TY - JOUR
T1 - Effectiveness of contact tracing apps for SARS-CoV-2: A rapid systematic review
AU - Jenniskens, Kevin
AU - Bootsma, Martin C. J.
AU - Damen, Johanna A. A. G.
AU - Oerbekke, Michiel S.
AU - Vernooij, Robin W. M.
AU - Spijker, René
AU - Moons, Karel G. M.
AU - Kretzschmar, Mirjam E. E.
AU - Hooft, Lotty
N1 - Funding Information: *This work was supported by gifts from the Reid Hoffman Foundation and the Open Philanthropy Project (to KME) and cluster time granted by the COVID-19 HPC consortium (MCB20071 to KME). ECA was supported by a fellowship from the Open Philanthropy Project. ALL is supported by the Drexel Endowment (NC State University). The funders had no role in the research, writing or decision to publish. Publisher Copyright: © 2021 BMJ Publishing Group. All rights reserved.
PY - 2021/7/12
Y1 - 2021/7/12
N2 - Objective To systematically review evidence on effectiveness of contact tracing apps (CTAs) for SARS-CoV-2 on epidemiological and clinical outcomes. Design Rapid systematic review. Data sources EMBASE (OVID), MEDLINE (PubMed), BioRxiv and MedRxiv were searched up to 28 October 2020. Study selection Studies, 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 extraction Empirical 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. Results 2140 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. Conclusions CTAs 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.
AB - Objective To systematically review evidence on effectiveness of contact tracing apps (CTAs) for SARS-CoV-2 on epidemiological and clinical outcomes. Design Rapid systematic review. Data sources EMBASE (OVID), MEDLINE (PubMed), BioRxiv and MedRxiv were searched up to 28 October 2020. Study selection Studies, 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 extraction Empirical 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. Results 2140 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. Conclusions CTAs 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.
KW - COVID-19
KW - epidemiology
KW - microbiology
KW - statistics & research methods
UR - http://www.scopus.com/inward/record.url?scp=85110529456&partnerID=8YFLogxK
U2 - https://doi.org/10.1136/bmjopen-2021-050519
DO - https://doi.org/10.1136/bmjopen-2021-050519
M3 - Review article
C2 - 34253676
SN - 2044-6055
VL - 11
JO - BMJ Open
JF - BMJ Open
IS - 7
M1 - e050519
ER -