Carnegie Mellon University has released five interactive maps which will display real-time information on COVID-19 symptoms, doctor visits, medical tests and browser searches related to the virus.
These interactive maps will highlight country-level data which will be used to forecast disease activity in the US.
These interactive maps include data developed with the help of partners including Google, Facebook, Quidel Corp. and a national health system. The real-time daily updated data will provide the general public and decision-makers with a new and unique means of monitoring the ebb and flow of the disease across the country.
According to their website — “COVIDcast displays signals related to COVID-19 activity levels across the United States, derived from a variety of anonymised, aggregated data sources made available by multiple partners. Each signal may reflect the prevalence of COVID-19 infection, mild symptoms, or more severe disease over time, and can be presented at multiple geographic resolutions — state, county, and/or metropolitan area. All these signals taken together may suggest heightened or rising COVID-19 activity in specific locations. They will provide useful inputs to CMU’s pandemic forecasting system.”
According to CMU President Farnam Jahanian, COVIDcast leverages Carnegie Mellon’s leadership in machine learning, statistics and data science. And it is built upon the partnership with the Centres for Disease Control and Prevention (CDC) in epidemic forecasting at a time when policymakers and health care providers are eager for more insights into the spread of COVID-19.
He said, “Our multidisciplinary team of researchers has worked tirelessly to bring together a variety of data sources to support informed decision-making throughout our global society.”
Users can use the tabs on COVIDcast:
- To select which data source is visualised on the US map
- To display the data at the level of states, metropolitan areas or counties
- To show either intensity of activity or whether the activity is rising or falling
COVIDcast was created by Carnegie Mellon’s Delphi Research Group and its COVID-19 Response Team to provide a detailed and up-to-date picture of current COVID-19 activity. The aim was to use this enhanced information in forecasting disease activity. These forecasts will provide up to four weeks of warning to hospitals in a given locale that they likely will see increases in the number of people requiring hospital care.
Ryan Tibshirani, co-leader of the Delphi group and an associate professor of statistics and machine learning said, “The forecasts, as well as “nowcasts” that attempt to provide a combined, integrated view of current conditions, promise to provide valuable guidance as government and health care officials plan next steps in addressing the pandemic.”
Jodi Forlizzi, professor and director of CMU’s Human-Computer Interaction Institute, led the team that created the visualisations of the data sources.
The data sources include responses to CMU surveys by users of Google Surveys, and by users of Facebook. Another data source for the maps is Google Health Trends, which has provided data for the Delphi group’s influenza forecasts for the past five years. For the latest forecasting project, Delphi uses the Google Health Trends interface to estimate how often people are in a given location and on a given day search Google for topics related to COVID-19. A national health system also is providing statistics on patient visits to doctors and telemedicine visits.
This enables the CMU Delphi researchers to estimate the percentage of visits for COVID-19 related symptoms in any given location for a given day.
Another partnership is with Quidel Corp., a medical test maker, who provides the group with statistics on influenza tests. Flu tests are routinely ordered for people suffering COVID-19 symptoms as a means of excluding flu as a diagnosis; thus, requests for flu tests are indicators of possible COVID-19 activity.
“All of these signals are just rough indicators of COVID-19,” emphasised Roni Rosenfeld, co-leader of Delphi and head of CMU’s Machine Learning Department.
Rosenfeld said, “Anyone data source may not be conclusive, but if multiple sources indicate the same thing, people can have greater confidence about what is happening or will soon happen in various locales.”
The Delphi Group is continuously providing all of its estimates in a computer-accessible way to anyone. The Delphi Research Group has been performing epidemic forecasts for the past eight years, most notably for each influenza season. Last year, the CDC named Delphi one of two National Centers of Excellence for Influenza Forecasting. At the CDC’s request, the group this spring extended and adapted its flu forecasting efforts to encompass COVID-19.