Effectiveness of a COVID-19 contact tracing app in a simulation model with indirect and informal contact tracing
Ka Yin Leung,
Esther Metting,
Wolfgang Ebbers,
Irene Veldhuijzen,
Stijn P. Andeweg,
Guus Luijben,
Marijn de Bruin,
Jacco Wallinga,
Don Klinkenberg
Affiliations
Ka Yin Leung
National Institute for Public Health and the Environment, Centre for Infectious Disease Control, Bilthoven, the Netherlands; Corresponding author.
Esther Metting
University of Groningen, University Medical Center Groningen, Data Science Center in Health, the Netherlands; University of Groningen, University Medical Center Groningen, Department of Primary Care, the Netherlands; University of Groningen, faculty of Economics and Business, Department of Operations, the Netherlands
Wolfgang Ebbers
Erasmus School of Social and Behavioural Sciences, Department of Public Administration and Sociology, Erasmus University Rotterdam, Rotterdam, the Netherlands
Irene Veldhuijzen
National Institute for Public Health and the Environment, Centre for Infectious Disease Control, Bilthoven, the Netherlands
Stijn P. Andeweg
National Institute for Public Health and the Environment, Centre for Infectious Disease Control, Bilthoven, the Netherlands
Guus Luijben
National Institute for Public Health and the Environment, Centre for Health and Society, Bilthoven, the Netherlands
Marijn de Bruin
National Institute for Public Health and the Environment, Centre for Health and Society, Bilthoven, the Netherlands; Radboud University Medical Centre, Radboud Institute of Health Sciences, IQ Healthcare, Nijmegen, the Netherlands
Jacco Wallinga
National Institute for Public Health and the Environment, Centre for Infectious Disease Control, Bilthoven, the Netherlands; Leiden University Medical Centre, Department of Biomedical Datasciences, Leiden, the Netherlands
Don Klinkenberg
National Institute for Public Health and the Environment, Centre for Infectious Disease Control, Bilthoven, the Netherlands
During the COVID-19 pandemic, contact tracing was used to identify individuals who had been in contact with a confirmed case so that these contacted individuals could be tested and quarantined to prevent further spread of the SARS-CoV-2 virus. Many countries developed mobile apps to find these contacted individuals faster. We evaluate the epidemiological effectiveness of the Dutch app CoronaMelder, where we measure effectiveness as the reduction of the reproduction number R. To this end, we use a simulation model of SARS-CoV-2 spread and contact tracing, informed by data collected during the study period (December 2020 - March 2021) in the Netherlands. We show that the tracing app caused a clear but small reduction of the reproduction number, and the magnitude of the effect was found to be robust in sensitivity analyses. The app could have been more effective if more people had used it, and if notification of contacts could have been done directly by the user and thus reducing the time intervals between symptom onset and reporting of contacts. The model has two innovative aspects: i) it accounts for the clustered nature of social networks and ii) cases can alert their contacts informally without involvement of health authorities or the tracing app.
