JMIR Publications

ABSTRACT

Background:

The free app Ada allows users to enter symptoms they are experiencing, and applies a probabilistic reasoning model to provide a list of possible causes for those symptoms.

Objective:

The objective of our study was to explore the potential contribution of Ada data to syndromic surveillance, by comparing symptoms of influenza-like illness (ILI) entered by Ada users in Germany with data from a national population-based reporting system called GrippeWeb.

Methods:

We extracted data for all assessments performed by Ada users in Germany over three seasons (2017/18, 2018/19 and 2019/20), and identified those with ILI (report of fever with cough or sore throat). The weekly proportion of assessments in which ILI was reported was calculated (overall and stratified by age-group), standardised for the German population, and compared with trends in ILI rates reported by GrippeWeb using time series graphs, scatterplots, and Pearson’s correlation coefficient.

Results:

In total 2.1 million Ada assessments (for any symptoms) were included. Within seasons and across age-groups, the Ada data broadly replicated trends in estimated weekly ILI rates when compared with GrippeWeb data (Pearson’s correlations: 2017-18: r = 0.86 (95% CI 0.76-0.92), P<.0001; 2018-19: r = 0.90 (95% CI 0.84-0.94), P <.0001; 2019-20: r = 0.64 (95% CI 0.44-0.78), P <.0001). However, there were differences in the exact timing and nature of the epidemic curves between years.

Conclusions:

With careful interpretation, Ada data could contribute to identifying broad ILI trends in countries without existing population-based monitoring systems, or to the syndromic surveillance of symptoms not covered by existing systems.