasible resolution possible while maintaining its desired utility.
  • The use of data must be transparent, inclusive, and safeguarded against unintended consequences.

The Network itself will not be the recipient of data. The use of data facilitated by the Network will be subject to the various approval and oversight mechanisms provided by the academic home institutions of the individual researchers participating in the Network. The Network facilitates the sharing of consolidated daily situation reports with government health officials and provides analytic support. It does not share the underlying data sets with governments, third parties, or the public at large. Participants in the Network embrace appropriate legal, organizational, and computational safeguards to minimize – and carefully manage any remaining – data privacy risks associated with this research effort in general and the use of aggregated data in particular.

Case Studies

  • Direct Relief is a nonprofit and a leading partner within the COVID19 Mobility Data Network. By analyzing Facebook Movement Range data, Direct Relief was able to share insights with the State of California. Governor Gavin Newsom praised these insights in a press conference regarding the State of California’s COVID19 response efforts. 

Future of Business Survey

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About

The Future of Business survey is a collaboration between Facebook, the OECD and the World Bank to provide timely insights on the perceptions, challenges, and outlook of online Small and Medium Enterprises (SMEs). First launched as a monthly survey in February 2016, we began releasing a COVID-focused survey in July 2020 given the economic impacts particular to the pandemic. 

Privacy

When we share data from this survey, we remove personally identifiable information from survey questions and only share country-level data publicly. To achieve better representation of the broader small business population, we also weight our results based on known characteristics of the Facebook Page admin population. Click here for more details on the methodology.

Case Studies

The World Bank used Future of Business Survey data to better understand how the COVID-19 pandemic could affect women and girls disproportionately. Read more here.

Access

  • Nonprofits and researchers interested in accessing Business Activity Trends should email disastermaps@fb.com

About

Business Activity Trends help quantify how businesses are affected by crisis events around the world such as natural disasters and disease outbreaks. In the COVID-19 context, these trends can be used by economists and other researchers to understand the rate at which businesses remain open or have closed in response to stay at home orders or lockdowns.

This dataset provides two daily metrics for the businesses inside a crisis-affected region. First, it provides the aggregate number of public posts on Facebook Business Pages compared to pre-crisis activity levels. Second, it provides the aggregate number of people who are visiting businesses in-person also compared to pre-crisis levels. Together, these metrics help quantify how businesses are affected by crisis events across the world such as disease outbreaks or natural disasters.

Privacy

Only scaled values of business page post counts and visits are contained in this dataset and all data is aggregated. Read more about the methodology in this Nature publication

Case Studies

Coming soon!

Commuting Zones

Access

  • Nonprofits and researchers interested in accessing Commuting Zones should email disastermaps@fb.com

About

Facebook Commuting Zones are geographic areas where people live and work. Similar to commuting zones built by the United States Department of Agriculture, our zones can cross political boundaries and can be useful to understand local economies, areas in which people spend the majority of their time and how diseases might be transmitted. For each Commuting Zone, we include its shape, as well as metrics about its economic and commuting characteristics.

Privacy

We aggregate users’ home and work locations to create a graph that measures movements between locations over the previous few weeks. Home and work locations are assigned to users based on information they provide 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 then use a community detection algorithm to identify clusters that represent commuting zones, and build our commuting zone shapes by using another partitioning methodology. Read more about the methodology here.

Case Studies

The Center for Economic Performance at the London School of Economics used Commuting Zones to conclude that informal social ties and geographic proximity promote knowledge flows between two locations. Read more here

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