1999 10 20655 https://www.socictopen.socict.org/files/original/384b5b7413b618cf2d7c114687ee7c40.pdf e3f7cfbdca608354c446e12ae47459ef Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Coronavirus Description An account of the resource Dominio científico: Coronavirus Text A resource consisting primarily of words for reading. Examples include books, letters, dissertations, poems, newspapers, articles, archives of mailing lists. Note that facsimiles or images of texts are still of the genre Text. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Using All-Atom Potentials to Refine RNA Structure Predictions of SARS-CoV-2 Stem Loops Creator An entity primarily responsible for making the resource Christina Bergonzo, Andrea L. Szakal Description An account of the resource A considerable amount of rapid-paced research is underway to combat the SARS-CoV-2 pandemic. In this work, we assess the 3D structure of the 5′ untranslated region of its RNA, in the hopes that stable secondary structures can be targeted, interrupted, or otherwise measured. To this end, we have combined molecular dynamics simulations with previous Nuclear Magnetic Resonance measurements for stem loop 2 of SARS-CoV-1 to refine 3D structure predictions of that stem loop. We find that relatively short sampling times allow for loop rearrangement from predicted structures determined in absence of water or ions, to structures better aligned with experimental data. We then use molecular dynamics to predict the refined structure of the transcription regulatory leader sequence (TRS-L) region which includes stem loop 3, and show that arrangement of the loop around exchangeable monovalent potassium can interpret the conformational equilibrium determined by in-cell dimethyl sulfate (DMS) data. Date A point or period of time associated with an event in the lifecycle of the resource 2020 Subject The topic of the resource molecular dynamics, structure refinement, RNA stem loops, discontinuous transcription Identifier An unambiguous reference to the resource within a given context 10.3390/ijms21176188 Source A related resource from which the described resource is derived Epidemiology and Health Publisher An entity responsible for making the resource available Korean Society of Epidemiology Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Biology (General), Chemistry https://www.socictopen.socict.org/files/original/943a1599c69c8518ebeb975e61414db2.pdf eede920bcd94b824d0a82400709785b4 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Coronavirus Description An account of the resource Dominio científico: Coronavirus Text A resource consisting primarily of words for reading. Examples include books, letters, dissertations, poems, newspapers, articles, archives of mailing lists. Note that facsimiles or images of texts are still of the genre Text. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Using Artificial Neural Network with Prey Predator Algorithm for Prediction of the COVID-19: The Case of Brazil and Mexico Creator An entity primarily responsible for making the resource Waqar A. Khan, Nawaf N. Hamadneh, Muhammad Tahir Description An account of the resource The spread of the COVID-19 epidemic worldwide has led to investigations in various aspects, including the estimation of expected cases. As it helps in identifying the need to deal with cases caused by the pandemic. In this study, we have used artificial neural networks (ANNs) to predict the number of cases of COVID-19 in Brazil and Mexico in the upcoming days. Prey predator algorithm (PPA), as a type of metaheuristic algorithm, is used to train the models. The proposed ANN models’ performance has been analyzed by the root mean squared error (RMSE) function and correlation coefficient (R). It is demonstrated that the ANN models have the highest performance in predicting the number of infections (active cases), recoveries, and deaths in Brazil and Mexico. The simulation results of the ANN models show very well predicted values. Percentages of the ANN’s prediction errors with metaheuristic algorithms are significantly lower than traditional monolithic neural networks. The study shows the expected numbers of infections, recoveries, and deaths that Brazil and Mexico will reach daily at the beginning of 2021. Date A point or period of time associated with an event in the lifecycle of the resource 2021 Subject The topic of the resource covid-19, machine learning, Artificial Neural Networks, prey predator algorithm Identifier An unambiguous reference to the resource within a given context 10.3390/math9020180 Source A related resource from which the described resource is derived Epidemiology and Health Publisher An entity responsible for making the resource available Korean Society of Epidemiology Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Mathematics https://www.socictopen.socict.org/files/original/8c6b77c27a2233ec05961c914f061b20.pdf 95c6d3d64eede584c7c7ccd383b3ed4a Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Coronavirus Description An account of the resource Dominio científico: Coronavirus Text A resource consisting primarily of words for reading. Examples include books, letters, dissertations, poems, newspapers, articles, archives of mailing lists. Note that facsimiles or images of texts are still of the genre Text. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Using Biosecurity Measures to Combat Respiratory Disease in Cattle: The Norwegian Control Program for Bovine Respiratory Syncytial Virus and Bovine Coronavirus Creator An entity primarily responsible for making the resource Maria Stokstad, Thea Blystad Klem, Mette Myrmel, Veslemøy Sunniva Oma, Ingrid Toftaker, Olav Østerås, Ane Nødtvedt Description An account of the resource Bovine respiratory disease (BRD) cause important health problems in all cattle husbandry systems. It contributes substantially to the use of antimicrobial substances and compromises animal welfare and the sustainability of the cattle industry. The existing preventive measures of BRD focus at the individual animal or herd level and include vaccination, mass treatment with antimicrobials and improvement of the animal's environment and general health status. Despite progress in our understanding of disease mechanism and technological development, the current preventive measures are not sufficiently effective. Thus, there is a need for alternative, sustainable strategies to combat the disease. Some of the primary infectious agents in the BRD complex are viruses that are easily transmitted between herds such as bovine respiratory syncytial virus (BRSV) and bovine coronavirus (BCoV). This conceptual analysis presents arguments for combatting BRD through improved external biosecurity in the cattle herds. As an example of a population-based approach to the control of BRD, the Norwegian BRSV/BCoV control-program is presented. The program is voluntary and launched by the national cattle industry. The core principle is classification of herds based on antibody testing and subsequent prevention of virus-introduction through improved biosecurity measures. Measures include external herd biosecurity barriers and regulations in the organization of animal trade to reduce direct and indirect transmission of virus. Improved biosecurity in a large proportion of herds will lead to a considerable effect at the population level. Positive herds are believed to gain freedom by time if new introduction is avoided. Vaccination is not used as part of the program. Dissemination of information to producers and veterinarians is essential. We believe that reducing the incidence of BRD in cattle is essential and will lead to reduced antimicrobial usage while at the same time improving animal health, welfare and production. Alternative approaches to the traditional control measures are needed. Date A point or period of time associated with an event in the lifecycle of the resource 2020 Subject The topic of the resource Bovine Respiratory Disease, winter dysentery, Disease control, population-based, prevention, BRSV Identifier An unambiguous reference to the resource within a given context DOI: 10.3389/fvets.2020.00167 Source A related resource from which the described resource is derived Frontiers in Veterinary Science Publisher An entity responsible for making the resource available Frontiers Media S.A. Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Veterinary medicine Language A language of the resource EN https://www.socictopen.socict.org/files/original/6507b768a6bf55646dd926ecd734a40d.pdf 195d47af664b5ac4350fb5ffa58e78da Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Coronavirus Description An account of the resource Dominio científico: Coronavirus Text A resource consisting primarily of words for reading. Examples include books, letters, dissertations, poems, newspapers, articles, archives of mailing lists. Note that facsimiles or images of texts are still of the genre Text. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Using common spatial distributions of atoms to relate functionally divergent influenza virus N10 and N11 protein structures to functionally characterized neuraminidase structures, toxin cell entry domains, and non-influenza virus cell entry domains. Creator An entity primarily responsible for making the resource Arthur Weininger, Susan Weininger Description An account of the resource The ability to identify the functional correlates of structural and sequence variation in proteins is a critical capability. We related structures of influenza A N10 and N11 proteins that have no established function to structures of proteins with known function by identifying spatially conserved atoms. We identified atoms with common distributed spatial occupancy in PDB structures of N10 protein, N11 protein, an influenza A neuraminidase, an influenza B neuraminidase, and a bacterial neuraminidase. By superposing these spatially conserved atoms, we aligned the structures and associated molecules. We report spatially and sequence invariant residues in the aligned structures. Spatially invariant residues in the N6 and influenza B neuraminidase active sites were found in previously unidentified spatially equivalent sites in the N10 and N11 proteins. We found the corresponding secondary and tertiary structures of the aligned proteins to be largely identical despite significant sequence divergence. We found structural precedent in known non-neuraminidase structures for residues exhibiting structural and sequence divergence in the aligned structures. In N10 protein, we identified staphylococcal enterotoxin I-like domains. In N11 protein, we identified hepatitis E E2S-like domains, SARS spike protein-like domains, and toxin components shared by alpha-bungarotoxin, staphylococcal enterotoxin I, anthrax lethal factor, clostridium botulinum neurotoxin, and clostridium tetanus toxin. The presence of active site components common to the N6, influenza B, and S. pneumoniae neuraminidases in the N10 and N11 proteins, combined with the absence of apparent neuraminidase function, suggests that the role of neuraminidases in H17N10 and H18N11 emerging influenza A viruses may have changed. The presentation of E2S-like, SARS spike protein-like, or toxin-like domains by the N10 and N11 proteins in these emerging viruses may indicate that H17N10 and H18N11 sialidase-facilitated cell entry has been supplemented or replaced by sialidase-independent receptor binding to an expanded cell population that may include neurons and T-cells. Date A point or period of time associated with an event in the lifecycle of the resource 2015 Identifier An unambiguous reference to the resource within a given context DOI: 10.1371/journal.pone.0117499 Source A related resource from which the described resource is derived PLoS ONE Publisher An entity responsible for making the resource available Public Library of Science (PLoS) Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Science, Medicine Language A language of the resource EN https://www.socictopen.socict.org/files/original/2ab14d1ab20085fe89cb875b3494ca4f.pdf 989b9a3d3d4bbfc67445dbab1eb730ab Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Coronavirus Description An account of the resource Dominio científico: Coronavirus Text A resource consisting primarily of words for reading. Examples include books, letters, dissertations, poems, newspapers, articles, archives of mailing lists. Note that facsimiles or images of texts are still of the genre Text. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Using Contingent Valuation Method to Estimate Adults' Willingness to Pay for a Future Coronavirus 2019 Vaccination. Creator An entity primarily responsible for making the resource Nam Xuan Vo, Tram Thi Huyen Nguyen, Pol Van Nguyen, Quang Vinh Tran, Trung Quang Vo Description An account of the resource Vaccines are recognized as the most effective strategy for long-term prevention of coronavirus disease 2019 (COVID-19) because they can reduce morbidity and mortality. The purpose of the present study was to evaluate willingness to pay (WTP) for a future COVID-19 vaccination among young adults in Southern Vietnam. A cross-sectional, descriptive, and analytic study was undertaken with data collected from a community-based survey in southern Vietnam for 2 weeks in May 2020. The contingent valuation method was used to estimate WTP for COVID-19 vaccine. The average amount that respondents were willing to pay for the vaccine was US$ 85.9 2 ± 69.01. We also found the differences in WTP according to sex, living area, monthly income, and the level of self-rated risk of COVID-19. Our findings possibly contribute to the implementation of a pricing policy when the COVID-19 vaccine is introduced in Vietnam. Date A point or period of time associated with an event in the lifecycle of the resource 2021 Subject The topic of the resource Vietnam, covid-19, Vaccination, willingness to pay, contingent valuation method Identifier An unambiguous reference to the resource within a given context 10.1016/j.vhri.2021.01.002 Source A related resource from which the described resource is derived Value in health regional issues https://www.socictopen.socict.org/files/original/8057c1e18523c85ab91ebb9306db5ee2.pdf aed55c9decfec28a19bfbb25e2726828 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Coronavirus Description An account of the resource Dominio científico: Coronavirus Text A resource consisting primarily of words for reading. Examples include books, letters, dissertations, poems, newspapers, articles, archives of mailing lists. Note that facsimiles or images of texts are still of the genre Text. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Using control charts to understand community variation in COVID-19. Creator An entity primarily responsible for making the resource Moira Inkelas, Cheríe Blair, Daisuke Furukawa, Vladimir G Manuel, Jason H Malenfant, Emily Martin, Iheanacho Emeruwa, Tony Kuo, Lisa Arangua, Brenda Robles, Lloyd P Provost Description An account of the resource Decision-makers need signals for action as the coronavirus disease 2019 (COVID-19) pandemic progresses. Our aim was to demonstrate a novel use of statistical process control to provide timely and interpretable displays of COVID-19 data that inform local mitigation and containment strategies. Healthcare and other industries use statistical process control to study variation and disaggregate data for purposes of understanding behavior of processes and systems and intervening on them. We developed control charts at the county and city/neighborhood level within one state (California) to illustrate their potential value for decision-makers. We found that COVID-19 rates vary by region and subregion, with periods of exponential and non-exponential growth and decline. Such disaggregation provides granularity that decision-makers can use to respond to the pandemic. The annotated time series presentation connects events and policies with observed data that may help mobilize and direct the actions of residents and other stakeholders. Policy-makers and communities require access to relevant, accurate data to respond to the evolving COVID-19 pandemic. Control charts could prove valuable given their potential ease of use and interpretability in real-time decision-making and for communication about the pandemic at a meaningful level for communities. Date A point or period of time associated with an event in the lifecycle of the resource 2021 Identifier An unambiguous reference to the resource within a given context 10.1371/journal.pone.0248500 Source A related resource from which the described resource is derived Epidemiology and Health Publisher An entity responsible for making the resource available Korean Society of Epidemiology Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Science, Medicine https://www.socictopen.socict.org/files/original/ca6654cf6e19439a674b6348de9a50d3.pdf 6f8c9014ec0c310bc1a2b8c7c3591bdf Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Coronavirus Description An account of the resource Dominio científico: Coronavirus Text A resource consisting primarily of words for reading. Examples include books, letters, dissertations, poems, newspapers, articles, archives of mailing lists. Note that facsimiles or images of texts are still of the genre Text. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Using country-level variables to classify countries according to the number of confirmed COVID-19 cases: An unsupervised machine learning approach [version 3; peer review: 2 approved] Creator An entity primarily responsible for making the resource Manuel Castillo-Cara, Rodrigo M. Carrillo-Larco Description An account of the resource Background: The COVID-19 pandemic has attracted the attention of researchers and clinicians whom have provided evidence about risk factors and clinical outcomes. Research on the COVID-19 pandemic benefiting from open-access data and machine learning algorithms is still scarce yet can produce relevant and pragmatic information. With country-level pre-COVID-19-pandemic variables, we aimed to cluster countries in groups with shared profiles of the COVID-19 pandemic. Methods: Unsupervised machine learning algorithms (k-means) were used to define data-driven clusters of countries; the algorithm was informed by disease prevalence estimates, metrics of air pollution, socio-economic status and health system coverage. Using the one-way ANOVA test, we compared the clusters in terms of number of confirmed COVID-19 cases, number of deaths, case fatality rate and order in which the country reported the first case. Results: The model to define the clusters was developed with 155 countries. The model with three principal component analysis parameters and five or six clusters showed the best ability to group countries in relevant sets. There was strong evidence that the model with five or six clusters could stratify countries according to the number of confirmed COVID-19 cases (p Date A point or period of time associated with an event in the lifecycle of the resource 2020 Identifier An unambiguous reference to the resource within a given context DOI: 10.12688/wellcomeopenres.15819.3 Source A related resource from which the described resource is derived Wellcome Open Research Publisher An entity responsible for making the resource available Wellcome Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Science, Medicine https://www.socictopen.socict.org/files/original/1b77466afa118a592f61c48d8017e16d.pdf 7f23c61382fa5b6756595e88bd10ca7d Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Coronavirus Description An account of the resource Dominio científico: Coronavirus Text A resource consisting primarily of words for reading. Examples include books, letters, dissertations, poems, newspapers, articles, archives of mailing lists. Note that facsimiles or images of texts are still of the genre Text. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Using CPAP in COVID-19 patients outside of the intensive care setting: a comparison of survival and outcomes between dialysis and non-dialysis dependent patients Creator An entity primarily responsible for making the resource Lauren Floyd, Madelena Stauss, Joshua Storrar, Parthvi Vanalia, Anna France, Ajay Dhaygude Description An account of the resource Abstract Background SARS-CoV-2 (COVID-19) is a novel coronavirus associated with high mortality rates. The use of Continuous Positive Airway Pressure (CPAP) has been recognised as a management option for severe COVID-19 (NHS, Specialty guides for patient management during the coronavirus pandemic Guidance for the role and use of non-invasive respiratory support in adult patients with coronavirus (confirmed or suspected), https://www.nice.org.uk/guidance/ng159 ). We offered ward-based CPAP to COVID-19, dialysis patients not suitable for escalation to ICU. The aim of the study was to evaluate the use of CPAP for COVID-19 dialysis patients compared to non-dialysis COVID-19 patients outside of the intensive care setting. We further aimed to investigate factors associated with improved outcomes. Methods Data was collected from a single centre (Royal Preston Hospital, UK), from March to June 2020. Treatment outcomes were compared for dialysis and non-dialysis dependent patients who received CPAP with limitations on their escalation and resuscitation status. Kaplan-Meier survival curves and Cox regression models were used to compare outcomes. The primary study outcome was 30 day mortality. Confounders including length of admission, systemic anticoagulation and ultrafiltration volumes on dialysis were also analysed. Results Over the study period, 40 dialysis patients tested positive for COVID-19, with 30 requiring hospital admission. 93% (n = 28) required supplementary oxygen and 12% (n = 9) required CPAP on the ward. These patients were compared to a serial selection of 14 non-dialysis patients treated with CPAP during the same period. Results showed a significant difference in 30 day survival rates between the two groups: 88.9% in the dialysis group vs. 21.4% in the non-dialysis group. Statistical modelling showed that anticoagulation was also an important factor and correlated with better outcomes. Conclusion This is to the best of our knowledge, the largest series of COVID-19 dialysis patients treated with CPAP in a ward-based setting. In general, dialysis dependent patients have multiple co-morbidities including cardiovascular disease and diabetes mellitus making them vulnerable to COVID-19 and not always suitable for treatment in ICU. We showed a significantly lower 30 day mortality rate with the use of CPAP in the dialysis group (11.1%) compared to the non-dialysis group (78.6%). Despite a small sample size, we believe this study provides impetus for further work clarifying the role of CPAP in treating COVID-19 dialysis dependent patients. Date A point or period of time associated with an event in the lifecycle of the resource 2021 Subject The topic of the resource covid-19, Anti coagulation, dialysis, CPAP Identifier An unambiguous reference to the resource within a given context 10.1186/s12882-021-02341-x Source A related resource from which the described resource is derived Epidemiology and Health Publisher An entity responsible for making the resource available Korean Society of Epidemiology Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Diseases of the genitourinary system. Urology https://www.socictopen.socict.org/files/original/df0f13004a9983f9cd1dd4b34449e890.pdf 5b37252216b3070ec875f05828fd39fb Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Coronavirus Description An account of the resource Dominio científico: Coronavirus Text A resource consisting primarily of words for reading. Examples include books, letters, dissertations, poems, newspapers, articles, archives of mailing lists. Note that facsimiles or images of texts are still of the genre Text. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Using Digital Data to Protect and Promote the Most Vulnerable in the Fight Against COVID-19 Creator An entity primarily responsible for making the resource Rumi Chunara, Stephanie H. Cook Date A point or period of time associated with an event in the lifecycle of the resource 2020 Subject The topic of the resource Public Health, digital, Data, disparities, COVID-19 Identifier An unambiguous reference to the resource within a given context DOI: 10.3389/fpubh.2020.00296 Source A related resource from which the described resource is derived Frontiers in Public Health Publisher An entity responsible for making the resource available Frontiers Media S.A. Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Public aspects of medicine https://www.socictopen.socict.org/files/original/7816d0a3c6e27d9b442a84bd08e5ddcf.pdf bae264c2a8c78da66535bb6b0c11df2b Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Coronavirus Description An account of the resource Dominio científico: Coronavirus Text A resource consisting primarily of words for reading. Examples include books, letters, dissertations, poems, newspapers, articles, archives of mailing lists. Note that facsimiles or images of texts are still of the genre Text. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Using digital technologies to create equal opportunities in higher education in the Russian Federation: COVID-2019 lessons Creator An entity primarily responsible for making the resource Kozyreva Anna, Nadtoka Ruslan Description An account of the resource The article examines the experience of higher education educational organizations of the Russian Federation in the development and implementation of digital tools and services to form equal access to educational content. The Anti-Crisis Measures adopted by the Ministry of Science and Higher Education of the Russian Federation to regulate the higher education sector are being evaluated to ensure that education is accessible and that the learning process is stopped during the COVID-19 pandemic.Over the past few months, studies in higher education on the quality of digital solutions used and their adequacy during the spread of the pandemic of the new COVID-2019 coronavirus infection and the transition mainly to remote forms of educational services show a low degree of readiness to provide equal access to education and reflect the risks of social conflict. It is important to ensure the digital readiness of higher education organizations to provide quality educational services through the introduction of advanced domestic programs and technologies, including those with elements of artificial intelligence; training of teachers and the administrative staff of educational institutions. Particular attention is paid to ensuring access to education in the subjects of the Russian Federation, where students and entrants face difficulties in remotely studying national languages and national culture. The study proposes to consider, among other things, support for the creation and implementation of online educational courses in the languages of national minorities, the expansion of e-library services containing unique cultural and language content, taking into account the specifics of the region’s learners. Date A point or period of time associated with an event in the lifecycle of the resource 2020 Identifier An unambiguous reference to the resource within a given context 10.1051/e3sconf/202020809035 Source A related resource from which the described resource is derived Epidemiology and Health Publisher An entity responsible for making the resource available Korean Society of Epidemiology Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Environmental sciences