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1.
Healthcare Analytics ; 2022.
Article in English | EuropePMC | ID: covidwho-1837923

ABSTRACT

In the later stages of the COVID-19 pandemic, hotels are taking various measures to balance pandemic prevention and business operations. Some hotels require travelers to be fully vaccinated prior to check-in, while others do not. In the latter type of hotels, fully vaccinated travelers may encounter others who are not vaccinated. All of these have created constraints for travelers to choose suitable hotel accommodation during this time. To address this issue, a fuzzy multi-criteria decision-making approach is proposed in this study to help traveler choose suitable hotel accommodation. In the proposed methodology, firstly, hotels are divided into two types considering their requirements for COVID-19 vaccination. Travelers are then asked to list the key factors to consider when choosing between these two types of hotels. To derive the priorities of these key factors, the proportionally calibrated fuzzy geometric mean (pcFGM) method is proposed. Subsequently, the fuzzy VIšekriterijumskoKOmpromisnoRangiranje (fuzzy VIKOR) method is applied to evaluate and compare the overall performances of different types of hotels for recommendations to travelers. The applicability of the proposed methodology is illustrated by a real case study. According to the experimental results, most hotels did not request travelers to be full vaccinated. Nevertheless, the hotels recommended to travelers covered both hotel types.

2.
SN applied sciences ; 4(6), 2022.
Article in English | EuropePMC | ID: covidwho-1837920

ABSTRACT

Surface ozone pollution has attracted extensive attention with the decreasing of haze pollution, especially in China. However, it is still difficult to efficiently control the pollution in time despite numbers of reports on mechanism of ozone pollution. Here we report a method for implementing effective control of ozone pollution through power big data. Combining the observation of surface ozone, NO2, meteorological parameters together with hourly electricity consumption data from volatile organic compounds (VOCs) emitting companies, a generalized additive model (GAM) is established for quantifying the influencing factors on the temporal and spatial distribution of surface ozone pollution from 2020 to 2021 in Anhui province, central China. The average R2 value for the modelling results of 16 cities is 0.82, indicating that the GAM model effectively captures the characteristics of ozone. The model quantifies the contribution of input variables to ozone, with both NO2 and industrial VOCs being the main contributors to ozone, contributing 33.72% and 21.12% to ozone formation respectively. Further analysis suggested the negative correlation between ozone and NO2, revealing VOCs primarily control the increase in ozone. Under scenarios controlling for a 10% and 20% reduction in electricity use in VOC-electricity sensitive industries that can be identified by power big data, ozone concentrations decreased by 9.7% and 19.1% during the pollution period. This study suggests a huge potential for controlling ozone pollution through power big data and offers specific control pathways. Supplementary Information The online version contains supplementary material available at 10.1007/s42452-022-05045-5. Article Highlights Surface ozone pollution in central China was investigated during the prevalence of the COVID-19 (2020.1–2021.5) NO2 and industrial VOCs contributing 33.72% and 21.12% to ozone formation Potential controlling pathway was proposed Supplementary Information The online version contains supplementary material available at 10.1007/s42452-022-05045-5.

3.
Frontiers in Molecular Neuroscience ; 15, 2022.
Article in English | ProQuest Central | ID: covidwho-1834482

ABSTRACT

Disruption of the blood-brain barrier (BBB) causes or contributes to neuronal dysfunction and several central nervous system (CNS) disorders. Wnt/b-catenin signaling is essential for maintaining the integrity of the adult BBB in physiological and pathological conditions, including stroke. However, how the impairment of the endothelial Wnt/b-catenin signaling results in BBB breakdown remains unclear. Furthermore, the individual contributions of different BBB permeability-inducing mechanisms, including intercellular junction damage, endothelial transcytosis, and fenestration, remains unexplored. Here, we induced b-catenin endothelial-specific conditional knockout (ECKO) in adult mice and determined its impact on BBB permeability and the underlying mechanism. b-catenin ECKO reduced the levels of active b-catenin and the mRNA levels of Wnt target genes in mice, indicating downregulation of endothelial Wnt/b-catenin signaling. b-catenin ECKO mice displayed severe and widespread leakage of plasma IgG and albumin into the cerebral cortex, which was absent in wild-type controls. Mechanistically, both the paracellular and transcellular transport routes were disrupted in b-catenin ECKO mice. First, b-catenin ECKO reduced the tight junction protein levels and disrupted the intercellular junction ultrastructure in the brain endothelium. Second, b-catenin ECKO substantially increased the number of endothelial vesicles and caveolae-mediated transcytosis through downregulating Mfsd2a and upregulating caveolin-1 expression. Interestingly, fenestration and upregulated expression of the fenestration marker Plvap were not observed in b-catenin ECKO mice. Overall, our study reveals that endothelial Wnt/b-catenin signaling maintains adult BBB integrity via regulating the paracellular as well as transcellular permeability. These findings may have broad applications in understanding and treatment of CNS disorders involving BBB disruption.

4.
EuropePMC; 2022.
Preprint in English | EuropePMC | ID: ppcovidwho-335283

ABSTRACT

ABSTRACT Background It is important for understanding the impact of COVID-19 pandemic on the missing opportunity for the early detection of oral cancer. This study aimed to assess the impact of COVID-19 pandemic on the existing population-based oral cancer (OC) service screening program in Taiwan. Methods Before and after COVID-19 pandemic design was used to assess the impact of COVID-19 on the reduction of screening rate, referral rate, and the effectiveness of this OC service screening. Data and analysis after pandemic covered non-VOC period in 2020 and VOC period in 2021 compared to the historical control before pandemic in 2019. Results The screening rate decreased substantially from 26.6% before COVID-19 in 2019 to 16.7% in 2020 and 15.3% in 2021 after pandemic. The reduction of screening rate varied with months, being the most remarkable decline in March (RR=0.61, 95% CI (0.60-0.62)) and June (RR=0.09, 95% CI (0.09-0.10)) in 2021 compared with January. The referral rate was stable at 81.5% in 2020 but it was reduced to 73.1% in 2021. The reduction of screening and referral rate led to the attenuation of effectiveness of advance cancer and mortality attenuated by 4% and 5%, respectively. Conclusion COVID-19 pandemic disrupted the screening and the referral rate and further led to statistically significant reduction in effectiveness for preventing advanced cancer and death. Appropriate prioritized strategies must be adopted to ameliorate malignant transformation and tumor upstaging due to deference from participation in the screening. Funding This study was financially supported by Health Promotion Administration of the Ministry of Health and Welfare of Taiwan (A1091116).

5.
ISPRS International Journal of Geo-Information ; 11(4):267, 2022.
Article in English | ProQuest Central | ID: covidwho-1809936

ABSTRACT

The cross-impact of environmental pollution among cities has been reported in more research works recently. To implement the coordinated control of environmental pollution, it is necessary to explore the structural characteristics and influencing factors of the PM2.5 spatial correlation network from the perspective of the metropolitan area. This paper utilized the gravity model to construct the PM2.5 spatial correlation network of ten metropolitan areas in China from 2019 to 2020. After analyzing the overall characteristics and node characteristics of each spatial correlation network based on the social network analysis (SNA) method, the quadratic assignment procedure (QAP) regression analysis method was used to explore the influence mechanism of each driving factor. Patent granted differences, as a new indicator, were also considered during the above. The results showed that: (1) In the overall network characteristics, the network density of Chengdu and the other three metropolitan areas displayed a downward trend in two years, and the network density of Wuhan and Chengdu was the lowest. The network density and network grade of Hangzhou and the other four metropolitan areas were high and stable, and the network structure of each metropolitan area was unstable. (2) From the perspective of the node characteristics, the PM2.5 spatial correlation network all performed trends of centralization and marginalization. Beijing-Tianjin-Hebei and South Central Liaoning were “multi-core” metropolitan areas, and the other eight were “single-core” metropolitan areas. (3) The analysis results of QAP regression illustrated that the top three influencing factors of the six metropolitan areas were geographical locational relationship, the secondary industrial proportion differences, respectively, and patent granted differences, and the other metropolitan areas had no dominant influencing factors.

6.
Journal of Computer Science and Technology ; 37(2):330-343, 2022.
Article in English | ProQuest Central | ID: covidwho-1803050

ABSTRACT

COVID-19 is a contagious infection that has severe effects on the global economy and our daily life. Accurate diagnosis of COVID-19 is of importance for consultants, patients, and radiologists. In this study, we use the deep learning network AlexNet as the backbone, and enhance it with the following two aspects: 1) adding batch normalization to help accelerate the training, reducing the internal covariance shift;2) replacing the fully connected layer in AlexNet with three classifiers: SNN, ELM, and RVFL. Therefore, we have three novel models from the deep COVID network (DC-Net) framework, which are named DC-Net-S, DC-Net-E, and DC-Net-R, respectively. After comparison, we find the proposed DC-Net-R achieves an average accuracy of 90.91% on a private dataset (available upon email request) comprising of 296 images while the specificity reaches 96.13%, and has the best performance among all three proposed classifiers. In addition, we show that our DC-Net-R also performs much better than other existing algorithms in the literature.

7.
Journal of Medical Virology ; n/a(n/a), 2022.
Article in English | Wiley | ID: covidwho-1802454

ABSTRACT

There is a potential risk for SARS-CoV-2 spread through human contact with seafood and the inanimate materials contaminated by the virus. In this study, we examined the stability of the virus in artificial seawater (ASW) and on the surface of selected materials. SARS-CoV-2 (3.75 log10 TCID50) in ASW at 22? maintained infectious about 3 days and at 4? the virus survived more than 7 days. It should be noticed that viable virus at high titer (5.50 log10 TCID50) may survive more than 20 days in ASW at 4? and for 7 days at 22?. SARS-CoV-2 on stainless steel and plastic bag maintained infectious for 3 days, and on non-woven fabric for 1 day at 22?. In addition, the virus remained infectious for 9 days on stainless steel and non-woven fabric, and on plastic bag for 12 days at 4?. It is important to highlight the role of inanimate material surfaces as a source of infection and the necessity for surface decontamination and disinfection.This article is protected by copyright. All rights reserved.

8.
Preprint in English | medRxiv | ID: ppmedrxiv-22274618

ABSTRACT

BackgroundIt is important for understanding the impact of COVID-19 pandemic on the missing opportunity for the early detection of oral cancer. This study aimed to assess the impact of COVID-19 pandemic on the existing population-based oral cancer (OC) service screening program in Taiwan. MethodsBefore and after COVID-19 pandemic design was used to assess the impact of COVID-19 on the reduction of screening rate, referral rate, and the effectiveness of this OC service screening. Data and analysis after pandemic covered non-VOC period in 2020 and VOC period in 2021 compared to the historical control before pandemic in 2019. ResultsThe screening rate decreased substantially from 26.6% before COVID-19 in 2019 to 16.7% in 2020 and 15.3% in 2021 after pandemic. The reduction of screening rate varied with months, being the most remarkable decline in March (RR=0.61, 95% CI (0.60-0.62)) and June (RR=0.09, 95% CI (0.09-0.10)) in 2021 compared with January. The referral rate was stable at 81.5% in 2020 but it was reduced to 73.1% in 2021. The reduction of screening and referral rate led to the attenuation of effectiveness of advance cancer and mortality attenuated by 4% and 5%, respectively. ConclusionCOVID-19 pandemic disrupted the screening and the referral rate and further led to statistically significant reduction in effectiveness for preventing advanced cancer and death. Appropriate prioritized strategies must be adopted to ameliorate malignant transformation and tumor upstaging due to deference from participation in the screening. FundingThis study was financially supported by Health Promotion Administration of the Ministry of Health and Welfare of Taiwan (A1091116).

9.
Phytomedicine ; : 154100, 2022.
Article in English | ScienceDirect | ID: covidwho-1796222

ABSTRACT

Background A number of studies have shown that gastrointestinal manifestations co-exist with respiratory symptoms in coronavirus disease 2019 (COVID-19) patients. Xuanfei Baidu decoction (XFBD) was recommended by the National Health Commission to treat mild and moderate COVID-19 patients and proved to effectively alleviate intestinal symptoms. However, the exact mechanisms remain elusive. Purpose This study aimed at exploring potential mechanisms of XFBD by utilizing a mouse model of dextran sulfate sodium (DSS)-induced acute experimental colitis, mimicking the disease conditions of intestinal microecological disorders. Methods The network pharmacology approach was employed to identify the potential targets and pathways of XFBD on the intestinal disorders. Mice with DSS-induced intestinal disorders were utilized to evaluate the protective effect of XFBD in vivo, including body weight, disease activity index (DAI) score, colon length, spleen weight, and serum tumor necrosis factor-α (TNF-α) level. Colon tissues were used to perform hematoxylin-eosin (H&E) staining, western blot analysis, and transcriptome sequencing. Macrophages, neutrophils and the proportions of T helper cell (Th) 1 and Th2 cells were measured by flow cytometry. Intestinal contents were collected for 16S rRNA gene sequencing. Results Network pharmacology analysis indicated that XFBD inhibited the progression of COVID-19-related intestinal diseases by repressing inflammation. In mice with DSS-induced intestinal inflammation, XFBD treatment significantly reduced weight loss, the spleen index, the disease activity index, TNF-α levels, and colonic tissue damage, and prevented colon shortening. Transcriptomics and flow cytometry results suggested that XFBD remodeled intestinal immunity by downregulating the Th1/Th2 ratio. Western blot analysis showed that XFBD exerted its anti-inflammatory effects by blocking the nuclear factor-κB (NF-κB) signaling pathway. Indicator analysis of microbiota showed that 27 operational taxonomic units (OTUs) were affected after XFBD administration. Among them, Akkermansia, Muribaculaceae, and Lachnospiraceae were simultaneously negatively correlated with intestinal inflammatory parameters, and Bacteroides, Escherichia-Shigella, Eubacterium nodatum, and Turicibacter, which could serve as anti-inflammatory biomarkers in the gut, showed positive correlations with intestinal inflammatory parameters. Conclusions Our data indicate that XFBD treatment attenuated intestinal disorders associated with inhibiting inflammation, remodeling of intestinal immunity, and improving intestinal flora. These findings provide a scientific basis for the clinical use of XFBD and offer a potential therapeutic approach for the treatment of COVID-19 patients with intestinal symptoms.

10.
Front Public Health ; 10: 808988, 2022.
Article in English | MEDLINE | ID: covidwho-1776006

ABSTRACT

Objective: This study aimed to assess the knowledge, attitude, and practice (KAP) of diabetic subjects with diabetic retinopathy (DR) and those without DR (NDR) in an urban community in Northeast China, as well as their risk factors in subjects with DR and NDR. Methods: A community-based survey involving 1,662 subjects was conducted in Fushun, China, between July 2012 and May 2013. The subjects included diabetics with DR (n = 783) and those NDR (n = 879), and questionnaires were completed to collect information about their sociodemographic and healthcare characteristics. A Chi-square test and multiple logistic analyses were performed to analyze the data. Results: Among the DR group, 21.88% had a good knowledge of DR, 94.15% had a positive attitude, and 68.07% followed good practice, whereas 20.98% of the NDR group had a good knowledge of DR, 94.18% had a positive attitude, and 66.92% followed good practice. There was no significant difference in the KAP of the two groups of subjects. In the NDR group, a good level of knowledge was associated with a high-level of education (OR = 0.1, 0.2; p < 0.05), a good attitude was associated with retirement (OR = 0.2; p < 0.05), and good practice was associated with being female, having a high-level of education, and the type of treatment (OR = 0.5, 0.4, 2.3, 3.1; p < 0.05). In the DR group, good practice was associated with older age and retirement (OR = 0.6, 0.4; p < 0.05). Conclusions: There was no significant difference between the DR and NDR subjects in the overall levels of KAP, but both groups showed a poor level of knowledge. Age, gender, education, occupation, and type of treatment were the main factors associated with the KAP scores, more risk factors in the NDR group than in the DR group. There is an urgent need for coordinated educational campaigns with a prioritized focus on the northeast region of China, especially NDR group.


Subject(s)
Diabetes Mellitus , Diabetic Retinopathy , Health Knowledge, Attitudes, Practice , China , Cross-Sectional Studies , Female , Humans , Urban Population
11.
Sci Rep ; 12(1): 5493, 2022 Mar 31.
Article in English | MEDLINE | ID: covidwho-1768855

ABSTRACT

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) emerged in Wuhan, China, has led to the rapid development of Coronavirus disease 2019 (COVID-19) pandemic. COVID-19 represents a fatal disease with a great global public health importance. This study aims to develop a three-parameter Weibull mathematical model using continuous functions to represent discrete COVID-19 data. Subsequently, the model was applied to quantitatively analyze the characteristics for the mortality of COVID-19, including the age, sex, the length of symptom time to hospitalization time (SH), hospitalization date to death time (HD) and symptom time to death time time (SD) and others. A three-parameter mathematical model was developed by combining the reported cases in the Data Repository from the Center for Systems Science and Engineering at Johns Hopkins University and applied to estimate and analyze the characteristics for mortality of COVID-19. We found that the scale parameters of males and females were 5.85 and 5.45, respectively. Probability density functions in both males and females were negative skewness. 5% of male patients died under the age of 43.28 (44.37 for females), 50% died under 69.55 (73.25 for females), and 95% died under 86.59 (92.78 for females). The peak age of male death was 67.45 years, while that of female death was 71.10 years. The peak and median values of SH, HD and SD in male death were correspondingly 1.17, 5.18 and 10.30 days, and 4.29, 11.36 and 16.33 days, while those in female death were 1.19, 5.80 and 12.08 days, and 4.60, 12.44 and 17.67 days, respectively. The peak age of probability density in male and female deaths was 69.55 and 73.25 years, while the high point age of their mortality risk was 77.51 and 81.73 years, respectively. The mathematical model can fit and simulate the impact of various factors on IFR. From the simulation results of the model, we can intuitively find the IFR, peak age, average age and other information of each age. In terms of time factors, the mortality rate of the most susceptible population is not the highest, and the distribution of male patients is different from the distribution of females. This means that Self-protection and self-recovery in females against SARS-CoV-2 virus might be better than those of males. Males were more likely to be infected, more likely to be admitted to the ICU and more likely to die of COVID-19. Moreover, the infection fatality ration (IFR) of COVID-19 population was intrinsically linked to the infection age. Public health measures to protect vulnerable sex and age groups might be a simple and effective way to reduce IFR.


Subject(s)
COVID-19 , Aged , Aged, 80 and over , Disease Susceptibility , Female , Humans , Male , Models, Theoretical , Public Health , SARS-CoV-2
12.
Biosens Bioelectron ; 209: 114226, 2022 Mar 31.
Article in English | MEDLINE | ID: covidwho-1767929

ABSTRACT

Protein sensors based on allosteric enzymes responding to target binding with rapid changes in enzymatic activity are potential tools for homogeneous assays. However, a high signal-to-noise ratio (S/N) is difficult to achieve in their construction. A high S/N is critical to discriminate signals from the background, a phenomenon that might largely vary among serum samples from different individuals. Herein, based on the modularized luciferase NanoLuc, we designed a novel biosensor called NanoSwitch. This sensor allows direct detection of antibodies in 1 µl serum in 45 min without washing steps. In the detection of Flag and HA antibodies, NanoSwitches respond to antibodies with S/N ratios of 33-fold and 42-fold, respectively. Further, we constructed a NanoSwitch for detecting SARS-CoV-2-specific antibodies, which showed over 200-fold S/N in serum samples. High S/N was achieved by a new working model, combining the turn-off of the sensor with human serum albumin and turn-on with a specific antibody. Also, we constructed NanoSwitches for detecting antibodies against the core protein of hepatitis C virus (HCV) and gp41 of the human immunodeficiency virus (HIV). Interestingly, these sensors demonstrated a high S/N and good performance in the assays of clinical samples; this was partly attributed to the combination of off-and-on models. In summary, we provide a novel type of protein sensor and a working model that potentially guides new sensor design with better performance.

13.
Nat Methods ; 19(4): 479-485, 2022 Apr.
Article in English | MEDLINE | ID: covidwho-1764194

ABSTRACT

The recent development of solvent- and polymer-based brain-clearing techniques has advanced our ability to visualize the mammalian nervous system in three dimensions. However, it remains challenging to image the mammalian body en bloc. Here we developed HYBRiD (hydrogel-based reinforcement of three-dimensional imaging solvent-cleared organs (DISCO)), by recombining components of organic- and polymer-based clearing pipelines. We achieved high transparency and protein retention, as well as compatibility with direct fluorescent imaging and immunostaining in cleared mammalian bodies. Using parvalbumin- and somatostatin-Cre models, we demonstrated the utility of HYBRiD for whole-body imaging of genetically encoded fluorescent reporters without antibody enhancement of signals in newborn and juvenile mice. Using K18-hACE2 transgenic mice, HYBRiD enabled perfusion-free clearing and visualization of SARS-CoV-2 infection in a whole mouse chest, revealing macroscopic and microscopic features of viral pathology in the same sample. HYBRiD offers a simple and universal solution to visualize large heterogeneous body parts or entire animals for basic and translational research.


Subject(s)
COVID-19 , Hydrogels , Animals , Imaging, Three-Dimensional/methods , Mammals , Mice , Polymers , SARS-CoV-2 , Solvents
14.
Soc Sci Med ; 298: 114800, 2022 04.
Article in English | MEDLINE | ID: covidwho-1747569

ABSTRACT

Despite unprecedented progress in developing COVID-19 vaccines, global vaccination levels needed to reach herd immunity remain a distant target, while new variants keep emerging. Obtaining near universal vaccine uptake relies on understanding and addressing vaccine resistance. Simple questions about vaccine acceptance however ignore that the vaccines being offered vary across countries and even population subgroups, and differ in terms of efficacy and side effects. By using advanced discrete choice models estimated on stated choice data collected in 18 countries/territories across six continents, we show a substantial influence of vaccine characteristics. Uptake increases if more efficacious vaccines (95% vs 60%) are offered (mean across study areas = 3.9%, range of 0.6%-8.1%) or if vaccines offer at least 12 months of protection (mean across study areas = 2.4%, range of 0.2%-5.8%), while an increase in severe side effects (from 0.001% to 0.01%) leads to reduced uptake (mean = -1.3%, range of -0.2% to -3.9%). Additionally, a large share of individuals (mean = 55.2%, range of 28%-75.8%) would delay vaccination by 3 months to obtain a more efficacious (95% vs 60%) vaccine, where this increases further if the low efficacy vaccine has a higher risk (0.01% instead of 0.001%) of severe side effects (mean = 65.9%, range of 41.4%-86.5%). Our work highlights that careful consideration of which vaccines to offer can be beneficial. In support of this, we provide an interactive tool to predict uptake in a country as a function of the vaccines being deployed, and also depending on the levels of infectiousness and severity of circulating variants of COVID-19.


Subject(s)
COVID-19 , Vaccines , COVID-19/prevention & control , COVID-19 Vaccines/therapeutic use , Humans , Immunity, Herd , Vaccination
15.
Acta Pharmacol Sin ; 2022 Mar 16.
Article in English | MEDLINE | ID: covidwho-1747246

ABSTRACT

VV116 (JT001) is an oral drug candidate of nucleoside analog against SARS-CoV-2. The purpose of the three phase I studies was to evaluate the safety, tolerability, and pharmacokinetics of single and multiple ascending oral doses of VV116 in healthy subjects, as well as the effect of food on the pharmacokinetics and safety of VV116. Three studies were launched sequentially: Study 1 (single ascending-dose study, SAD), Study 2 (multiple ascending-dose study, MAD), and Study 3 (food-effect study, FE). A total of 86 healthy subjects were enrolled in the studies. VV116 tablets or placebo were administered per protocol requirements. Blood samples were collected at the scheduled time points for pharmacokinetic analysis. 116-N1, the metabolite of VV116, was detected in plasma and calculated for the PK parameters. In SAD, AUC and Cmax increased in an approximately dose-proportional manner in the dose range of 25-800 mg. T1/2 was within 4.80-6.95 h. In MAD, the accumulation ratio for Cmax and AUC indicated a slight accumulation upon repeated dosing of VV116. In FE, the standard meal had no effect on Cmax and AUC of VV116. No serious adverse event occurred in the studies, and no subject withdrew from the studies due to adverse events. Thus, VV116 exhibited satisfactory safety and tolerability in healthy subjects, which supports the continued investigation of VV116 in patients with COVID-19.

16.
Int J Environ Res Public Health ; 19(6)2022 03 11.
Article in English | MEDLINE | ID: covidwho-1742439

ABSTRACT

Taiwan has been a world leader in controlling the spread of SARS-CoV-2 during the COVID-19 pandemic. Recently, the Taiwan Government launched its COVID-19 tracing app, 'Taiwan Social Distancing App'; however, the effectiveness of this tracing app depends on its acceptance and uptake among the general population. We measured the acceptance of three hypothetical tracing technologies (telecommunication network tracing, a government app, and the Apple and Google Bluetooth exposure notification system) in four nationally representative Taiwanese samples. Using Bayesian methods, we found a high acceptance of all three tracking technologies, with acceptance increasing with the inclusion of additional privacy measures. Modeling revealed that acceptance increased with the perceived technology benefits, trust in the providers' intent, data security and privacy measures, the level of ongoing control, and one's level of education. Acceptance decreased with data sensitivity perceptions and a perceived low policy compliance by others among the general public. We consider the policy implications of these results for Taiwan during the COVID-19 pandemic and in the future.


Subject(s)
COVID-19 , Bayes Theorem , COVID-19/epidemiology , COVID-19/prevention & control , Humans , Pandemics/prevention & control , SARS-CoV-2 , Taiwan/epidemiology , Technology
17.
Nat Prod Res ; : 1-5, 2021 Nov 30.
Article in English | MEDLINE | ID: covidwho-1730494

ABSTRACT

Artemisia argyi is a widely distributed and inexpensive plant resource, and study on its chemical compositions and biological activities will provide an important basis for its food applications and pharmaceutical developments. In this study, fourteen known guaiane-type sesquiterpenes (1-14), four known eudesmane-type sesquiterpenes (15-18), two known germacranolide-type sesquiterpenes (19, 20), and eight other types of terpenoids (20-28) were isolated from the leaves of A. argyi by polyamide and ODS CC and HPLC. The structures of all compounds are determined by 1 D NMR (1H-NMR、13C-NMR) and literature comparison. Among them, compounds 1 and 8 were isolated from Chinese folk medicine A. argyi for the first time. Besides, the LPS-induced RAW264.7 cell model has been evaluated the anti-inflammatory activities in vitro by the Griess reagent. The results indicated that the guaianolide sesquiterpenoids obtained from A. argyi have an excellent ability to inhibit NO production, especially Argyin A, a guaianolide sesquiterpenoid with isovaleryloxy substitution.

18.
Journal of Zhejiang University ; 48(3):356-367, 2021.
Article in Chinese | GIM | ID: covidwho-1726094

ABSTRACT

The global outbreak of novel Coronavirus Disease (COVID-19) epidemic has seriously endangered people's health and hindered rapid economic development. Geographic analysis of spatial and temporal transmission patterns in key regions can help prevent and control the epidemic. This paper takes Zhejiang province as the research area. With the help of POI data, the methods such as textual analysis, mathematical statistics, and spatial regression analysis are used to analyze the socio-demographic characteristics of confirmed cases and the spatio-temporal evolution of the epidemic, and then analyze its influencing factors. The results show that: (1) The age distribution of confirmed cases spanned a wide range, showing normal distribution of "large in the middle and small at both ends." (2) The epidemic period is divided into five stages: the initial period, the outbreak period, the steady decline period, the internal stable period, and the oversea input period. The interval between the onset time and announcing a confirmed case was mostly 0-6 d, and the time interval of non-local cases is longer than that of local cases, and the onset of most of the non-local cases occur on the day the patients leave their original place. There was no significant gender difference in the proportion of daily incidence, and the proportion of age had stage features. (3) The spatial distribution aligned in the direction of "Southeast-Northwest", the evolution trend developed from "single place distribution" to "multi-area cluster cases" and then to "key input" evolution, with "high-high" "high-low" clustering characteristics;The migration path of confirmed cases presented an obvious core-edge structure, and the first significant flow was from the center of Wuhan. (4) By analyzing the factors affecting the distribution of the epidemic,it is found that the ratio of the elderly population, per capita GDP, the proportion of the tertiary industry, the number of industries above the scale, and the distance from Wuhan were the dominant factors. Finally, several suggestions on targeted prevention and control measures are made, and the weaknesses of the study and future directions of efforts are pointed out.

19.
Sens Actuators B Chem ; 357: 131415, 2022 Apr 15.
Article in English | MEDLINE | ID: covidwho-1720936

ABSTRACT

Facing the unstopped surges of COVID-19, an insufficient capacity of diagnostic testing jeopardizes the control of disease spread. Due to a centralized setting and a long turnaround, real-time reverse transcription polymerase chain reaction (real-time RT-PCR), the gold standard of viral detection, has fallen short in timely reflecting the epidemic status quo during an urgent outbreak. As such, a rapid screening tool is necessitated to help contain the spread of COVID-19 amid the countries where the vaccine implementations have not been widely deployed. In this work, we propose a saliva-based COVID-19 antigen test using the electrical double layer (EDL)-gated field-effect transistor-based biosensor (BioFET). The detection of SARS-CoV-2 nucleocapsid (N) protein is validated with limits of detection (LoDs) of 0.34 ng/mL (7.44 pM) and 0.14 ng/mL (2.96 pM) in 1× PBS and artificial saliva, respectively. The specificity is inspected with types of antigens, exhibiting low cross-reactivity among MERS-CoV, Influenza A virus, and Influenza B virus. This portable system is embedded with Bluetooth communication and user-friendly interfaces that are fully compatible with digital health, feasibly leading to an on-site turnaround, an effective management, and a proactive response taken by medical providers and frontline health workers.

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