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1.
Talanta ; 225: 122038, 2021 Apr 01.
Artigo em Inglês | MEDLINE | ID: mdl-33592762

RESUMO

Demand for high quality Basmati rice has increased significantly in the last decade. This commodity is highly vulnerable to fraud, especially in the post COVID-19 era. A unique two-tiered analytical system comprised of rapid on-site screening of samples using handheld portable Near-infrared NIR and laboratory confirmatory technique using a Head space gas chromatography mass spectrometry (HS-GC-MS) strategy for untargeted analysis was developed. Chemometric models built using NIR data correctly predicted nearly 100% of Pusa 1121 and Taraori, two high value types of Basmati, from potential adulterants. Furthermore, rice VOC profile fingerprints showed very good classification (R2 >0.9, Q2 > 0.9, Accuracy > 0.99) for these high quality Basmati varieties from potential adulterant varieties with aldehydes identified as key VOC marker compounds. Using a two-tiered system of a rapid method for on-site screening of many samples alongside a laboratory-based confirmatory method can classify Basmati rice varieties, protecting the supply chain from fraud.


Assuntos
/prevenção & controle , Análise de Alimentos/métodos , Cromatografia Gasosa-Espectrometria de Massas/métodos , Oryza/química , Compostos Orgânicos Voláteis/análise , /epidemiologia , Fraude/prevenção & controle , Humanos , Índia , Oryza/classificação , Pandemias , Reprodutibilidade dos Testes , /fisiologia
2.
Soc Sci Med ; 269: 113569, 2021 01.
Artigo em Inglês | MEDLINE | ID: mdl-33309154

RESUMO

We investigate the links between corruption and compliance with social distancing during COVID-19 pandemic in America. Both theory and empirical evidence point to a corrosive effect of corruption on trust/social capital which in turn determine people's behavior towards compliance with public health policies. Using data from 50 states we find that people who live in more corrupt states are less likely to comply with so called shelter in place/stay at home orders. Our results are robust to different measures of corruption.


Assuntos
/prevenção & controle , Fraude/estatística & dados numéricos , Fidelidade a Diretrizes/estatística & dados numéricos , Quarentena/legislação & jurisprudência , /epidemiologia , Guias como Assunto , Humanos , Capital Social , Confiança/psicologia , Estados Unidos/epidemiologia
3.
Food Chem ; 335: 127640, 2021 Jan 15.
Artigo em Inglês | MEDLINE | ID: mdl-32738536

RESUMO

In order to distinguish different vegetable oils, adulterated vegetable oils, and to identify and quantify counterfeit vegetable oils, a method based on a small sample size of total synchronous fluorescence (TSyF) spectra combined with convolutional neural network (CNN) was proposed. Four typical vegetable oils were classified by three ways of fine-tuning the pre-trained CNN, the pre-trained CNN as a feature extractor, and traditional chemometrics. The pre-trained CNN was combined with support vector machines to distinguish adulterated sesame oil and counterfeit sesame oil separately with 100% correct classification rates. The pre-trained CNN combined with partial least square regression was used to predict the level of counterfeit sesame oil. The coefficient of determination for calibration (Rc2) values were all greater than 0.99, and the root mean square errors of validation were 0.81% and 1.72%, respectively. These results show that it is feasible to combine TSyF spectra with CNN for vegetable oil identification.


Assuntos
Redes Neurais de Computação , Óleos Vegetais/química , Espectrometria de Fluorescência/métodos , Qualidade dos Alimentos , Fraude , Análise dos Mínimos Quadrados , Óleo de Gergelim/química , Máquina de Vetores de Suporte
4.
Food Chem ; 338: 127936, 2021 Feb 15.
Artigo em Inglês | MEDLINE | ID: mdl-32932081

RESUMO

The trace and rare earth elements content of 93 honeys of different botanical type and origin have been studied through ICP-MS. Discriminant Analysis (DA) was successful for botanical type and geographical origin classification while Cluster Analysis (CA) was successful only for botanical type. Through Probabilistic Neural Network (PNN) analysis, 85.3% were correctly classified by the network according to their geographical origin and 73.3% according to their organic characterization. A Partial Least Squares (PLS) model was constructed, giving a prediction accuracy of more than 95%. Information obtained using Rare Earths (Y, La, Ce, Pr, Nd, Sm, Eu, Gd, Tb, Dy, Ho, Er, Tm, Yb, Lu) and trace elements (Li, Mg, Mn, Ni, Co, Cu, Sr, Ba, Pb) via chemometric evaluation facilitated classification of honey samples.


Assuntos
Quimioinformática , Geografia , Mel/análise , Metabolômica , Análise por Conglomerados , Análise Discriminante , Fraude/prevenção & controle , Análise dos Mínimos Quadrados , Metais Terras Raras/análise , Redes Neurais de Computação , Análise Espectral , Oligoelementos/análise
6.
J Med Internet Res ; 22(11): e20044, 2020 11 20.
Artigo em Inglês | MEDLINE | ID: mdl-33151895

RESUMO

BACKGROUND: Individuals with large followings can influence public opinions and behaviors, especially during a pandemic. In the early days of the pandemic, US president Donald J Trump has endorsed the use of unproven therapies. Subsequently, a death attributed to the wrongful ingestion of a chloroquine-containing compound occurred. OBJECTIVE: We investigated Donald J Trump's speeches and Twitter posts, as well as Google searches and Amazon purchases, and television airtime for mentions of hydroxychloroquine, chloroquine, azithromycin, and remdesivir. METHODS: Twitter sourcing was catalogued with Factba.se, and analytics data, both past and present, were analyzed with Tweet Binder to assess average analytics data on key metrics. Donald J Trump's time spent discussing unverified treatments on the United States' 5 largest TV stations was catalogued with the Global Database of Events, Language, and Tone, and his speech transcripts were obtained from White House briefings. Google searches and shopping trends were analyzed with Google Trends. Amazon purchases were assessed using Helium 10 software. RESULTS: From March 1 to April 30, 2020, Donald J Trump made 11 tweets about unproven therapies and mentioned these therapies 65 times in White House briefings, especially touting hydroxychloroquine and chloroquine. These tweets had an impression reach of 300% above Donald J Trump's average. Following these tweets, at least 2% of airtime on conservative networks for treatment modalities like azithromycin and continuous mentions of such treatments were observed on stations like Fox News. Google searches and purchases increased following his first press conference on March 19, 2020, and increased again following his tweets on March 21, 2020. The same is true for medications on Amazon, with purchases for medicine substitutes, such as hydroxychloroquine, increasing by 200%. CONCLUSIONS: Individuals in positions of power can sway public purchasing, resulting in undesired effects when the individuals' claims are unverified. Public health officials must work to dissuade the use of unproven treatments for COVID-19.


Assuntos
Comunicação , Infecções por Coronavirus/tratamento farmacológico , Infecções por Coronavirus/epidemiologia , Governo Federal , Internet/estatística & dados numéricos , Meios de Comunicação de Massa/estatística & dados numéricos , Pneumonia Viral/tratamento farmacológico , Pneumonia Viral/epidemiologia , Monofosfato de Adenosina/análogos & derivados , Monofosfato de Adenosina/uso terapêutico , Alanina/análogos & derivados , Alanina/uso terapêutico , Azitromicina/uso terapêutico , Cloroquina/uso terapêutico , Fraude/estatística & dados numéricos , Humanos , Hidroxicloroquina/uso terapêutico , Idioma , Pandemias , Saúde Pública/estatística & dados numéricos , Saúde Pública/tendências , Estados Unidos/epidemiologia
7.
JAMA ; 324(17): 1735-1736, 2020 11 03.
Artigo em Inglês | MEDLINE | ID: mdl-33141194
9.
BMC Public Health ; 20(1): 1595, 2020 Oct 22.
Artigo em Inglês | MEDLINE | ID: mdl-33092568

RESUMO

BACKGROUND: Since the time of declaration of global pandemic of COVID-19 by World Health Organization (WHO), falsified hand sanitizers surfaced regularly in markets, posing possible harm to public due to unlisted inclusion of methanol. The current research is an attempt to develop and validate a tool to document falsified hand sanitizer in the UAE community. METHOD: A descriptive cross-sectional community-based study was conducted among 1280 randomly selected participants. Respondents were sent a web-based electronic link to the survey via email. Content validity, factor analyses and known group validity were used to develop and validate a new scale to identify falsified hand sanitizer. Test-retest reliability, internal consistency, item internal consistency (IIC), and intraclass correlation coefficients (ICCs) were used to assess the reliability of the scale. SPSS version 24 was used to conduct data analysis. RESULTS: A total of 1280 participants were enrolled in the study. The content validity index (CVI) was 0.83 with the final scale of 12 items. The Kaiser-Meyer-Olkin (KMO) value was 0.788, with the Bartlett test of sphericity achieving statistical significance (p < 0.001). Our factor analysis revealed a 3-component model. The 3-factor solution was confirmed by PCFA analysis and had associations with good fit values. The PCFA for NFI was 0.970, CFI 0.978, and TLI 0.967. All values were in excess of 0.95, with RMSEA values below 0.06 at 0.03; all of these values indicated a good model fit. The Cronbach's alpha was good overall (0.867). All factors had a Cronbach's alpha value in excess of 0.70. The instrument demonstrated that every item met the IIC correlation standard ≥0.40. The scale displayed good overall ICC statistics of 0.867 (95% CI 0.856-0.877) with statistical significance (p < 0.001). The scale's test-retest reliability was assessed through correlation of the falsified hand sanitizer identification score of respondents at the two time points. The test-retest correlation coefficient was 0.770 (p value < 0.01). Participants with post-graduate education were more likely to identify the falsified hand sanitizer compared to those with high school education. (p < 0.001). CONCLUSIONS: This study developed and validated a new scale for the measurement of falsified hand sanitizer. This is expected to improve and promote collaboration between the health regulators and the public and hereby encourage customer satisfaction and participation.


Assuntos
Fraude , Higienizadores de Mão/normas , Inquéritos e Questionários , Adolescente , Adulto , Infecções por Coronavirus/epidemiologia , Estudos Transversais , Análise Fatorial , Feminino , Humanos , Masculino , Pessoa de Meia-Idade , Pandemias , Projetos Piloto , Pneumonia Viral/epidemiologia , Saúde Pública/legislação & jurisprudência , Reprodutibilidade dos Testes , Emirados Árabes Unidos/epidemiologia , Adulto Jovem
10.
Global Health ; 16(1): 101, 2020 10 20.
Artigo em Inglês | MEDLINE | ID: mdl-33081805

RESUMO

Corruption is recognized by the global community as a threat to development generally and to achieving health goals, such as the United Nations Sustainable Development Goal # 3: ensuring healthy lives and promoting well-being for all. As such, international organizations such as the World Health Organizations and the United Nations Development Program are creating an evidence base on how best to address corruption in health systems. At present, the risk of corruption is even more apparent, given the need for quick and nimble responses to the COVID-19 pandemic, which may include a relaxation of standards and the rapid mobilization of large funds. As international organizations and governments attempt to respond to the ever-changing demands of this pandemic, there is a need to acknowledge and address the increased opportunity for corruption.In order to explore how such risks of corruption are addressed in international organizations, this paper focuses on the question: How are international organizations implementing measures to promote accountability and transparency, and anti-corruption, in their own operations? The following international organizations were selected as the focus of this paper given their current involvement in anti-corruption, transparency, and accountability in the health sector: the World Health Organization, the United Nations Development Program, the World Bank Group, and the Global Fund to Fight Aids, Tuberculosis and Malaria. Our findings demonstrate that there has been a clear increase in the volume and scope of anti-corruption, accountability, and transparency measures implemented by these international organizations in recent years. However, the efficacy of these measures remains unclear. Further research is needed to determine how these measures are achieving their transparency, accountability, and anti-corruption goals.


Assuntos
Revelação , Fraude/prevenção & controle , Saúde Global/economia , Responsabilidade Social , Nações Unidas , Organização Mundial da Saúde , Síndrome de Imunodeficiência Adquirida/prevenção & controle , Humanos , Malária/prevenção & controle , Tuberculose/prevenção & controle
11.
Int J Law Psychiatry ; 72: 101611, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-32911444

RESUMO

Fear, anxiety and even paranoia can proliferate during a pandemic. Such conditions, even when subclinical, tend to be a product of personal and predispositional factors, as well as shared cultural influences, including religious, literary, film, and gaming, all of which can lead to emotional and less than rational responses. They can render people vulnerable to engage in implausible conspiracy theories about the causes of illness and governmental responses to it. They can also lead people to give credence to simplistic and unscientific misrepresentations about medications and devices which are claimed to prevent, treat or cure disease. In turn such vulnerability creates predatory opportunities for the unscrupulous. This article notes the eruption of quackery during the 1889-1892 Russian Flu and the 1918-1920 Spanish Flu and the emergence during 2020 of spurious claims during the COVID-19 pandemic. It identifies consumer protection strategies and interventions formulated during the 2020 pandemic. Using examples from the United States, Japan, Australia and the United Kingdom, it argues that during a pandemic there is a need for three responses by government to the risks posed by conspiracy theories and false representations: calm, scientifically-based messaging from public health authorities; cease and desist warnings directed toward those making extravagant or inappropriate claims; and the taking of assertive and well publicised legal action against individuals and entities that make false representations in order to protect consumers rendered vulnerable by their emotional responses to the phenomenology of the pandemic.


Assuntos
Infecções por Coronavirus/epidemiologia , Fraude/prevenção & controle , Pneumonia Viral/epidemiologia , Prática de Saúde Pública/estatística & dados numéricos , Charlatanismo/prevenção & controle , Revelação da Verdade , Austrália , Betacoronavirus , Fraude/estatística & dados numéricos , Comportamentos Relacionados com a Saúde , Conhecimentos, Atitudes e Prática em Saúde , Humanos , Japão , Pandemias , Saúde Pública , Charlatanismo/estatística & dados numéricos , Mídias Sociais/estatística & dados numéricos , Estados Unidos
12.
JMIR Public Health Surveill ; 6(3): e20794, 2020 08 25.
Artigo em Inglês | MEDLINE | ID: mdl-32750006

RESUMO

BACKGROUND: The coronavirus disease (COVID-19) pandemic is perhaps the greatest global health challenge of the last century. Accompanying this pandemic is a parallel "infodemic," including the online marketing and sale of unapproved, illegal, and counterfeit COVID-19 health products including testing kits, treatments, and other questionable "cures." Enabling the proliferation of this content is the growing ubiquity of internet-based technologies, including popular social media platforms that now have billions of global users. OBJECTIVE: This study aims to collect, analyze, identify, and enable reporting of suspected fake, counterfeit, and unapproved COVID-19-related health care products from Twitter and Instagram. METHODS: This study is conducted in two phases beginning with the collection of COVID-19-related Twitter and Instagram posts using a combination of web scraping on Instagram and filtering the public streaming Twitter application programming interface for keywords associated with suspect marketing and sale of COVID-19 products. The second phase involved data analysis using natural language processing (NLP) and deep learning to identify potential sellers that were then manually annotated for characteristics of interest. We also visualized illegal selling posts on a customized data dashboard to enable public health intelligence. RESULTS: We collected a total of 6,029,323 tweets and 204,597 Instagram posts filtered for terms associated with suspect marketing and sale of COVID-19 health products from March to April for Twitter and February to May for Instagram. After applying our NLP and deep learning approaches, we identified 1271 tweets and 596 Instagram posts associated with questionable sales of COVID-19-related products. Generally, product introduction came in two waves, with the first consisting of questionable immunity-boosting treatments and a second involving suspect testing kits. We also detected a low volume of pharmaceuticals that have not been approved for COVID-19 treatment. Other major themes detected included products offered in different languages, various claims of product credibility, completely unsubstantiated products, unapproved testing modalities, and different payment and seller contact methods. CONCLUSIONS: Results from this study provide initial insight into one front of the "infodemic" fight against COVID-19 by characterizing what types of health products, selling claims, and types of sellers were active on two popular social media platforms at earlier stages of the pandemic. This cybercrime challenge is likely to continue as the pandemic progresses and more people seek access to COVID-19 testing and treatment. This data intelligence can help public health agencies, regulatory authorities, legitimate manufacturers, and technology platforms better remove and prevent this content from harming the public.


Assuntos
Comércio/legislação & jurisprudência , Infecções por Coronavirus/prevenção & controle , Fraude/estatística & dados numéricos , Marketing/legislação & jurisprudência , Pandemias/prevenção & controle , Pneumonia Viral/prevenção & controle , Mídias Sociais/estatística & dados numéricos , Big Data , Infecções por Coronavirus/epidemiologia , Aprendizado Profundo , Humanos , Processamento de Linguagem Natural , Pneumonia Viral/epidemiologia , Estados Unidos/epidemiologia
16.
Food Chem ; 332: 127344, 2020 Dec 01.
Artigo em Inglês | MEDLINE | ID: mdl-32619937

RESUMO

There is a contentious need for robust and rapid methodologies for maintaining the authenticity of foods and food additives. The current paper presented a new Raman spectroscopy-based methodology for detection and quantification of lard in butter. Hierarchical cluster analysis (HCA) and principal component analysis (PCA) were successfully performed for the classification and discrimination of butter and lard-adulterated samples. Strong discrimination pattern was observed in the HCA analysis. Also, partial least squares regression and principal component regression (R2 = 0.99) were applied for quantification of lard in butter samples. Quite favorable prediction capabilities were observed in the cross-validation of PLS and PCR analysis for the adulteration levels between 0% and 100% lard fat (w/w). Raman spectroscopy coupled chemometrics was employed effectively for quantification of lard fat in butter fat samples with easy, robust, effective, low-cost and reliable application in the quality control of butter.


Assuntos
Manteiga/análise , Gorduras na Dieta/análise , Informática , Análise Espectral Raman , Análise por Conglomerados , Contaminação de Alimentos/análise , Fraude/prevenção & controle , Análise dos Mínimos Quadrados , Análise de Componente Principal
18.
Lancet ; 396(10245): 161-162, 2020 07 18.
Artigo em Inglês | MEDLINE | ID: mdl-32682473
20.
BMC Public Health ; 20(1): 880, 2020 06 08.
Artigo em Inglês | MEDLINE | ID: mdl-32513131

RESUMO

BACKGROUND: The dynamic intersection of a pluralistic health system, large informal sector, and poor regulatory environment have provided conditions favourable for 'corruption' in the LMICs of south and south-east Asia region. 'Corruption' works to undermine the UHC goals of achieving equity, quality, and responsiveness including financial protection, especially while delivering frontline health care services. This scoping review examines current situation regarding health sector corruption at frontlines of service delivery in this region, related policy perspectives, and alternative strategies currently being tested to address this pervasive phenomenon. METHODS: A scoping review following the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) was conducted, using three search engines i.e., PubMed, SCOPUS and Google Scholar. A total of 15 articles and documents on corruption and 18 on governance were selected for analysis. A PRISMA extension for Scoping Reviews (PRISMA-ScR) checklist was filled-in to complete this report. Data were extracted using a pre-designed template and analysed by 'mixed studies review' method. RESULTS: Common types of corruption like informal payments, bribery and absenteeism identified in the review have largely financial factors as the underlying cause. Poor salary and benefits, poor incentives and motivation, and poor governance have a damaging impact on health outcomes and the quality of health care services. These result in high out-of-pocket expenditure, erosion of trust in the system, and reduced service utilization. Implementing regulations remain constrained not only due to lack of institutional capacity but also political commitment. Lack of good governance encourage frontline health care providers to bend the rules of law and make centrally designed anti-corruption measures largely in-effective. Alternatively, a few bottom-up community-engaged interventions have been tested showing promising results. The challenge is to scale up the successful ones for measurable impact. CONCLUSIONS: Corruption and lack of good governance in these countries undermine the delivery of quality essential health care services in an equitable manner, make it costly for the poor and disadvantaged, and results in poor health outcomes. Traditional measures to combat corruption have largely been ineffective, necessitating the need for innovative thinking if UHC is to be achieved by 2030.


Assuntos
Fraude/economia , Setor de Assistência à Saúde/organização & administração , Política de Saúde/economia , Setor Privado/economia , Setor Público/economia , Ásia , Países em Desenvolvimento , Governo , Pessoal de Saúde/economia , Humanos , Renda , Assistência Médica/economia , Características de Residência
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