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1.
J Formos Med Assoc ; 2021 Jul 09.
Article in English | MEDLINE | ID: covidwho-1587282
2.
Trans GIS ; 2021 Aug 05.
Article in English | MEDLINE | ID: covidwho-1341296

ABSTRACT

COVID-19 maps convey hazard and risk information to the public, which play an important role in the risk communication for individual protection. The aim of this study is to improve the effectiveness and efficiency of communicating the specific risk of COVID-19 maps. By testing 71 subjects from Wuhan, China, this study explored how color schemes (cool, warm, and mixed colors) and data presentation forms (choropleth maps, graduated symbol maps) influence visual cognition patterns, risk perception, comprehension, and subjective satisfaction. The results indicated that the warm scheme (yellow/red) has significant strengths in visual cognition and understanding, and the choropleth map (vs. the graduated symbol map) has significant strengths in risk expression. On subjective satisfaction, the combination of the mixed scheme (blue/yellow/red) and the choropleth map scored highest mean value. These results have implications for enhancing the focused functions of COVID-19 maps that fit different terms: in the early and medium terms of disease transmission, choropleth maps with warm or cool colors should be considered as a priority design for their better risk perception. When the epidemic conditions are on the upturn, a better reading experience combination of choropleth maps with mixed colors can be considered.

3.
Front Public Health ; 9: 695931, 2021.
Article in English | MEDLINE | ID: covidwho-1325588

ABSTRACT

Unlike past health crises that were more localized, the highly contagious coronavirus disease 2019 (COVID-19) crisis is impacting the world to an unprecedented extent. This is the first study examining how and whether the COVID-19 pandemic affects herding behavior in the Eastern European stock markets. Using samples from the stock markets of Russia, Poland, the Czech Republic, Hungary, Croatia, and Slovenia from January 1, 2010 to March 10, 2021, we demonstrate that the COVID-19 pandemic has increased herding behavior in all the sample stock markets. Our results show that the COVID-19 crisis reinforces the impact of global market returns on herding behavior in these specific stock markets. We find that COVID-19 strengthens the spillover effect of regional herding on herding behavior. Thus, financial authorities should monitor investors in the stock market to avoid the increase in herding behavior as well as the reinforcement of the global market returns and regional return dispersion on herding during the period of pandemic.


Subject(s)
COVID-19 , Pandemics , Commerce , Croatia , Czech Republic , Humans , Hungary , Investments , Poland , Russia , SARS-CoV-2 , Slovenia
4.
BMC Med Inform Decis Mak ; 21(1): 207, 2021 07 01.
Article in English | MEDLINE | ID: covidwho-1296596

ABSTRACT

BACKGROUND: Clinical risk prediction models (CRPMs) use patient characteristics to estimate the probability of having or developing a particular disease and/or outcome. While CRPMs are gaining in popularity, they have yet to be widely adopted in clinical practice. The lack of explainability and interpretability has limited their utility. Explainability is the extent of which a model's prediction process can be described. Interpretability is the degree to which a user can understand the predictions made by a model. METHODS: The study aimed to demonstrate utility of patient similarity analytics in developing an explainable and interpretable CRPM. Data was extracted from the electronic medical records of patients with type-2 diabetes mellitus, hypertension and dyslipidaemia in a Singapore public primary care clinic. We used modified K-nearest neighbour which incorporated expert input, to develop a patient similarity model on this real-world training dataset (n = 7,041) and validated it on a testing dataset (n = 3,018). The results were compared using logistic regression, random forest (RF) and support vector machine (SVM) models from the same dataset. The patient similarity model was then implemented in a prototype system to demonstrate the identification, explainability and interpretability of similar patients and the prediction process. RESULTS: The patient similarity model (AUROC = 0.718) was comparable to the logistic regression (AUROC = 0.695), RF (AUROC = 0.764) and SVM models (AUROC = 0.766). We packaged the patient similarity model in a prototype web application. A proof of concept demonstrated how the application provided both quantitative and qualitative information, in the form of patient narratives. This information was used to better inform and influence clinical decision-making, such as getting a patient to agree to start insulin therapy. CONCLUSIONS: Patient similarity analytics is a feasible approach to develop an explainable and interpretable CRPM. While the approach is generalizable, it can be used to develop locally relevant information, based on the database it searches. Ultimately, such an approach can generate a more informative CRPMs which can be deployed as part of clinical decision support tools to better facilitate shared decision-making in clinical practice.


Subject(s)
Clinical Decision-Making , Electronic Health Records , Humans , Logistic Models , Singapore , Support Vector Machine
5.
Sens Actuators B Chem ; 343: 130139, 2021 Sep 15.
Article in English | MEDLINE | ID: covidwho-1240621

ABSTRACT

Owing to the over-increasing demands in resisting and managing the coronavirus disease 2019 (COVID-19) pandemic, development of rapid, highly sensitive, accurate, and versatile tools for monitoring total antibody concentrations at the population level has been evolved as an urgent challenge on measuring the fatality rate, tracking the changes in incidence and prevalence, comprehending medical sequelae after recovery, as well as characterizing seroprevalence and vaccine coverage. To this end, herein we prepared highly luminescent quantum dot nanobeads (QBs) by embedding numerous quantum dots into polymer matrix, and then applied it as a signal-amplification label in lateral flow immunoassay (LFIA). After covalently linkage with the expressed recombinant SARS-CoV-2 spike protein (RSSP), the synthesized QBs were used to determine the total antibody levels in sera by virtue of a double-antigen sandwich immunoassay. Under the developed condition, the QB-LFIA can allow the rapid detection of SARS-CoV-2 total antibodies within 15 min with about one order of magnitude improvement in analytical sensitivity compared to conventional gold nanoparticle-based LFIA. In addition, the developed QB-LFIA performed well in clinical study in dynamic monitoring of serum antibody levels in the whole course of SARS-CoV-2 infection. In conclusion, we successfully developed a promising fluorescent immunological sensing tool for characterizing the host immune response to SARS-CoV-2 infection and confirming the acquired immunity to COVID-19 by evaluating the SRAS-CoV-2 total antibody level in the crowd.

6.
Biosens Bioelectron ; 171: 112753, 2021 Jan 01.
Article in English | MEDLINE | ID: covidwho-885210

ABSTRACT

A polyethyleneimine (PEI)-assisted copper in-situ growth (CISG) strategy was proposed as a controlled signal amplification strategy to enhance the sensitivity of gold nanoparticle-based lateral flow sensors (AuNP-LFS). The controlled signal amplification is achieved by introducing PEI as a structure-directing agent to regulate the thermodynamics of anisotropic Cu nanoshell growth on the AuNP surface, thus controlling shape and size of the resultant AuNP@Cu core-shell nanostructures and confining free reduction and self-nucleation of Cu2+ for improved reproducibility and decreased false positives. The PEI-CISG-enhanced AuNP-LFS showed ultrahigh sensitivities with the detection limits of 50 fg mL-1 for HIV-1 capsid p24 antigen and 6 CFU mL-1 for Escherichia coli O157:H7. We further demonstrated its clinical diagnostic efficacy by configuring PEI-CISG into a commercial AuNP-LFS detection kit for SARS-CoV-2 antibody detection. Altogether, this work provides a reliable signal amplification platform to dramatically enhance the sensitivity of AuNP-LFS for rapid and accurate diagnostics of various infectious diseases.


Subject(s)
Biosensing Techniques/methods , Copper/chemistry , Coronavirus Infections/diagnosis , Escherichia coli Infections/diagnosis , Gold/chemistry , HIV Infections/diagnosis , Pneumonia, Viral/diagnosis , Betacoronavirus/isolation & purification , Biosensing Techniques/instrumentation , COVID-19 , COVID-19 Testing , Clinical Laboratory Techniques , Equipment Design , Escherichia coli O157/isolation & purification , HIV Core Protein p24/analysis , HIV-1/isolation & purification , Humans , Limit of Detection , Metal Nanoparticles/chemistry , Metal Nanoparticles/ultrastructure , Oxidation-Reduction , Pandemics , Polyethyleneimine/chemistry , Reagent Strips/analysis , SARS-CoV-2
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