T he scientific, academic, medical and data science communities have come together in the face of the COVID-19 pandemic crisis to rapidly assess novel paradigms in artificial intelligence (AI) that are rapid and secure, and potentially incentivize data sharing and model training and testing without the usual privacy and data ownership hurdles of conventional collaborations 1,2 . Healthcare providers, researchers and industry have pivoted their focus to address unmet and critical clinical needs created by the crisis, with remarkable results [3][4][5][6][7][8][9] . Clinical trial recruitment has been expedited and facilitated by national regulatory bodies and an international cooperative spirit 10-12 . The data analytics and AI disciplines have always fostered open

of 200 words)In the age of a pandemic, such as the ongoing one caused by SARS-CoV-2, the world faces a limited supply of tests, personal protective equipment, and factories and supply chains are struggling to meet the growing demands. This study aimed to This article is protected by copyright. All rights reserved. Accepted Articleevaluate the efficacy of specimen pooling for testing of SARS-CoV-2 virus, to determine whether costs and resource savings could be achieved without impacting the sensitivity of the testing. Ten previously tested nasopharyngeal and throat swab specimens by real-time PCR, were pooled for testing, containing either one or two known positive specimens of varying viral concentrations. Specimen pooling did not affect the sensitivity of detecting SARS-CoV-2 when the PCR cycle threshold (Ct) of original specimen was lower than 35. In specimens with low viral load (Ct>35), 2 out of 15 pools (13.3%) were false negative. Pooling specimens to test for COVID-19 infection in low prevalence (≤1%) areas or in low risk populations can dramatically decrease the resource burden on laboratory operations by up to 80%. This paves the way for large-scale population screening, allowing for assured policy decisions by governmental bodies to ease lockdown restrictions in areas with a low incidence of infection, or with lower risk populations.

Background A greater understanding of the antibody response to SARS-CoV-2 in an infected population is important for the development of a vaccination. Aim To investigate SARS-CoV-2 IgA and IgG antibodies in Thai patients with differing severities of COVID-19. Methods Plasma from the following patient groups was examined: 118 adult patients with confirmed SARS-CoV-2 infections, 49 patients under investigation (without confirmed infections), 20 patients with other respiratory infections, and 102 healthy control patients. Anti-SARS-CoV-2 enzyme-linked immunosorbent assay (ELISA) from EUROIMMUN was performed to assess for IgA and IgG antibodies. The optical density (OD) ratio cutoff for a positive result was 1.1 for IgA and 0.8 for IgG. Additionally, the association of the antibody response with both the severity of disease and the date after onset of symptoms was analyzed. Results A total of 289 participants were enrolled and 384 samples analyzed from March 10 to May 31, 2020. Patients were categorized, based on their clinical manifestations, as mild (n = 59), moderate (n = 27), or severe (n = 32). The overall sensitivity of IgA and IgG from the