Tagged "symptom surveys"
Building on our previous two posts (on our COVID-19 symptom surveys through Facebook and Google) this post offers a deeper dive into empirical analysis, examining whether the % CLI-in-community indicators from our two surveys can be used to improve the accuracy of short-term forecasts of county-level COVID-19 case rates.
Since April 2020, in addition to our massive daily survey advertised on Facebook, we’ve been running (even-more-massive) surveys through Google to track the spread of COVID-19 in the United States. At its peak, our Google survey was taken by over 1.2 million people in a single day, and over its first month in operation, averaged over 600,000 daily respondents. In mid-May, we paused daily dissemination of this survey in order to focus on our (longer, more complex) survey through Facebook, but we plan to bring back the Google survey this fall. This short post covers some key differences between our Google and Facebook surveys, explains the backstory behind the “CLI-in-community” question as it arose through our collaboration with Google, and shares some of our thinking about next steps for the Google survey.
Since April 2020, in collaboration with Facebook, partner universities, and public health officials, we’ve been conducting a massive daily survey to monitor the spread and impact of the COVID-19 pandemic in the United States. Our survey, advertised by Facebook, is taken by about 74,000 people each day. Respondents provide information about COVID-related symptoms, contacts, risk factors, and demographics, allowing us to examine county-level trends across the US. We believe that this combination of detail and scale has never before been available in a public health emergency. In this post, we’ll share some of our initial survey findings, show you how to access the data, and highlight some of the exciting new directions that we’re pursuing.