Evidence map›Paper›PMID 35131045›Full record

ArticleThe Lancet. Public health2022

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

Florian Vogt, Bridget Haire, Linda Selvey, Anthea L Katelaris, John Kaldor

Open access · goldAbstract readEvaluation Study
In one paragraph

Article in The Lancet. Public health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 38 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
38citing papers in PubMed, 2 pooled it
35.6field-weighted citation impact, top 1% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

38 citing papers in PubMed, 2 syntheses or guidelines pooled it, 112 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
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  4. Assessing the Impact of Haulage Drivers in Uganda's COVID-19 Delta Wave.Journal of epidemiology and global health · 2025
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  14. Time trends and modifiable factors of COVID-19 contact tracing coverage, Geneva, Switzerland, June 2020 to February 2022.Euro surveillance : bulletin Europeen sur les maladies transmissibles = European communicable disease bulletin · 2024
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

5 authors at 3 institutions in 1 country.

Florian VogtThe Kirby Institute, University of New South Wales, Sydney, NSW, Australia; National Centre for Epidemiology and Population Health, Australian National University, Canberra, ACT, Australia. Electronic address: florianvogt@hotmail.com.
Bridget HaireThe Kirby Institute, University of New South Wales, Sydney, NSW, Australia.
Linda SelveySchool of Public Health, University of Queensland, Brisbane, QLD, Australia.
Anthea L KatelarisPublic Health Unit, Western Sydney Local Health District, North Parramatta, NSW, Australia.
John KaldorThe Kirby Institute, University of New South Wales, Sydney, NSW, Australia.
UNSW Sydney · AUSydney Local Health District · AUUniversity of Queensland · AU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDigital proximity tracing apps were rolled out early in the COVID-19 pandemic in many countries to complement conventional contact tracing. Empirical evidence about their benefits for pandemic response remains scarce. We evaluated the effectiveness and usefulness of COVIDSafe, Australia's national smartphone-based proximity tracing app for COVID-19.

methodsIn this prospective study, done in New South Wales (NSW), Australia, we included all individuals in the state who were older than 12 years with confirmed, locally acquired SARS-CoV-2 infection between May 4 and Nov 4, 2020. We used data from the NSW Notifiable Conditions Information Management System, the national COVIDSafe database, and information from case interviews, including information on app usage, the number of app-suggested contacts, and the number of app-suggested contacts determined by public health staff to be actual close contacts. We calculated the positive predictive value and sensitivity of COVIDSafe, its additional contact yield, and the number of averted public exposure events. Semi-structured interviews with public health staff were done to assess the app's perceived usefulness.

findingsThere were 619 confirmed COVID-19 cases with more than 25 300 close contacts identified by conventional contact tracing during the study period. COVIDSafe was used by 137 (22%) cases and detected 205 contacts, 79 (39%) of whom met the close contact definition. Its positive predictive value was therefore 39%. 35 (15%) of the 236 close contacts who could have been expected to have been using the app during the study period were identified by the app, making its estimated sensitivity 15%. 79 (0·3%) of the estimated 25 300 contacts in NSW were app-suggested and met the close contact definition. The app detected 17 (<0·1%) additional close contacts who were not identified by conventional contact tracing. COVIDSafe generated a substantial additional perceived workload for public health staff and was not considered useful.

interpretationThe low uptake of the app among cases probably led to a reduced sensitivity estimate in our study, given that only contacts who were using the app could be detected. COVIDSafe was not sufficiently effective to make a meaningful contribution to the COVID-19 response in Australia's most populous state over a 6 month period. We provide an empirical evaluation of this digital contact tracing app that questions the potential benefits of digital contact tracing apps to the public health response to COVID-19. Effectiveness evaluations should be integrated into future implementations of proximity contact tracing systems to justify their investment.

fundingNew South Wales Ministry of Health (Australia); National Health and Medical Research Council (Australia).

Indexed as

Mobile ApplicationsPublic HealthAdultAustraliaContact TracingCOVID-19HumansInterviews as TopicNew South WalesProspective StudiesSurveys and Questionnaires

Identifiers

PMID35131045
PMCPMC8816387
OpenAlexW4210765912

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.