Effectiveness of a COVID-19 contact tracing app in a simulation model with indirect and informal contact tracing
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 conta...
| Autores principales: | , , , , , , , , |
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| Formato: | Artículo |
| Lenguaje: | English |
| Publicado: |
Elsevier
2024-03-01
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| Colección: | Epidemics |
| Materias: | |
| Acceso en línea: | http://www.sciencedirect.com/science/article/pii/S1755436523000713 |
| _version_ | 1827321739076435968 |
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| author | Ka Yin Leung Esther Metting Wolfgang Ebbers Irene Veldhuijzen Stijn P. Andeweg Guus Luijben Marijn de Bruin Jacco Wallinga Don Klinkenberg |
| author_facet | Ka Yin Leung Esther Metting Wolfgang Ebbers Irene Veldhuijzen Stijn P. Andeweg Guus Luijben Marijn de Bruin Jacco Wallinga Don Klinkenberg |
| author_sort | Ka Yin Leung |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-03-08T21:30:58Z |
| format | Article |
| id | doaj.art-3f11350d7264438ea7e9df42c521247e |
| institution | Directory Open Access Journal |
| issn | 1755-4365 |
| language | English |
| last_indexed | 2024-04-25T01:12:22Z |
| publishDate | 2024-03-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Epidemics |
| spelling | doaj.art-3f11350d7264438ea7e9df42c521247e2024-03-10T05:11:34ZengElsevierEpidemics1755-43652024-03-0146100735Effectiveness of a COVID-19 contact tracing app in a simulation model with indirect and informal contact tracingKa Yin Leung0Esther Metting1Wolfgang Ebbers2Irene Veldhuijzen3Stijn P. Andeweg4Guus Luijben5Marijn de Bruin6Jacco Wallinga7Don Klinkenberg8National Institute for Public Health and the Environment, Centre for Infectious Disease Control, Bilthoven, the Netherlands; Corresponding author.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 NetherlandsErasmus School of Social and Behavioural Sciences, Department of Public Administration and Sociology, Erasmus University Rotterdam, Rotterdam, the NetherlandsNational Institute for Public Health and the Environment, Centre for Infectious Disease Control, Bilthoven, the NetherlandsNational Institute for Public Health and the Environment, Centre for Infectious Disease Control, Bilthoven, the NetherlandsNational Institute for Public Health and the Environment, Centre for Health and Society, Bilthoven, the NetherlandsNational 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 NetherlandsNational 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 NetherlandsNational Institute for Public Health and the Environment, Centre for Infectious Disease Control, Bilthoven, the NetherlandsDuring 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.http://www.sciencedirect.com/science/article/pii/S1755436523000713Non-pharmaceutical interventionsDigital contact tracingBranching processClustering coefficientBehaviourTransmission model |
| spellingShingle | Ka Yin Leung Esther Metting Wolfgang Ebbers Irene Veldhuijzen Stijn P. Andeweg Guus Luijben Marijn de Bruin Jacco Wallinga Don Klinkenberg Effectiveness of a COVID-19 contact tracing app in a simulation model with indirect and informal contact tracing Epidemics Non-pharmaceutical interventions Digital contact tracing Branching process Clustering coefficient Behaviour Transmission model |
| title | Effectiveness of a COVID-19 contact tracing app in a simulation model with indirect and informal contact tracing |
| title_full | Effectiveness of a COVID-19 contact tracing app in a simulation model with indirect and informal contact tracing |
| title_fullStr | Effectiveness of a COVID-19 contact tracing app in a simulation model with indirect and informal contact tracing |
| title_full_unstemmed | Effectiveness of a COVID-19 contact tracing app in a simulation model with indirect and informal contact tracing |
| title_short | Effectiveness of a COVID-19 contact tracing app in a simulation model with indirect and informal contact tracing |
| title_sort | effectiveness of a covid 19 contact tracing app in a simulation model with indirect and informal contact tracing |
| topic | Non-pharmaceutical interventions Digital contact tracing Branching process Clustering coefficient Behaviour Transmission model |
| url | http://www.sciencedirect.com/science/article/pii/S1755436523000713 |
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