Abstract

As of June 1, 2023, the SARS-CoV-2 virus has infected ~700 million people and caused ~7 million deaths worldwide. During the pandemic two types of diagnostic testing were developed in an effort to identify infected people with the goal of limiting the spread of the COVID-19 disease: real-time, quantitative polymerase chain reactions (PCR) that detect the SARS-CoV-2 genome, and lateral flow assays (LFAs) that detect the SARS-CoV-2 nucleocapsid and/or the spike antigens. PCR is used to quantify infection in terms of cycles-to-threshold of detection (Ct) values using saliva or nasopharyngeal samples. Unfortunately, the test employs expensive reagents and instruments and the sample collection-to-result remains 1 to 2 days. In contrast, LFAs are inexpensive, can be used at home and provide yes/no infection information in 15 to 30 minutes. However, the home tests have two limitations: 1) they lack numerical data that indicates the person’s infectious level, and 2) the results are not automatically supplied to agencies that track the number and location of cases. The latter information is crucial to stopping outbreaks. In an effort to provide a product that has the advantages of both methods, we present the development of a smartphone App that correlates the intensities of the test line of at-home LFAs measured by a smartphone camera to their corresponding PCR measured Ct values, with the added capability of sharing results with health agencies. The correlation follows an Avrami equation and covers the Ct value range from 20 to 31. The smartphone App was used to predict the Ct values of 6 purchased samples measured as unknowns with an average Ct difference and standard deviation between predicted and actual values of 0.62±0.21. In use the smartphone App calculated Ct values can be used to categorize the level of infection as not-infected, infected, contagious, and most importantly, highly contagious. As such, the combination lateral flow assay and smartphone is well suited for identifying, quantifying, and slowing the spread of current and future corona and other viruses.