Asia Pacific perspectives on the second year of the COVID-19 pandemic: A follow-up survey.

BACKGROUND: The Coronavirus disease 2019 (COVID-19) pandemic is currently in its third year. This follow-up survey was commissioned by the Asia Pacific Association of Allergy Asthma and Clinical Immunology (APAAACI) Task Force on COVID-19 to compare and contrast changes in the epidemiology, clinical profile, therapeutics and public health measures of the pandemic in the Asia Pacific region. METHODS: A questionnaire-based survey comprising 32 questions was electronically sent out to all 15 member countries of APAAACI using Survey Monkey® from 1 December 2021 to 28 February 2022. RESULTS: Seventeen responses were received from 14/15 (93.4%) member countries and 3 individual members. Mild-to-moderate COVID-19 predominated over severe infection, largely contributed by COVID-19 vaccination programmes in the region. The incidence of vaccine adverse reactions in particular anaphylaxis from messenger ribonucleic acid (mRNA) vaccines was no longer as high as initially anticipated, although perimyocarditis remains a concern in younger males. Novel therapeutics for mild-to-moderate disease including neutralizing antibodies casirivimab/imdevimab (REGEN-COV®) and sotrovimab (Xevudy®), anti-virals Paxlovid® (nirmatrelvir and ritonavir) and Molnupiravir pre-exposure prophylaxis for high-risk persons with Tixagevimab and Cilgavimab (Evusheld) are now also available to complement established therapeutics (e.g., remdesivir, dexamethasone and baricitinib) for severe disease. In the transition to endemicity, public health measures are also evolving away from containment/elimination strategies. CONCLUSIONS: With access to internationally recommended standards of care including public health preventive measures, therapeutics and vaccines among most APAAACI member countries, much progress has been made over the 2-year period in minimizing the morbidity and mortality from COVID-19 disease.

Depressive Symptoms Feature-Based Machine Learning Approach to Predicting Depression Using Smartphone.

With the impact of the COVID-19 pandemic, the number of patients suffering from depression is rising around the world. It is important to diagnose depression early so that it may be treated as soon as possible. The self-response questionnaire, which has been used to diagnose depression in hospitals, is impractical since it requires active patient engagement. Therefore, it is vital to have a system that predicts depression automatically and recommends treatment. In this paper, we propose a smartphone-based depression prediction system. In addition, we propose depressive features based on multimodal sensor data for predicting depressive mood. The multimodal depressive features were designed based on depression symptoms defined in the Diagnostic and Statistical Manual of Mental Disorders (DSM-5). The proposed system comprises a "Mental Health Protector" application that collects data from smartphones and a big data-based cloud platform that processes large amounts of data. We recruited 106 mental patients and collected smartphone sensor data and self-reported questionnaires from their smartphones using the proposed system. Finally, we evaluated the performance of the proposed system's prediction of depression. As the test dataset, 27 out of 106 participants were selected randomly. The proposed system showed 76.92% on an f1-score for 16 patients with depression disease, and in particular, 15 patients, 93.75%, were successfully predicted. Unlike previous studies, the proposed method has high adaptability in that it uses only smartphones and has a distinction of evaluating prediction accuracy based on the diagnosis.

Age-Specific Characteristics of Adult and Pediatric Respiratory Viral Infections: A Retrospective Single-Center Study.

This study aimed to identify age-specific characteristics of respiratory viral infections. Hospitalized patients with confirmed viral respiratory infections were included in the sample. The patients were divided into the pediatric group (<19 years old) and the adult group (≥19 years old). The groups were then subdivided based on age: 0-6, 7-12, 13-18, 19-49, 50-64, and ≥65 years old. These groups were compared to evaluate the differences in the pattern of respiratory viral infections. Among a total of 4058 pediatric patients (mean age 3.0 ± 2.9 years, n = 1793 females), 2829 (48.9%) had mono-infections, while 1229 (51.1%) had co-infections. Co-infections were the most common in the 0-6-year-old group (31.6%). Among 1550 adult patients (mean age 70.2 ± 15.3 years, n = 710 females), 1307 (85.6%) had mono-infections and 243 (14.4%) had co-infections. Co-infections were most common in the ≥65-year-old group (16.8%). Viral infection and co-infection rates decreased with age in pediatric patients but increased with increasing age in adults. In pediatric patients, the rates of viral infections and co-infections were high; the rate of co-infections was higher in younger patients. In adult patients, the rates of viral infections and co-infections were lower than those in pediatric patients; the rate of co-infections was higher in older patients.

Analysis of the Association Among Air Pollutants, Allergenic Pollen, and Respiratory Virus Infection of Children in Guri, Korea During Recent 5 Years.

PURPOSE: Concerns about the spread of infectious diseases have increased due to the coronavirus disease pandemic. Knowing the factors that exacerbate or increase the contagiousness of a virus could be a key to pandemic prevention. Therefore, we investigated whether the pandemic potential of infectious diseases correlates with the concentration of atmospheric substances. We also investigated whether environmental deterioration causes an increase in viral infections. METHODS: Pediatric patients (0-18 years old; n = 6,223) were recruited from those hospitalized for aggravated respiratory symptoms at Hanyang University Guri Hospital between January 1, 2015 and December 31, 2019. The number of viral infections was defined as the total number of virus-infected patients hospitalized for respiratory symptoms. We analyzed the association between the number of viral infections/week and the average concentrations of atmospheric substances including particulate matter (PM)10, PM2.5, O3, NO2, CO, SO2, and allergenic pollen) for that week. The cross-correlation coefficient between the weekly measures of pollens and viral infections was checked to determine which time point had the most influence. The association of atmospheric substances in that time, with the number of viral infections/week was investigated using multiple linear regression analysis to identify factors with the greatest influence. RESULTS: In spring the tree pollen average concentration one week earlier (t-1) had the greatest correlation with the average virus infection of a given week (t) (ρXY (h) =0.5210). The number of viral infections showed a statistically significant correlation with especially tree pollen concentration of 1 week prior (adj R²=0.2280). O3 concentration was correlated to the number of viral infections within that week (adj R²=0.2552) in spring, and weed pollen and CO concentration correlated (adj R²=0.1327) in autumn. CONCLUSIONS: Seasonal co-exposure to air pollutants and allergenic pollens may enhance respiratory viral infection susceptibility in children. Therefore, reducing the concentrations of air pollutants and pollens may help prevent future epidemics.