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1.
Chemosphere ; 262: 127788, 2021 Jan.
Artículo en Inglés | MEDLINE | ID: mdl-33182082

RESUMEN

Lead (Pb) interferes with various bodily functions. Although high blood Pb (Pb-B) levels in residents from Kabwe, Zambia have been reported, the accumulation pattern of other metals remains unknown. The study was designed to determine the Pb-B, blood cadmium (Cd-B), and zinc (Zn-B) values of 504 representative samples from Kabwe, as well as the potential associated adverse health effects. The Pb-B level ranged from 0.79 to 154.75 µg/dL and generally increased in areas near the mine. A significant elevation of Cd-B was observed in two areas (0.37 ± 0.26 and 0.32 ± 0.30 µg/L) where the two highest mean Pb-B levels were recorded. By contrast, the Zn-B values did not differ greatly with respect to area. Some blood biochemical parameters relating to hepatic and renal functions were out of the normal range in approximately 20-50% of studied adult participants. The δ-aminolevulinic acid dehydratase (δ-ALAD) activity was significantly inhibited in the two areas contaminated by Pb and Cd. A significant negative relationship was observed between metal levels and clinical parameters, e.g., between Pb-B and δ-ALAD for all the age categories and between Cd-B and the estimated glomerular filtration rate for all the age categories except 0-4 years. The elevated Cd-B in areas near the mine relative to the other areas suggested the potential adverse health effects of Cd and/or the interaction of Pb and Cd. A significant association of metal levels with clinical parameters also indicated the effects of metal exposure on hematopoietic, hepatic, and renal systems.


Asunto(s)
Exposición a Riesgos Ambientales/análisis , Contaminantes Ambientales/análisis , Metales/análisis , Adulto , Cadmio/análisis , Recolección de Datos , Efectos Colaterales y Reacciones Adversas Relacionados con Medicamentos , Exposición a Riesgos Ambientales/estadística & datos numéricos , Monitoreo del Ambiente/métodos , Tasa de Filtración Glomerular , Humanos , Hígado/química , Registros , Valores de Referencia , Adulto Joven , Zambia , Zinc
2.
Rev. enferm. UERJ ; 28: e48514, jan.-dez. 2020.
Artículo en Inglés, Portugués | LILACS, BDENF - Enfermería | ID: biblio-1117619

RESUMEN

Objetivo: analisar as dissertações e teses defendidas nos cursos de Pós-Graduação Stricto Sensu em Enfermagem, no Brasil, relativas ao tema criança com estoma, destacando seus aspectos epistemológicos. Método: estudo documental, descritivo, considerando o recorte temporal entre 2009 e 2019. Utilizou-se a Metodologia de Categorização Epistemológica para a Pesquisa na Enfermagem. Resultados: selecionaram-se doze estudos: dez dissertações de mestrado e duas teses de doutorado. Nota-se o predomínio de estudos na área/campo epistêmico assistencial, na linha de pesquisa: Processo de Cuidar em Saúde e Enfermagem. Identificou-se um maior interesse de estudos no contexto domiciliar e ambulatorial. Há predomínio da abordagem qualitativa e uso da entrevista para coleta de dados. Conclusão: os aspectos epistemológicos destacados possibilitam afirmar que as dissertações e teses relacionadas ao tema estão predominantemente orientadas para um pragmatismo epistemológico da assistência de enfermagem à criança com estoma e sua família, com objetos científicos delimitados para alcançar a compreensão desse fenômeno.


Objective: to examine postgraduate Nursing dissertations and theses defended in Brazil on the subject of children with stoma, highlighting their epistemological aspects. Method: this descriptive study considered studies published between 2009 and 2019 using the Epistemological Categorization methodology for research in Nursing. Results: twelve studies were selected: ten master's dissertations and two doctoral theses. The predominant epistemic area/field was "care", in the research line: "care process in health, and nursing". Studies were found to show greater interest in the home and outpatient context. The qualitative approach and data collection by interview predominated. Conclusion: from the epistemological aspects highlighted, it can be said that the dissertations and theses on the subject of children with stomata were predominantly oriented towards an epistemological pragmatism in nursing care for children with stoma and their families, with scientific objects delimited to achieve an understanding of this phenomenon.


Objetivo: analizar las disertaciones y tesis de posgrado en Enfermería defendidas en Brazil sobre el tema de niños con estoma, destacando sus aspectos epistemológicos. Método: este estudio descriptivo consideró estudios publicados entre 2009 y 2019 utilizando la metodología de Categorización Epistemológica para la investigación en Enfermería. Resultados: se seleccionaron doce estudios: diez tesis de maestría y dos tesis doctorales. El área / campo epistémico predominante fue el "cuidado", en la línea de investigación: "proceso de cuidado en salud y enfermería". Se encontró que los estudios muestran un mayor interés en el contexto domiciliario y ambulatorio. Predominó el enfoque cualitativo y la recolección de datos por entrevista. Conclusión: a partir de los aspectos epistemológicos destacados, se puede decir que las disertaciones y tesis sobre el tema de los niños con estoma estuvieron orientadas predominantemente hacia un pragmatismo epistemológico en la atención de enfermería al niño con estoma y sus familias, con objetos científicos delimitados para lograr un entendimiento. de este fenómeno.


Asunto(s)
Humanos , Niño , Estomía/educación , Cuidado del Niño , Educación de Postgrado en Enfermería , Brasil , Investigación en Enfermería , Recolección de Datos , Estomas Quirúrgicos , Atención de Enfermería
3.
Chaos ; 30(10): 103120, 2020 Oct.
Artículo en Inglés | MEDLINE | ID: mdl-33138458

RESUMEN

We present a phenomenological procedure of dealing with the COVID-19 (coronavirus disease 2019) data provided by government health agencies of 11 different countries. Usually, the exact or approximate solutions of susceptible-infected-recovered (or other) model(s) are obtained fitting the data by adjusting the time-independent parameters that are included in those models. Instead of that, in this work, we introduce dynamical parameters whose time-dependence may be phenomenologically obtained by adequately extrapolating a chosen subset of the daily provided data. This phenomenological approach works extremely well to properly adjust the number of infected (and removed) individuals in time for the countries we consider. Besides, it can handle the sub-epidemic events that some countries may experience. In this way, we obtain the evolution of the pandemic without using any a priori model based on differential equations.


Asunto(s)
Infecciones por Coronavirus/epidemiología , Susceptibilidad a Enfermedades , Neumonía Viral/epidemiología , Algoritmos , Betacoronavirus , Recolección de Datos , Salud Global , Humanos , Modelos Estadísticos , Pandemias , Cuarentena , Factores de Tiempo
4.
PLoS One ; 15(11): e0241466, 2020.
Artículo en Inglés | MEDLINE | ID: mdl-33147252

RESUMEN

As the number of global coronavirus disease (COVID-19) cases increases, the number of imported cases is gradually rising. Furthermore, there is no reduction in domestic outbreaks. To assess the risks from imported COVID-19 cases in South Korea, we suggest using the daily risk score. Confirmed COVID-19 cases reported by John Hopkins University Center, roaming data collected from Korea Telecom, and the Oxford COVID-19 Government Response Tracker index were included in calculating the risk score. The risk score was highly correlated with imported COVID-19 cases after 12 days. To forecast daily imported COVID-19 cases after 12 days in South Korea, we developed prediction models using simple linear regression and autoregressive integrated moving average, including exogenous variables (ARIMAX). In the validation set, the root mean squared error of the linear regression model using the risk score was 6.2, which was lower than that of the autoregressive integrated moving average (ARIMA; 22.3) without the risk score as a reference. Correlation coefficient of ARIMAX using the risk score (0.925) was higher than that of ARIMA (0.899). A possible reason for this time lag of 12 days between imported cases and the risk score could be the delay that occurs before the effect of government policies such as closure of airports or lockdown of cities. Roaming data could help warn roaming users regarding their COVID-19 risk status and inform the national health agency of possible high-risk areas for domestic outbreaks.


Asunto(s)
Teléfono Celular , Infecciones por Coronavirus/epidemiología , Predicción/métodos , Pandemias , Neumonía Viral/epidemiología , Análisis de Datos , Recolección de Datos/métodos , Brotes de Enfermedades/prevención & control , Humanos , Modelos Lineales , Modelos Estadísticos , República de Corea/epidemiología , Riesgo
5.
Biomedica ; 40(Supl. 2): 96-103, 2020 10 30.
Artículo en Inglés, Español | MEDLINE | ID: mdl-33152193

RESUMEN

Introduction: The COVID pandemic is a challenge for public health surveillance and an opportunity to assess its strengths and weaknesses to improve the response. Objective: To evaluate the performance of the Colombian public health surveillance system during the first 50 days of the COVID-19 pandemic in the country. Materials and methods: We analyzed the data published between March 6 and April 24, 2020, by the Instituto Nacional de Salud and the World Health Organization (WHO). We evaluated: i) the quality of the data according to the fulfillment of Benford's law, and ii) the timeliness of the information measured as the difference in dates between the data generated by the Instituto Nacional de Salud and WHO's situational reports. We assessed the fulfillment of Benford's law using the p values of the log-likelihood ratio, the chi square or Moreno's exact tests. Results: Until April 24 there were 4,881 cases of COVID-19 in Colombia. During most of the first 50 days of the pandemic, Benford's law was fulfilled except the first days of the epidemic. The difference between Instituto Nacional de Salud and WHO reports largely depends on the different reporting times. Conclusion: In general, the Colombian public health surveillance system fulfilled Benford's law suggesting that there was quality in the data. Future studies comparing the performance of the departments and districts will improve the diagnosis of the Colombian surveillance system.


Asunto(s)
Betacoronavirus , Infecciones por Coronavirus/epidemiología , Recolección de Datos/normas , Pandemias , Neumonía Viral/epidemiología , Vigilancia de la Población , Salud Pública , Colombia/epidemiología , Recolección de Datos/métodos , Recolección de Datos/estadística & datos numéricos , Brotes de Enfermedades , Humanos , Subtipo H1N1 del Virus de la Influenza A , Gripe Humana/epidemiología , Internet , Vigilancia de la Población/métodos , Control de Calidad , Distribuciones Estadísticas , Infección por el Virus Zika/epidemiología
6.
Probl Sotsialnoi Gig Zdravookhranenniiai Istor Med ; 28(Special Issue): 1075-1080, 2020 Oct.
Artículo en Ruso | MEDLINE | ID: mdl-33219761

RESUMEN

Accuracy of statistical registration of mortality in Russia, especially in times of crisis, is a pressing and relevant issue; this problem was challenging Moscow in the 2000s: until recently, the capital was a complete outsider in terms of accuracy of statistical registration of mortality. The purpose of the study was to identify peculiar features of evolution and the structure of mortality from an event of undetermined intent among Moscow working-age population in the 2000s against the background of the processes taking place in Russia. The article analyzes mortality from an event of undetermined intent among Moscow population of young and old working age in the 2000s, as well as its nosological aspects in 2011-2018, when certain events of undetermined intent were separated as individual nosological units. A sharp decline in indicators in 1999-2000 and their growth in 2015-2017 have been identified. It is shown that these shifts were due to all leading events of undetermined intent (falls/jumps from a high place, hanging/strangulation/suffocation, medicament, alcohol and drug poisoning as well as specified and unspecified events). As a result, the structure of mortality after 2015 has significantly changed due to a sharp increase in the significance of alcohol, medicament and especially drug poisoning. It should be emphasized that in the 2010s the significance of latent suicide in all age and gender groups of Moscow working-age population is significantly higher than in Russia.


Asunto(s)
Suicidio , Recolección de Datos , Moscú/epidemiología , Federación de Rusia/epidemiología
9.
Rev Paul Pediatr ; 39: e2020267, 2020.
Artículo en Inglés, Portugués | MEDLINE | ID: mdl-33146295

RESUMEN

OBJECTIVE: Social isolation is currently identified as the best way to prevent the infection by the new coronavirus. However, for some social groups, such as children and adolescents, this measure carries a contradiction: the home, which should be the safest place for them, is also a frequent environment of a sad aggravation: domestic violence. This study aims to evaluate the notifications of interpersonal/self-inflicted violence available in the Information System for Notifiable Diseases in the State of Santa Catarina (southern Brazil), for the juvenile age group, before and during the new coronavirus pandemics. METHODS: Cross-sectional, descriptive study of violence against children and adolescents (from 0 to 19 years) notified by health professionals by completing and entering the occurrence in the Information System for Notifiable Diseases of the State of Santa Catarina in 11 weeks in which the social isolation measure was instituted as mandatory, comparing with the same period before this measure. RESULTS: During the study period, 136 municipalities in Santa Catarina made 1,851 notifications. There was a decrease of 55.3% of them in the isolation period, and the difficulties encountered in seeking protection and assistance institutions were listed. CONCLUSIONS: The society needs to be aware of possible cases of violence in the children and adolescent population. It is important to provide accessible, effective, and safe ways for complaints and notifications, as well as a quick response to the cases, aiming at protecting victims and minimizing damages to prevent the perpetuation of the violence.


Asunto(s)
Maltrato a los Niños , Bienestar del Niño , Infecciones por Coronavirus/epidemiología , Violencia Doméstica , Neumonía Viral/epidemiología , Adolescente , Salud del Adolescente/tendencias , Betacoronavirus , Brasil/epidemiología , Niño , Maltrato a los Niños/prevención & control , Maltrato a los Niños/estadística & datos numéricos , Salud del Niño/tendencias , Estudios Transversales , Recolección de Datos/métodos , Recolección de Datos/estadística & datos numéricos , Violencia Doméstica/prevención & control , Violencia Doméstica/tendencias , Femenino , Humanos , Masculino , Evaluación de Necesidades , Pandemias
10.
Annu Int Conf IEEE Eng Med Biol Soc ; 2020: 5714-5717, 2020 07.
Artículo en Inglés | MEDLINE | ID: mdl-33019272

RESUMEN

Advanced sensing technologies, driven by the Internet of Things, have caused a sharp increase in data availability within the healthcare system. The newfound availability of data offers an unprecedented opportunity to develop new analytical methods to improve the quality of patient care. Data availability, however, is a double-edged sword. Malicious attacks and data breaches are increasingly seen in the healthcare field, which result in costly disruptions to operations. Adversaries exploit analytic models to infer participation in a dataset or estimate sensitivity attributes about a target patient. This paper is aimed at developing a differentially private gradient-based mechanism and assessing its utility in mitigating the impact of these attack risks within the context of the intensive care units. Experimental results showed that this methodology is capable of greatly reducing the risk of model inversion while retaining model accuracy. Thus, health systems that employ this technique can be given more peace of mind that high-quality services can be delivered in such a way that privacy is preserved.


Asunto(s)
Prestación de Atención de Salud , Privacidad , Recolección de Datos , Humanos
11.
Nat Commun ; 11(1): 5208, 2020 10 15.
Artículo en Inglés | MEDLINE | ID: mdl-33060581

RESUMEN

Cryo-electron microscopy (cryoEM) is becoming the preferred method for resolving protein structures. Low signal-to-noise ratio (SNR) in cryoEM images reduces the confidence and throughput of structure determination during several steps of data processing, resulting in impediments such as missing particle orientations. Denoising cryoEM images can not only improve downstream analysis but also accelerate the time-consuming data collection process by allowing lower electron dose micrographs to be used for analysis. Here, we present Topaz-Denoise, a deep learning method for reliably and rapidly increasing the SNR of cryoEM images and cryoET tomograms. By training on a dataset composed of thousands of micrographs collected across a wide range of imaging conditions, we are able to learn models capturing the complexity of the cryoEM image formation process. The general model we present is able to denoise new datasets without additional training. Denoising with this model improves micrograph interpretability and allows us to solve 3D single particle structures of clustered protocadherin, an elongated particle with previously elusive views. We then show that low dose collection, enabled by Topaz-Denoise, improves downstream analysis in addition to reducing data collection time. We also present a general 3D denoising model for cryoET. Topaz-Denoise and pre-trained general models are now included in Topaz. We expect that Topaz-Denoise will be of broad utility to the cryoEM community for improving micrograph and tomogram interpretability and accelerating analysis.


Asunto(s)
Microscopía por Crioelectrón/métodos , Aprendizaje Automático , Cementos de Resina , Cadherinas , Recolección de Datos , Tamaño de la Partícula , Relación Señal-Ruido
12.
Math Biosci Eng ; 17(5): 4875-4890, 2020 07 13.
Artículo en Inglés | MEDLINE | ID: mdl-33120532

RESUMEN

At the beginning of 2020, the novel coronavirus disease (COVID-19) became an outbreak in China. On January 23, China raised its national public health response to the highest level. As part of the emergency response, a series of public social distancing interventions were implemented to reduce the transmission rate of COVID-19. In this article, we explored the feasibility of using mobile terminal positioning data to study the impact of some nonpharmaceutical public health interventions implemented by China. First, this article introduced a hybrid method for measuring the number of people in public places based on anonymized mobile terminal positioning data. Additionally, the difference-in-difference (DID) model was used to estimate the effect of the interventions on reducing public gatherings in different provinces and during different stages. The data-driven experimental results showed that the interventions that China implemented reduced the number of people in public places by approximately 60% between January 24 and February 28. Among the 31 provinces in the Chinese mainland, some provinces, such as Tianjin and Chongqing, were more affected by the interventions, while other provinces, such as Gansu, were less affected. In terms of the stages, the phase with the greatest intervention effect was from February 3 to 14, during which the number of daily confirmed cases in China showed a turning point. In conclusion, the interventions significantly reduced public gatherings, and the effects of interventions varied with provinces and time.


Asunto(s)
Teléfono Celular , Control de Enfermedades Transmisibles/legislación & jurisprudencia , Infecciones por Coronavirus/epidemiología , Infecciones por Coronavirus/prevención & control , Conductas Relacionadas con la Salud , Pandemias/prevención & control , Neumonía Viral/epidemiología , Neumonía Viral/prevención & control , Política Pública , Aislamiento Social , Betacoronavirus , China/epidemiología , Control de Enfermedades Transmisibles/métodos , Recolección de Datos , Brotes de Enfermedades , Humanos , Viaje
13.
Math Biosci Eng ; 17(5): 4891-4904, 2020 07 13.
Artículo en Inglés | MEDLINE | ID: mdl-33120533

RESUMEN

The outbreak of COVID-19 disrupts the life of many people in the world. The state of Arizona in the U.S. emerges as one of the country's newest COVID-19 hot spots. Accurate forecasting for COVID-19 cases will help governments to implement necessary measures and convince more people to take personal precautions to combat the virus. It is difficult to accurately predict the COVID- 19 cases due to many human factors involved. This paper aims to provide a forecasting model for COVID-19 cases with the help of human activity data from the Google Community Mobility Reports. To achieve this goal, a specific partial differential equation (PDE) is developed and validated with the COVID-19 data from the New York Times at the county level in the state of Arizona in the U.S. The proposed model describes the combined effects of transboundary spread among county clusters in Arizona and human activities on the transmission of COVID-19. The results show that the prediction accuracy of this model is well acceptable (above 94%). Furthermore, we study the effectiveness of personal precautions such as wearing face masks and practicing social distancing on COVID-19 cases at the local level. The localized analytical results can be used to help to slow the spread of COVID- 19 in Arizona. To the best of our knowledge, this work is the first attempt to apply PDE models on COVID-19 prediction with the Google Community Mobility Reports.


Asunto(s)
Infecciones por Coronavirus/epidemiología , Brotes de Enfermedades , Internet , Neumonía Viral/epidemiología , Algoritmos , Arizona/epidemiología , Betacoronavirus , Infecciones por Coronavirus/transmisión , Recolección de Datos , Geografía , Conductas Relacionadas con la Salud , Humanos , Máscaras , Modelos Teóricos , Pandemias , Neumonía Viral/transmisión , Política Pública , Aislamiento Social
16.
Annu Int Conf IEEE Eng Med Biol Soc ; 2020: 1388-1381, 2020 07.
Artículo en Inglés | MEDLINE | ID: mdl-33018248

RESUMEN

This study reports on the development of a high-resolution 4K multispectral camera designed to enhance telepathology support systems for remote gross-pathological diagnosis. We experimentally examine and evaluate the camera's effectiveness in three subjects: the reconstruction of precise color images, the emphasis of cancerous tissue areas, and pre-fixed image reproduction from fixed images. The evaluation results of the first and second subjects showed that the camera and supporting methods could be effectively used in gross pathology diagnosis. The images obtained in the third subject received positive evaluations from some pathologists, but others expressed reservations as to its utility.


Asunto(s)
Neoplasias , Telepatología , Recolección de Datos , Humanos , Organizaciones , Patólogos
17.
Annu Int Conf IEEE Eng Med Biol Soc ; 2020: 1400-1403, 2020 07.
Artículo en Inglés | MEDLINE | ID: mdl-33018251

RESUMEN

As many algorithms depend on a suitable representation of data, learning unique features is considered a crucial task. Although supervised techniques using deep neural networks have boosted the performance of representation learning, the need for a large sets of labeled data limits the application of such methods. As an example, high-quality delineations of regions of interest in the field of pathology is a tedious and time-consuming task due to the large image dimensions. In this work, we explored the performance of a deep neural network and triplet loss in the area of representation learning. We investigated the notion of similarity and dissimilarity in pathology whole-slide images and compared different setups from unsupervised and semi-supervised to supervised learning in our experiments. Additionally, different approaches were tested, applying few-shot learning on two publicly available pathology image datasets. We achieved high accuracy and generalization when the learned representations were applied to two different pathology datasets.


Asunto(s)
Algoritmos , Redes Neurales de la Computación , Recolección de Datos , Suplementos Dietéticos , Sistema Linfático
18.
Annu Int Conf IEEE Eng Med Biol Soc ; 2020: 1641-1645, 2020 07.
Artículo en Inglés | MEDLINE | ID: mdl-33018310

RESUMEN

Since the thickness and shape of the choroid layer are indicators for the diagnosis of several ophthalmic diseases, the choroid layer segmentation is an important task. There exist many challenges in segmentation of the choroid layer. In this paper, in view of the lack of context information due to the ambiguous boundaries, and the subsequent inconsistent predictions of the same category targets ascribed to the lack of context information or the large regions, a novel Skip Connection Attention (SCA) module which is integrated into the U-Shape architecture is proposed to improve the precision of choroid layer segmentation in Optical Coherence Tomography (OCT) images. The main function of the SCA module is to capture the global context in the highest level to provide the decoder with stage-by-stage guidance, to extract more context information and generate more consistent predictions for the same class targets. By integrating the SCA module into the U-Net and CE-Net, we show that the module improves the accuracy of the choroid layer segmentation.


Asunto(s)
Aprendizaje Profundo , Tomografía de Coherencia Óptica , Atención , Coroides/diagnóstico por imagen , Recolección de Datos
19.
Annu Int Conf IEEE Eng Med Biol Soc ; 2020: 2969-2972, 2020 07.
Artículo en Inglés | MEDLINE | ID: mdl-33018629

RESUMEN

Subject-independent brain-computer interfaces (SI-BCIs) which require no calibration process, are increasingly affect researchers in BCI field. The efficiencies (accuracies), however, were not satisfying till now. In this paper, we proposed a weighted subject-semi-independent classification method (WSSICM) for ERP based BCI system in which a few blocks data of target subject were used. 47 participants were attended in this study. We compared the accuracies of proposed method with traditional subject-specific classification method(SSCM) which used 15 blocks data of target subject. The averaged accuracies were 95.2% for the WSSICM at 5 blocks and 95.7% for the SSCM at 15 blocks. The accuracies of two method did not show significant difference (p-value=0.652). The method we proposed in this paper which could reduce the calibration time can be used for future BCI systems.


Asunto(s)
Interfaces Cerebro-Computador , Calibración , Recolección de Datos , Humanos , Proyectos de Investigación
20.
J Med Internet Res ; 22(10): e21980, 2020 10 09.
Artículo en Inglés | MEDLINE | ID: mdl-33001836

RESUMEN

BACKGROUND: In the prevention and control of infectious diseases, previous research on the application of big data technology has mainly focused on the early warning and early monitoring of infectious diseases. Although the application of big data technology for COVID-19 warning and monitoring remain important tasks, prevention of the disease's rapid spread and reduction of its impact on society are currently the most pressing challenges for the application of big data technology during the COVID-19 pandemic. After the outbreak of COVID-19 in Wuhan, the Chinese government and nongovernmental organizations actively used big data technology to prevent, contain, and control the spread of COVID-19. OBJECTIVE: The aim of this study is to discuss the application of big data technology to prevent, contain, and control COVID-19 in China; draw lessons; and make recommendations. METHODS: We discuss the data collection methods and key data information that existed in China before the outbreak of COVID-19 and how these data contributed to the prevention and control of COVID-19. Next, we discuss China's new data collection methods and new information assembled after the outbreak of COVID-19. Based on the data and information collected in China, we analyzed the application of big data technology from the perspectives of data sources, data application logic, data application level, and application results. In addition, we analyzed the issues, challenges, and responses encountered by China in the application of big data technology from four perspectives: data access, data use, data sharing, and data protection. Suggestions for improvements are made for data collection, data circulation, data innovation, and data security to help understand China's response to the epidemic and to provide lessons for other countries' prevention and control of COVID-19. RESULTS: In the process of the prevention and control of COVID-19 in China, big data technology has played an important role in personal tracking, surveillance and early warning, tracking of the virus's sources, drug screening, medical treatment, resource allocation, and production recovery. The data used included location and travel data, medical and health data, news media data, government data, online consumption data, data collected by intelligent equipment, and epidemic prevention data. We identified a number of big data problems including low efficiency of data collection, difficulty in guaranteeing data quality, low efficiency of data use, lack of timely data sharing, and data privacy protection issues. To address these problems, we suggest unified data collection standards, innovative use of data, accelerated exchange and circulation of data, and a detailed and rigorous data protection system. CONCLUSIONS: China has used big data technology to prevent and control COVID-19 in a timely manner. To prevent and control infectious diseases, countries must collect, clean, and integrate data from a wide range of sources; use big data technology to analyze a wide range of big data; create platforms for data analyses and sharing; and address privacy issues in the collection and use of big data.


Asunto(s)
Macrodatos , Infecciones por Coronavirus/prevención & control , Pandemias/prevención & control , Neumonía Viral/prevención & control , Betacoronavirus , China/epidemiología , Seguridad Computacional , Infecciones por Coronavirus/epidemiología , Recolección de Datos , Humanos , Difusión de la Información , Almacenamiento y Recuperación de la Información , Neumonía Viral/epidemiología , Privacidad
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