Intra-host mutation rate of acute SARS-CoV-2 infection during the initial pandemic wave.

SARS-CoV-2 mutation is minimized through a proofreading function encoded by NSP-14. Most estimates of the SARS-CoV-2 mutation rate are derived from population based sequence data. Our understanding of SARS-CoV-2 evolution might be enhanced through analysis of intra-host viral mutation rates in specific populations. Viral genome analysis was performed between paired samples and mutations quantified at allele frequencies (AF) ≥ 0.25, ≥ 0.5 and ≥ 0.75. Mutation rate was determined employing F81 and JC69 evolution models and compared between isolates with (ΔNSP-14) and without (wtNSP-14) non-synonymous mutations in NSP-14 and by patient comorbidity. Forty paired samples with median interval of 13 days [IQR 8.5-20] were analyzed. The estimated mutation rate by F81 modeling was 93.6 (95%CI 90.8-96.4], 40.7 (95%CI 38.9-42.6) and 34.7 (95%CI 33.0-36.4) substitutions/genome/year at AF ≥ 0.25, ≥ 0.5, ≥ 0.75 respectively. Mutation rate in ΔNSP-14 were significantly elevated at AF ≥ 0.25 vs wtNSP-14. Patients with immune comorbidities had higher mutation rate at all allele frequencies. Intra-host SARS-CoV-2 mutation rates are substantially higher than those reported through population analysis. Virus strains with altered NSP-14 have accelerated mutation rate at low AF. Immunosuppressed patients have elevated mutation rate at all AF. Understanding intra-host virus evolution will aid in current and future pandemic modeling.

Factors Affecting Self-Harm- or Violence-Related Urgent Psychiatric Consultation During the COVID-19 Pandemic in Taiwan.

Purpose: People's health-care-seeking behaviors considerably changed during the COVID-19 pandemic. This study evaluated the changes in self-harm- and violence-related urgent psychiatric consultation (UPC) in the emergency department (ED) during different stages of the pandemic and at different levels of hospitals. Patients and Methods: We recruited patients who received UPC during the baseline (2019), peak (2020), and slack (2021) periods of the same time window (calendar weeks 4-18) during the COVID-19 pandemic. Demographic data such as age, sex, and referral type (by the police/emergency medical system) were also recorded. Results: We found female gender and younger age associated with higher risk of self-harm-related UPCs, whereas patients visiting regional hospitals, male patients, and patients referred by the policy/emergency medical system, had a higher risk of violence-related UPCs. After adjustment, the different pandemic stages were not significantly associated with self-harm- or violence-related UPCs. Conclusion: Patient's demographic data, but not the pandemic itself, may be responsible for the changes in self-harm- and violence-related UPCs during the pandemic.

Facile and Unplugged Surface Plasmon Resonance Biosensor with NIR-Emitting Perovskite Nanocomposites for Fast Detection of SARS-CoV-2.

The emergence of the coronavirus disease 2019 (COVID-19) pandemic prompted researchers to develop portable biosensing platforms, anticipating to detect the analyte in a label-free, direct, and simple manner, for deploying on site to prevent the spread of the infectious disease. Herein, we developed a facile wavelength-based SPR sensor built with the aid of a 3D printing technology and synthesized air-stable NIR-emitting perovskite nanocomposites as the light source. The simple synthesis processes for the perovskite quantum dots enabled low-cost and large-area production and good emission stability. The integration of the two technologies enabled the proposed SPR sensor to exhibit the characteristics of lightweight, compactness, and being without a plug, just fitting the requirements of on-site detection. Experimentally, the detection limit of the proposed NIR SPR biosensor for refractive index change reached the 10-6 RIU level, comparable with that of state-of-the-art portable SPR sensors. In addition, the bio-applicability of the platform was validated by incorporating a homemade high-affinity polyclonal antibody toward the SARS-CoV-2 spike protein. The results demonstrated that the proposed system was capable of discriminating between clinical swab samples collected from COVID-19 patients and healthy subjects because the used polyclonal antibody exhibited high specificity against SARS-CoV-2. Most importantly, the whole measurement process not only took less than 15 min but also needed no complex procedures or multiple reagents. We believe that the findings disclosed in this work can open an avenue in the field of on-site detection for highly pathogenic viruses.

The ascendancy of research in acronyms related to COVID-19 displayed on a growth-share matrix (GSM): Bibliometric analysis.

BACKGROUND: The acronym COVID, which stands for coronavirus disease, has become one of the most infamous acronyms in the world since 2020. An analysis of acronyms in health and medical journals has previously found that acronyms have become more common in titles and abstracts over time (e.g., DNA and human immunodeficiency virus are the most common acronyms). However, the trends in acronyms related to COVID remain unclear. It is necessary to verify whether the dramatic rise in COVID-related research can be observed by visualizations. The purpose of this study was to display the acronym trends in comparison through the use of temporal graphs and to verify that the COVID acronym has a significant edge over the other 2 in terms of research dominance. METHODS: An analysis of the 30 most frequently used acronyms related to COVID in PubMed since 1950 was carried out using 4 graphs to conduct this bibliometric analysis, including line charts, temporal bar graphs (TBGs), temporal heatmaps (THM), and growth-share matrices (GSM). The absolute advantage coefficient (AAC) was used to measure the dominance strength for COVID acronym since 2020. COVID's AAC trend was expected to decline over time. RESULTS: This study found that COVID, DNA, and human immunodeficiency virus have been the most frequently observed research acronyms since 2020, followed by computed tomography and World Health Organization; although there is no ideal method for displaying acronym trends over time, researchers can utilize the GSM to complement traditional line charts, TBGs, and THMs, as shown in this study; and COVID has a significant edge over the other 2 in terms of research dominance by ACC (≥0.67), but COVID's AAC trend has declined (e.g., AACs 0.83, 0.80, and 0.69) since 2020. CONCLUSIONS: It is recommended that the GSM complement traditional line charts, TBGs, and THMs in trend analysis, rather than being restricted to acronyms in future research. This research provides readers with the AAC to understand how research dominates its counterparts, which will be useful for future bibliometric analyses.

The Impact of a Lockdown for the COVID-19 Pandemic on Seasonal HbA1c Variation in Patients with Type 2 Diabetes.

Glycemic control in patients with type 2 diabetes may be disrupted due to restricted medical service access and lifestyle changes during COVID-19 lockdown period. This retrospective cohort study examined changes of HbA1c levels in adults with type 2 diabetes 12 weeks before and after May 19 in 2021, the date that COVID-19 lockdown began in Taiwan. The mean levels of HbA1c-after were significantly lower than HbA1c-before in 2019 (7.27 ± 1.27% vs 7.43 ± 1.38%, p < 0.001), 2020 (7.27 ± 1.28% vs 7.37 ± 1.34%, p < 0.001), and 2021 (7.03 ± 1.22% vs 7.17 ± 1.29%, p < 0.001). Considering the seasonal variation of HbA1c, ΔHbA1c values (HbA1c-after minus HbA1c-before) in 2020 (with sporadic COVID-19 cases and no lockdown) were not significantly different from 2021 (regression coefficient [95% CI] = 0.01% [-0.02%, 0.03%]), while seasonal HbA1c variation in 2019 (no COVID-19) was significantly more obvious than in 2021 (-0.05% [-0.07, -0.02%]). In conclusion, HbA1c level did not deteriorate after a lockdown measure during the COVID-19 pandemic in Taiwan. However, the absolute seasonal reduction in HbA1c was slightly less during the COVID-19 pandemic compared with the year without COVID-19.

Digital health literacy and well-being among university students: Mediating roles of fear of COVID-19, information satisfaction, and internet information search.

Background: Digital health literacy (DHL) enables healthy decisions, improves protective behaviors and adherence to COVID-19 measures, especially during the era of the "infodemic", and enhances psychological well-being. Objective: We aimed to explore the mediating roles of fear of COVID-19, information satisfaction, and the importance of online information searching on the association between DHL and well-being. Methods: A cross-sectional web-based survey was conducted among 1631 Taiwanese university students, aged 18 years and above, from June 2021 to March 2022. The collected data include sociodemographic characteristics (sex, age, social status, and financial satisfaction), the importance of online information searching, information satisfaction, fear of COVID-19, DHL, and well-being. A linear regression model was utilized to investigate factors associated with well-being, followed by a pathway analysis to assess the direct and indirect relationship between DHL and well-being. Results: The scores of DHL and overall well-being were 3.1 ± 0.4 and 74.4 ± 19.7, respectively. Social status (B = 2.40, 95% confidence interval (CI) 1.73-3.07, p < 0.001), DHL (B 0.29, 95% CI 0.10-0.49, p < 0.001), importance of online information searching (B = 0.78, 95% CI 0.38-1.17, p < 0.001), and information satisfaction (B = 3.59, 95% CI 2.22-4.94, p < 0.001) were positively associated with well-being, whereas higher fear of COVID-19 scores (B = -0.38, 95% CI -0.55-(-0.21), p < 0.001) and female (B = -2.99, 95% CI -5.02-0.6, p = 0.004) were associated with lower well-being, when compared with lower fear scores and male, respectively. Fear of COVID-19 (B = 0.03, 95% CI 0.016-0.04, p < 0.001), importance of online information searching (B = 0.03, 95% CI 0.01-0.05, p = 0.005), and information satisfaction (B = 0.05, 95% CI 0.023-0.067, p < 0.001) were significantly mediated the relationship between DHL and well-being. Conclusion: Higher DHL scores show direct and indirect associations with higher well-being scores. Fear, importance of online information searching, and information satisfaction significantly contributed to the association.

Factors associated with viral rebound among COVID-19 patients receiving oral antivirals.

BACKGROUND: COVID-19 rebound is usually reported among patients experiencing concurrent symptomatic and viral rebound. But longitudinal viral RT-PCR results from early stage to rebound of COVID-19 was less characterized. Further, identifying the factors associated with viral rebound after nirmatrelvir-ritonavir (NMV/r) and molnupiravir may expand understanding of COVID-19 rebound. METHODS: We retrospectively analyzed clinical data and sequential viral RT-PCR results from COVID-19 patients receiving oral antivirals between April and May, 2022. Viral rebound was defined by the degree of viral load increase (ΔCt ≥ 5 units). RESULTS: A total of 58 and 27 COVID-19 patients taking NMV/r and molnupiravir, respectively, were enrolled. Patients receiving NMV/r were younger, had fewer risk factors for disease progression and faster viral clearance rate compared to those receiving molnupiravr (All P < 0.05). The overall proportion of viral rebound (n = 11) was 12.9%, which was more common among patients receiving NMV/r (10 [17.2%] vs. 1 [3.7%], P = 0.16). Of them, 5 patients experienced symptomatic rebound, suggesting the proportion of COVID-19 rebound was 5.9%. The median interval to viral rebound was 5.0 (interquartile range, 2.0-8.0) days after completion of antivirals. Initial lymphopenia (<0.8 × 109/L) was associated with viral rebound among overall population (adjusted odds ratio [aOR], 5.34; 95% confidence interval [CI], 1.33-21.71), and remained significant (aOR, 4.50; 95% CI, 1.05-19.25) even when patients receiving NMV/r were considered. CONCLUSION: Our data suggest viral rebound after oral antivirals may be more commonly observed among lymphopenic individuals in the context of SARS-CoV-2 Omicron BA.2 variant.

What role does mindfulness play in regulating fear of COVID-19 and associated mental health? The results of a cross-sectional study.

Objectives: The pandemic has greatly impacted people's lives and mental health. Therefore, it is now especially important to help people maintain good mental health. The positive effects of mindfulness-based practices on mental health have been demonstrated previously. However, no consensus has yet been reached on the potential mechanisms of mindfulness. This study adopted the two-component model of mindfulness to explain the relationships between fear of COVID-19, and mental health. We proposed the following hypothetical model: (1) fear of COVID-19 could affect orientation to experience; (2) orientation to experience could affect mental health. Directly; (3) fear of COVID-19 could mental health directly; (4) orientation to experience could be a mediator between fear of COVID-19 and mental health. Methods: We conducted an online survey in the present study. Three hundred and forty-four respondents were recruited to participate in the present study. After informed consent, they completed the questionnaires on the websites. The participants were asked to complete a questionnaire including the Beck Depression Inventory-II, Beck Anxiety Inventory, the Taiwan version of the Five Facet Mindfulness Questionnaire, and the Fear of COVID-19 Scale. Descriptive analysis and structural equation modeling were used to analyze the data and examine the goodness-of-fit indices. Results: Our results not only showed orientation to experience playing as a mediator between fear of COVID-19 and mental health; but also confirmed the roles of nonjudgment and nonreactivity in regulating emotions. Conclusion: Experimentation and longitudinal study could be applied to examine the roles of nonjudgment and nonreactivity in the future.

Effect of mask coverage on face identification in Taiwanese men and women.

Mask wearing is the easiest and most effective way to avoid COVID-19 infection; however, it affects interpersonal activities, especially face identification. This study examined the effects of three mask coverage levels (full coverage, FC; coverage up to the middle [MB] or bottom of the nose bridge [BB]) on face identification accuracy and time. A total of 115 university students (60 men and 55 women) were recruited to conduct a computer-based simulation test consisting of 30 questions (10 questions [five face images each of men and women] for the three mask coverage levels). One unmasked target face and four face images with a specified mask coverage level were designed for each question, and the participants were requested to select the same face from the four covered face images on the basis of the target face. The ANOVA results indicated that identification accuracy was significantly affected by sex (p < 0.01) and the mask coverage level (p < 0.001), whereas identification time was only influenced by sex (p < 0.05). The multiple comparison results indicated that the identification accuracy rate for faces wearing a mask with FC (90.3%) was significantly lower than for those wearing masks with coverage up to the MB (93.7%) and BB (94.9%) positions; however, no difference in identification accuracy rate was observed between the MB and BB levels. Women exhibited a higher identification accuracy rate than men (94.1% vs. 91.9%) in identifying unfamiliar faces, even though they may spend less time identifying the images. A smaller mask coverage level (i.e., the BB level) does not facilitate face identification. The findings can be served as a reference for people to trade-off between wearing a mask and interpersonal interaction in their daily activities.

Perceived Stress, Hope, and Health Outcomes Among Medical Staff in China During the COVID-19 Pandemic.

This study investigated the buffering role of hope between perceived stress and health outcomes among front-line medical staff treating patients with suspected COVID-19 infection in Shenzhen, China. In the cross-sectional study with online questionnaires, medical staff's perceived stress, anxiety, depression, sleep quality, and hope were measured by the 10-item Chinese Perceived Stress Scale, Hospital Anxiety and Depression Scale, the Pittsburgh Sleep Quality Index, and the Locus-of-Hope Scale, respectively. A total of 319 eligible front-line medical staff participated. The prevalence of anxiety (29.70%), depression (28.80%), poor sleep quality (38.90%) indicated that a considerable proportion of medical staff experienced mood and sleep disturbances during the COVID-19 pandemic. Internal locus-of-hope significantly moderated the effects of stress on anxiety, depression, and sleep quality. Moreover, external family locus-of-hope and external peer locus-of-hope significantly moderated the association between perceived stress and depression. The prevalence of symptoms indicates that both mental and physical health outcomes of front-line medical staff deserve more attention. Internal and external locus-of-hope functioned differently as protective factors for medical staffs' health and might be promising targets for intervention.

Alpha to Omicron: Disease Severity and Clinical Outcomes of Major SARS-CoV-2 Variants.

BACKGROUND: Four SARS-CoV-2 variants predominated in the United States since 2021. Understanding disease severity related to different SARS-CoV-2 variants remains limited. METHOD: Viral genome analysis was performed on SARS-CoV-2 clinical isolates circulating March 2021 through March, 2022 in Cleveland, Ohio. Major variants were correlated with disease severity and patient outcomes. RESULTS: 2779 patients identified with either alpha (N = 1153), gamma (N = 122), delta (N = 808) or omicron variants (N = 696) were selected for analysis. No difference in frequency of hospitalization, ICU admission, and death were found among alpha, gamma, and delta variants. However, patients with omicron infection were significantly less likely to be admitted to the hospital, require oxygen, or admission to the ICU (X2 = 12.8 p < 0.001, X2 = 21.6 p < 0.002, X2 = 9.6 p = 0.01, respectively). In patients whose vaccination status was known, a substantial number had breakthrough infections with delta or omicron variants (218/808 [26.9%] and 513/696 [73.7%], respectively). In breakthrough infections, hospitalization rate was similar regardless of variant by multivariate analysis. No difference in disease severity was identified between omicron sub-variants BA.1 and BA.2. CONCLUSIONS: Disease severity associated with alpha, gamma, and delta variants is comparable while omicron infections are significantly less severe. Breakthrough disease is significantly more common in patients with omicron infection.

Evolution of anti-SARS-CoV-2 spike protein titers after two-dose of COVID-19 vaccination among people living with HIV.

Background: A community COVID-19 outbreak caused by the B.1.1.7 SARS-CoV-2 variant occurred in Taiwan in May 2021. High-risk populations such as people living with HIV (PLWH) were recommended to receive two doses of COVID-19 vaccines. While SARS-CoV-2 vaccines have demonstrated promising results in general population, real-world information on the serological responses remains limited among PLWH. Methods: PLWH receiving the first dose of SARS-CoV-2 vaccine from 2020 to 2021 were enrolled. Determinations of anti-SARS-CoV-2 spike IgG titers were performed every one to three months, the third dose of the SARS-CoV-2 vaccine or confirmed SARS-CoV-2 infection. All serum samples were tested for anti-nucleocapsid antibody and those tested positive were excluded from analysis. Results: A total of 1189 PLWH were enrolled: 829 (69.7%) receiving two doses of the AZD1222 vaccine, 232 (19.5%) of the mRNA-1273 vaccine, and 128 (10.8%) of the BNT162b2 vaccine. At all time-points, PLWH receiving two doses of mRNA vaccines had consistently higher antibody levels than those receiving the AZD1222 vaccine (p <0.001 for all time-point comparisons). Factors associated with failure to achieve an anti-spike IgG titer >141 BAU/mL within 12 weeks, included type 2 diabetes mellitus (DM) (adjusted odds ratio [aOR], 2.24; 95% CI, 1.25-4), a CD4 T cell count <200 cells/mm3 upon receipt of the first dose of vaccination (aOR, 3.43; 95% CI, 1.31-9) and two homologous AZD1222 vaccinations (aOR, 16.85; 95%CI, 10.13-28). For those receiving two doses of mRNA vaccines, factors associated with failure to achieve an anti-spike IgG titer >899 BAU/mL within 12 weeks were a CD4 T cell count <200 cells/mm3 on first-dose vaccination (aOR, 3.95; 95% CI, 1.08-14.42) and dual BNT162b2 vaccination (aOR, 4.21; 95% CI, 2.57-6.89). Conclusions: Two doses of homologous mRNA vaccination achieved significantly higher serological responses than vaccination with AZD1222 among PLWH. Those with CD4 T cell counts <200 cells/mm3 and DM had consistently lower serological responses.

The Benefits of Molnupiravir Treatment in Healthcare Facilities Patients with COVID-19.

Background: Molnupiravir (MOL) is an oral antiviral medication that has recently been treated for COVID-19. Objectively: We perform a prospective and observational study to elucidate the efficacy and safety of MOL in healthcare patients with COVID-19. Materials and Methods: A observational, non-randomized study of patients diagnosed with COVID-19 in 46 healthcare facilities and treated with MOL started within 5 days after the onset of signs or symptoms. We recorded data for all patients, including demographic data, clinical features, and symptoms. Treatment response was classified into cure, stable, hospitalization and death. Multivariate analysis was performed with stepwise logistic regression for hospitalization and death risk factors. Results: In total, 856 patients were diagnosed as having COVID-19 and treated with MOL during the study period. Of those, 496 patients (57.9%) were cured, 256 patients (29.9%) in stable condition, 104 patients (12.2%) hospitalized, and 22 patients (2.6%) died, respectively. There was significant effectiveness (87.8%) in COVID-19 patients using MOL. Multivariate analysis was performed to confirm the risk factors for hospitalization and death and included elder age (>80 years old) (odds ratio (OR) 2.2, 95% confidence interval (CI): 1.1-6.9), old cerebrovascular accident (CVA) (OR=4.1, 95% CI: 1.3-9.9), the presence of diabetes mellitus (DM) (OR=2.6, 95% CI: 1.2-9.1) and chronic respiratory diseases (OR=2.4, 95% (CI): 1.3-8.1). Limitations: This is an observational study, neither randomized study nor control group study. Conclusion: Initial treatment with MOL has the treatment benefits and is well tolerated for patients with COVID-19 in healthcare facilities. Older age, old CVA, DM, and chronic respiratory diseases were independent risk factors for hospitalization and mortality. The results demonstrate there are important clinical benefits of MOL beyond the reduction in hospitalization or death for these patients with more comorbidities in Taiwan.

Clinical assessment of SARS-CoV-2 infectivity by rapid antigen test compared with virus isolation.

Although real-time reverse transcriptase polymerase chain reaction (real-time RT-PCR) remains as a golden standard for detection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, it can not be easily expanded to large-scaled screening during outbreaks, and the positive results do not necessarily correlate with infectious status of the identified subjects. In this study, the performance of Vstrip® RV2 COVID-19 Antigen Rapid Test (RAT) and its correlation with virus infectivity was examined by virus culture using 163 sequential respiratory specimens collected from 26 SARS-CoV-2 infected patients. When the presence of cytopathic effects (CPE) in cell culture was used as a reference method for virus infectivity, the sensitivity, specificity and accuracy of Vstrip® RV2 COVID-19 Antigen Rapid Test was 96.43%, 89.63%, and 90.8%, respectively. The highest Ct value was 27.7 for RdRp gene and 25.79 for E gene within CPE-positive samples, and the highest Ct value was 31.9 for RdRp gene and 29.1 for E gene within RAT positive samples. When the Ct values of specimens were below 25, the CPE and RAT results had high degree of consistency. We concluded that the RAT could be a great alternative method for determining the infectious potential of individuals with high viral load.

Association of Digital Health Literacy with Future Anxiety as Mediated by Information Satisfaction and Fear of COVID-19: A Pathway Analysis among Taiwanese Students.

Digital Health Literacy (DHL) helps online users with navigating the infodemic and co-existing conspiracy beliefs to avoid mental distress and maintain well-being. We aimed to investigate the association between DHL and future anxiety (FA); and examine the potential mediation roles of information satisfaction and fear of COVID-19 (F-CoV). A web-based cross-sectional survey was carried out among 1631 Taiwanese university students aged 18 years and above from June 2021 to March 2022. Data collected were socio-demographic characteristics (sex, age, social status, university location), information satisfaction, F-CoV, DHL and FA (using Future Dark scale). The linear regression model was used to explore factors associated with FA. The pathway analysis was further used to evaluate the direct and indirect relationship between DHL and FA. A higher score of DHL (B = -0.21; 95% CI, -0.37, -0.06; p = 0.006), and information satisfaction (B = -0.16; 95% CI, -0.24, -0.08; p < 0.001) were associated with a lower FA score, whereas a higher F-CoV score was associated with a higher FA score (B = 0.43; 95% CI, 0.36, 0.50; p < 0.001). DHL showed the direct impact (B = -0.1; 95% CI, -0.17, -0.04; p = 0.002) and indirect impact on FA as mediated by information satisfaction (B = -0.04; 95% CI, -0.06, -0.01; p = 0.002) and F-CoV (B = -0.06, 95% CI, -0.08, -0.04; p < 0.001). Strategic approaches to promote DHL, information satisfaction, lower F-CoV are suggested to reduce FA among students.

Contribution of Testing Strategies and Contact Tracing towards COVID-19 Outbreaks Control: A Mathematical Modeling Study.

This modeling study considers different screening strategies, contact tracing, and the severity of novel epidemic outbreaks for various population sizes, providing insight into multinational containment effectiveness of emerging infectious diseases, prior to vaccines development. During the period of the ancestral SARS-Cov-2 virus, contact tracing alone is insufficient to achieve outbreak control. Although universal testing is proposed in multiple nations, its effectiveness accompanied by other measures is rarely examined. Our research investigates the necessity of universal testing when contact tracing and symptomatic screening measures are implemented. We used a stochastic transmission model to simulate COVID-19 transmission, evaluating containment strategies via contact tracing, one-time high risk symptomatic testing, and universal testing. Despite universal testing having the potential to identify subclinical cases, which is crucial for non-pharmaceutical interventions, our model suggests that universal testing only reduces the total number of cases by 0.0009% for countries with low COVID-19 prevalence and 0.025% for countries with high COVID-19 prevalence when rigorous contact tracing and symptomatic screening are also implemented. These findings highlight the effectiveness of testing strategies and contact tracing in reducing COVID-19 cases by identifying subclinical cases.

The requirements of nucleic acid test for COVID-19 during public health emergency: Current regulatory in Taiwan, Singapore, and the United States.

In mid-2022, the COVID-19 cases have reached close to 562 million, but its overall infection rate is hard to confirm. Even with effective vaccines, break-through infections with new variants occur, and safe and reliable testing still plays a critical role in isolation of infected individuals and in control of an outbreak of a COVID-19 pandemic. In response to this urgent need, the diagnostic tests for COVID-19 are rapidly evolving and improving these days. The health authorities of many countries issued requirements for detecting SARS-CoV-2 diagnosis tests during the pandemic and have timely access to these tests to ensure safety and effectiveness. In this study, we compared the requirements of EUA in Taiwan, Singapore, and the United States. For the performance evaluations of nucleic acid extraction, inclusivity, limit of detection (LoD), cross-reactivity, interference, cutoff, and stability, the requirements are similar in the three countries. The use of natural clinical specimens is needed for clinical evaluation in Taiwan and the United States. However, carry-over and cross-contamination studies can be exempted in Taiwan and the United States but are required in Singapore. This review outlines requirements and insight to guide the test developers on the development of IVDs. Considering the rapidly evolving viruses and severe pandemic of COVID-19, timely and accurate diagnostic testing is imperative to the management of diseases. As noted above, the performance requirements for SARS-CoV-2 nucleic acid tests are similar between Taiwan, Singapore and the United States. The differences are mainly in two points: the recommended microorganisms for cross-reactivity study, and the specimen requirement for clinical evaluation. This study provides an overview of current requirements of SARS-CoV-2 nucleic acid tests in Taiwan, Singapore, and the United States.

Microfluidic Gas Sensors: Detection Principle and Applications.

With the rapid growth of emerging point-of-use (POU)/point-of-care (POC) detection technologies, miniaturized sensors for the real-time detection of gases and airborne pathogens have become essential to fight pollution, emerging contaminants, and pandemics. However, the low-cost development of miniaturized gas sensors without compromising selectivity, sensitivity, and response time remains challenging. Microfluidics is a promising technology that has been exploited for decades to overcome such limitations, making it an excellent candidate for POU/POC. However, microfluidic-based gas sensors remain a nascent field. In this review, the evolution of microfluidic gas sensors from basic electronic techniques to more advanced optical techniques such as surface-enhanced Raman spectroscopy to detect analytes is documented in detail. This paper focuses on the various detection methodologies used in microfluidic-based devices for detecting gases and airborne pathogens. Non-continuous microfluidic devices such as bubble/droplet-based microfluidics technology that have been employed to detect gases and airborne pathogens are also discussed. The selectivity, sensitivity, advantages/disadvantages vis-a-vis response time, and fabrication costs for all the microfluidic sensors are tabulated. The microfluidic sensors are grouped based on the target moiety, such as air pollutants such as carbon monoxide and nitrogen oxides, and airborne pathogens such as E. coli and SARS-CoV-2. The possible application scenarios for the various microfluidic devices are critically examined.

Investor sentiment based on scaled PCA method: A powerful predictor of realized volatility in the Chinese stock market

In this study, we construct an investor sentiment indicator (SsPCA) to predict stock volatility in the Chinese stock market by applying the scaled principal component analysis (sPCA). As a new dimension reduction technique for supervised learning, sPCA is employed to extract useful information from six individual sentiment proxies and obtain the common variations to characterize the investor sentiment (SsPCA). The empirical results indicate that SsPCA is a significant and powerful volatility predictor both in and out of sample. We also employ the partial least squares (PLS)-based investor sentiment index, three extra sentiment measures in past studies, and six individual sentiment proxies for comparison, and find SsPCA outperforms them on predicting stock volatility in the Chinese stock market. More importantly, the predictability of SsPCA remains significant before and after the famous financial crises (the sub-prime mortgage crisis and Chinese stock market turbulence) and the spread of the pandemic (COVID-19). Additionally, our findings imply that SsPCA still plays an essential role in predicting sock volatility after considering the leverage effect. The robustness of SsPCA in volatility forecasting is further verified in various industry indices of the Chinese stock market. Finally, we state that the strong predictability of SsPCA is highly related to its dimensionality reduction. Our results indicate that SsPCA is a robust volatility predictor from various aspects and performs better compared with existing sentiment indicators.

Tree-Based Algorithms and Association Rule Mining for Predicting Patients' Neurological Outcomes After First-Aid Treatment for an Out-of-Hospital Cardiac Arrest During COVID-19 Pandemic: Application of Data Mining.

Objective: The authors performed several tree-based algorithms and an association rules mining as data mining tools to find useful determinants for neurological outcomes in out-of-hospital cardiac arrest (OHCA) patients as well as to assess the effect of the first-aid and basic characteristics in the EMS system. Patients and Methods: This was a retrospective cohort study. The outcome was Cerebral Performance Categories grading on OHCA patients at hospital discharge. Decision tree-based models inclusive of C4.5 algorithm, classification and regression tree and random forest were built to determine an OHCA patient's prognosis. Association rules mining was another data mining method which we used to find the combination of prognostic factors linked to the outcome. Results: The total of 3520 patients were included in the final analysis. The mean age was 67.53 (±18.4) year-old and 63.4% were men. To overcome the imbalance outcome issue in machine learning, the random forest has a better predictive ability for OHCA patients in overall accuracy (91.19%), weighted precision (88.76%), weighted recall (91.20%) and F1 score (0.9) by oversampling adjustment. Under association rules mining, patients who had any witness on the spot when encountering OHCA or who had ever ROSC during first-aid would be highly correlated with good CPC prognosis. Conclusion: The random forest has a better predictive ability for OHCA patients. This paper provides a role model applying several machine learning algorithms to the first-aid clinical assessment that will be promising combining with Artificial Intelligence for applying to emergency medical services.