Chemical explosion, COVID-19, and environmental justice: Insights from low-cost air quality sensors.

OBJECTIVES: To examine the impact of the Intercontinental Terminals Company (ITC) fire and COVID-19 on airborne particulate matter (PM) concentrations and the PM disproportionally affecting communities in Houston using low-cost sensors. METHODS: We compared measurements from a network of low-cost sensors with a separate network of monitors from the Environmental Protection Agency (EPA) in the Houston metropolitan area from Mar 18, 2019, to Dec 31, 2020. Further, we examined the associations between neighborhood-level sociodemographic status and air pollution patterns by linking the low-cost sensor data to EPA environmental justice screening and mapping systems. FINDINGS: We found increased PM levels during ITC fire and pre-COVID-19, and lower PM levels after the COVID-19 lockdown, comparable to observations from the regulatory monitors, with higher variations and a greater number of locations with high PM levels detected. In addition, the environmental justice analysis showed positive associations between higher PM levels and the percentage of minority, low-income population, and demographic index. IMPLICATION: Our study indicates that low-cost sensors provide pollutant measures with higher spatial variations and a better ability to identify hot spots and high peak concentrations. These advantages provide critical information for disaster response and environmental justice studies. SYNOPSIS: We used measurements from a low-cost sensor network for air pollution monitoring and environmental justice analysis to examine the impact of anthropogenic and natural disasters.

COVID-19 Symptoms and Deaths among Healthcare Workers, United States.

We evaluated whether demographics and COVID-19 symptoms predicted COVID-19 deaths among healthcare workers (HCWs) in the United States by comparing COVID-19 deaths in HCWs with 3 control groups (HCW nondeaths, non-HCW deaths, and non-HCW nondeaths) using a case-control design. We obtained patient-level data of 33 variables reported during January 1, 2020-October 12, 2021, in all US states. We used logistic regression analysis while controlling for confounders. We found that persons who were >50 years of age, male, Black, or Asian experienced significantly more deaths than matched controls. In addition, HCWs who died had higher risks for the most severe clinical indicators. We also found that the most indicative symptoms were preexisting medical conditions, shortness of breath, fever, cough, and gastrointestinal symptoms. In summary, minority, male, and older HCWs had greater risk for COVID-19 death. Severe clinical indicators and specific symptoms may predict COVID-19-related deaths among HCWs.

A review on COVID-19 transmission, epidemiological features, prevention and vaccination.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused hundreds of millions of infections and millions of deaths over past two years. Currently, many countries have still not been able to take the pandemic under control. In this review, we systematically summarized what we have done to mitigate the COVID-19 pandemic, from the perspectives of virus transmission, public health control measures, to the development and vaccination of COVID-19 vaccines. As a virus most likely coming from bats, the SARS-CoV-2 may transmit among people via airborne, faecal-oral, vertical or foodborne routes. Our meta-analysis suggested that the R0 of COVID-19 was 2.9 (95% CI: 2.7-3.1), and the estimates in Africa and Europe could be higher. The median Rt could decrease by 23-96% following the nonpharmacological interventions, including lockdown, isolation, social distance, and face mask, etc. Comprehensive intervention and lockdown were the most effective measures to control the pandemic. According to the pooled R0 in our meta-analysis, there should be at least 93.3% (95% CI: 89.9-96.2%) people being vaccinated around the world. Limited amount of vaccines and the inequity issues in vaccine allocation call for more international cooperation to achieve the anti-epidemic goals and vaccination fairness.

Rapid differentiation of SARS-CoV-2 variants on a nanotechnology enhanced DNA-chip (preprint)

With the persistence of the COVID-19 pandemic caused primarily by constant viral mutations, rapid identification of different lineages of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) by large-scale screening at the point-of-care could be key to monitoring and assessing viral evolutions. Herein, we developed a Fluorescence Enhanced Microarray for Multiplex Analysis of Nucleic acids (FEMMAN) for detecting 8 SARS-CoV-2 variants simultaneously in ~ 3 hours without the need of RNA extraction, opening the possibility of point-of-care testing of multiple SARS-CoV-2 variants while reducing the cost significantly to ~ $ 7 per sample from ~ $100 by Next-Generation Sequencing (NGS). Combined with isothermal amplification, the multiplexed RNA assay achieved single-copy detection sensitivity and single nucleotide variant (SNV) distinction owing to the nanotechnology based plasmonic gold (pGOLD) near-infrared fluorescence enhancing platform. Probing 10 targets of three mutational hotspots in S gene, we differentiated 8 viral lineages (Wild type, Alpha, Beta, Gamma, Delta, Lambda, Mu, and Omicron) of SARS-CoV-2, validated using nasopharyngeal swabs obtained from 127 individuals, achieving a 100% sensitivity and 100% specificity in SARS-CoV-2 detection, and a 91.1% concordance with NGS in variant identification. The scalable, multiplexed FEMMAN assay could shift the paradigm of COVID-19 diagnostic and surveillance from positive/negative assessments to simultaneous lineage identification in large-scale screening, greatly facilitating the global monitoring of SARS-CoV-2 variants.

Building a predictive model to identify clinical indicators for COVID-19 using machine learning method.

Although some studies tried to identify risk factors for COVID-19, the evidence comparing COVID-19 and community-acquired pneumonia (CAP) is inconclusive, and CAP is the most common pneumonia with similar symptoms as COVID-19. We conducted a case-control study with 35 routine-collected clinical indicators and demographic factors to identify predictors for COVID-19 with CAP as controls. We randomly split the dataset into a training set (70%) and testing set (30%). We built Explainable Boosting Machine to select the important factors and built a decision tree on selected variables to interpret their relationships. The top five individual predictors of COVID-19 are albumin, total bilirubin, monocyte count, alanine aminotransferase, and percentage of monocyte with the importance scores ranging from 0.078 to 0.567. The top systematic predictors for COVID-19 are liver function, monocyte increasing, plasma protein, granulocyte, and renal function (importance scores ranging 0.009-0.096). We identified five combinations of important indicators to screen COVID-19 patients from CAP patients with differentiating abilities ranging 83.3-100%. An online predictive tool for our model was published. Certain clinical indicators collected routinely from most hospitals could help screen and distinguish COVID-19 from CAP. While further verification is needed, our findings and predictive tool could help screen suspected COVID-19 cases.

Constructing Sports Promotion Models for an Accessibility and Efficiency Analysis of City Governments

This study provides a systematic analysis of sports promotion efficiency in 22 administrative districts in Taiwan from 2011 to 2018. We first considered sports behavior and sports information promotion and connected the multiple intermediate products using network DEA, used the public performance and outputs to measure the total efficiency of sports promotion in the 22 administrative districts, and then established the final input–output indicators. The long-term tracking of sports promotion efficiency shows that, while Taipei and Taoyuan experienced upward trends, the other 20 administrative districts saw declining trends. We also used truncated regression to identify 14 environmental variables that affected the efficiency of sports promotion in the 22 administrative districts from 2016 to 2018, with the results showing that funding, satisfaction with life, and average BMI in each administrative district were significant factors, revealing the latest trends in and measurements of governance in terms of government accessibility.

New insights into price drivers of crude oil futures markets: Evidence from quantile ARDL approach (preprint)

This paper investigates the cointegration between possible determinants of crude oil futures prices during the COVID-19 pandemic period. We perform comparative analysis of WTI and newly-launched Shanghai crude oil futures (SC) via the Autoregressive Distributed Lag (ARDL) model and Quantile Autoregressive Distributed Lag (QARDL) model. The empirical results confirm that economic policy uncertainty, stock markets, interest rates and coronavirus panic are important drivers of WTI futures prices. Our findings also suggest that the US and China's stock markets play vital roles in movements of SC futures prices. Meanwhile, CSI300 stock index has a significant positive short-run impact on SC futures prices while S\&P500 prices possess a positive nexus with SC futures prices both in long-run and short-run. Overall, these empirical evidences provide practical implications for investors and policymakers.

Mapping Generation Y Tourists’ E-Loyalty: A Sustainable Framework through Hierarchical Structure and Fuzzy Set Theory

Generation Y (Gen Y) travel spending is set to soar and has enormous implications for hospitality firms’ economic sustainability. However, previous studies have failed to examine the hierarchical interrelationship between e-loyalty attributes in the presence of a hierarchical structure and linguistic preferences. Consequently, the purpose of this paper is to identify a list of e-loyalty attributes and to examine each attribute’s importance to Gen Y consumers’ e-loyalty intentions in the context of tourism. Drawing on an ad hoc survey of 230 graduate students in Taiwan, the study employs exploratory factor analysis to analyze the method’s validity and reliability. Furthermore, 30 Gen Y consumers are invited to evaluate the identified measures using fuzzy linguistic scales. The fuzzy set theory is then employed to translate the qualitative responses into crisp values. The decision-making trial evaluation laboratory is used to understand the interrelationships between the e-loyalty attributes. The empirical findings reveal that trust, utilitarian features, and hedonic features all play essential roles in Gen Y tourists’ e-loyalty. In addition, perceived enjoyment, website competency, emotional connection, candid and authentic site information, and delightful experiences are crucial factors in the formation of customer e-loyalty. Both theoretical and managerial implications are discussed.

Does Serum Vitamin D Level Affect COVID-19 Infection and Its Severity?-A Case-Control Study.

BACKGROUND: As effective medication to treat COVID-19 is currently unavailable, preventive remedies may be particularly important. OBJECTIVE: To examine the relationship between serum 25-hydroxy vitamin D (25(OH)D) level and COVID-19 infection, its severity, and its clinical case characteristics. METHODS: This case-control study compared serum 25(OH)D levels and rates of vitamin D deficiency (VDD) between 80 healthy controls and 62 patients diagnosed with COVID-19 and admitted to Guangxi People's Hospital, China, 2/16/2020-3/16/2020. Cases were categorized into asymptomatic, mild/moderate, and severe/critical disease. Logistic regression analysis was conducted to examine the associations between 25(OH)D level, or VDD, and case status/severity of COVID-19 while controlling for demographics and comorbidities. A threshold level of vitamin D for conveying COVID-19 risk was estimated. RESULTS: Severe/critical COVID-19 cases were significantly older and had higher percentages of comorbidity (renal failure) compared to mild cases. The serum 25(OH)D concentration in COVID-19 patient was much lower than that in healthy control. And 25(OH)D level was the lowest in severe/critical cases, compared with mild cases. In further, significantly higher rates of VDD were found in COVID-19 cases (41.9%) compared to healthy controls (11.1%). And VDD was the greatest in severe/critical cases (80%), compared with mild cases (36%). These statistically significant associations remained even after controlling for demographics and comorbidities. A potential threshold of 25(OH)D (41.19 nmol/L) to protect against COVID-19 was identified. CONCLUSION: Elderly and people with comorbidities were susceptible to severe COVID-19 infection. VDD was a risk factor for COVID-19, especially for severe/critical cases. While further confirmation is needed, vitamin D supplementation may have prevention or treatment potential for COVID-19 disease.