Effectiveness of contact tracing apps for SARS-CoV-2: a rapid systematic review

Abstract

ObjectiveTo systematically review evidence on effectiveness of contact tracing apps (CTAs) for SARS-CoV-2 on epidemiological and clinical outcomes.DesignRapid systematic review.Data sourcesEMBASE (OVID), MEDLINE (PubMed), BioRxiv and MedRxiv were searched up to 28 October 2020.Study selectionStudies, both empirical and model-based, assessing effect of CTAs for SARS-CoV-2 on reproduction number (R), total number of infections, hospitalisation rate, mortality rate, and other epidemiologically and clinically relevant outcomes, were eligible for inclusion.Data extractionEmpirical and model-based studies were critically appraised using separate checklists. Data on type of study (ie, empirical or model-based), sample size, (simulated) time horizon, study population, CTA type (and associated interventions), comparator and outcomes assessed, were extracted. The most important findings were extracted and narratively summarised. Specifically for model-based studies, characteristics and values of important model parameters were collected.Results2140 studies were identified, of which 17 studies (2 empirical, 15 model-based studies) were eligible and included in this review. Both empirical studies were observational (non-randomised) studies and at high risk of bias, most importantly due to risk of confounding. Risk of bias of model-based studies was considered low for 12 out of 15 studies. Most studies demonstrated beneficial effects of CTAs on R, total number of infections and mortality rate. No studies assessed effect on hospitalisation. Effect size was dependent on model parameters values used, but in general, a beneficial effect was observed at CTA adoption rates of 20% or higher.ConclusionsCTAs have the potential to be effective in reducing SARS-CoV-2 related epidemiological and clinical outcomes, though effect size depends on other model parameters (eg, proportion of asymptomatic individuals, or testing delays), and interventions after CTA notification. Methodologically sound comparative empirical studies on effectiveness of CTAs are required to confirm findings from model-based studies.

Appsolutely secure? Psychometric properties of the German version of an app information privacy concerns measure during COVID-19

“…The apps inform users about contact with positive (infected) cases, suggest adequate preventive and mitigation measures, and allow governmental institutions to define containment or hotspot zones (Kahnbach et al, 2021). Previous studies examined barriers and facilitators of adopting tracing app use and showed that they are effective in reducing infection rates (e.g., Jenniskens et al, 2021;Kahnbach et al, 2021;Kolasa et al, 2021). However, tracing apps often do not provide sufficient information about personal data breaches, which might increase privacy concerns and subsequently, reduce use intentions (Jenniskens et al, 2021).…”

Covira: A COVID-19 risk assessment, visualization and communication tool

“…Visualization ( [10] ), machine learning ( [11] , [12] , [13] ) and statistical modeling ( [14] ), robotics ( [11] ), and contact tracing ( [15] ) has been the major focus of the engineers in the recent past that have helped slow down the spread of COVID-19 and reduce the moveability. Geostatistical modeling helps better understanding the disease trend and facilitates the informed decision-making process ( [16] ).…”

Effectiveness of digital contact tracing for COVID-19 in New South Wales, Australia

“…Despite implementation in many countries, little empirical evidence exists about the effectiveness of digital tracing applications. (13, 14) While two recent evaluations from the United Kingdom and Switzerland suggest that systems based on the decentralised approach may be able to provide some benefits to a country’s COVID-19 response under certain conditions, (15, 16) no evidence exists to date about the population-level effectiveness of decentralized digital contact tracing applications. Considering the substantial investments to develop, promote and maintain these systems, it is important to establish how well they work, and what their added value within the existing contact tracing system is.…”

“…(8)(9)(10)(11)(12) Despite implementation in many countries, little empirical evidence exists about the effectiveness of digital tracing applications. (13,14) While two recent evaluations from the United Kingdom and Switzerland suggest that systems based on the decentralised approach may be able to provide some benefits to a country's COVID-19 response under certain conditions, (15,16) no evidence exists to date about the population-level effectiveness of decentralized digital contact tracing applications.Considering the substantial investments to develop, promote and maintain these systems, it is important to establish how well they work, and what their added value within the existing contact tracing system is. (17) Therefore, we assessed the effectiveness and usefulness of the COVIDSafe app, Australia's national smartphone-based proximity tracing application.…”