Can Smart Thermometer Data Predict the COVID-19 Pandemic?

Rapidly identifying emerging epidemics remains a massive challenge that limits our ability to effectively curtail outbreaks, such as COVID-19. In response, smart thermometer company Kinsa has developed a method to identify anomalous influenza-like illness incidence (ILI) outbreaks in real-time using their county-level illness signals, developed from real-time geospatial thermometer data and highly accurate 12-week illness forecasts. Through their analysis, Kinsa flags anomalously high incidence data by comparing real-time ILI to expected seasonal influenza trends, where these expectations are generated from geo-specific influenza forecasts made from a point prior to potential outbreaks.

Creation of The U.S Health Weather Map

The U.S. Health Weather Map is a visualization of seasonal illness linked to influenza-like illness. The aggregate, anonymized data visualized is derived from Kinsa’s network of Smart Thermometers and the accompanying mobile applications.

The mapping was Created in collaboration with Benjamin Dalziel, Oregon State University. It shows two key data points: The illness levels currently…