Laboratory diagnosis of emerging human infections by SARS-COVID-19: Prevalence and challenges

The COVID-19 pandemic has created a global storm in the world, and nations worldwide are skirmishing with this unprecedented health crisis. The outbreak of Corona Virus Disease-19 (COVID-19), caused by Severe Acute Respiratory Syndrome Corona Virus-2 (SARS-CoV-2), had a significant impact on the healthcare system, especially in the clinical microbiology laboratories worldwide. The choice of a correct anatomical site for good samples collections with the proper precautions is essential for prompt and accurate diagnosis of COVID-19. This review aimed to cover the challenges faced during the choice of appropriate sample collection sites, transport and tests for detection of SARS-CoV-2 infection. The diagnosis tests of COVID-19 can be divided into direct, indirect and complementary tests. In the direct tests, Real-time polymerase chain reaction (RT-PCR) assays are the molecular tests of choice for the diagnosis of COVID-19. The remaining direct tests include GeneXpert and TrueNAT assays. In the indirect testing's;antigen-antibody-based techniques are recommended for surveillance of the disease, which may help to formulate the control measures. These tests not only help in assessing the disease severity, but also they benefit in evaluating the prognosis and management strategies. © 2022, Egyptian Association for Medical Mycologists (EAMM). All rights reserved.

PRS24 Utilizing Blue Cross Blue Shield of Louisiana (BCBSLA) Risk of Hospitalization (ROH) AI Predictive Model to Help Louisiana Identify Patients at High Risk for a COVID-19 Hospital Admission

Objectives: Advanced modeling techniques have been employed by BCBSLA to predict the risk of hospitalization (ROH) among its members. BCBSLA noted a strong association between members who were predicted as “high risk” in their ROH AI Predictive Model and members who actually had a COVID-19 admission. As a result, BCBSLA was asked to create a simplified model that could extend to the entire state of Louisiana knowing that detailed member data would not be available to score Louisiana’s entire population. Methods: The current ROH model employed by BCBSLA for its members was simplified for State use by focusing on available health factors that could be easily assessed. The simplified model was tested using 2019 BCBSLA membership to predict all future hospitalizations between Jan-Jun 2020. Results: The factors chosen for the new simplified model were age, comorbid conditions (diseases of the circulatory system, Hypertension, etc.) and particular events such as hospital or skilled nursing home facility admission within the past 12 months. The simplified model was shown to be highly predictive of future all-cause hospitalizations. The top 20% of predicted high risk members accounted for 70% of all admissions;AUC was very good at 0.89. The model was also predictive of COVID-19 admissions on a naïve population. The top 20% of members captured nearly 50% of COVID-19 admissions, AUC 0.74. The model performance was good considering early COVID-19 admissions were likely misclassified in claims data. Conclusions: Using simplified rules, BCBSLA was able to modify their current ROH model so that Louisiana’s health department could identify patients who would be at the highest risk for hospitalized if they contracted COVID-19.

Perceived vulnerability of job loss and satisfaction with life in the hospitality sector in times of pandemic: a multi-mediational approach

Purpose: The COVID-19 pandemic has severely impacted business and viability of firms in the hospitality sector. This paper aims to examine the impact of perceived vulnerability of employees in this sector related to job loss and satisfaction with life. Additionally, it tests whether the impact is reduced for an individual possessing high emotional and financial well-being. Design/methodology/approach: This study uses cross-sectional data obtained through a survey of 312 hospitality sector employees. Using PLS-SEM, hypothesized relationships between constructs are tested. Findings: Perceived vulnerability of job loss negatively impacts satisfaction with life;however, this negative impact gets significantly reduced in the presence of emotional and financial well-being. Research limitations/implications: The results provide an impetus to focus on emotional and financial well-being to reduce employees’ vulnerabilities and improve their life satisfaction. In the absence of specific relief programs by the Government and with reduced business activity, employers need to look for innovative ways for ensuring their own sustenance and employee well-being. Originality/value: This study is one of the initial works on examining how perceived vulnerability of job loss induced by the pandemic on hospitality sector employees’ impacts their satisfaction with life. It also makes a novel attempt to examine emotional well-being and financial well-being, as mediators in this relationship. © 2021, Emerald Publishing Limited.