Predictive model for real-world performance of COVID-19 antigen tests based on laboratory evaluation

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Abstract

Controlling spread of disease due to infectious agents require a quick response from public health sector. In the ongoing COVID-19 pandemic, the use of antigen tests has shown to be an excellent tool to inform authorities and mitigate the spread of the disease. In this communication we demonstrated how performance of an antigen test -- as a diagnostic in vitro device -- can be properly validated using quantitative laboratory experimentation and self-testing data from a clinical study. We also show how clinical performance of an antigen test can be predicted using mathematical modeling. The proposed appraisal methodology of antigen test performance under real-world conditions could be a useful tool to inform regulatory decision making. This approach allows to standardize, democratize, and speed up the process of validation, analysis, and comparison of antigen rapid tests, and thus to help developing effective public health response strategies.

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