Survey and map data

Supporting COVID-19 research

With over two billion people on Facebook, we are in a unique position to support public health research. We have partnered with trusted academic and non-profit institutions since 2017, through our Data for Good programme, to build a research network to address some of the world's greatest humanitarian issues. Recently, we partnered with Carnegie Mellon University and the University of Maryland to invite people to participate in surveys about COVID-19 symptoms and risk factors. We use the survey data on our map, and we also show other publicly available aggregate data to provide a more holistic view of the COVID-19 pandemic. Our partner initiatives are designed with privacy in mind from the start.

Survey methodology

In partnership with Carnegie Mellon University and the University of Maryland, we invite people on Facebook to participate in surveys that ask about how they are feeling, including any COVID-19 symptoms they or members of their household have experienced, and about their risk factors for contracting COVID-19. The surveys are designed to provide valuable information to help monitor and forecast how COVID-19 may be spreading, without trading off the privacy of survey respondents. Over a million people responded to the surveys within the first two weeks.

About the surveys

The surveys conducted by Carnegie Mellon University and the University of Maryland ask people to report symptoms associated with COVID-19 or the flu that they or members of their household have experienced in the last 24 hours. Public health research surveys like this have been conducted globally and used to forecast the spread of the flu and other illnesses in the past.

Who is taking the surveys

Facebook reaches large segments of the population, allowing for a significant representation of age, gender and location. Every day, a new sample of Facebook users over 18 years old are invited to participate in a survey. Users in the United States take a survey conducted by Carnegie Mellon University, and users outside the United States take a survey conducted by the University of Maryland. Facebook does not receive, collect or store individual survey responses. Carnegie Mellon University and the University of Maryland do not learn who took the surveys.

Adjusting for sample bias

Facebook shares a single statistic, known as a weight value, to correct for survey sample bias. The weight value does not identify the survey respondent. Adjusting for sample bias with weight values ensures that the sample more accurately reflects the characteristics of the population represented. The weight value for a person can be thought of as the number of people in the adult population that they represent, based on their age, gender and location. We do not show any data for countries that do not reflect sample bias adjustments.

Using the survey data

The survey data can help policymakers and researchers forecast COVID-19 outbreaks and respond to the pandemic in their communities. Facebook's research partners are committed to using symptom survey results to study and help contain COVID-19 only. Learn more about requesting access to survey data as an academic or non-profit researcher.

Data on our map

The data on our map can be used to better understand reported COVID-19 symptoms and confirmed cases, as well as how preventative measures and policies or population characteristics, such as age and density, are affecting disease spread. When used together, the data can help policymakers and public health systems plan for their communities more effectively. There are three categories of data we show on our map: symptoms and cases, physical distancing, and risk factors.

Symptoms and cases

Reported symptoms and confirmed cases are key in understanding the pandemic because they give an indication of how preventative measures and policies, such as physical distancing, affect COVID-19 spread.

Physical distancing

Physical distancing, school closure and state of emergency dates, along with mobility data, give an indication of how shelter-in-place and stay-at-home policies decrease mobility to slow COVID-19 spread.

Risk factors

Risk factors are population characteristics associated with an increased risk of COVID-19 spread or the development of serious illness, including population total, density and people aged 65 and over. These three characteristics can be used to understand the other categories of data more effectively.