Understanding Rhinovirus Circulation and Impact on Illness

Rhinoviruses (RVs) have been reported as one of the main viral causes for severe respiratory illnesses that may require hospitalization, competing with the burden of other respiratory viruses such as influenza and RSV in terms of severity, economic cost, and resource utilization. With three species and 169 subtypes, RV presents the greatest diversity within the Enterovirus genus, and despite the efforts of the research community to identify clinically relevant subtypes to target therapeutic strategies, the role of species and subtype in the clinical outcomes of RV infection remains unclear. This review aims to collect and organize data relevant to RV illness in order to find patterns and links with species and/or subtype, with a specific focus on species and subtype diversity in clinical studies typing of respiratory samples.

A 2-Gene Host Signature for Improved Accuracy of COVID-19 Diagnosis Agnostic to Viral Variants

The continued emergence of SARS-CoV-2 variants is one of several factors that may cause false negative viral PCR test results. Such tests are also susceptible to false positive results due to trace contamination from high viral titer samples. Host immune response markers provide an orthogonal indication of infection that can mitigate these concerns when combined with direct viral detection. Here, we leverage nasopharyngeal swab RNA-seq data from patients with COVID-19, other viral acute respiratory illnesses and non-viral conditions (n=318) to develop support vector machine classifiers that rely on a parsimonious 2-gene host signature to predict COVID-19. Optimal classifiers achieve an area under the receiver operating characteristic curve (AUC) greater than 0.9 when evaluated on an independent RNA-seq cohort (n=553). We show that a classifier relying on a single interferon-stimulated gene, such as IFI6 or IFI44, measured in RT-qPCR assays (n=144) achieves AUC values as high as 0.88. Addition of a second gene, such as GBP5, significantly improves the specificity compared to other respiratory viruses. The performance of a clinically practical 2-gene RT-qPCR classifier is robust across common SARS-CoV-2 variants, including Omicron, and is unaffected by cross-contamination, demonstrating its utility for improving accuracy of COVID-19 diagnostics.

Effect of Dehydrated Bovine Colostrum upon Immunity and Development of Dorper Lambs

Background: Ruminants, during the newborn stage, are considered as agammaglobulinemic (calves and buffalos) or hypogammaglobulinemic (kids and lambs), where the colostrum intake is important for the decrease of illness incidence, an adequate development and a low peripartum mortality. The aim was to evaluate the use of dehydrated bovine colostrum as an alternative to natural ovine colostrum upon de development and immunity of Dorper lambs. Methods: A total of 35 lambs, divided in two groups, one (CN; n=17) fed with natural colostrum directly from the mother, the second (CB; n=18) fed with a colostrum substitute based on dehydrated bovine colostrum, were used. Result: The colostrum quality was better for the CN group regarding lipids, CP, density, solids and fat when compared to the CB (p less than 0.05). Glucose levels were higher in the CN than the CB 24 h after colostrum administration (116 mg/dl and 97 mg/dl, respectively; p less than 0.05). There were no diarrheas or respiratory illnesses in lambs from both groups at 24 h after birth (p greater than 0.05). Maybe, the use of bovine dehydrated colostrum transfers a similar immunization than natural colostrum, which generated a low incidence of respiratory and metabolic illnesses and a good body development.

Performance of the EQ-5D-Y Interviewer Administered Version in Young Children

(1) Background: An estimated 78% of South African children aged 9–10 years have not mastered basic reading, therefore potentially excluding them from self-reporting on health-related outcome measures. Thus, the aim of this study was to compare the performance of the EQ-5D-Y-3L self-complete to the newly developed interviewer-administered version in children 8–10 years. (2) Methods: Children (n = 207) with chronic respiratory illnesses, functional disabilities, orthopaedic conditions and from the general population completed the EQ-5D-Y-3L self-complete and interviewer-administered versions, Moods and Feelings Questionnaire (MFQ) and Faces Pain Scale-Revised (FPS-R). A functional independence measure (WeeFIM) was completed by the researcher. (3) Results: The 8-year-olds had significantly higher missing responses (x2 = 14.23, p < 0.001) on the self-complete version. Known-group and concurrent validity were comparable across dimensions, utility and VAS scores for the two versions. The dimensions showed low to moderate convergent validity with similar items on the MFQ, FPS-R and WeeFIM with significantly higher correlations between the interviewer-administered dimensions of Mobility and WeeFIM mobility total (z = 1.91, p = 0.028) and Looking After Myself and WeeFIM self-care total (z = 3.24, p = 0.001). Children preferred the interviewer-administered version (60%) (x2 = 21.87, p < 0.001) with 22% of the reasons attributed to literacy level. (4) Conclusions: The EQ-5D-Y-3L interviewer-administered version is valid and reliable in children aged 8–10 years. The results were comparable to the self-complete version indicating that versions can be used interchangeably.

Using machine learning to examine drivers of inappropriate outpatient antibiotic prescribing in acute respiratory illnesses

Using a machine-learning model, we examined drivers of antibiotic prescribing for antibiotic-inappropriate acute respiratory illnesses in a large US claims data set. Antibiotics were prescribed in 11% of the 42 million visits in our sample. The model identified outpatient setting type, patient age mix, and state as top drivers of prescribing.

A 2-Gene Host Signature for Improved Accuracy of COVID-19 Diagnosis Agnostic to Viral Variants

The continued emergence of SARS-CoV-2 variants is one of several factors that may cause false negative viral PCR test results. Such tests are also susceptible to false positive results due to trace contamination from high viral titer samples. Host immune response markers provide an orthogonal indication of infection that can mitigate these concerns when combined with direct viral detection. Here, we leverage nasopharyngeal swab RNA-seq data from patients with COVID-19, other viral acute respiratory illnesses and non-viral conditions (n=318) to develop support vector machine classifiers that rely on a parsimonious 2-gene host signature to predict COVID-19. Optimal classifiers achieve an area under the receiver operating characteristic curve (AUC) greater than 0.9 when evaluated on an independent RNA-seq cohort (n=553). We show that a classifier relying on a single interferon-stimulated gene, such as IFI6 or IFI44, measured in RT-qPCR assays (n=144) achieves AUC values as high as 0.88. Addition of a second gene, such as GBP5, significantly improves the specificity compared to other respiratory viruses. The performance of a clinically practical 2-gene RT-qPCR classifier is robust across common SARS-CoV-2 variants, including Omicron, and is unaffected by cross-contamination, demonstrating its utility for improving accuracy of COVID-19 diagnostics.

Pandemic-related declines in hospitalization for non-COVID-19-related illness in the United States from January through July 2020

Background The COVID-19 pandemic, caused by the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has substantially impacted healthcare utilization worldwide. The objective of this retrospective analysis of a large hospital discharge database was to compare all-cause and cause-specific hospitalizations during the first six months of the pandemic in the United States with the same months in the previous four years. Methods Data were collected from all hospitals in the Premier Healthcare Database (PHD) and PHD Special Release reporting hospitalizations from January through July for each year from 2016 through 2020. Hospitalization trends were analyzed stratified by age group, major diagnostic categories (MDCs), and geographic region. Results The analysis included 286 hospitals from all 9 US Census divisions. The number of all-cause hospitalizations per month was relatively stable from 2016 through 2019 and then fell by 21% (57,281 fewer hospitalizations) between March and April 2020, particularly in hospitalizations for non-respiratory illnesses. From April onward there was a rise in the number of monthly hospitalizations per month. Hospitalizations per month, nationally and in each Census division, decreased for 20 of 25 MDCs between March and April 2020. There was also a decrease in hospitalizations per month for all age groups between March and April 2020 with the greatest decreases in hospitalizations observed for patients 50–64 and ≥65 years of age. Conclusions Rates of hospitalization declined substantially during the first months of the COVID-19 pandemic, suggesting delayed routine, elective, and emergency care in the United States. These lapses in care for illnesses not related to COVID-19 may lead to increases in morbidity and mortality for other conditions. Thus, in the current stage of the pandemic, clinicians and public-health officials should work, not only to prevent SARS-CoV-2 transmission, but also to ensure that care for non-COVID-19 conditions is not delayed.

Psychological Predictors of Self-reported COVID-19 Outcomes: Results From a Prospective Cohort Study

Background Previous research has shown that psychological factors, such as stress and social support, are associated with greater susceptibility to viral respiratory illnesses and more severe symptoms. During the COVID-19 pandemic there has been a well-documented deterioration in psychological well-being and increased social isolation. This raises questions as to whether those experiencing psychological adversity during the pandemic are more at risk of contracting and/or experiencing COVID-19 symptoms. Purpose To examine the relationship between psychological factors and the risk of COVID-19 self-reported infection and the symptomatic experience of SARS-CoV-2 (indicated by the number and severity of symptoms). Methods As part of a longitudinal prospective observational cohort study, 1,087 adults completed validated measures of psychological well-being during April 2020 and self-reported incidence of COVID-19 infection and symptom experience across the pandemic through to December 2020. Regression models were used to explore these relationships controlling for demographic and occupational factors. Results Greater psychological distress during the early phase of the pandemic was significantly associated with subsequent self-reported SARS-CoV-2 infection as well as the experience of a greater number and more severe symptoms. Conclusions COVID-19 infection and symptoms may be more common among those experiencing elevated psychological distress. Further research to elucidate the mechanisms underlying these associations is needed.