Model simulations for use of rapid antigen testing for COVID-19 diagnosis

In a recent study posted to the medRxiv* preprint server, researchers overviewed the impact of rapid antigen tests (RDT) use cases (for surveillance; testing, tracing, and isolation [TTI]) with and without surveillance; hospital-based screening to decrease nosocomial coronavirus disease 2019 (COVID-19), and COVID-19 testing to enable prompt and expanded treatment for different country settings.

Study: Is there a role for RDTs as we live with COVID? An assessment of different strategies. Image Credit: CROCOTHERY/Shutterstock
Study: Is there a role for RDTs as we live with COVID? An assessment of different strategies. Image Credit: CROCOTHERY/Shutterstock

By 2022, increased severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection counts, with high vaccination coverage and Omicron emergence, have shifted health policies towards burden diminution. RDTs could contribute to policy-making by enabling rapid detection, isolation and/or COVID-19 treatment. However, evidence for informing the policy-makers of lower- and middle-income countries (LMICs) are limited.

About the study

In the present study, researchers overviewed several RDT usage cases and their potential impacts to attain more time and decrease health burdens and COVID-19-associated deaths.

Conceptual model simulations and literature reviews were used to identify use cases likely to provide benefits and the potential effects of SARS-CoV-2 outbreak characteristics. The RDT usage cases comprised (1) RDT-aided surveillance, (2a) TTI without surveillance (2b) TTI and surveillance, (iii) hospital-based tests to reduce nosocomial COVID-19, and (iv) RDTs for prompt treatment. Impacts were assessed through six outcomes concerning time gains and reductions in health burdens and deaths.

The A1 outcome pertained to time availability for immune boosting, i.e., duration between the SARS-CoV-2 outbreak in a previously uninfected community (t0) and seven days post-outbreak. Two COVID-19 vaccination speeds were assessed: the speed of initial COVID-19 vaccination and that after one percent of the total population was vaccinated. The A2 outcome pertained to time availability for intensive care unit (ICU) capacity enhancements, i.e., the duration between detecting the SARS-CoV-2 outbreak and 50% of ICU days used.

The B1, B2 and B3, and C outcomes pertained to % reductions in ICU demand peaks or unmet needs, ICU admissions, hospitalizations, and deaths. In the base case scenario, the SARS-CoV-2 outbreak had R0=10, denoting the previous infection- or vaccination-immunized individuals (s0 was 50%), and the mean periods of latency and infectivity of four (early outbreak detection) and six days (outbreak peak), respectively. RDT was assumed to have 80% sensitivity and provide immediate results.

The impacts of RDT use cases were assessed for six ‘archetypes’ denoting country situations differing in capacity and resources. For the lowest resource scenario, it was assumed that five percent of symptomatic COVID-19 cases using RDTs were achieved. The following LMIC patterned scenarios included 10% reached in LMICs, 20% to 40% (upper MICs), and 60% to 80% (highly-resourced settings).

In RDT usage case 1, it was assumed that RDT-enabled testing for individuals with SARS-CoV-2 infection-like clinical presentation for prompt outbreak detection and accelerating the A1 outcome and the A2 outcome. The South African surveillance model was used as an example. In 2a and 2b cases, it was assumed that symptomatic cases and their contact testing enabled isolating infected individuals and contact tracing to improve the A1, A2, and B outcomes.

The model translated transmission reductions into time gained for immune boosting and strengthening ICU capacities. In use case 3, it was assumed that RDT-based screening staff and/or hospitalized individual screening, with polymerase chain reaction (PCR) tests, could decrease nosocomial COVID-19 (and the B2 and C outcome) than using PCR only.

In use case 4, it was assumed that greater RDT access would change healthcare opportunities for highly-prone individuals with mild or moderate COVID-19 enabling prompt treatment and therefore, lower B3 and C outcomes. A sensitivity analysis was also performed by altering the outbreak characteristics.

Results

With optimized resources and capacity, for all use cases (except TTI with no surveillance) time gains of ≥7 days through surveillance and TTI with surveillance, ≥6.0% reductions in ICU admissions and peaks (hospital-based screening, TTI), and >6.0% lesser COVID-19-associated deaths (hospital-based screening, test and treat). However, only a few high-risk individuals could be reached in the available time. RDT impacts were reduced with lesser capacity and resources, more transmissible and immune-evasive variants and lower test sensitivity.

TTI without surveillance does could reduce peak ICU requirements by 8.0%. Even in the best-case scenario, immune boosting in median LMICs at the initial vaccination rollout speed was <6.0% for those aged >60 years. Use cases involving RDT screening in healthcare settings and surveillance showed less sensitivity to test availability than others. Considering use case 4 assumptions, testing and treating retained a high potential impact on hospitalizations even when testing levels were low. Large-scale TTI with good surveillance could lower ICU demand peaks and delay outbreak peaks by seven days; however, TTI impacts were lowered with lower testing scales and country incomes.

Overall, the study findings showed that RDTs used alone are unlikely to markedly reduce the COVID-19 burden in LMICs, but could be a valuable adjunct to other COVID-19 interventions such as vaccinations, therapeutic antiviral drugs, increased healthcare capacity and non-pharmaceutical measures (NPIs) such as mask-wearing.

*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.

Journal reference:
Pooja Toshniwal Paharia

Written by

Pooja Toshniwal Paharia

Dr. based clinical-radiological diagnosis and management of oral lesions and conditions and associated maxillofacial disorders.

Citations

Please use one of the following formats to cite this article in your essay, paper or report:

  • APA

    Toshniwal Paharia, Pooja Toshniwal Paharia. (2022, October 04). Model simulations for use of rapid antigen testing for COVID-19 diagnosis. News-Medical. Retrieved on December 08, 2022 from https://www.news-medical.net/news/20221004/Model-simulations-for-use-of-rapid-antigen-testing-for-COVID-19-diagnosis.aspx.

  • MLA

    Toshniwal Paharia, Pooja Toshniwal Paharia. "Model simulations for use of rapid antigen testing for COVID-19 diagnosis". News-Medical. 08 December 2022. <https://www.news-medical.net/news/20221004/Model-simulations-for-use-of-rapid-antigen-testing-for-COVID-19-diagnosis.aspx>.

  • Chicago

    Toshniwal Paharia, Pooja Toshniwal Paharia. "Model simulations for use of rapid antigen testing for COVID-19 diagnosis". News-Medical. https://www.news-medical.net/news/20221004/Model-simulations-for-use-of-rapid-antigen-testing-for-COVID-19-diagnosis.aspx. (accessed December 08, 2022).

  • Harvard

    Toshniwal Paharia, Pooja Toshniwal Paharia. 2022. Model simulations for use of rapid antigen testing for COVID-19 diagnosis. News-Medical, viewed 08 December 2022, https://www.news-medical.net/news/20221004/Model-simulations-for-use-of-rapid-antigen-testing-for-COVID-19-diagnosis.aspx.

Comments

The opinions expressed here are the views of the writer and do not necessarily reflect the views and opinions of News Medical.
Post a new comment
Post
You might also like...
Impact of COVID-19 booster vaccination and breakthrough infection