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

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 datasets, when combined with epidemiological information from health systems, assist nonprofits in reaching vulnerable communities more effectively and in better understanding the pathways of disease outbreaks that are spread by human-to-human contact.

Features

Privacy-Preserving

All maps that use Facebook data are aggregated, and privacy-preserving measures are applied.

Global Reach

Movement Maps and Network Coverage Maps are derived from Facebook data that is global in nature.

Timeliness

Our Disease Prevention Maps can be generated quickly as the situation on the ground unfolds. This allows agencies to respond to changing circumstances.

One of the most important pieces of information we need to respond to epidemics is where people are moving. This kind of data can be integrated into our epidemiological models to help us estimate how quickly a disease might spread, and where to put resources to contain it.”

Caroline Buckee, Assistant Professor of Epidemiology, Harvard School of Public Health

Who Uses Disease Prevention Maps

Universities and researchers

Researchers and universities can combine information from health systems with aggregated and anonymous Facebook movement data to glean insights about where the next case of cholera or drug-resistant malaria is likely to occur.

Map Types

Case Studies

The Social Analytics Lab at the MIT Initiative on the Digital Economy (IDE) just released a comprehensive study of the cost of uncoordinated responses to COVID-19. We combined daily, county-level data... The Social Analytics Lab at the MIT Initiative on the Digital Economy (IDE) just released a comprehensive study of the cost of uncoordinated responses to COVID-19. We combined daily, county-level data on shelter-in-place and business closure policies with movement data from more than 27 million mobile devices, social network connections among over 220 million Facebook users, daily temperature and precipitation data from 62,000 weather stations, and county-level census data on population demographics to estimate the geographic and social network spillovers created by regional policies across the United States.

Read more

Disease Prevention Maps

The Cost of Uncoordinated Responses to COVID-19

The Social Analytics Lab at the MIT Initiative on the Digital Economy (IDE) just released a comprehensive study of the cost of uncoordinated responses to COVID-19. We combined daily, county-level data on shelter-in-place and business closure policies with movement data from more than 27 million mobile devices, social network connections among over 220 million Facebook users, daily temperature and precipitation data from 62,000 weather stations, and county-level census data on population demographics to estimate the geographic and social network spillovers created by regional policies across the United States.

In the News

Get Involved

Check out our high resolution population density maps, including demographic estimates, available for download on the United Nations Office for the Coordination of Humanitarian Affairs (OCHA)’s Humanitarian Data Exchange. Each country-level dataset contains the demographic estimates. If you're interested in working with movement or network coverage maps, please email diseaseprevmaps@fb.com.

Explore

To personalize content, tailor and measure ads and provide a safer experience, we use cookies. By clicking "Accept All", you agree to our use of cookies on and off Facebook. Learn more, including about controls: Cookie Policy