Long-term longitudinal evaluation of the prevalence of SARS-CoV-2 antibodies in healthcare and university workers.

Asymptomatic and pauci-symptomatic cases contribute to underestimating the prevalence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections. Moreover, we have few studies available on the longitudinal follow-up of SARS-CoV-2 antibodies after natural infection. We tested staff members of a Belgian tertiary academic hospital for SARS-CoV-2 IgG, IgM, and IgA antibodies. We analyzed the evolution of IgM and IgG after 6 weeks, and the persistence of IgG after 3 and 10 months. At the first evaluation, 409/3776 (10.8%) participants had a positive SARS-CoV-2 serology. Among initially seropositive participants who completed phases 2 and 3, IgM were still detected after 6 weeks in 53.1% and IgG persisted at 12 weeks in 82.0% (97.5% of those with more than borderline titers). IgG levels were higher and increased over time in symptomatic but were lower and stable in asymptomatic participants. After 10 months, 88.5% of participants had sustained IgG levels (97.0% of those with more than borderline titers).

AI-Based Chest CT Analysis for Rapid COVID-19 Diagnosis and Prognosis: A Practical Tool to Flag High-Risk Patients and Lower Healthcare Costs.

Early diagnosis of COVID-19 is required to provide the best treatment to our patients, to prevent the epidemic from spreading in the community, and to reduce costs associated with the aggravation of the disease. We developed a decision tree model to evaluate the impact of using an artificial intelligence-based chest computed tomography (CT) analysis software (icolung, icometrix) to analyze CT scans for the detection and prognosis of COVID-19 cases. The model compared routine practice where patients receiving a chest CT scan were not screened for COVID-19, with a scenario where icolung was introduced to enable COVID-19 diagnosis. The primary outcome was to evaluate the impact of icolung on the transmission of COVID-19 infection, and the secondary outcome was the in-hospital length of stay. Using EUR 20000 as a willingness-to-pay threshold, icolung is cost-effective in reducing the risk of transmission, with a low prevalence of COVID-19 infections. Concerning the hospitalization cost, icolung is cost-effective at a higher value of COVID-19 prevalence and risk of hospitalization. This model provides a framework for the evaluation of AI-based tools for the early detection of COVID-19 cases. It allows for making decisions regarding their implementation in routine practice, considering both costs and effects.

Predictive factors for the presence and long-term persistence of SARS-CoV-2 antibodies in healthcare and university workers.

While patient groups at risk for severe COVID-19 infections are now well identified, the risk factors associated with SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) transmission and immunization are still poorly understood. In a cohort of staff members of a Belgian tertiary academic hospital tested for SARS-CoV-2 antibodies during the early phase of the pandemic and followed-up after 6 weeks, 3 months and 10 months, we collected personal, occupational and medical data, as well as symptoms based on which we constructed a COVID-19 score. Seroprevalence was higher among participants in contact with patients or with COVID-19 confirmed subjects or, to a lesser extent, among those handling respiratory specimens, as well as among participants reporting an immunodeficiency or a previous or active hematological malignancy, and correlated with several symptoms. In multivariate analysis, variables associated with seropositivity were: contact with COVID-19 patients, immunodeficiency, previous or active hematological malignancy, anosmia, cough, nasal symptoms, myalgia, and fever. At 10 months, participants in contact with patients and those with higher initial COVID-19 scores were more likely to have sustained antibodies, whereas those with solid tumors or taking chronic medications were at higher risk to become seronegative.