Benefits, risks, and cost-effectiveness of COVID-19 self-tests from a consumer’s perspective

Abstract

Background The aim of this study is to quantify the health benefits, risks, and cost-effectiveness of COVID-19 self-tests from a consumer’s perspective in Germany. Methods The analysis is based on a modelling approach using secondary data. The clinical endpoints considered in this analysis are avoided SARS-CoV-2 infections and secondary severe clinical events (death, intensive care unit (ICU) admission, and long COVID syndrome). The study determines the number of self-tests that need to be conducted under a 7-day incidence of 75 per 100,000 population to prevent one infection or severe clinical event. Furthermore, the study calculates the cost of testing per avoided clinical event and quality-adjusted life year (QALY) gained from a consumer perspective. Results Disregarding the rate of unreported COVID-19 cases, 4556 self-tests need to be conducted (over 12 years) in order to avoid one undesirable event (death, intensive care unit stay, or long COVID syndrome). Ninety percent of infections are not avoided among direct contacts but along the chain of infection. The costs per quality-adjusted life year gained from a consumer’s perspective are €5870. This ratio is particularly sensitive to the 7-day incidence, effective reproduction number, and the age of contacts. Conclusions The benefits of self-testing in the general population at a 7-day incidence rate of 75 per 100,000 appear to be minor. Nevertheless, cost-effectiveness may still be acceptable in the presence of higher-risk contacts given the low costs of self-test kits in Germany.

Cost-effectiveness of interventions for the prevention and control of COVID-19: Systematic review of 85 modelling studies

“…The fail-safe number was 37, indicating that 37 negative studies or interventions might change the current results. Among the remaining 38 un-pooled studies about NPIs against COVID-19, five reported the interventions were not cost-effective [ 15 , 52 - 55 ], 21 concluded that the interventions were cost-effective or cost-saving [ 56 - 76 ], 10 reported that parts of the studied interventions were cost-effective or cost-effective with minor benefit [ 77 - 85 ], and one study concluded the results were uncertain and conditional [ 86 ].…”

COVID-19 patient experiences in pre-hospital pathways: a processual qualitative approach using the life-events calendar method highlights diagnostic delays and healthcare renunciation.

“…During a pandemic with a large in ux of patients, it may be more e cient for a GP to rely on a negative test despite symptoms (test and treat strategy). We point out however that the of tests with poor sensitivity at high economic and social cost is still debated [25,26,27]. as they are sometimes counterproductive, and false-negatives can mistakenly reassure the GP, as observed in our study.…”

Evaluating the Usefulness of Population-Wide COVID-19 Testing in the Omicron Era: Insights from a German Model

“…A previously published decision-analytic model [12] was updated with data on the Omicron variant (specifically, real-world data on vaccine effectiveness and outcomes of an infection). In the base case, the study assumed contacts at average risk of infection with the Omicron variant and an average disease course in the event of an infection.…”

“…By multiplying the 7-day incidence per 100,000 population, test sensitivity, and effective reproduction number (R t ), taking the reciprocal of the product, and dividing the resulting figure by the number of infections avoided over the entire infection chain, the number of self-tests that need to be conducted to prevent exactly one infection was calculated [12] (see Appendix for formulas). Further dividing by the incidence of a combined endpoint yields the number of self-tests that need to be conducted to prevent one severe clinical event [12].…”