Daily Updates Research Articles

Information to the Population About COVID-19 in the First Year of the Pandemic: Case Study on the Portal of the Health Department of Campina Grande, Paraíba, Brazil

Objective: To analyze the risk communication about the COVID-19 pandemic carried out on the website of the Health Department of Campina Grande, Paraíba, Brazil. Theoretical Framework: Risk communication in public health emergencies, according to the WHO guideline for policy and practice of this health communication in crises. Method: Qualitative study, focused on the content analysis of the publications made on the website of the Health Department of Campina Grande, Paraíba, from March 2020 to December 2021. Results and Discussion: The Health Department of Campina Grande, Paraíba, effectively used its website to disseminate information about the COVID-19 pandemic, such as social isolation measures and partial lockdown in areas with a high incidence of cases; sanitary barriers to monitor symptoms and control circulation; the installation of a field hospital, expansion of testing in Basic Health Units and distribution of masks and hygiene kits in vulnerable areas. The most frequent words on the portal in 2022 were “pandemic”, “mask” and “coronavirus”, in daily updates, guidelines on prevention measures, service protocols, decrees and restrictions, education and awareness and vaccination campaign at the end of the year. Research Implications: There was publication of accurate and accessible information, publication of administrative acts, positive culture in public health and, therefore, these actions demonstrate a significant effort by the Campina Grande Health Department to use digital communication to face the COVID-19 pandemic in accordance with the UN guideline. However, it was observed that in terms of clarity, some messages used technical terms that may have made it difficult for less educated audiences to understand. The portal did not provide accessible versions for people with visual impairments. Originality/Value: This study contributes to demonstrating that during the pandemic, the Campina Grande Health Department portal was an essential tool for residents of Campina Grande-PB in a practical and accessible way, with constant updates, disseminating information on the progress of the disease, vaccination campaigns and preventive measures, such as the use of masks and social distancing, with potential contribution to the implementation of preventive measures and adherence to vaccination. It is suggested that there could be greater accessibility for people with less education and sensory disabilities.

AIGD-PFT: the first AI-driven global daily gap-free 4 km phytoplankton functional type data product from 1998 to 2023

Abstract. Long time series of spatiotemporally continuous phytoplankton functional type (PFT) data are essential for understanding marine ecosystems and global biogeochemical cycles as well as for effective marine management. In this study, we integrated artificial intelligence (AI) technology with multisource marine big data to develop a spatial–temporal–ecological ensemble model based on deep learning (STEE-DL). This model generated the first AI-driven global daily gap-free 4 km PFT chlorophyll a concentration product from 1998 to 2023 (AIGD-PFT). The AIGD-PFT significantly enhances the accuracy and spatiotemporal coverage of quantifying eight major PFTs: diatoms, dinoflagellates, haptophytes, pelagophytes, cryptophytes, green algae, prokaryotes, and Prochlorococcus. The model input encompasses (1) physical oceanographic, biogeochemical, and spatiotemporal information and (2) ocean colour data (OC-CCI v6.0) that have been gap-filled using a discrete cosine transform–penalized least squares (DCT-PLS) approach. The STEE-DL model utilizes an ensemble strategy with 100 residual neural network (ResNet) models, applying Monte Carlo and bootstrapping methods to estimate the optimal PFT chlorophyll a concentration and assess the model uncertainty through ensemble means and standard deviations. The model's performance was validated using multiple cross-validation strategies – random, spatial-block, and temporal-block methods – combined with in situ data, demonstrating STEE-DL's robustness and generalization capability. The daily updates and seamless nature of the AIGD-PFT data product capture the complex dynamics of coastal regions effectively. Finally, through a comparative analysis using a triple-collocation analysis (TCA) approach, the competitive advantages of the AIGD-PFT data product over existing products were validated. The complete product dataset (1998–2023) can be freely downloaded from https://doi.org/10.11888/RemoteSen.tpdc.301164 (Zhang and Shen, 2024a).

NICU Caregiver Communication Preferences and Disparities by Primary Language: A Qualitative Study.

Effective communication between clinical providers and infant caregivers is vital to family-centered care and engagement in the NICU. Infants in the level IV NICU often have complex medical needs and prolonged lengths of stay, leading to challenges maintaining effective and consistent communication, particularly for families with a primary language other than English. The objective of this qualitative study is to determine the facilitators and barriers to effective communication among English- and Spanish-speaking caregivers in a level IV NICU. This phenomenology qualitative study consisted of interviews with English- or Spanish-speaking caregivers of infants admitted to a single-site level IV NICU for at least 7 days. Interviews were conducted using a semistructured interview guide that sought to understand the lived experience of parents communicating with providers. Themes from coded interview transcripts were identified using inductive thematic analysis. Nineteen interviews were completed in participants' primary language (English or Spanish), and 5 themes emerged from the analysis. For English- and Spanish-speaking caregivers, we discovered the importance of personal connection, the desire for receiving communication about changes directly from providers, and a strong desire for daily updates. For Spanish-speaking families, we found disparities in the use of communication-related technology and consistent communication from providers in their primary language. In this qualitative study, we identified caregiver preferences for communication from providers in a level IV NICU and demonstrated disparate experiences for Spanish-speaking caregivers. Future work should focus on developing interventions that address these identified barriers to communication.

Leveraging the use of a social media app as a collaborative medical information and knowledge sharing tool—insights from experiential use and survey of a CME WhatsApp community

Background and aimContinuing Medical Education (CME) is crucial for physicians to stay current in the rapidly advancing field of medicine. A WhatsApp (WA) based community of physicians was initiated in 2016 ‘WhatsApp CME India Group’ to facilitate learning, knowledge sharing, and discussion among physicians. Due to participant size constraints of the technology, it evolved into seven distinct WA groups, overseen by a central administrator. A survey undertaken in the group’s 7th year aimed to evaluate its effectiveness in achieving its goals, measure participant engagement, and uncover the primary factors driving its usage.MethodsThe survey questionnaire was distributed to 3500 members across the 07 WhatsApp CME groups for voluntary participation. Data collected was analysed using SPSS version 24.0 (SPSS Inc., Chicago, IL, USA) and reported using descriptive statistics.ResultsAmong the 581 survey respondents, the study found 43% of physicians use the WhatsApp academic groups for CME content, with 32% accessing their group over four times daily. The primary motivation for 77% was to discuss challenging cases and to gain knowledge updates from fellow physician (70%). Medical websites (57%), referral books (49%), and Google (43%) were other significant resources. Every participant (100%) found the WhatsApp CME India group the most beneficial resource for daily medical science updates. A significant portion (57%) of the respondents found the group valuable for real-time information exchange. Over 78% stated it kept them current with knowledge and guidelines. Notably, 94% viewed WhatsApp CME as complementary to physical conferences, not a replacement. The post-conference/webinar summaries were appreciated by 81% participants. Case discussions (31%) and update posts from fellow physicians sharing their insights and learnings (24%) were noted as activities of great academic interest.ConclusionThis study underscores the potential of digital platforms like WhatsApp in supplementing CME in India and potentially other comparable settings. The blend of digital and traditional resources suggests a balanced learning approach. While real-time engagement is a strength, challenges like information overload and privacy concerns require careful management. Striking a balance is crucial for ensuring content quality, structured discussions and privacy. As the digital age advances, professionals must critically assess shared information on these platforms to guarantee evidence-based and reliable knowledge dissemination.Trial registrationARK 001.

Unit-based Pathways to Reduce InequitieS for familiEs speaking languages other than English (UPRISE).

Health care inequities are common among individuals who speak languages other than English (LOE). Within our PICU, LOE families prefer communication via in-person interpreters (IPI). Spanish-speaking patient families are our largest LOE population; therefore, we sought to increase Spanish IPI utilization for medical updates in the PICU. A quality improvement initiative in a 36-bed PICU included: the addition of a dedicated weekday Spanish-speaking IPI, the creation of communication tools, staff education, optimized identification of LOE families, and development of a language dashboard across multiple Plan, Do, Study, Act cycles. The primary outcome was IPI utilization rates for daily medical updates. Spanish IPI utilization for daily weekday medical updates among 442 Spanish-speaking patient families increased from a median of 39.4% at baseline to a new centerline median of 51.9% during implementation, exhibiting 66.3% (465 of 701) utilization in the final 6 months of implementation. The greatest sustained increases in Spanish IPI utilization occurred after PICU-based IPI implementation, staff education, electronic health record optimization, and a split work week between 2 PICU-based IPIs. This quality improvement initiative increased Spanish IPI utilization for daily weekday medical updates in the PICU across multiple Plan, Do, Study, Act cycles. Future work will adapt these interventions to other languages and other hospital-based units.

Analisis Manajemen Risiko Produk Pembiayaan Multijasa Pada PT. Bank Tabungan Negara Syariah

This research discusses the risk management analysis carried out by PT. Sharia State Savings Bank towards multi-service financing products. The method used in this study is descriptive qualitative, the data collected in this study is in the form of words, sentences or images that describe the actual situation. The author collects data through observation, interviews, and documentation to facilitate the research process. The results showed that the risks faced by PT. Sharia State Savings Bank towards multi-service financing, namely financing risks and operational risks. The application of risk management carried out by PT. Sharia State Savings Bank is by conducting an identification process by looking at 5C (Character, Capacity, Capital, Collateral, Condition Of Economy), measuring by looking at the NPF value every month, monitoring by providing daily report updates, as well as controlling with several collection processes, visits, saving financing using Reconditioning and Rescheduling, as well as conducting collateral auctions. Pt. Sharia State Savings Bank has carried out risk management of multi-service financing properly and in accordance with PBI No. 13/23/PBI/2011 concerning the Application of Risk Management for Sharia Commercial Banks and Sharia Business Units, namely a series of procedures and methodologies used to identify, measure, monitor, and control risks that arise.

Caregiver Satisfaction with Medical Providers' Communication: Comparison Between Spanish-Speaking Caregivers with Limited English Proficiency (LEP) and Caregivers Who Are English-Proficient (EP).

Barriers to communication have been observed with patients and families who prefer a language other than English for medical conversations, referred to as individuals with limited English proficiency (LEP). We used the pediatric Family Satisfaction with ICU 24R (FS-ICU) survey to assess communication satisfaction for English-proficient (EP) and Spanish-speaking LEP caregivers. We added additional questions related to attendance at morning rounds, frequency of provider updates, interpreter use, and general satisfaction with communication. This was a single-center, prospective, observational cohort study in the pediatric intensive care unit (PICU) and cardiothoracic intensive care unit (CICU) of a tertiary, academic, free-standing children's hospital. Caregivers of children < 18 years old admitted for at least 48 h to the PICU or CICU between June and September 2022 were eligible for enrollment. 24LEP and 74 EP caregivers completed the survey questions. The LEP group had lower household income and education levels and higher incidence of public insurance. FS-ICU scores for both LEP and EP caregivers suggested high satisfaction, without significant difference between the groups. However, qualitative analysis revealed dissatisfaction for LEP caregivers related to information, inclusion, and language barriers. EP caregivers had more positive references to information and emotional connection but indicated dissatisfaction around consistency and responsiveness. 18%of LEP caregivers reported regularly attending rounds, versus 67% of the EP group (p value < .001). 39% ofLEP versus 52% of EP caregivers reported multiple daily updates, although the difference was not statistically significant. 29% of LEP respondents reported nonfluent MD/NPs using an interpreter never, rarely, or some of the time. There was no difference in satisfaction scores between LEP and EP caregivers. LEP caregivers had lower socioeconomic status based on public insurance and reported income and education level. Qualitative data allowed more nuanced understanding of communication satisfaction, which correlated with LEP caregivers' reported lower attendance at morning rounds, inconsistent interpreter use, and a trend toward less frequent provider updates.

Humanism during the COVID-19 pandemic: video call as a strategy to satisfy the communication needs of Intensive Care Unit patients and their family members.

Background: Patients affected by the COVID-19 pandemic required physical/social isolation due to the transmissibility of SARs CoV-2; those hospitalized in healthcare facilities often suffered loneliness due to a complete separation from their loved ones through visitor restrictions.(1) Human contact and movement were restricted to contain the spread of disease. When this kind of restriction must be employed, the “Guidance for Managing Ethical Issues in Infectious Disease Outbreaks”, states that it is necessary to provide people with “effective alternative communication strategies”. (2) Methods: This is an observational descriptive study that uses qualitative variables to analyze information obtained by virtual focus groups consisting of either medical professionals or family members of hospitalized patients in the ICU of the Eugenio Espejo Hospital (EEH) in Quito, Ecuador. Each video call allowed us to assess anonymous opinions concerning communication methods utilized during the delivery of daily clinical updates in the ICU. By focusing on a patient-and family-centered model, this study aims to minimize the impact of social isolation in hospitalized patients through the implementation of regular doctor-led video conference calls with family members, as well as video calls between the patient and family members when feasible.(1) Results: This study evaluates the increased satisfaction of family members and medical professionals with the implementation of video calls when compared to traditional telephone calls. A contrast between the time before implementing the telehealth team and the time afterward was observed in at least five positive characteristics: 1) the general telehealth experience, 2) the clarity of the messages, 3) the quality of care, 4) the sense of comfort, and 5) the improvement of communication. Conclusions: There was a positive effect on communication quality for both family members and medical professionals, increasing their satisfaction in terms of finding new methods to reduce the social isolation enforced by the current pandemic. Nevertheless, the future role of virtual communication remains undefined as we return to individualized face-to-face meetings.

The Influence of Time-Varying Sea Ice Concentration on Antarctic and Southern Ocean Numerical Weather Prediction

Abstract Although operational weather forecasting centers are increasingly using global coupled atmosphere–ocean–ice models to replace atmosphere-only models for short- and medium-range (10 day) weather forecasting, the influence of sea ice on such forecasting has yet to be fully quantified, especially in the Southern Ocean. To address this gap, a polar-specific version of the Weather Research and Forecasting Model is implemented with a circumpolar Antarctic domain to investigate the impact of daily updates of sea ice concentration on short- and medium- range weather forecasting. A statistically significant improvement in near-surface atmospheric temperature and humidity is shown from +24 to +192 h when updating the daily sea ice concentration in the model. The forecast skill improvements for 2-m temperature and dewpoint temperature are enhanced from June to September, which is the period of late sea ice advance. Regionally, model improvement is shown to occur in most sea ice regions, although the improvement is strongest in the Ross Sea and Weddell Sea sectors. The surface heat budget also shows remarkable improvement in outgoing radiative heat fluxes and both sensible and latent heat fluxes. This idealized research demonstrates the nonnegligible effect of including more accurate time-varying sea ice concentration in numerical weather forecasting. Significance Statement The purpose of this study is to understand how a more realistic Antarctic sea ice field may influence the skill of short- and medium-range weather forecasts. Many operational atmospheric numerical weather prediction (NWP) models use a static forecast field through the time frame of the model’s forecast—often 3–10 days. In this study, we updated the sea ice concentration field daily and compared the forecast outcomes with those from model runs using a static sea ice concentration field. We found the forecast skill of near-surface temperature and humidity show the most significant improvements in our idealized experiments. This indicates the importance of incorporating improved dynamic sea ice representation in Antarctic short- to medium-range operational weather forecasting.

Style and language of television news on the Iraqi issue on TRT and RT

Interest in mass media discourse has increased significantly in recent decades, which is confirmed by numerous studies that are aimed at studying the features of the language and style used on news channels, the manifestation of the manipulative function, the rhetoric of the sender of the communication message and the reaction of recipients. TRT and RT are major international news channels. Having a similar mission (24-hour daily updates of news from politics, business, finance, sports, science, culture...), these TV channels actively use modern digital technologies in their activities, which allows them to take leading positions in the rankings in their niche. Already at the end of the twentieth century, there was a regular change in the forms of speech styles of communication due to the development of communication and other technologies. The information revolution and the subsequent technological development gave a new impetus to the journalistic profession, bringing it to a completely new level of the digital space. Research methods used in the article: systematization, generalization, critical analysis, discourse analysis, stylistic analysis, pragmatic analysis. Television which occupies an important place among the media due to its wide coverage acted as the subject of our consideration. The authors identified a common feature among many researchers of the language and style of television news - anxiety about their ambiguous influence on the broad masses of the population, as J. Bloomer talks about. This concern stems from concerns about the power of the media to influence modern democratic societies, the protection of various freedoms, and the dangers of propaganda tools and information manipulation.

Harnessing Twitter: Sentiment Analysis for Predicting Election Outcomes in India

This paper explores the potential of Twitter, a popular social media platform, as a tool for predicting election outcomes. Sentiment analysis has emerged as a powerful tool for predicting election outcomes, with numerous studies showcasing its effectiveness in various countries. For instance, research has utilized sentiment analysis to forecast election results in nations like the USA, India, Pakistan and other countries, demonstrating the utility of social media data in gauging public opinion and predicting electoral results [1]. Elections in India are always considered important events that most people look forward to the rapid growth of social media in the past has provided end users with powerful tools to share their ideas. Twitter, which is one such platform, provides daily updates on political events through various hashtags and trends. People react to political events and give their opinions. Our approach is to collect tweets from top political parties contesting the Gujarat Assembly Elections 2022, and then calculate sentiment scores. The database includes a variety of recent and well-liked tweets about a specific political party. Party tweets are generated with specific keywords like “BJP”, “AAP”,“Congress” and so on. In the context of India, Twitter sentiment analysis tools and classification have been used to predict the outcomes of state assembly elections, underscoring the potential of social media data in forecasting electoral results within the country [2]. We used standard machine learning algorithms like VADER sentiment analyzer on Random Forest and Decision Tree for our classification and testing data to classify tweets as positive and negative. As a result, this work uses sentiment analysis to evaluate tweets gathered from Twitter and forecast election outcomes. This work shows the growing influence of social media on politics and the feasibility of using such platforms for predictive analysis. The findings of this study could provide valuable insights for political parties, policymakers, and researchers interested in the intersection of social media and politics. Random Forest and Decision Tree models performed well in predicting election outcomes based on sentiment analysis on Twitter data with 89% and 86% respectively.

In-Hospital Code Status Updates: Trends Over Time and the Impact of COVID-19.

The primary objective was to evaluate if the percentage of patients with missing or inaccurate code status documentation at a Trauma Level 1 hospital could be reduced through daily updates. The secondary objective was to examine if patient preferences for DNR changed during the COVID-19 pandemic. This retrospective study, spanning March 2019 to December 2022, compared the code status in ICU and ED patients drawn from two data sets. The first was based on historical electronic medical records (EHR), and the second involved daily updates of code status following patient admission. Implementing daily updates upon admission was more effective in ICUs than in the ED in reducing missing code status documentation. Around 20% of patients without a specific code status chose DNR under the new system. During COVID-19, a decrease in ICU patients choosing DNR and an increase in full code (FC) choices were observed. This study highlights the importance of regular updates and discussions regarding code status to enhance patient care and resource allocation in ICU and ED settings. The COVID-19 pandemic's influence on shifting patient preferences towards full code status underscores the need for adaptable documentation practices. Emphasizing patient education about DNR implications and benefits is key to supporting informed decisions that reflect individual health contexts and values. This approach will help balance the considerations for DNR and full code choices, especially during health care crises.

Ultra-short-term forecasting of agricultural intelligent greenhouse power load based on ISDS and MDUS-LSTM

The agricultural smart greenhouse electric load differs significantly from the traditional building electric load. It is more susceptible to the influence of meteorological conditions, featuring poor regularity and significant random fluctuations, so load forecasting faces new challenges. To address this challenge, this paper focuses on a variety of meteorological and historical similar feature extraction, innovates model updating strategies, and proposes a new ultra-short-term forecasting method for agricultural smart greenhouse electric loads. Firstly, an improved similar day selection (ISDS) method is designed. This method considers both trend similarity and magnitude similarity of time series. It sets weights according to the degree of influence of different meteorological features on load, thus improving the learning efficiency of the model. Next, a model dynamic update strategy (MDUS) is designed. This strategy consists of initial training of forecasting model parameters based on historical similar daily loads and online updating of forecasting model parameters based on adjacent daily load data. Then, the forecasting model is trained online and fine-tuned with the parameters based on the adjacent daily load data. The dynamically updated forecasting model is used to achieve ultra-short-term forecasting of the electric load to improve the forecasting accuracy and adaptability of the model. Finally, the effectiveness of the proposed method is verified by actual electrical load data, real-time meteorological data, and NWP data collected in an agricultural smart greenhouse in Shouguang, China.

The role of digital surveillance during outbreaks: the Ghana experience from COVID-19 response.

Over the years, Ghana has made notable strides in adopting digital approaches to address societal challenges and meet demands. While the health sector, particularly the disease surveillance structure, has embraced digitization to enhance case detection, reporting, analysis, and information dissemination, critical aspects remain to be addressed. Although the Integrated Disease Surveillance and Response (IDSR) structure has experienced remarkable growth in digitization, certain areas require further attention as was observed during the COVID-19 pandemic. Ghana during the COVID-19 pandemic, recognized the importance of leveraging digital technologies to bolster the public health response. To this end, Ghana implemented various digital surveillance tools to combat the pandemic. These included the 'Surveillance Outbreak Response Management and Analysis System (SORMAS)', the digitalized health declaration form, ArcGIS Survey123, Talkwalker, 'Lightwave Health information Management System' (LHIMS), and the 'District Health Information Management System (DHIMS)'. These digital systems significantly contributed to the country's success in responding to the COVID-19 pandemic. One key area where digital systems have proved invaluable is in the timely production of daily COVID-19 situational updates. This task would have been arduous and delayed if reliant solely on paper-based forms, which hinder efficient reporting to other levels within the health system. By adopting these digital systems, Ghana has been able to overcome such challenges and provide up-to-date information for making informed public health decisions. This paper attempts to provide an extensive description of the digital systems currently employed to enhance Ghana's paper-based disease surveillance system in the context of its response to COVID-19. The article explores the strengths and challenges or limitations associated with these digital systems for responding to outbreaks, offering valuable lessons that can be learned from their implementation.

Evolution of Scientific Production on Phlebitis Secondary to Vascular Access: A 71-Year Bibliometric Analysis.

Phlebitis secondary to vascular access is one of the most frequent complications in hospital care. This study aims to evaluate the scientific activity related to this complication through a bibliometric analysis. The search was performed on a single day, 23 January 2023, to ensure the inclusion of all articles and to avoid bias caused by the daily updates of the open access database. The data were recovered from Web of Science. The sample comprised a total of 1596 publications that met the inclusion criteria. The United States was the country with the largest number of publications, citations, and international cooperation with respect to phlebitis and vascular access. The most important author was Rickard CM. Of all the publications selected, a total of 1586 (99.37%) were original articles. The highest number of articles on the subject was recorded in 2021, and the most common research areas were General Internal Medicine and Nursing. The analysis of the clusters (KeyWords Plus and Author keywords) and co-occurrences enabled identification of areas of interest and their possible development. These areas included the prevention, risk, and associated complications of catheter-associated phlebitis. Other aspects that are a priori relevant, such as assessment and treatment, were found to be little investigated. While research on this subject is increasing internationally, more collaborations are still required between researchers, as well as new approaches related to the management of catheter-associated phlebitis. The dimensions that should continue to be considered in new research, according to the findings of this review, are instruments for phlebitis assessment and their validation, and the treatments to follow in the case of established phlebitis. For this reason, the bibliometric information presented is key for new or consolidated researchers in the field, especially because of its practical and clinical implications for patient safety.

Situation report (SITREP) visualization for effective management of disaster incidents in Sri Lanka

During and after any disaster, a situation report (SITREP) is prepared, based on the Daily Incident Updates (DIU), as an initial decision support information base. It is observed that the decision support system and best practices are not optimized through the available formal reporting on disaster incidents. The rapidly evolving situation, misunderstood terms, inaccurate data and delivery delays of DIU are challenges to the daily SITREP. Multiple stakeholders stipulated with different tasks should be properly understood for the SITREP to initiate relevant response tasks. To fill this research gap, this paper identifies the weaknesses of the current practice and discusses the upgrading of the incident-reporting process using a freely available software tool, enabling further visualization, and producing a comprehensive timely output to share among the stakeholders. In this case, “Power-BI” (a data visualization software) is used as a 360-degree view of useful metrics—in a single place, with real-time updates while being available on all devices for operational decision-making. When a dataset is transformed into several analytical reports and dashboards, it can be easily shared with the target users and action groups. This article analyzed two sources of data, namely the Disaster Management Center (DMC) and the National Disaster Relief Service Center (NDRSC) of Sri Lanka. Senior managers of disaster emergencies were interviewed and explored social media to develop a scheme of best practices for disaster reporting, starting from just before the occurrence, and following the unfolding sequence of the disasters. Using a variety of remotely acquired imageries, rapid mapping, grading, and delineating impacts of natural disasters, were made available to concerned users.

RCoV19: A One-stop Hub for SARS-CoV-2 Genome Data Integration, Variant Monitoring, and Risk Pre-warning

The Resource for Coronavirus 2019 (RCoV19) is an open-access information resource dedicated to providing valuable data on the genomes, mutations, and variants of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). In this updated implementation of RCoV19, we have made significant improvements and advancements over the previous version. Firstly, we have implemented a highly refined genome data curation model. This model now features an automated integration pipeline and optimized curation rules, enabling efficient daily updates of data in RCoV19. Secondly, we have developed a global and regional lineage evolution monitoring platform, alongside an outbreak risk pre-warning system. These additions provide a comprehensive understanding of SARS-CoV-2 evolution and transmission patterns, enabling better preparedness and response strategies. Thirdly, we have developed a powerful interactive mutation spectrum comparison module. This module allows users to compare and analyze mutation patterns, assisting in the detection of potential new lineages. Furthermore, we have incorporated a comprehensive knowledgebase on mutation effects. This knowledgebase serves as a valuable resource for retrieving information on the functional implications of specific mutations. In summary, RCoV19 serves as a vital scientific resource, providing access to valuable data, relevant information, and technical support in the global fight against COVID-19. The complete contents of RCoV19 are available to the public at https://ngdc.cncb.ac.cn/ncov/.

Empiric antimicrobial therapy in the intensive care unit based on the risk of multidrug-resistant bacterial infection: a single-centre case‒control study of blood culture results in Japan

BackgroundInfections and sepsis are the leading causes of death in intensive care units (ICUs). Antimicrobial agent selection is challenging because the intervention is directly related to the outcome, and the problem of antimicrobial resistance (AMR) must be considered. Therefore, in this study, we aimed to clarify the epidemiological data and examine whether the detection rate of multidrug-resistant (MDR) bacteria differed depending on the presence or absence of the risk of MDR bacterial infections to establish guidance regarding the choice of antimicrobial therapy for ICU patients.MethodsThis retrospective case‒control study was performed in a single ICU in Japan. Patients admitted to the ICU who underwent blood culture (BC) analysis were considered for inclusion in this study; patients were at risk of MDR bacterial infections, and controls were not. The primary outcome measure was the detection rate of MDR bacteria in BCs collected from patients and controls. The secondary outcome measure was the selection rate of anti-Pseudomonas and anti-methicillin-resistant Staphylococcus aureus (MRSA) drugs for patients and controls.ResultsAmong the 1,730 patients admitted to the ICU during the study period, BCs were obtained from 186 patients, and 173 samples were finally included in the analysis (n = 129 cases; n = 44 controls). No MDR bacteria or Pseudomonas aeruginosa were detected in the controls (14 (11%) vs. 0 (0%)) (P = 0.014) However, there was no difference in empiric antimicrobials, including anti-MRSA (30 (23%) vs. 12 (27%)) (P = 0.592) and anti-Pseudomonas aeruginosa (61 (47%) vs. 16 (36%)) (P = 0.208) drugs, that were administered to the two groups.ConclusionsEven in critically ill patients in the ICU, MDR bacteria are unlikely to be detected in patients without the risk of MDR bacterial infections. Therefore, for such patients, a strategy of starting empiric narrow-spectrum antimicrobial therapy rather than empiric broad-spectrum therapy should be considered. This strategy, in conjunction with daily updates of clinical and epidemiological data at each facility, will promote the appropriate use of antimicrobials and reduce the emergence of MDR bacteria in the ICU.Trial registration: None.

An Extract-Transform-Load Process Design for the Incremental Loading of German Real-World Data Based on FHIR and OMOP CDM: Algorithm Development and Validation.

In the Medical Informatics in Research and Care in University Medicine (MIRACUM) consortium, an IT-based clinical trial recruitment support system was developed based on the Observational Medical Outcomes Partnership (OMOP) Common Data Model (CDM). Currently, OMOP CDM is populated with German Fast Healthcare Interoperability Resources (FHIR) using an Extract-Transform-Load (ETL) process, which was designed as a bulk load. However, the computational effort that comes with an everyday full load is not efficient for daily recruitment. The aim of this study is to extend our existing ETL process with the option of incremental loading to efficiently support daily updated data. Based on our existing bulk ETL process, we performed an analysis to determine the requirements of incremental loading. Furthermore, a literature review was conducted to identify adaptable approaches. Based on this, we implemented three methods to integrate incremental loading into our ETL process. Lastly, a test suite was defined to evaluate the incremental loading for data correctness and performance compared to bulk loading. The resulting ETL process supports bulk and incremental loading. Performance tests show that the incremental load took 87.5% less execution time than the bulk load (2.12 min compared to 17.07 min) related to changes of 1 day, while no data differences occurred in OMOP CDM. Since incremental loading is more efficient than a daily bulk load and both loading options result in the same amount of data, we recommend using bulk load for an initial load and switching to incremental load for daily updates. The resulting incremental ETL logic can be applied internationally since it is not restricted to German FHIR profiles.

Online News Displaces Print Newspaper: Media Students' Preferences and Perceptions

This study extends the uses and gratifications theory to explore the uses of general, time, daily, and weekly news. It also applies the theory of media displacement to investigate the ease, preference, emergency use, credibility perception, and confidence in forming opinions for news from print newspapers and online sources. A survey with 244 students from communication and media disciplines in Lahore's universities revealed that 68% of media students read news for only 30 minutes daily. 65% preferred daily updates and found it easier to access news online (62%). During emergencies, 79% relied on online news, but only 52% considered it authentic. Despite concerns about tree wastage, 67% favoured free access to online news, with only 33% willing to purchase print newspapers. This study supports the media displacement hypothesis, suggesting that online news is displacing print newspapers due to affordability, posing significant implications for newspaper management.