Epidemiolgia (Basel, Switzerland)最新文献

{"title":"Right to Occupational Safety: Prevalence of Latent Tuberculosis Infection in Healthcare Workers. A 1-Year Retrospective Survey Carried out at Hospital of Lecce (Italy)","authors":"Gabriele d’Ettorre, Stela Karaj, Prisco Piscitelli, Osvaldo Maiorano, Carmen Attanasi, Roberta Tornese, Eugenia Carluccio, Paolo Giannuzzi, Enrico Greco, Giancarlo Ceccarelli, Gabriella d’Ettorre, Giambattista Lobreglio, Pierpaolo Congedo, Francesco Broccolo, Alessandro Miani","doi":"10.3390/epidemiologia4040038","DOIUrl":"https://doi.org/10.3390/epidemiologia4040038","url":null,"abstract":"Background: Prevention of latent tuberculosis infection (LTBI) in healthcare workers (HCWs) to ensure the “Right to Occupational Safety” is a special challenge globally, as HCWs have a higher risk of acquiring the infection in hospital settings because of frequent close exposure to patients suffering from tuberculosis (TB). Methods: Aretrospective study was performed with the aim of assessing the prevalence of LTBI related to demographical and occupational risk factors among HCWs employed in a large hospital in Italy. The study involved 1461 HCWs screened for LTBI by Mantoux tuberculin skin test (TST) and then confirmed with Interferon Gamma Release Assay (IGRA) test in case of positivity. Immunosuppressed and BGC-vaccinated workers were tested directly with IGRA. Results: LTBI was diagnosed in 4.1% of the HCWs and the prevalence resulted lower than other studies conducted in low TB incidence countries. The variables significantly linked with higher frequency of the infection were: age ≥40 years (OR = 3.14; 95% CI: 1.13–8.74; p < 0.05), length of service ≥15 years (OR = 4.11; 95% CI: 1.48–11.43; p < 0.05) and not being trained on TB prevention (OR = 3.46; 95% CI: 1.85–6.46; p < 0.05). Not trained HCWs presented a higher risk of LTBI also after adjustment for age and length of service, compared to trained HCWs. Conclusions: screening of HCWs for LTBI should be always considered in routinely occupational surveillance in order to early diagnose the infection and prevent its progression. Safety policies in hospital settings centered on workers’ training on TB prevention is crucial to minimize LTBI occurrence in HCWs.","PeriodicalId":72944,"journal":{"name":"Epidemiolgia (Basel, Switzerland)","volume":"135 ","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135870677","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Data-Driven Deep Learning Neural Networks for Predicting the Number of Individuals Infected by COVID-19 Omicron Variant.","authors":"Ebenezer O Oluwasakin, Abdul Q M Khaliq","doi":"10.3390/epidemiologia4040037","DOIUrl":"10.3390/epidemiologia4040037","url":null,"abstract":"<p><p>Infectious disease epidemics are challenging for medical and public health practitioners. They require prompt treatment, but it is challenging to recognize and define epidemics in real time. Knowing the prediction of an infectious disease epidemic can evaluate and prevent the disease's impact. Mathematical models of epidemics that work in real time are important tools for preventing disease, and data-driven deep learning enables practical algorithms for identifying parameters in mathematical models. In this paper, the SIR model was reduced to a logistic differential equation involving a constant parameter and a time-dependent function. The time-dependent function leads to constant, rational, and birational models. These models use several constant parameters from the available data to predict the time and number of people reported to be infected with the COVID-19 Omicron variant. Two out of these three models, rational and birational, provide accurate predictions for countries that practice strict mitigation measures, but fail to provide accurate predictions for countries that practice partial mitigation measures. Therefore, we introduce a time-series model based on neural networks to predict the time and number of people reported to be infected with the COVID-19 Omicron variant in a given country that practices both partial and strict mitigation measures. A logistics-informed neural network algorithm was also introduced. This algorithm takes as input the daily and cumulative number of people who are reported to be infected with the COVID-19 Omicron variant in the given country. The algorithm helps determine the analytical solution involving several constant parameters for each model from the available data. The accuracy of these models is demonstrated using error metrics on Omicron variant data for Portugal, Italy, and China. Our findings demonstrate that the constant model could not accurately predict the daily or cumulative infections of the COVID-19 Omicron variant in the observed country because of the long series of existing data of the epidemics. However, the rational and birational models accurately predicted cumulative infections in countries adopting strict mitigation measures, but they fell short in predicting the daily infections. Furthermore, both models performed poorly in countries with partial mitigation measures. Notably, the time-series model stood out for its versatility, effectively predicting both daily and cumulative infections in countries irrespective of the stringency of their mitigation measures.</p>","PeriodicalId":72944,"journal":{"name":"Epidemiolgia (Basel, Switzerland)","volume":"4 4","pages":"420-453"},"PeriodicalIF":0.0,"publicationDate":"2023-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10594457/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49694739","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Modeling Transmission Dynamics of Tuberculosis-HIV Co-Infection in South Africa.","authors":"Simeon Adeyemo,&nbsp;Adekunle Sangotola,&nbsp;Olga Korosteleva","doi":"10.3390/epidemiologia4040036","DOIUrl":"10.3390/epidemiologia4040036","url":null,"abstract":"<p><p>South Africa has the highest number of people living with the human immunodeficiency virus (HIV) in the world, accounting for nearly one in five people living with HIV globally. As of 2021, 8 million people in South Africa were infected with HIV, which is 13% of the country's total population. Approximately 450,000 people in the country develop tuberculosis (TB) disease every year, and 270,000 of those are HIV positive. This suggests that being HIV positive significantly increases one's susceptibility to TB, accelerating the spread of the epidemic. To better understand the disease burden at the population level, a Susceptible-Infected-Recovered-Dead (SIRD) TB-HIV co-infection epidemic model is presented. Parameter values are estimated using the method of moments. The disease-free equilibrium and basic reproduction number of the model are also obtained. Finally, numeric simulations are carried out for a 30-year period to give insights into the transmission dynamics of the co-infection.</p>","PeriodicalId":72944,"journal":{"name":"Epidemiolgia (Basel, Switzerland)","volume":"4 4","pages":"408-419"},"PeriodicalIF":0.0,"publicationDate":"2023-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10594517/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49694740","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Predictive Strategies to Reduce the Risk of Rehospitalization with a Focus on Frail Older Adults: A Narrative Review.","authors":"Rabia Bag Soytas,&nbsp;Elise J Levinoff,&nbsp;Lee Smith,&nbsp;Alper Doventas,&nbsp;José A Morais,&nbsp;Nicola Veronese,&nbsp;Pinar Soysal","doi":"10.3390/epidemiologia4040035","DOIUrl":"10.3390/epidemiologia4040035","url":null,"abstract":"<p><p>Frailty is a geriatric syndrome that has physical, cognitive, psychological, social, and environmental components and is characterized by a decrease in physiological reserves. Frailty is associated with several adverse health outcomes such as an increase in rehospitalization rates, falls, delirium, incontinence, dependency on daily living activities, morbidity, and mortality. Older adults may become frailer with each hospitalization; thus, it is beneficial to develop and implement preventive strategies. The present review aims to highlight the epidemiological importance of frailty in rehospitalization and to compile predictive strategies and related interventions to prevent hospitalizations. Firstly, it is important to identify pre-frail and frail older adults using an instrument with high validity and reliability, which can be a practically applicable screening tool. Comprehensive geriatric assessment-based care is an important strategy known to reduce morbidity, mortality, and rehospitalization in older adults and aims to meet the needs of frail patients with a multidisciplinary approach and intervention that includes physiological, psychological, and social domains. Moreover, effective multimorbidity management, physical activity, nutritional support, preventing cognitive frailty, avoiding polypharmacy and anticholinergic drug burden, immunization, social support, and reducing the caregiver burden are other recommended predictive strategies to prevent post-discharge rehospitalization in frail older adults.</p>","PeriodicalId":72944,"journal":{"name":"Epidemiolgia (Basel, Switzerland)","volume":"4 4","pages":"382-407"},"PeriodicalIF":0.0,"publicationDate":"2023-10-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10594531/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49694741","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Agreement in All-in-One Dataset between Diagnosis and Prescribed Medication for Common Cardiometabolic Diseases in the NDB-K7Ps.","authors":"Airi Sekine,&nbsp;Kei Nakajima","doi":"10.3390/epidemiologia4040034","DOIUrl":"10.3390/epidemiologia4040034","url":null,"abstract":"<p><p>The Japanese National Database (NDB), a useful data source for epidemiological studies, contains information on health checkups, disease diagnoses, and medications, which can be used when investigating common cardiometabolic diseases. However, before the initiation of an integrated analysis, we need to combine several pieces of information prepared separately into an all-in-one dataset (AIOD) and confirm the validation of the dataset for the study. In this study, we aimed to confirm the degree of agreement in data entries between diagnoses and prescribed medications and self-reported pharmacotherapy for common cardiometabolic diseases in newly assembled AIODs. The present study included 10,183,619 people who underwent health checkups from April 2018 to March 2019. Over 95% of patients prescribed antihypertensive and antidiabetic medications were diagnosed with each disease. For dyslipidemia, over 95% of patients prescribed medications were diagnosed with at least one of the following: dyslipidemia, hypercholesterolemia, or hyperlipidemia. Similarly, over 95% of patients prescribed medications for hyperuricemia were diagnosed with either hyperuricemia or gout. Additionally, over 90% of patients with self-reported medications for hypertension, diabetes, and dyslipidemia were diagnosed with each disease, although the proportions differed among age groups. Our study demonstrated high levels of agreement between diagnoses and prescribed medications for common cardiometabolic diseases and self-reported pharmacotherapy in our AIOD.</p>","PeriodicalId":72944,"journal":{"name":"Epidemiolgia (Basel, Switzerland)","volume":"4 4","pages":"370-381"},"PeriodicalIF":0.0,"publicationDate":"2023-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10594522/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49694738","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Monkeypox Patients Living with HIV: A Systematic Review and Meta-Analysis of Geographic and Temporal Variations.","authors":"Aravind P Gandhi,&nbsp;Bijaya K Padhi,&nbsp;Mokanpally Sandeep,&nbsp;Muhammad Aaqib Shamim,&nbsp;Tarun K Suvvari,&nbsp;Prakasini Satapathy,&nbsp;Abdelmonem Siddiq,&nbsp;Ranjit Sah,&nbsp;Sarvesh Rustagi,&nbsp;Zahraa H Al-Qaim,&nbsp;Jagdish Khubchandani","doi":"10.3390/epidemiologia4030033","DOIUrl":"https://doi.org/10.3390/epidemiologia4030033","url":null,"abstract":"<p><p>This index meta-analysis estimated the pooled prevalence of human immunodeficiency virus (HIV) among individuals with monkeypox (mpox) globally. We searched seven databases: PubMed, Scopus, Web of Science, EMBASE, ProQuest, EBSCOHost, and Cochrane, for human studies published in English till 4 January 2023, as per International Prospective Register of Systematic Reviews (PROSPERO) registration protocol (CRD42022383275). A random effects regression model was used to estimate the pooled prevalence owing to high heterogeneity. The risk of bias in the included studies was assessed using the National Heart, Lung, and Blood Institute (NHLBI) quality assessment tool. The systematic search yielded 677 articles; finally, 32 studies were found eligible for systematic review and 29 studies for meta-analysis. The pooled prevalence of HIV infection was 41% (95% confidence interval [CI], 35-48). All studies were rated as fair or good quality. Studies from Europe and North America reported a high prevalence of HIV infection among individuals with mpox- 41% (95% CI 33-49) and 52% (95% CI 28-76), respectively, while studies from Nigeria, Africa reported a relatively low prevalence of HIV infection of 21% (95% CI 15-26)<b>.</b> A history of sexual orientation and sexual partners in the last 21 days must be taken from individuals with mpox to identify the potential source and contacts for quarantining and testing them.</p>","PeriodicalId":72944,"journal":{"name":"Epidemiolgia (Basel, Switzerland)","volume":"4 3","pages":"352-369"},"PeriodicalIF":0.0,"publicationDate":"2023-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10528863/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41163631","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Trends, Projections, and Regional Disparities of Maternal Mortality in Africa (1990-2030): An ARIMA Forecasting Approach.","authors":"Luc Onambele,&nbsp;Sara Guillen-Aguinaga,&nbsp;Laura Guillen-Aguinaga,&nbsp;Wilfrido Ortega-Leon,&nbsp;Rocio Montejo,&nbsp;Rosa Alas-Brun,&nbsp;Enrique Aguinaga-Ontoso,&nbsp;Ines Aguinaga-Ontoso,&nbsp;Francisco Guillen-Grima","doi":"10.3390/epidemiologia4030032","DOIUrl":"https://doi.org/10.3390/epidemiologia4030032","url":null,"abstract":"<p><p>With the United Nations Sustainable Development Goals (SDG) (2015-2030) focused on the reduction in maternal mortality, monitoring and forecasting maternal mortality rates (MMRs) in regions like Africa is crucial for health strategy planning by policymakers, international organizations, and NGOs. We collected maternal mortality rates per 100,000 births from the World Bank database between 1990 and 2015. Joinpoint regression was applied to assess trends, and the autoregressive integrated moving average (ARIMA) model was used on 1990-2015 data to forecast the MMRs for the next 15 years. We also used the Holt method and the machine-learning Prophet Forecasting Model. The study found a decline in MMRs in Africa with an average annual percentage change (APC) of -2.6% (95% CI -2.7; -2.5). North Africa reported the lowest MMR, while East Africa experienced the sharpest decline. The region-specific ARIMA models predict that the maternal mortality rate (MMR) in 2030 will vary across regions, ranging from 161 deaths per 100,000 births in North Africa to 302 deaths per 100,000 births in Central Africa, averaging 182 per 100,000 births for the continent. Despite the observed decreasing trend in maternal mortality rate (MMR), the MMR in Africa remains relatively high. The results indicate that MMR in Africa will continue to decrease by 2030. However, no region of Africa will likely reach the SDG target.</p>","PeriodicalId":72944,"journal":{"name":"Epidemiolgia (Basel, Switzerland)","volume":"4 3","pages":"322-351"},"PeriodicalIF":0.0,"publicationDate":"2023-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10528291/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41142614","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Essential Business Visits and Social Vulnerability during New York City's Initial COVID-19 Outbreak.","authors":"Debra F Laefer,&nbsp;Delphine Protopapas","doi":"10.3390/epidemiologia3040039","DOIUrl":"https://doi.org/10.3390/epidemiologia3040039","url":null,"abstract":"<p><p>New York City (NYC) was deeply impacted by COVID-19 in spring 2020, with thousands of new cases daily. However, the pandemic's effects were not evenly distributed across the city, and the specific contributors have not yet been systematically considered. To help investigate that topic, this study analyzed the interaction of people with neighborhood businesses and other points of interest (POIs) in parts of three NYC neighborhoods in the spring of 2020 during the peak of the first COVID-19 wave through anonymized cellphone data and direct the observation of 1313 individuals leaving healthcare facilities. This study considered social vulnerability index (SVI) levels, population density, and POI visit behaviors from both cellphone data and firsthand observations of behavior around select NYC health facilities in different boroughs as various proxies. By considering equivalent businesses or groups of businesses by neighborhood, POI visits better aligned with COVID-19 infection levels than SVI. If tracking POI visit levels proves a reliable direct or relative proxy for disease transmission when checked against larger datasets, this method could be critical in both predictions of future outbreaks and the setting of customer density limits.</p>","PeriodicalId":72944,"journal":{"name":"Epidemiolgia (Basel, Switzerland)","volume":"3 4","pages":"518-532"},"PeriodicalIF":0.0,"publicationDate":"2022-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9680471/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10384470","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Knowledge, Attitudes, Practices and Zoonotic Risk Perception of Bovine Q Fever (<i>Coxiella burnetii</i>) among Cattle Farmers and Veterinary Personnel in Northern Regions of Cameroon.","authors":"Camille Teitsa Zangue,&nbsp;Justin Kouamo,&nbsp;Ferdinand Ngoula,&nbsp;Ludovic Pépin M'bapté Tawali,&nbsp;Moustapha Mohamed Fokom Ndebé,&nbsp;Dinayen Edwin Somnjom,&nbsp;Ranyl Noumedem Guefack Nguena,&nbsp;Mohamed Moctar Mouliom Mouiche","doi":"10.3390/epidemiologia3040036","DOIUrl":"https://doi.org/10.3390/epidemiologia3040036","url":null,"abstract":"A cross-sectional survey was conducted to investigate the knowledge, attitudes, practices and zoonotic risk perception of Q fever among 484 selected cattle farmers (438) and veterinary personnel (46) in three northern regions of Cameroon. Data collection was conducted using questionnaires and responses were recoded into binary scale. An ANOVA test was used to assess significant differences in mean knowledge, attitude, practice and zoonotic risk perception (KAPP) scores between regions, while Linear regression was done to explore the relationship between demographic characteristic and KAPP. Overall, surveyed had low mean scores for knowledge (0.02 ± 0.11), desirable attitude (0.30 ± 0.16), appropriate practice (0.43 ± 0.13) and negative perception of zoonotic risks (0.05 ± 0.11). The means knowledge, attitude, practice and risks perception scores of cattle farmers were lower than those of veterinary personnel. The nature of respondent was negatively associated to knowledge and risks perception, while regions were negatively correlated to attitude and practice. These results revealed significant knowledge gaps, low levels of desired attitudes, and high-risk behavioral practices. To improve awareness, control programs are needed to update knowledge on medical personnel and to prevent animal-to-human transmission.","PeriodicalId":72944,"journal":{"name":"Epidemiolgia (Basel, Switzerland)","volume":"3 4","pages":"482-492"},"PeriodicalIF":0.0,"publicationDate":"2022-10-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9680217/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10384469","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Molecular Epidemiological Investigations of Localized SARS-CoV-2 Outbreaks-Utility of Public Algorithms.","authors":"Mahmood Y Bilal, James S Klutts","doi":"10.3390/epidemiologia3030031","DOIUrl":"10.3390/epidemiologia3030031","url":null,"abstract":"<p><p>The recent rapid expansion of targeted viral sequencing approaches in conjunction with available bioinformatics have provided an effective platform for studying severe acute respiratory syndrome coronavirus-2 (CoV-2) virions at the molecular level. These means can be adapted to the field of viral molecular epidemiology, wherein localized outbreak clusters can be evaluated and linked. To this end, we have integrated publicly available algorithms in conjunction with targeted RNASeq data in order to qualitatively evaluate similarity or dissimilarity between suspect outbreak strains from hospitals, or assisted living facilities. These tools include phylogenetic clustering and mutational analysis utilizing Nextclade and Ultrafast Sample placement on Existing tRee (UShER). We herein present these outbreak screening tools utilizing three case examples in the context of molecular epidemiology, along with limitations and potential future developments. We anticipate that these methods can be performed in clinical molecular laboratories equipped with CoV-2-sequencing technology.</p>","PeriodicalId":72944,"journal":{"name":"Epidemiolgia (Basel, Switzerland)","volume":"3 3","pages":"402-411"},"PeriodicalIF":0.0,"publicationDate":"2022-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9620882/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10690449","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}