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1.
Cien Saude Colet ; 25(11): 4237-4248, 2020 Nov.
Artigo em Português | MEDLINE | ID: mdl-33175033

RESUMO

Sex workers become increasingly economically vulnerable due to the restrictive measures implemented to combat the coronavirus pandemic. In this respect, the scope of this study is to analyze the content of prostitution websites and advertisements regarding measures related to the COVID-19 pandemic. It involved a description of the visits and analysis of content of communications on websites that advertise commercial sex transactions. The percentage change in the number of visits for three periods from 02/2019 to 04/2020 was calculated. Subsequently, ads with the terms "corona," "pandemic" and "quarantine" on websites that offer search engines were extracted. The Bardin method was then used for content analysis. There was an increase in the number of visits to prostitution websites between 2019 and 2020, followed by a decrease with the advent of the coronavirus pandemic crisis. With regard to the protection measures during the pandemic, health recommendations and the incentive to engage in virtual sex are highlighted. Of the 1,991,014 advertisements, 0.51% mention the COVID-19 crisis regarding noncompliance with social distancing, protection measures and the offer of online sex.


Assuntos
Publicidade/estatística & dados numéricos , Betacoronavirus , Infecções por Coronavirus/prevenção & controle , Internet/estatística & dados numéricos , Pandemias/prevenção & controle , Pneumonia Viral/prevenção & controle , Trabalho Sexual/estatística & dados numéricos , Publicidade/métodos , Publicidade/tendências , Infecções por Coronavirus/epidemiologia , França , Humanos , Itália , América Latina , Pneumonia Viral/epidemiologia , Portugal , Ferramenta de Busca/estatística & dados numéricos , Espanha
2.
Mayo Clin Proc ; 95(11): 2370-2381, 2020 11.
Artigo em Inglês | MEDLINE | ID: mdl-33164756

RESUMO

OBJECTIVE: To evaluate whether a digital surveillance model using Google Trends is feasible for obtaining accurate data on coronavirus disease 2019 and whether accurate predictions can be made regarding new cases. METHODS: Data on total and daily new cases in each US state were collected from January 22, 2020, to April 6, 2020. Information regarding 10 keywords was collected from Google Trends, and correlation analyses were performed for individual states as well as for the United States overall. RESULTS: Among the 10 keywords analyzed from Google Trends, face mask, Lysol, and COVID stimulus check had the strongest correlations when looking at the United States as a whole, with R values of 0.88, 0.82, and 0.79, respectively. Lag and lead Pearson correlations were assessed for every state and all 10 keywords from 16 days before the first case in each state to 16 days after the first case. Strong correlations were seen up to 16 days prior to the first reported cases in some states. CONCLUSION: This study documents the feasibility of syndromic surveillance of internet search terms to monitor new infectious diseases such as coronavirus disease 2019. This information could enable better preparation and planning of health care systems.


Assuntos
Informação de Saúde ao Consumidor , Infecções por Coronavirus/epidemiologia , Comportamento de Busca de Informação , Internet/tendências , Pneumonia Viral/epidemiologia , Vigilância em Saúde Pública/métodos , Ferramenta de Busca/tendências , Betacoronavirus , Humanos , Pandemias , Estados Unidos/epidemiologia
3.
Sci Rep ; 10(1): 18680, 2020 10 29.
Artigo em Inglês | MEDLINE | ID: mdl-33122686

RESUMO

Two clusters of the coronavirus disease 2019 (COVID-19) were confirmed in Hokkaido, Japan, in February 2020. To identify these clusters, this study employed web search query logs of multiple devices and user location information from location-aware mobile devices. We anonymously identified users who used a web search engine (i.e., Yahoo! JAPAN) to search for COVID-19 or its symptoms. We regarded them as web searchers who were suspicious of their own COVID-19 infection (WSSCI). We extracted the location of WSSCI via a mobile operating system application and compared the spatio-temporal distribution of WSSCI with the actual location of the two known clusters. In the early stage of cluster development, we confirmed several WSSCI. Our approach was accurate in this stage and became biased after a public announcement of the cluster development. When other cluster-related resources, such as detailed population statistics, are not available, the proposed metric can capture hints of emerging clusters.


Assuntos
Infecções por Coronavirus/epidemiologia , Monitoramento Epidemiológico , Controle de Infecções/métodos , Pneumonia Viral/epidemiologia , Vigilância da População/métodos , Ferramenta de Busca/estatística & dados numéricos , Smartphone/estatística & dados numéricos , Infecções por Coronavirus/prevenção & controle , Utilização de Instalações e Serviços/estatística & dados numéricos , Humanos , Internet/estatística & dados numéricos , Japão , Pandemias/prevenção & controle , Pneumonia Viral/prevenção & controle
4.
J Glob Health ; 10(2): 020511, 2020 Dec.
Artigo em Inglês | MEDLINE | ID: mdl-33110594

RESUMO

Background: Internet search engine data, such as Google Trends, was shown to be correlated with the incidence of COVID-19, but only in several countries. We aim to develop a model from a small number of countries to predict the epidemic alert level in all the countries worldwide. Methods: The "interest over time" and "interest by region" Google Trends data of Coronavirus, pneumonia, and six COVID symptom-related terms were searched. The daily incidence of COVID-19 from 10 January to 23 April 2020 of 202 countries was retrieved from the World Health Organization. Three alert levels were defined. Ten weeks' data from 20 countries were used for training with machine learning algorithms. The features were selected according to the correlation and importance. The model was then tested on 2830 samples of 202 countries. Results: Our model performed well in 154 (76.2%) countries, of which each had no more than four misclassified samples. In these 154 countries, the accuracy was 0.8133, and the kappa coefficient was 0.6828. While in all 202 countries, the accuracy was 0.7527, and the kappa coefficient was 0.5841. The proposed algorithm based on Random Forest Classification and nine features performed better compared to other machine learning methods and the models with different numbers of features. Conclusions: Our result suggested that the model developed from 20 countries with Google Trends data and Random Forest Classification can be applied to predict the epidemic alert levels of most countries worldwide.


Assuntos
Infecções por Coronavirus/epidemiologia , Saúde Global/estatística & dados numéricos , Aprendizado de Máquina/estatística & dados numéricos , Modelos Estatísticos , Pneumonia Viral/epidemiologia , Ferramenta de Busca/estatística & dados numéricos , Betacoronavirus , Confiabilidade dos Dados , Humanos , Incidência , Pandemias , Estudos Retrospectivos
5.
Nutrients ; 12(10)2020 Oct 12.
Artigo em Inglês | MEDLINE | ID: mdl-33053656

RESUMO

The severe acute respiratory syndrome coronavirus (SARS-CoV)-2 disease (COVID)-19 is having profound effects on the global economy and food trade. Limited data are available on how this pandemic is affecting our dietary and lifestyle-related behaviors at the global level. Google Trends was used to obtain worldwide relative search volumes (RSVs) covering a timeframe from before the COVID-19 pandemic 1 June 2019 to 27 April 2020. Spearman's rank-order correlation coefficients were used to measure relationships between daily confirmed cases and aforementioned RSVs between 31 December 2019 and 15 April 2020. RSV curves showed increased interest in multiple keywords related to dietary and lifestyle behaviors during the COVID-19 lockdown period in March and April 2020. Spearman's correlation analysis showed that the strongest variables in each keyword category were (1) food security (food shortage: r = 0.749, food bank: r = 0.660, and free food: r = 0.555; all p < 0.001), (2) dietary behaviors (delivery: r = 0.780, restaurant: r = -0.731, take-away: r = 0.731, and food-delivery: r = 0.693; all p < 0.001), (3) outdoor-related behaviors (resort: r = -0.922, hotel: r = -0.913, cinema: r = -0.844, park: r = -0.827, fitness: r = -0.817, gym: r = -0.811; plant: r = 0.749, sunbathing: r = 0.668, and online: r = 0.670; all p < 0.001), and (4) immune-related nutrients/herbs/foods (vitamin C: r = 0.802, vitamin A: r = 0.780, zinc: r = 0.781, immune: r = 0.739, vitamin E: r = 0.707, garlic: r = 0.667, omega-3 fatty acid: r = -0.633, vitamin D: r = 0.549, and turmeric: r = 0.545; all p < 0.001). Restricted movement has affected peoples' dietary and lifestyle behaviors as people tend to search for immune-boosting nutrients/herbs and have replaced outdoor activities with sedentary indoor behaviors.


Assuntos
Infecções por Coronavirus , Dieta , Comportamento Alimentar , Abastecimento de Alimentos , Estilo de Vida , Pandemias , Pneumonia Viral , Isolamento Social , Betacoronavirus , Coronavirus , Infecções por Coronavirus/epidemiologia , Infecções por Coronavirus/imunologia , Infecções por Coronavirus/virologia , Curcuma , Ácidos Graxos Ômega-3 , Alho , Comportamentos Relacionados com a Saúde , Humanos , Comportamento de Busca de Informação , Nutrientes , Pneumonia Viral/epidemiologia , Pneumonia Viral/imunologia , Pneumonia Viral/virologia , Restaurantes , Ferramenta de Busca , Comportamento Sedentário , Síndrome Respiratória Aguda Grave , Oligoelementos , Vitaminas
6.
Acta Biomed ; 91(3): e2020006, 2020 09 07.
Artigo em Inglês | MEDLINE | ID: mdl-32921704

RESUMO

BACKGROUND AND AIM: Digital epidemiology is increasingly used for supporting traditional epidemiology. This study was hence aimed to explore whether the Google search volume may have been useful to predict the trajectory of coronavirus disease 2019 (COVID-19) outbreak in Italy. MATERIALS AND METHODS: We accessed Google Trends for collecting data on weekly Google searches for the keywords "tosse" (i.e., cough), "febbre" (i.e., fever) and "dispnea" (dyspnea) in Italy, between February and May 2020. The number of new weekly cases of COVID-19 in Italy was also obtained from the website of the National Institute of Health. RESULTS: The peaks of Google searches for the three terms predicted by 3 weeks that of newly diagnosed COVID-19 cases. The peaks of weekly Google searches for "febbre" (fever), "tosse"( cough) and "dispnea" (dyspnea) were 1.7-, 2.2- and 7.7-fold higher compared to the week before the diagnosis of the first national case. No significant correlation was found between the number of newly diagnosed COVID-19 cases and Google search volumes of "tosse" (cough) and "febbre" (fever), whilst "dyspnea" (dyspnea) was significantly correlated (r= 0.50; p=0.034). The correlation between newly diagnosed COVID-19 cases and "tosse" (cough; r=0.65; p=0.008) or "febbre" (fever; 0.69; p=0.004) become statistically significant with a 3-week delay. All symptoms were also significantly inter-correlated. Conclusions; Continuously monitoring the volume of Google searches and mapping their origin can be a potentially valuable instrument to help predicting and identifying local recrudescence of COVID-19.


Assuntos
Betacoronavirus , Infecções por Coronavirus/epidemiologia , Surtos de Doenças/estatística & dados numéricos , Pneumonia Viral/epidemiologia , Ferramenta de Busca/métodos , Humanos , Itália/epidemiologia , Pandemias , Valor Preditivo dos Testes
7.
J Med Internet Res ; 22(10): e22068, 2020 10 08.
Artigo em Inglês | MEDLINE | ID: mdl-32946412

RESUMO

BACKGROUND: The COVID-19 pandemic has markedly affected renal transplant care. During this time of social distancing, limited in-person visits, and uncertainty, patients and donors are relying more than ever on telemedicine and web-based information. Several factors can influence patients' understanding of web-based information, such as delivery modes (instruction, interaction, and assessment) and social-epistemological dimensions (choices in interactive knowledge building). OBJECTIVE: The aim of this study was to systemically evaluate the content, delivery modes, and social-epistemological dimensions of web-based information on COVID-19 and renal transplantation at time of the pandemic. METHODS: Multiple keyword combinations were used to retrieve websites on COVID-19 and renal transplantation using the search engines Google.com and Google.nl. From 14 different websites, 30 webpages were examined to determine their organizational sources, topics, delivery modes, and social-epistemological dimensions. RESULTS: The variety of topics and delivery modes was limited. A total of 13 different delivery modes were encountered, of which 8 (62%) were instructional and 5 (38%) were interactional; no assessment delivery modes were observed. No website offered all available delivery modes. The majority of delivery modes (8/13, 62%) focused on individual and passive learning, whereas group learning and active construction of knowledge were rarely encountered. CONCLUSIONS: By taking interactive knowledge transfer into account, the educational quality of eHealth for transplant care could increase, especially in times of crisis when rapid knowledge transfer is needed.


Assuntos
Infecções por Coronavirus/epidemiologia , Internet , Transplante de Rim , Conhecimento , Doadores Vivos/educação , Educação de Pacientes como Assunto , Pneumonia Viral/epidemiologia , Telemedicina , Betacoronavirus , Humanos , Pandemias , Educação de Pacientes como Assunto/normas , Educação de Pacientes como Assunto/estatística & dados numéricos , Ferramenta de Busca , Incerteza
8.
J Med Internet Res ; 22(9): e19788, 2020 09 29.
Artigo em Inglês | MEDLINE | ID: mdl-32931446

RESUMO

BACKGROUND: South Korea is among the best-performing countries in tackling the coronavirus pandemic by using mass drive-through testing, face mask use, and extensive social distancing. However, understanding the patterns of risk perception could also facilitate effective risk communication to minimize the impacts of disease spread during this crisis. OBJECTIVE: We attempt to explore patterns of community health risk perceptions of COVID-19 in South Korea using internet search data. METHODS: Google Trends (GT) and NAVER relative search volumes (RSVs) data were collected using COVID-19-related terms in the Korean language and were retrieved according to time, gender, age groups, types of device, and location. Online queries were compared to the number of daily new COVID-19 cases and tests reported in the Kaggle open-access data set for the time period of December 5, 2019, to May 31, 2020. Time-lag correlations calculated by Spearman rank correlation coefficients were employed to assess whether correlations between new COVID-19 cases and internet searches were affected by time. We also constructed a prediction model of new COVID-19 cases using the number of COVID-19 cases, tests, and GT and NAVER RSVs in lag periods (of 1-3 days). Single and multiple regressions were employed using backward elimination and a variance inflation factor of <5. RESULTS: The numbers of COVID-19-related queries in South Korea increased during local events including local transmission, approval of coronavirus test kits, implementation of coronavirus drive-through tests, a face mask shortage, and a widespread campaign for social distancing as well as during international events such as the announcement of a Public Health Emergency of International Concern by the World Health Organization. Online queries were also stronger in women (r=0.763-0.823; P<.001) and age groups ≤29 years (r=0.726-0.821; P<.001), 30-44 years (r=0.701-0.826; P<.001), and ≥50 years (r=0.706-0.725; P<.001). In terms of spatial distribution, internet search data were higher in affected areas. Moreover, greater correlations were found in mobile searches (r=0.704-0.804; P<.001) compared to those of desktop searches (r=0.705-0.717; P<.001), indicating changing behaviors in searching for online health information during the outbreak. These varied internet searches related to COVID-19 represented community health risk perceptions. In addition, as a country with a high number of coronavirus tests, results showed that adults perceived coronavirus test-related information as being more important than disease-related knowledge. Meanwhile, younger, and older age groups had different perceptions. Moreover, NAVER RSVs can potentially be used for health risk perception assessments and disease predictions. Adding COVID-19-related searches provided by NAVER could increase the performance of the model compared to that of the COVID-19 case-based model and potentially be used to predict epidemic curves. CONCLUSIONS: The use of both GT and NAVER RSVs to explore patterns of community health risk perceptions could be beneficial for targeting risk communication from several perspectives, including time, population characteristics, and location.


Assuntos
Infecções por Coronavirus/epidemiologia , Infecções por Coronavirus/psicologia , Surtos de Doenças/estatística & dados numéricos , Internet , Pneumonia Viral/epidemiologia , Pneumonia Viral/psicologia , Opinião Pública , Ferramenta de Busca , Adolescente , Adulto , Técnicas de Laboratório Clínico/estatística & dados numéricos , Comunicação , Infecções por Coronavirus/diagnóstico , Infecções por Coronavirus/transmissão , Feminino , Humanos , Masculino , Pessoa de Meia-Idade , Pandemias , Pneumonia Viral/diagnóstico , Pneumonia Viral/transmissão , Saúde Pública , República da Coreia/epidemiologia , Medição de Risco , Fatores de Tempo , Adulto Jovem
10.
JMIR Public Health Surveill ; 6(4): e23098, 2020 10 22.
Artigo em Inglês | MEDLINE | ID: mdl-32960177

RESUMO

BACKGROUND: The COVID-19 pandemic has become a global public health event, attracting worldwide attention. As a tool to monitor public awareness, internet search engines have been widely used in public health emergencies. OBJECTIVE: This study aims to use online search data (Baidu Index) to monitor the public's attention and verify internet search engines' function in public attention monitoring of public health emergencies. METHODS: We collected the Baidu Index and the case monitoring data from January 20, 2020, to April 20, 2020. We combined the Baidu Index of keywords related to COVID-19 to describe the public attention's temporal trend and spatial distribution, and conducted the time lag cross-correlation analysis. RESULTS: The Baidu Index temporal trend indicated that the changes of the Baidu Index had a clear correspondence with the development time node of the pandemic. The Baidu Index spatial distribution showed that in the regions of central and eastern China, with denser populations, larger internet user bases, and higher economic development levels, the public was more concerned about COVID-19. In addition, the Baidu Index was significantly correlated with six case indicators of new confirmed cases, new death cases, new cured discharge cases, cumulative confirmed cases, cumulative death cases, and cumulative cured discharge cases. Moreover, the Baidu Index was 0-4 days earlier than new confirmed and new death cases, and about 20 days earlier than new cured and discharged cases while 3-5 days later than the change of cumulative cases. CONCLUSIONS: The national public's demand for epidemic information is urgent regardless of whether it is located in the hardest hit area. The public was more sensitive to the daily new case data that represents the progress of the epidemic, but the public's attention to the epidemic situation in other areas may lag behind. We could set the Baidu Index as the sentinel and the database in the online infoveillance system for infectious disease and public health emergencies. According to the monitoring data, the government needs to prevent and control the possible outbreak in advance and communicate the risks to the public so as to ensure the physical and psychological health of the public in the epidemic.


Assuntos
Infecções por Coronavirus/epidemiologia , Internet/estatística & dados numéricos , Pandemias , Pneumonia Viral/epidemiologia , Vigilância em Saúde Pública/métodos , Ferramenta de Busca , China/epidemiologia , Humanos
11.
PLoS One ; 15(9): e0238538, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-32881969

RESUMO

Self-medication and antibiotic utilization without healthcare oversight may lead to delayed appropriate treatment, transmission of communicable infections, untoward adverse events, and contribute to antimicrobial resistance. Previous data suggest people obtain over-the-counter (OTC) animal antibiotics for their personal use. This study examined the availability of OTC fish antibiotics online and the documented intent for self-medication. The authors conducted a web-based cross-sectional study using Google search engine to identify vendor websites selling fish antibiotics in the United States. Vendor websites were included if product information, consumer reviews, and comments were publicly available. Nine fish antibiotics were chosen due to their possibility of having consequences to human misuse. The cost and availability of fish antibiotics was recorded. The proportion of reviews and comments related to human consumption was calculated. Consumer review traffic based on "likes" and "dislikes" received was compared between human- and non-human consumption-related reviews. Selected fish antibiotics were purchased and evaluated for physical appearance and compared to FDA-approved available equivalents. We found 24 website vendors with online ordering available for OTC fish antibiotics. Cost varied significantly by antibiotic and quantity ranging from USD $8.99 to $119.99. There were 2,288 reviews documented for the 9 selected antibiotics being sold. Among consumer reviews, 2.4% were potentially associated with human consumption. Human consumption-related reviews constituted 30.2% of all "likes" received and 37.5% of all "dislikes" received. Human consumption-related reviews received an average of 9.2 likes compared to 0.52 likes for non-human consumption-related reviews. The 8 fish antibiotics purchased were consistent with FDA-approved equivalents in physical appearance. Although infrequent, antibiotics intended for fish use are being purchased online without a prescription for self-medication to circumvent professional medical care. Reviews related to human consumption generate significant online traffic compared to reviews unrelated to human consumption.


Assuntos
Antibacterianos/administração & dosagem , Uso Indevido de Medicamentos/estatística & dados numéricos , Medicamentos sem Prescrição/administração & dosagem , Disponibilidade de Medicamentos Via Internet/estatística & dados numéricos , Automedicação/estatística & dados numéricos , Drogas Veterinárias/administração & dosagem , Estudos Transversais , Humanos , Conhecimento do Paciente sobre a Medicação , Ferramenta de Busca/estatística & dados numéricos , Estados Unidos
12.
Am J Orthod Dentofacial Orthop ; 158(4): 612-620, 2020 Oct.
Artigo em Inglês | MEDLINE | ID: mdl-32988569

RESUMO

INTRODUCTION: The evaluation of online information regarding orthodontic temporary anchorage devices (TADs) is lacking despite the increase in their use by orthodontists. This cross-sectional study aimed to investigate the quality of information regarding TADs available on the Internet to the general public. METHODS: Two search terms ("orthodontic temporary anchorage device" and "orthodontic miniscrew") were entered separately into a total of 5 search engines. The DISCERN instrument, Journal of the American Medical Association (JAMA) benchmarks, and Health on the Net Foundation Code of Conduct were used to evaluate the quality of information contained within Web sites that satisfied the inclusion and/or exclusion criteria. Web site readability was assessed via the Simple Measure of Gobbledygook and Flesch Reading Ease Score tools. Descriptive statistical analyses and Cohen's kappa intrarater reliability tests were performed. RESULTS: Thirty-one Web sites were evaluated. Most were authored by orthodontists (77.4%) and originated from the U.S. (38.7%). The mean (standard deviation [SD]) DISCERN score was 41.87 (8.45) out of 80, with a range of 27-57. Intrarater reliability testing for DISCERN scores was excellent (0.84). Four Web sites achieved all 4 JAMA benchmarks, and 2 achieved none. Referencing of content sources throughout the Web sites scored least via DISCERN (mean 1.49 out of 5 per Web site [SD, 0.77]) and JAMA (19.35% of Web sites). One Web site contained the Health on the Net Foundation Code of Conduct seal. The mean (SD) Simple Measure of Gobbledygook score was 8.75 (1.25), with a range of 6.5-11.3. The mean (SD) Flesch Reading Ease Score was 59.81 (7.17), with a range of 47.6-73.8. CONCLUSIONS: The quality of information related to TADs on the Internet is moderate. The usefulness of the information may be further reduced because it was beyond the readability of the average member of the general public. Web site authors should consider the use of additional expertise, quality of information tools, and readability formulas to ensure high-quality and easily readable content.


Assuntos
Informação de Saúde ao Consumidor , Estudos Transversais , Internet , Reprodutibilidade dos Testes , Ferramenta de Busca , Estados Unidos
14.
J Med Internet Res ; 22(9): e22181, 2020 09 21.
Artigo em Inglês | MEDLINE | ID: mdl-32924951

RESUMO

BACKGROUND: Real-time global mental health surveillance is urgently needed for tracking the long-term impact of the COVID-19 pandemic. OBJECTIVE: This study aimed to use Google Trends data to investigate the impact of the pandemic on global mental health by analyzing three keywords indicative of mental distress: "insomnia," "depression," and "suicide." METHODS: We examined increases in search queries for 19 countries. Significant increases were defined as the actual daily search value (from March 20 to April 19, 2020) being higher than the 95% CIs of the forecast from the 3-month baseline via ARIMA (autoregressive integrated moving average) modeling. We examined the correlation between increases in COVID-19-related deaths and the number of days with significant increases in search volumes for insomnia, depression, and suicide across multiple nations. RESULTS: The countries with the greatest increases in searches for insomnia were Iran, Spain, the United States, and Italy; these countries exhibited a significant increase in insomnia searches on more than 10 of the 31 days observed. The number of COVID-19-related deaths was positively correlated to the number of days with an increase in searches for insomnia in the 19 countries (ρ=0.64, P=.003). By contrast, there was no significant correlation between the number of deaths and increases in searches for depression (ρ=-0.12, P=.63) or suicide (ρ=-0.07, P=.79). CONCLUSIONS: Our analysis suggests that insomnia could be a part of routine mental health screening during the COVID-19 pandemic.


Assuntos
Infecções por Coronavirus/epidemiologia , Saúde Global/estatística & dados numéricos , Internacionalidade , Internet/estatística & dados numéricos , Saúde Mental/estatística & dados numéricos , Pandemias , Pneumonia Viral/epidemiologia , Ferramenta de Busca/estatística & dados numéricos , Distúrbios do Início e da Manutenção do Sono/epidemiologia , Betacoronavirus , Depressão/epidemiologia , Humanos , Estudos Longitudinais , Suicídio/estatística & dados numéricos
15.
Recurso educacional aberto em Português | CVSP - Regional | ID: oer-3903

RESUMO

A tabela de caracterização deve ser feita em Excel, seguindo o exemplo proposto. Os estudos de revisão poderão ser avaliados aplicando o AMSTAR2 AMSTAR - Ferramenta para avaliar estudos de revisões sistemáticas


Assuntos
Prática Clínica Baseada em Evidências , Bibliotecas Digitais , Ferramenta de Busca
16.
ScientificWorldJournal ; 2020: 1562028, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-32802003

RESUMO

Background: The novel coronavirus disease (COVID-19) has spread globally from its epicenter in Hubei, China, and was declared a pandemic by the World Health Organization (WHO) on March 11, 2020. The most popular search engine worldwide is Google, and since March 2020, COVID-19 has been a global trending search term. Misinformation related to COVID-19 from these searches is a problem, and hence, it is of high importance to assess the quality of health information over the internet related to COVID-19. The objective of our study is to examine the quality of COVID-19 related health information over the internet using the DISCERN tool. Methods: The keywords included in assessment of COVID-19 related information using Google's search engine were "Coronavirus," "Coronavirus causes," "Coronavirus diagnosis," "Coronavirus prevention," and "Coronavirus management". The first 20 websites from each search term were gathered to generate a list of 100 URLs. Duplicate sites were excluded from this search, allowing analysis of unique sites only. Additional exclusion criteria included scientific journals, nonoperational links, nonfunctional websites (where the page was not loading, was not found, or was inactive), and websites in languages other than English. This resulted in a unique list of 48 websites. Four independent raters evaluated the websites using a 16-item DISCERN tool to assess the quality of novel coronavirus related information available on the internet. The interrater reliability agreement was calculated using the intracluster correlation coefficient. Results: Results showed variation in how the raters assigned scores to different website categories. The .com websites received the lowest scores. Results showed that .edu and .org website category sites were excellent in communicating coronavirus related health information; however, they received lower scores for treatment effect and treatment choices. Conclusion: This study highlights the gaps in the quality of information that is available on the websites related to COVID-19 and study emphasizes the need for verified websites that provide evidence-based health information related to the novel coronavirus pandemic.


Assuntos
Betacoronavirus , Infecções por Coronavirus , Educação em Saúde/normas , Internet , Pandemias , Pneumonia Viral , Infecções por Coronavirus/epidemiologia , Educação a Distância , Humanos , Pneumonia Viral/epidemiologia , Ferramenta de Busca
17.
Int J Comput Dent ; 23(3): 211-218, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-32789308

RESUMO

AIM: To assess the accuracy of DigiBrain4, Inc (DB4) Dental Classifier and DB4 Smart Search Engine* in recognizing, categorizing, and classifying dental visual assets as compared with Google Search Engine, one of the largest publicly available search engines and the largest data repository. MATERIALS AND METHODS: Dental visual assets were collected and labeled according to type, category, class, and modifiers. These dental visual assets contained radiographs and clinical images of patients' teeth and occlusion from different angles of view. A modified SqueezeNet architecture was implemented using the TensorFlow r1.10 framework. The model was trained using two NVIDIA Volta graphics processing units (GPUs). A program was built to search Google Images, using Chrome driver (Google web driver) and submit the returned images to the DB4 Dental Classifier and DB4 Smart Search Engine. The categorical accuracy of the DB4 Dental Classifier and DB4 Smart Search Engine in recognizing, categorizing, and classifying dental visual assets was then compared with that of Google Search Engine. RESULTS: The categorical accuracy achieved using the DB4 Smart Search Engine for searching dental visual assets was 0.93, whereas that achieved using Google Search Engine was 0.32. CONCLUSION: The current DB4 Dental Classifier and DB4 Smart Search Engine application and add-on have proved to be accurate in recognizing, categorizing, and classifying dental visual assets. The search engine was able to label images and reject non-relevant results.


Assuntos
Redes Neurais de Computação , Ferramenta de Busca , Humanos
19.
PLoS One ; 15(8): e0235697, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-32750051

RESUMO

In an era of big data, the availability of satellite-derived global climate, terrain, and land cover imagery presents an opportunity for modeling the suitability of malaria disease vectors at fine spatial resolutions, across temporal scales, and over vast geographic extents. Leveraging cloud-based geospatial analytical tools, we present an environmental suitability model that considers water resources, flow accumulation areas, precipitation, temperature, vegetation, and land cover. In contrast to predictive models generated using spatially and temporally discontinuous mosquito presence information, this model provides continuous fine-spatial resolution information on the biophysical drivers of suitability. For the purposes of this study the model is parameterized for Anopheles gambiae s.s. in Malawi for the rainy (December-March) and dry seasons (April-November) in 2017; however, the model may be repurposed to accommodate different mosquito species, temporal periods, or geographical boundaries. Final products elucidate the drivers and potential habitat of Anopheles gambiae s.s. Rainy season results are presented by quartile of precipitation; Quartile four (Q4) identifies areas most likely to become inundated and shows 7.25% of Malawi exhibits suitable water conditions (water only) for Anopheles gambiae s.s., approximately 16% for water plus another factor, and 8.60% is maximally suitable, meeting suitability thresholds for water presence, terrain characteristics, and climatic conditions. Nearly 21% of Malawi is suitable for breeding based on land characteristics alone and 28.24% is suitable according to climate and land characteristics. Only 6.14% of the total land area is suboptimal. Dry season results show 25.07% of the total land area is suboptimal or unsuitable. Approximately 42% of Malawi is suitable based on land characteristics alone during the dry season, and 13.11% is suitable based on land plus another factor. Less than 2% meets suitability criteria for climate, water, and land criteria. Findings illustrate environmental drivers of suitability for malaria vectors, providing an opportunity for a more comprehensive approach to malaria control that includes not only modeled species distributions, but also the underlying drivers of suitability for a more effective approach to environmental management.


Assuntos
Big Data , Malária/epidemiologia , Saúde Pública , Animais , Anopheles/fisiologia , Cruzamento , Clima , Humanos , Malária/transmissão , Malaui/epidemiologia , Mosquitos Vetores/fisiologia , Ferramenta de Busca , Estações do Ano
20.
PLoS One ; 15(8): e0236157, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-32764767

RESUMO

Despite significant potential for providing insight to private perceptions and behaviors, search engine data has yet to be utilized as a means of gauging the U.S. public's interest and understanding of mental health in the context of gun violence and politics. An analysis of Google Trends revealed that Mental health searches increased in volume starting in the beginning of the current decade. Notably, both "mental health" and "gun(s)" were searched with greater frequency the week after the mass shooting events occurred. Related searches after the event also observed a significant increase in interest in mental health and gun regulation, legal reform, mass shootings, and gun(s). Results suggest that the American public's perception of mental illness increasingly incorporates associations with themes of violence and politics, which becomes more apparent surrounding mass shooting events. Future studies are needed to determine implications for stigmatization of vulnerable groups, and possible relations to media coverage.


Assuntos
Violência com Arma de Fogo/estatística & dados numéricos , Incidentes com Feridos em Massa/estatística & dados numéricos , Transtornos Mentais/psicologia , Saúde Mental/estatística & dados numéricos , Política , Violência com Arma de Fogo/psicologia , Humanos , Comportamento de Busca de Informação , Incidentes com Feridos em Massa/psicologia , Opinião Pública , Ferramenta de Busca/estatística & dados numéricos , Estados Unidos
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