According to Eric Haller, EVP & Global Head of Experian DataLabs, the lack of reliable data is impacting regulations and policies around COPVID-19 can impact on measures to address the global pandemic. To redress this, Experian has designed its COVID-19 Outlook and Response Evaluator (CORE).
With the recent news that the Centers for Disease Control and Prevention has acknowledged that it is mixing the results of two different kinds of tests in the agency’s tally of testing for the coronavirus, Haller says there’s a raising concerns among some scientists that it could be creating an inaccurate picture of the state of the pandemic in the U.S.. With this in mind, it is clear that unreliable data is impeding the U.S. in decision making.
For example, Haller says, there is lack of a national case registry or medical inventory database. The epidemiological forecasting algorithms like SIR and IHME used by the U.S. federal and state government health officials do not have reliable data, so that is why we see inflated reports. There is clearly a need for more dependable data to help public officials navigate health and economic risks better.
To predict future hot zone, Experian which deals with financial and health data) produced its CORE tool, which is available for free in the U.S. Haller explains that the application allows health and government leaders to forecast how a specific area may be impacted economically or health-wise down to a specific hot zone.
With the Experian CORE heat map, Haller notes that Experian took a new approach to making the data and algorithms more reliable using artificial intelligence. The application also shows what areas may be most at risk based on the comorbidities (health conditions like heart disease or lung conditions that make COVID-19 more deadly) of the local population.
Haller says it will be crucial for health and government leaders in their responses to the public health emergency. The data for the new platform is generated from breakthrough experimentation and overall it is helping to leverage artificial intelligence and data assets from a variety of sources.
