In a recent study published in medRxiv*, researchers evaluated real-world evidence on the performance of coronavirus disease 2019 (COVID-19) self-testing strategies (COVIDSTs).
Study: Self-tests for COVID-19: what is the evidence? A living systematic review and meta-analysis (2020-2023). Image Credit: Basilico Studio Stock/Shutterstock.com
*Important notice: medRxiv publishes preliminary scientific reports that are not peer-reviewed and, therefore, should not be regarded as conclusive, guide clinical practice/health-related behavior, or treated as established information.
Background
COVID-19 cases have been decreasing due to extensive vaccination, with clustering of cases in some population subsets, such as immunosuppressed and non-vaccinated people. COVID-19 self-tests have been increasingly used since late 2021.
Through COVIDSTs, individuals collect and test their samples and interpret and use the results to inform their actions.
COVIDSTs are invaluable in regions with limited resources and during outbreaks. Rapid COVID-19 tests quickly detect active severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, offering a user-friendly and convenient alternative to reverse-transcription polymerase chain reaction (RT-PCR).
About the study
In the present study, researchers evaluated real-world evidence on COVIDST performance. They searched Embase, PubMed, Cochrane COVID-19 registry, and World Health Organization (WHO) databases for studies between April 1, 2020, and January 18, 2023.
Studies evaluating COVIDSTs were included; reviews, opinion pieces, commentaries, case reports, narratives, and modeling studies were excluded.
Interventions included antigen, antibody, or molecular COVID-19 self-tests. The primary outcome was diagnostic accuracy. Secondary outcomes were feasibility, acceptability, preferences, and impact of COVIDSTs. Tertiary outcomes were qualitative measures (motivation, barriers, and facilitators of COVIDSTs).
The risk of bias was evaluated using the Cochrane Risk of Bias tool 2, Newcastle-Ottawa Scale, and quality assessment of diagnostic accuracy study tool 2. The variability in COVIDST performance was examined in random-effects bivariate meta-analysis.
Additionally, sub-group analyses were performed according to symptom status, testing strategy, sampling site, and digital support.
Findings
The researchers included 70 studies from 25 countries. COVIDSTs included mass, targeted, and healthcare facility-based screening. Studied populations included the general public, laboratory and healthcare personnel, school or university students, parents and teachers, staff and residents of nursing homes, office employees, and patients receiving drug addiction treatment, among others.
Ten studies employed supervised self-testing, 34 reported unsupervised testing, and two analyzed both. Trained research staff or HCWs monitored the testing procedure in supervised testing.
Four studies evaluated the diagnostic performance of 15 self-test devices, and the sensitivities of four devices were above 80%; specificities for all devices were > 91%.
Further, four studies described diagnostic accuracy by the symptom onset day. Two revealed sensitivities of 99.1% a day before symptom onset, 98.7% – 100% within the first two days, and 100% from two to seven days post-symptom onset.
Contrastingly, a community-based study found sensitivities of 23% and 66.67% during 0-1 and 2-4 days of symptom onset, respectively.
Two studies compared the diagnostic performance of COVIDSTs between the SARS-CoV-2 Delta and Omicron periods. Of these, one observed a decline in sensitivity from 87% to 80.9% in the Omicron period.
Fourteen studies were included in the meta-analyses; the pooled sensitivity and specificity were 75% and 100%, respectively. Sub-group analyses revealed that sensitivity was the highest for mid-turbinate nasal samples and the lowest for saliva samples.
However, specificity remained above 98% regardless of the sampling site. The symptomatic and asymptomatic individuals' sensitivity was 73.9% and 40.18%, respectively. Sensitivity was higher with the supervised testing strategy (86.6%) than with the unsupervised approach (60.69%) and with digital support (70.15%) than without (65.69%).
Nevertheless, specificity was > 99% regardless of testing strategy or digital support. Thirteen studies revealed high acceptability and willingness to use self-tests; eight reported high feasibility and ease of use of COVIDSTs.
Preference for COVIDSTs varied between 29% and 87.9%, with a higher preference among White individuals, HCWs, urban populations, and college graduates. COVIDSTs reduced closures of schools, workplaces, and social events.
Twenty-six studies assessed qualitative outcomes. The motivation behind self-testing was to protect one's health, reduce transmission to contacts, partake in daily activities, travel, attend large gatherings, and dine outside.
COVIDST barriers were high costs, anxiety, difficulties in following instructions and interpreting faint positive results, and inequitable access to COVIDSTs, among others.
Conclusions
The study illustrated that COVIDSTs effectively screened SARS-CoV-2 infections; their use was instrumental in decreasing school closures and allowing people to attend social events. The meta-analysis revealed an above-average sensitivity of COVISTs but a high specificity.
Moreover, COVIDSTs were convenient, acceptable, and feasible to populations, and their usability increased with digital support interventions, such as app- or video-based instructions.
*Important notice: medRxiv publishes preliminary scientific reports that are not peer-reviewed and, therefore, should not be regarded as conclusive, guide clinical practice/health-related behavior, or treated as established information.
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