ABSTRACT
This paper explores the effect of COVID-19 outbreaks on human activity through nighttime light images of Greater Toronto Area (GTA), Canada. The methods used in this paper include image preprocessing, image classification, and spatial analysis. By using the nighttime light radiance data from VIIRS/NPP data products and COVID-19 cases and comparing this data from the pre-pandemic year, the impact of COVID-19 was analyzed. The result shows that during the pandemic year the monthly average nighttime light radiance has decreased about 4.3-5.0% compared to the pre-pandemic year. The classification results shows that the average percentage of changes in residential areas, public facilities, and commercial areas are 0.3%, -0.7%, and -1.2%, respectively of each corresponding month. Meanwhile, the spatial analysis results show population distribution patterns in GTA during the pandemic year. Overall, the nighttime lights (NTL) images can be used for a preliminary understanding of how COVID-19 affected human activities and is corroborated with other forms data collection used for the pandemic analysis.
ABSTRACT
After the outbreak of COVID-19, Taiwan has implemented rigorous border control and taken specific measures such as virus detection, contact tracing, and quarantine since 2020. Its epidemic prevention performance has been quite outstanding. Even in May 2021, when the epidemic situation worsens, the people in Taiwan fully cooperate with the government's control measures so as to successfully alleviate and control the epidemic in less than three months. Among them, the detection policy has played a pivotal role. We analyze and discuss the false positive and false negative problems from rapid antigen and PCR detection in the screening policy as well as the timing of using these two instruments. This paper provides theoretical verification of the appropriateness of screening policy in Taiwan, offering a few feasible suggestions for related policies in other countries or regions at different stages of this and other potential epidemics. (c) 2022 by the authors;licensee Growing Science, Canada.
ABSTRACT
In the diagnosis of severe contagious diseases such as Ebola, severe acute respiratory syndrome, and COVID-19, there is an urgent need for protein sensors with large refractive index sensitivities. Current terahertz metamaterials cannot be used to develop such protein sensors due to their low refractive index sensitivities. A simple method is proposed that is compatible with all geometrical structures of terahertz metamaterials to increase their refractive index sensitivities. This method uses patterned photoresist to float the split-ring resonators (SRRs) of a terahertz metamaterial at a height of 30 μm from its substrate that is deposited with complementary SRRs. The floating terahertz metamaterial has an extremely large refractive index sensitivity of 532 GHz/RIU because its near field is not distributed over the substrate and also because the complementary SRRs confine the field above the substrate. The floating terahertz metamaterial senses bovine serum albumin (BSA) and the protein binding of BSA and anti-BSA as BSA, and anti-BSA solutions with low concentrations that are smaller than 0.150 μmol/L are sequentially dropped onto it. The floating terahertz metamaterial is a great achievement to develop protein sensors with extremely large refractive index sensitivities, and has the potential to sense dangerous viruses. © 2021 Chinese Laser Press.
ABSTRACT
BACKGROUND AND AIM: Coronavirus disease 2019 (COVID-19) has attracted increasing worldwide attention. While diabetes is known to aggravate COVID-19 severity, it is not known whether nondiabetic patients with metabolic dysfunction are also more prone to more severe disease. The association of metabolic associated fatty liver disease (MAFLD) with COVID-19 severity in nondiabetic patients was investigated here. METHODS: The study cohort comprised 65 patients with (i.e. cases) and 65 patients without MAFLD (i.e. controls). Each case was randomly matched with one control by sex (1:1) and age (+/-5 years). The association between the presence of MAFLD (as exposure) and COVID-19 severity (as the outcome) was assessed by binary logistic regression analysis. RESULTS: In nondiabetic patients with COVID-19, the presence of MAFLD was associated with a four-fold increased risk of severe COVID-19;the risk increased with increasing numbers of metabolic risk factors. The association with COVID-19 severity persisted after adjusting for age, sex, and coexisting morbid conditions. CONCLUSION: Health-care professionals caring for nondiabetic patients with COVID-19 should be cognizant of the increased likelihood of severe COVID-19 in patients with MAFLD.