Back

Evaluating the adequacy of Prima Covid-19 IgG/IgM Rapid Test for the assessment of exposure to SARS-CoV-2 virus

Di Lorenzo, G.; Toniolo, P.; Lurani, C.; Foresti, L.; Carrisi, C.

2020-06-03 infectious diseases
10.1101/2020.05.30.20117424 medRxiv
Show abstract

1.The outbreak of the SARS-CoV-2 in early 2020 found health authorities worldwide unprepared to control the pandemic. The adoption of accurate, rapid and inexpensive methods to identify infected subjects in the general population is of paramount relevance for the control of the disease. We evaluated one of the available serological tests, the Prima Lab Covid-19 IgG/IgM Rapid Tests, on 739 volunteers. We first assessed the tests reproducibility by administering it twice on the same day on 104 subjects obtaining and overall score of 93 percent. Since the intensity of the color in the test line regions varies depending on the concentration of Covid-19 antibodies in each sample and that the determination of the positivity depends strictly on the subjective assessment by the reader, after excluding the subjects whose color intensity was too tenuous to be deemed unquestionably positive by the reader the reproducibility increased to 96%. The test would not perform properly for 6 subjects for a very limited overall technical failure of 0.83%. For 138 subjects information was available regarding a previous Real Time PCR nasopharyngeal swab test performed elsewhere. The correspondence of positive results between the two tests was 90.58% (125/138). In spite of some limitation owing especially to the choice of a self selected population sample, we conclude that Prima Lab Covid-19 IgG/IgM Rapid Test represents a low-cost, easily applicable and reproducible tool in detecting SARS-Cov-2 diffusion in the general population.

Matching journals

The top 7 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.