Our laboratory previously established the value of over-the-counter (OTC) sales data for the early detection of disease outbreaks. We found that thermometer sales (TS) increased significantly and early during influenza (flu) season. Recently, the 2009 H1N1 outbreak has highlighted the need for developing methods that not only detect an outbreak but also estimate incidence so that public-health decision makers can allocate appropriate resources in response to an outbreak. Although a few studies have tried to estimate the H1N1 incidence in the 2009 outbreak, these were done months afterward and were based on data that are either not easy to collect or not available in a timely fashion (for example, surveys or confirmed laboratory cases).
Here, we explore the hypothesis that OTC sales data can also be used for predicting a disease activity. Towards that end, we developed a model to predict the number of Emergency Departments (ED) flu cases in a region based on TS. We obtain sales information from the National Retail Data Monitor (NRDM) project. NRDM collects daily sales data of 18 OTC categories across the US.
Objective
We developed a model that predicts the incidence of flu cases that present to ED in a given region based on TS.