Contact tracing has been a core component of the public health response to the coronavirus 2019 (COVID-19) pandemic. Its main objective is to interrupt transmission chains by identifying people who had contact with a case to promptly quarantine people at risk of infection, thereby reducing further transmission. This is to effectively minimize the workload for public health staff, which increases in multiples when there is an increased incidence of disease.
Study: Effectiveness of digital contact tracing for COVID-19 in New South Wales, Australia. Image Credit: WESTOCK PRODUCTIONS/Shutterstock
Background
This news article was a review of a preliminary scientific report that had not undergone peer-review at the time of publication. Since its initial publication, the scientific report has now been peer reviewed and accepted for publication in a Scientific Journal. Links to the preliminary and peer-reviewed reports are available in the Sources section at the bottom of this article. View Sources
Most digital contact tracing applications use Bluetooth technology, wherein the occurrence of a ‘contact’ between two smartphone users is indicated by the duration, frequency, and transmission strength of Bluetooth signal exchanges. Information is either stored on individuals’ phones for a determined period of time (decentralized approach) or uploaded into a common database (centralized approach).
Countries like Canada, Finland, Germany, Switzerland, the United Kingdom, and Vietnam have used the decentralized approach without public health authorities. By contrast, contact identification under the centralized approach occurs via a common database, which gives public health authorities access to undertake contact risk assessment and notification. This approach has been implemented by Australia, China, France, New Zealand, Singapore, and Taiwan.
Despite countries opting for contact tracing-based approaches, there has been very little empirical evidence about their benefits for pandemic response.
Australian public health researchers published a report in the preprint server medRxiv* wherein they evaluated the effectiveness and usefulness of ‘COVIDSafe,’ Australia’s national smartphone-based proximity tracing application for COVID-19.
The study
The Australian national government launched the COVIDSafe app on the 26th of April 2020 to enhance COVID-19 contact tracing nationwide. The app is based on the centralized approach and is intended only to supplement conventional interview-based contact tracing.
Each app user’s smartphone stores coded information communicated by other smartphones that have come in sufficiently proximity to exchange Bluetooth signals. These data are automatically deleted after a rolling 21-day period. Once a person is diagnosed with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, public health staff can seek informed consent from the case to access app data for contact tracing purposes. App use is ascertained as part of the standard case interview. Once the patient provides consent, data are uploaded to the COVIDSafe National Data Store database.
This study included all confirmed SARS-CoV-2 cases notified in New South Wales between the 4th of May and the 4th of November 2020 unless they were in quarantine during their entire infectious period. Cases aged 12 years and younger were excluded since app use was not systematically assessed for this age group. Persons with infections acquired overseas were also excluded since all international arrivals into NSW were required to complete 14 days’ quarantine in state-managed facilities upon arrival.
The necessary information on app-using cases was extracted from the NSW Notifiable Conditions Information Management System (NCIMS), the standardized information center for all confirmed SARS-CoV-2 cases in NSW.
There were 619 confirmed SARS-CoV-2 cases over the age of 12 with infection acquired within Australia recorded in NSW between the 4th of May and the 4th of November 2020. Over 25,300 close contacts were identified through conventional contact tracing during the same period. 22% (137) of cases used the app for at least part of their infectious period.
App-using cases were less likely to live in socioeconomically disadvantaged areas and more likely to be born in Australia than non-app-using cases. They were also more likely to have acquired infection from a contact outside their household or as part of a community cluster and to have more close contacts than cases not using the app. There were no significant differences by sex, age, or geographic remoteness.
App data were accessed by public health staff for 92 (67%) app-using cases. Among those whose data were accessed, the app did not record any contact during the infectious period for 60 (65%) cases, leaving 32 with at least one app-suggested contact (5% of the total 619 cases in NSW). These 32 cases had 205 app-suggested contacts.
Following the risk assessment and data reconciliation by public health staff, 79 app-suggested contacts were assessed as meeting the close contact definition and were directed to self-quarantine, resulting in a positive predictive value of the app.
The 79 app-suggested contacts who met the close contact definition originated from 20 cases and represented 0·3% (79/25,300) of all close contacts in NSW during the study period. Of these 79 close contacts, 62 (78%) were also identified by conventional contact tracing, leaving the additional yield of close contacts identified only via the app at 17, or 0·07% of all close contacts. These 17 contacts originated from four app-using cases.
Implication
In this study, only 0.07% of contacts were successfully traced using the COVIDSafe app. This implied that the contact tracing approach was not sufficiently effective to make a meaningful contribution to COVID-19 contact tracing in Australia’s most populous state during a 6-month period in 2020. More technological advances were needed to make the approach more effective.
Key issues were low app uptake, its poor positive predictive value and sensitivity, and difficulties for public health staff in accessing app-derived data. The additional contact yield was minimal and did not prevent any public SARS-CoV-2 exposure. At the same time, the app generated a substantial workload for public health staff, leading to high opportunity costs.
This news article was a review of a preliminary scientific report that had not undergone peer-review at the time of publication. Since its initial publication, the scientific report has now been peer reviewed and accepted for publication in a Scientific Journal. Links to the preliminary and peer-reviewed reports are available in the Sources section at the bottom of this article. View Sources
Article Revisions
- Apr 29 2023 - The preprint preliminary research paper that this article was based upon was accepted for publication in a peer-reviewed Scientific Journal. This article was edited accordingly to include a link to the final peer-reviewed paper, now shown in the sources section.
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