www.coronabambini.ch: Development and usage of an online decision support tool for paediatric COVID-19-testing in Switzerland: a cross-sectional analysis

Abstract

Objectives To describe the development and usage of www.coronabambini.ch as an example of a paediatric electronic public health application and to explore its potential and limitations in providing information on disease epidemiology and public health policy implementation.Design We developed and maintained a non-commercial online decision support tool, www.coronabambini.ch, to translate the Swiss Federal Office of Public Health (FOPH) paediatric (age 0–18 years) COVID-19 guidelines around testing and school/daycare attendance for caregivers, teachers and healthcare personnel. We analysed the online decision tool as well as a voluntary follow-up survey from October 2020 to September 2021 to explore its potential as a surveillance tool for public health policy and epidemiology.Participants 68 269 users accessed and 52 726 filled out the complete online decision tool. 3% (1399/52 726) filled out a voluntary follow-up. 92% (18 797/20 330) of users were parents.Results Certain dynamics of the pandemic and changes in testing strategies were reflected in the data captured by www.coronabambini.ch, for example, in terms of disease epidemiology, gastrointestinal symptoms were reported more frequently in younger age groups (13% (3308/26 180) in children 0–5 years vs 9% (3934/42 089) in children ≥6 years, χ2=184, p≤0.001). As a reflection of public health policy, the proportion of users consulting the tool for a positive contact without symptoms in children 6–12 years increased from 4% (1415/32 215) to 6% (636/9872) after the FOPH loosened testing criteria in this age group, χ2=69, p≤0.001. Adherence to the recommendation was generally high (84% (1131/1352)) but differed by the type of recommendation: 89% (344/385) for ‘stay at home and observe’, 75% (232/310) for ‘school attendance’.Conclusions Usage of www.coronabambini.ch was generally high in areas where it was developed and promoted. Certain patterns in epidemiology and adherence to public health policy could be depicted but selection bias was difficult to measure showing the potential and challenges of digital decision support as public health tools.