Weights and Methodology Brief for the COVID-19 Symptom Survey by University of Maryland and Carnegie Mellon University, in Partnership with Facebook

TL;DR

This paper details the sampling design and weighting methodology used in COVID-19 symptom surveys conducted via Facebook in the US and globally, aiming to improve data representativeness.

Contribution

It introduces specific survey weighting and sampling strategies applied in large-scale international COVID-19 symptom surveys using Facebook data.

Findings

Development of weighting methods for survey representativeness

Implementation of sampling design for diverse populations

Guidelines for data users on applying weights

Abstract

Facebook is partnering with academic institutions to support COVID-19 research. Currently, we are inviting Facebook app users in the United States to take a survey collected by faculty at Carnegie Mellon University (CMU) Delphi Research Center, and we are inviting Facebook app users in more than 200 countries or territories globally to take a survey collected by faculty at the University of Maryland (UMD) Joint Program in Survey Methodology (JPSM). As part of this initiative, we are applying best practices from survey statistics to design and execute two components: (1) sampling design and (2) survey weights, which make the sample more representative of the general population. This paper describes the methods we used in these efforts in order to allow data users to execute their analyses using the weights.