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1226 articles on privacy and COVID-19 were published by authors from 69 countries in this year's issue. COVID 19's privacy is now the focus of many researchers' attention. The present body of knowledge on privacy for COVID-19 digital technologies has been thoroughly analyzed, and a concise overview of research status and future developments can be gleaned. This paper conducted a bibliometric examination of privacy using the Scopus dataset. Utilizing VOSviewer software, the relevant literature papers published on this topic were examined to determine the field's development history, research hotspots, and future directions. Over time, there has been a rise in the number of studies published in privacy for COVID-19, particularly after 2020, and the growth rate has been steadily increasing. Regarding published research, the United States and China lead the pack. These articles appeared in primarily English-language journals and conference proceedings. Privacy and COVID-19 research was mostly computer science. The most used terms in privacy and COVID-19 were data privacy and humans. This paper examines the evolution of privacy and COVID-19 research and indicates current research priorities and future research goals. Furthermore, the privacy and COVID-19 study seem to be a promising sphere as this study identifies 26 domains. © 2023, Institute of Advanced Engineering and Science. All rights reserved.
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Background: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is responsible for global pandemic, and it has caused more than 2.3 million deaths. Persistence and stability of immunoglobulin G (IgG) response after recovery from COVID-19 infection is still uncertain. Method(s): We performed a longitudinal cohort study in healthcare workers (HCW) and their close contacts (Non-HCW) with known resolved SARS-CoV-2 infection and undiagnosed infection at Maulana Azad Medical College and associated Lok Nayak hospital, New Delhi. Baseline IgG antibody titers was determined and the participants were followed over a period of six months. We also examined relationship between SARS-CoV-2 immunoglobulin G (IgG) response and new symptomatic infection in HCW and Non-HCW over time. Result(s): 176 (70.9%) healthcare workers and 72 (29.0%) non-healthcare workers were recruited from two cohorts. 82 subjects recovered from SARS-CoV-2 infection and 166 undiagnosed for the infection having history of close contact with COVID-19 patients were followed up for a median of 227 days (interquartile range, 166 to 202) after a positive IgG antibody test. In the recovered subjects 70.7% (58) were seropositive for first anti-spike IgG assay at baseline, followed by 80.0%, 90.6% and 82.6% at three visits respectively. In undiagnosed subjects 37.3% (62) were seropositive at baseline, followed by 70.9%, 75.8% and 82.2% respectively. Also, 46.8% (29) were asymptomatic with no symptoms of COVID-19 and were seropositive at baseline. However, presence of IgG antibodies was associated with substantial reduced risk of re-infection over the follow up duration. Conclusion(s): Our data showed that the antibodies levels measured increased over the first three months and decreased slightly after that and remained at a plateau and relatively stable for at least a period of six months. Copyright © 2022 International Medical Sciences Academy. All rights reserved.
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Background: Andaman and Nicobar Islands, a Union Territory of India is Tropical Island, has better air quality and since its specific geographic location that may have an impact on the clinical and pathological features. So, this study is intended to describe the clinical and pathological features of COVID-19 infection and its association with the severity of the disease among adult COVID-19 patients. Material and Method: A cross-sectional study done retrospectively among 100 adult COVID-19 RT PCR positive in Tertiary Hospital, tropical Islands by reviewing medical records. The clinical, laboratory parameters were assessed.
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There are currently no guidelines regarding clinician decision making in the type of hip fracture management among older adults. Cultural, social, structural and economic differences between global healthcare systems may result in differing approaches. This study's objectives were to identify possible factors influencing clinicians' decision to undertake a non-operative hip fracture management approach among older adults, and to determine whether there is global heterogeneity regarding these factors between high income countries (HIC), and low- and middle-income countries (LMIC) clinicians. A SurveyMonkey questionnaire was distributed to clinicians through the Fragility Fracture Network's Perioperative Special Interest Group and clinicians' personal networks between May 24 and July 25, 2021. 406 respondents from 51 countries returned the questionnaire, of which 225 respondents came from HIC and 180 from LMIC. Clinicians from HIC reported a greater median [IQR] estimated proportion of admitted patients with hip fracture undergoing surgery (96% [95–99]) than those from LMIC (85% [75–95]) of mean (SD) at 94% (8) compared to 81% (16) among LMIC clinicians (p=2.94e-23). Several factors seemed to influence the clinician hip fracture management decision making process. Global heterogeneity seems to exist between HIC and LMIC clinicians regarding factors such as anticipated life expectancy, ability to pay, treatment costs, insufficient resources, and perception of risk in hip fracture management decision-making. This is the first international sampling of clinician perspectives regarding hip fracture management. Further research is necessary for the development of best practice guidelines to improve hip fracture management decision-making and quality of hip fracture care among older adults.
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COVID-19 has created a pandemic worldwide, paused the path of building the future, and is still ongoing without any long-term solution. The time taken in vaccine distribution is too slow compared to the spread of COVID-19. Hence, it is important to be aware and take precautions on time without delaying and waiting for long-duration after getting infected with the virus. Technology nowadays is more advanced than ever before. Almost everyone has access to at least one mobile device with internet connection. Therefore, we propose a Fog Server (FS) based system that helps create awareness about the spread of COVID-19 within the surroundings of an individual, utilizing the concept of Hidden Markov Model (HMM) and Bluetooth contact tracing in polynomial computational time complexity. Moreover, we evaluate the effectiveness of the proposed model through real-world data analysis on different simulation settings. © 2023 ACM.
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Background. Global genomic surveillance has allowed identification of SARS-CoV-2 circulating variants responsible for the COVID-19 pandemic. Statewide variant characterization can guide local public health mitigations and provide educational opportunities. We characterized statewide evolution of SARS-CoV-2 variants in Rhode Island (RI). Methods. De identified RI SARS-CoV-2 sequences since 2/2020, generated at authors, CDC and commercial laboratories, were extracted from https://www.gisaid. org. Genomic and phylogenetic analyses were conducted with available tools and custom python scripts and, after quality control, sequences were classified as variants of Concern (VOC), variants being monitored (VBM), or non-VOC/ non-VBM, per CDC definitions. Specific mutations that are characteristic of the most recent VOCs (Delta or Omicron) were explored outside of their designated lineages. Results. Of the 1.1 million RI population, 14,933 SARS-CoV-2 sequences were available between 2/2020 and 3/2022. These included 1,542 (11%) sequences from 37 non-VOC/non-VBM lineages until 2/2021, most commonly B.1.2 (21%), B.1.375 (13%), and B.1.517 (6%);2,910 (19%) sequences from 7VBM lineages between 3-6/2021, most commonly Alpha (48%), Iota (34%), and Gamma (10%);and 10,481 (70%) sequences from 2 VOC lineages, including 7,574 (72%) Delta mostly between 6/2021 and 12/2021, and 2,907 (28%) Omicron mostly between 1/2022 and 3/2022. Phylogeny showed expected clustering of local variants within regional and global sequences, and continued viral evolution over time. Further VOC evolution was observed, including 87 Delta sub-lineages, most commonly AY.103 (17%), AY.3 (15%), and AY.44 (12%);and 4 Omicron sub-lineages BA.1 (61%), BA.1.1 (32%), BA.2 (7%), and BA.3 (< 1%). Omicron-associated mutations S:del69/70, S:H655Y, or N: P13L were observed in 219 Delta sequences, and Delta-associated mutations ORF1b: G662S, N:D377Y, or M:I82T were observed in 16 Omicron sequences. Conclusion. Statewide SARS-CoV-2 genomic surveillance allows for continued characterization of locally circulating variants and monitoring of viral evolution. Such data guide public health policies, inform the local health force, and mitigate the impact of SARS-CoV-2 on public health.
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Background. SARS-CoV-2 seroprevalence studies can inform pandemic spread. By February 2021, estimates demonstrated 11%-62% seroprevalence in diverse Kenyan populations, with geographic variability and temporal increase, and well in excess of 0.2% laboratory-confirmed cases. The impact of HIV on seropositivity, particularly in youth living with HIV (YLWH) is unclear. Methods. During February to September 2021, before SARS-CoV-2 vaccination, we cross-sectionally enrolled perinatally-infected YLWH in western Kenya in four sites (Eldoret, tertiary referral center;urban Kitale, peri-urban Turbo, rural Webuye), and determined seropositivity using the Bio-Rad Platelia assay. Additional evaluations included HIV viral load (VL), CD4 and a COVID-19-focused survey. Multiple logistic regression was used to measure associations of seropositivity with age, gender, enrollment month, site, HIV treatment failure (VL > 1,000 copies/ml), and CD4 (>= 500 vs < 500 cells/muL). Results. Of 241 YLWH, 29% were seropositive, 68% seronegative and 4% equivocal. Temporal trends (linear relationship per subsequent enrollment month;Odds Ratio (OR) 1.29 [95% Confidence Interval (CI), 1.06-1.58], p=0.013) and geographic variability (Eldoret-25%, Kitale-20%, Turbo-25%, Webuye-56%;p=0.027) were observed. Presumptive or laboratory-confirmed COVID-19 diagnosis, hospitalization, or death were absent. Self-reported illness was similar among seropositives and seronegatives, and highest in Webuye. Seropositivity was significantly associated with being male (OR, 1.06 [95% CI, 0.57-1.98], p=0.848), and age 15-17 years vs < 15 (OR, 2.57 [95% CI, 1.16-5.93], p=0.023), not with VL or CD4. Among seropositives, aboverange titers were seen in 57%. Conclusion. Of 241 Kenyan YLWH, 29% were SARS-CoV-2 seropositive by August 2021, with geographical, temporal, and age differences, and most seropositives mounting a robust response. Increased prevalence in rural Webuye may reflect less widespread mask-wearing, or its location on a busy transit route. Speculations on why seropositivity is low compared to earlier estimations, like HIV status, failed seroconversion, waning immunity, perception of risk promoting adherence to mitigations, or exposure to research-related guidance, should be investigated.
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Background: Emergency departments (EDs) have experienced increased patient boarding even before the pandemic which has led to significant challenges for both patients and clinicians. The COVID pandemic has only exacerbated ED crowding despite reduced ED volumes nationally. ED boarding has been erroneously attributed to inefficient ED practices but is often largely the result of hospital and systemic inefficiencies. While ED boarding is not solely an ED problem, the financial impact of boarding on the ED can be significant and the cost of ED crowding is often largely borne by already overburdened EDs. Study Objectives: There were two primary objectives;1) To quantify the number of ED beds occupied by inpatient boarding patients, 2) To estimate the financial impact of boarding on the ED in a large, academic, safety-net hospital. Method(s): A retrospective, cohort review of all ED encounters from July 1, 2020, through June 30, 2021, were identified at our large, academic, safety-net trauma center. Performance metrics were retrieved from a novel, interactive, digital data dashboard at the Zuckerberg San Francisco General Hospital (ZSFGH) including average Length of Stay (LOS) and Total Boarding Minutes. Boarding was defined as time spent occupying an ED bed beyond 120 minutes after the admit disposition was determined as defined by the Agency for Healthcare Research and Quality (AHRQ). An estimate of total missed encounters due to ED boarding time was made and total potential charges and revenue were then estimated using an institutional average of estimated charges as well as average realized reimbursement rate. Result(s): There were a total of 54,612 encounters, of which 50,980 (93.3%) were included and 3,632 (6.7%) were excluded due to alternative dispositions, such as Absent Without Leave (AWOL), Left Without Being Seen (LWBS), Left Without Being Triaged (LWBT) and Nursing Referrals (RN Referrals). Included were 11,850 (23.2%) admissions and 39,130 (76.8%) discharges and transfers. Total annual boarders were 7,410 (62.5%) with a total of 3,782,670 boarding minutes. The mean LOS for our ED patients during this period was 395 minutes (753 for admissions and 288 for discharges and transfers) resulting in an estimate of potential missed encounters of 9,576. The institutional average charge for all-comers to the ED is $780. At 9,576 missed encounters, an estimate for potential lost charges was $7.47M and at an average reimbursement rate of 23%, potential revenue loss of $1.72M [Figure 1]. During the pre-pandemic period with available data (August 1, 2019 - February 29, 2020) when boarding and nurse staffing were not as limited, the daily census was 184.1 patients, excluding LWBS, LWBT, and RN Referrals. During the pandemic period with significant ED boarding and nursing staffing shortages, the daily census was 149.6. Including the potential daily missed encounters of 26.2 would result in a total potential daily census of 175.8. Thus, we assume there would be sufficient patient volume and demand to occupy all available ED beds if boarding were eliminated. Conclusion(s): ED boarding is due to systemic health care system failures but results in significant lost ED revenue further straining already over-burdened EDs. Improving hospital patient flow can improve ED patient flow and revenues both during and after the COVID pandemic. [Formula presented] Yes, authors have interests to disclose Disclosure: FujiFilm-SonoSite Consultant/Advisor FujiFilm-SonoSite Disclosure: Inflammatix Consultant/Advisor Inflammatix Copyright © 2022
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Background: Emergency departments (EDs) have experienced increases in patient boarding, which has resulted in significant challenges to providing quality care. The COVID pandemic has exacerbated ED crowding despite reduced ED volumes nationally, which is in part due to national ED nursing shortages. Nursing-specific operational inefficiencies can have detrimental financial consequences for the ED and hospitals. Study Objectives: There were two primary objectives: 1) To quantify the amount of ED beds unavailable due to nurse-staffing challenges 2) To estimate the financial impact of this reduced capacity on the ED. Method(s): A retrospective, cohort review of all ED encounters from January 1, 2021 - December 31, 2021, was identified at our large, academic, safety-net trauma center. Performance metrics were retrieved from a novel, interactive, digital data dashboard at the Zuckerberg San Francisco General Hospital (ZSFGH). Average daily staffed nursing beds were obtained during two key time points daily: 11am and 7pm from Q4- 2021 (October 1, 2021 - December 31, 2021) and extrapolated for the calendar year. Total unavailable ED bed minutes were determined based on nursing staffing as were total potential missed encounters due to unavailable ED beds. These were estimated using the average LOS for ED encounters. Average institutional ED charges and realized payments were then used to determine a financial estimate of the impact of the nursing shortage during Q4-2021 and annualized for 2021. We assume, based on pre-pandemic census data, that there is sufficient ED demand and volume to occupy all available ED beds. Result(s): The ZSFGH is a 59-bed ED that when maximally staffed has a weighted average of 56.25 beds daily, accounting for nighttime closures. During the review period, the average daily nursing-staffed beds during Q4-2021 were 47.7 (84.7%). From January 1, 2021 - December 31, 2021, there were 57,888 encounters of which 53,012 (91.6%) were included and 4,876 (8.4%) were excluded due to alternative dispositions such as Absent Without Leave (AWOL), Left Without Being Seen (LWBS), Left Without Being Triaged (LWBT) and Nursing Referrals (RN Referrals). The total unstaffed ED bed minutes was an estimated 4,511,400. The average LOS excluding AWOL, LWBS, LWBT, RN Referrals, and Against Medical Advice (AMA) during this time period was 411 minutes resulting in an estimated 10,977 potential missed encounters, an estimated $8.56M in lost potential charges, and $1.97M in potential lost revenue [Figure 1]. During the pre-pandemic period with available data (August 1, 2019 - February 29, 2020) when boarding and nursing staffing weren't as limited, the daily census was 184.1 patients, excluding LWBS, LWBT, and RN Referrals with an average LOS of 407 minutes for a total daily bedtime of 74,929 minutes for a utilization of 92.5%. During this period, the total daily census with LWBS, LWBT, and RN Referrals was 210.1 patients. These additional patients would account for another 10,582 bed minutes for a total bed utilization of 85,511 mins (105.6%). Conclusion(s): The COVID pandemic has resulted in increasing challenges for already strained EDs. Increasing national nursing shortages reduce operational performance and result in a significant financial loss to EDs. Greater attention to the financial consequences of nursing shortages on EDs may allow for improved resource allocation, capacity recovery, and financial performance. [Formula presented] Yes, authors have interests to disclose Disclosure: FujiFilm-SonoSite Consultant/Advisor FujiFilm-SonoSite Disclosure: Inflammatix Consultant/Advisor Inflammatix Copyright © 2022
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Purpose: The study was conducted to observe the pattern of ocular morbidities in patients attending the ophthalmology department during the COVID-19 pandemic. Methodology: A prospective observational study was conducted in a tertiary eye care centre in Central India from 1 January 2020 to 31 December 2020, among a total of 982 patients with ocular manifestations who attended the outpatient department or emergency department. A detailed history was taken and a complete anterior and posterior segment examination was done. The standard investigation and treatment protocol of the institution was followed in all cases. Result: A total of 982 patients were enrolled in our study with a mean age of 36.42±18.05 years. Male preponderance was noted with an M: F ratio of 2.43. A wide spectrum of ocular manifestations during COVID-19 was observed. The anterior segment was involved in 85.1% and the posterior segment was involved in 14.9% and most common ocular manifestations affecting the anterior segment were noted as computer vision syndrome observed in 18.1% cases, followed by cataracts in 11.4% cases. Conclusion: Various programs should be implemented to help in reducing the load of visual disability and blindness in the community which is increased after the COVID outbreak. With changing trends in geographical and socio-economical patterns of diseases, similar kinds of a pandemic may occur in the future. There should be formation of flexible government strategies for changing dynamics that can be timely implemented in the future for better management of curable/avoidable diseases. © 2022 Innovative Publication, All rights reserved.
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Background: The coronavirus pandemic has impacted the globe, altering lives of people in all domains, and added insecurity, thereby taking a toll on their mental health. Addressing the parallel surge of psychological problems and identifying the vulnerable population is of equal concern. This study aims at assessing the symptoms of anxiety and depression in the population during the coronavirus pandemic. Methodology: It was a cross-sectional methodological web-based survey to assess psychological influence of the coronavirus pandemic. A sociodemographic pro forma, validated questionnaire consisting questions about awareness regarding coronavirus, and Goldberg Anxiety and Depression Scale were included in the survey. Results: A total of 1027 participants completed the survey questionnaire. Clinically significant anxiety and depressive symptoms were found in 17.9% and 40.7%, respectively. There was statistically significant difference in prevalence of anxiety symptoms by gender (P = 0.009), age group (P = 0.030), marital status (P = 0.001), and occupation (P = 0.012). Depressive symptoms also significantly differed across age group (P = 0.001), marital status (P = 0.000), education (P = 0.020), occupation (P = 0.009), income group (P = 0.038), and place of living (P = 0.039). A significant difference of knowledge (about COVID-19) was seen between the groups with and without clinically significant depressive symptoms. Distress was noted mostly with information overload and the fear of contracting coronavirus infection. Conclusion: More than one-third of participants had clinically significant psychological symptoms. This suggests the requirement of more structured and long-term studies, and the need for appropriate mental health services to masses. © 2022 Medical Journal of Dr. D.Y. Patil Vidyapeeth ;Published by Wolters Kluwer - Medknow.
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Introduction: Media have never been as essential as it has become during the time of pandemic. Every information related to disease, prevention, and precaution was on media. Since most of the people confined to their homes, they used media not only to get the information about pandemic but also used media as companion, which enhanced the overall consumption of media significantly. This study aims to assess the changed consumption pattern of media in Indian population before and during the pandemic and its relation to the psychological well-being. Materials and Methods: It was a cross-sectional web-based survey. Four hundred and five respondents participated in it. Data analysis was done using descriptive and inferential statistics. Results: It was found that media consumption pattern and duration both have changed during the pandemic. There was a significant difference between before and after usage of all types of media. There was also significant difference for viewing media category in demographic subgroups, age (P = 0.000), marital status (P = 0.000), occupation (P = 0.000), and place of living (P = 0.036). Females (odds ratio [OR] =2.045, 95% confidence interval [CI]: 1.305, 3.203) and retired (OR = 0.039, 95% CI: 0.003, 0.470) were significantly associated with poor mental well-being. Respondents consumed media for sometimes (OR = 2.045, 95% CI: 1.557, 4.012) and frequently (OR = 4.946, 95% CI: 1.995, 12.264) were also associated with poor mental well-being. Conclusion: The study demonstrates the existence of poor mental well-being among women and retires more. It also demonstrates that people who preferred watching news more during the pandemic had the chance of suffering from poor mental well-being. © 2022 by the Author(s).
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COVID-19, a perilous disease caused by SARS-CoV-2, has brought a massive damage to humankind, and turned into a global catastrophe. It was first reported in Wuhan, China in December 2019 and since then has been a constant source of worry for the scientists and the medical world, due to the carnage it has caused globally. Extensive clinical studies are being carried to explore drug therapy and prophylaxis to combat this pestilence. It is still an excessively big challenge for the scientists and pharmacological industry to develop potential drugs for the treatment of this deadly virus. At present though no specific drug has been identified as a perfect cure for this zoonotic disease, medical practitioners are using the therapy of repurposing of drugs for the treatment. Systemic research was carried out through e-resources to identify drugs for the treatment of COVID-19. A recent proposal of 2-DG drug as a cure for COVID-19 has also been discussed in this review.
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1226 articles on privacy and COVID-19 were published by authors from 69 countries in this year's issue. COVID 19's privacy is now the focus of many researchers' attention. The present body of knowledge on privacy for COVID-19 digital technologies has been thoroughly analyzed, and a concise overview of research status and future developments can be gleaned. This paper conducted a bibliometric examination of privacy using the Scopus dataset. Utilizing VOSviewer software, the relevant literature papers published on this topic were examined to determine the field's development history, research hotspots, and future directions. Over time, there has been a rise in the number of studies published in privacy for COVID-19, particularly after 2020, and the growth rate has been steadily increasing. Regarding published research, the United States and China lead the pack. These articles appeared in primarily English-language journals and conference proceedings. Privacy and COVID-19 research was mostly computer science. The most used terms in privacy and COVID-19 were data privacy and humans. This paper examines the evolution of privacy and COVID-19 research and indicates current research priorities and future research goals. Furthermore, the privacy and COVID-19 study seem to be a promising sphere as this study identifies 26 domains. © 2023, Institute of Advanced Engineering and Science. All rights reserved.
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In this paper, we describe an approach for representation learning of audio signals for the task of COVID-19 detection. The raw audio samples are processed with a bank of 1-D convolutional filters that are parameterized as cosine modulated Gaussian functions. The choice of these kernels allows the interpretation of the filterbanks as smooth band-pass filters. The filtered outputs are pooled, log-compressed and used in a self-attention based relevance weighting mechanism. The relevance weighting emphasizes the key regions of the time-frequency decomposition that are important for the downstream task. The subsequent layers of the model consist of a recurrent architecture and the models are trained for a COVID-19 detection task. In our experiments on the Coswara data set, we show that the proposed model achieves significant performance improvements over the baseline system as well as other representation learning approaches. Further, the approach proposed is shown to be uniformly applicable for speech and breathing signals and for transfer learning from a larger data set. Copyright © 2022 ISCA.
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Introduction: The telemedicine center of our hospital provides expert consultation services to two rural districts of Punjab. The aim of this study was to assess its utility in Fine needle aspiration Cytology (FNAC) diagnostic service. Material(s) and Method(s): A 2-year retrospective audit from April 2020-2022 covering the COVID pandemic time was carried out on all cases of telecytopathology consultation files of the E-sanjeevani platform. A total of 75 cases whose FNAC smear images clicked by android smartphones with 48MP cameras and sent by Whatsapp to the E-Sanjeevani administrator were included. The images along with brief case clinical details were e-mailed for expert opinion to the cytopathologist (RS). The image quality, ability to provide a diagnosis, site-wise differences and comparison of the referral and expert review diagnosis was made. Result(s): The ages of the patients ranged from 4-80 years (2 children, 73 adults), with 25 males and 50 females. The sites of FNA performed at the district hospital were lymph nodes (22), breast (21), thyroid (15), soft tissue (8), salivary gland (2), skin (4), lip (2) and glans penis(1). The number of Whatsapp images evaluated ranged from 3-20 with median of 11 per case. They were in JPEG file format with size ranging from 40-163kb. Image quality was rated visually as good, medium, and poor in 46 (61%), 21m (28%) and 8(11%) cases respectively. There was no distortion of images upon enlarging them for better visualization on a large monitor. Best accuracy was obtained in breast and lymph nodes FNA. Soft tissue FNA was difficult to interpret and was inconclusive in 3/8 cases. Conclusion(s): Telecytopathology by Whatsapp is simple, quick, feasible and very useful to provide expert opinion in FNAC of various sites thereby enabling the pathologist in the district hospital setting. [Formula presented] Copyright © 2022
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Internet hoaxes like COVID-19 pose a danger to the population in southern India. Studying the relevance of COVID's traits has helped academics debunk the bogus news spread on social media. A plethora of concerns were voiced when a small number of unverified reports made headlines recently;such stories may have implications across a wide range of topics, including religion, politics, health, and beyond. More than half of all health-related bogus news is itself fraudulent. Vaccine side effects, drug interactions, outdated medical technology, new viruses, and other factors all contribute to people's declining health. The fake news includes text content, audio files, video files, and photos—most of the fake news is in the form of video content 55%. Social media websites like YouTube, WhatsApp, Twitter, and Facebook, produce false news content. The COVID pandemic is universal, so more than 65% of news is connected internationally. Finally, 75% are treated as fake news;it could be a genuine risk to public health—fake news understanding the social media during the present and future situation. Unfortunately, internet users complain about being shown a flood of similar content that is either misleading or entirely false when searching for relevant and dependable information. Several worries about what has been termed an "infodemic" of misleading material being spread online, including possibly bad advice on some subjects. In this paper, the main objective is to identify fake news in online media and classify the fake news.
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Since the start of the COVID-19 pandemic, hospitals have been overwhelmed with the high number of ill and critically ill patients. The surge in ICU demand led to ICU wards running at full capacity, with no signs of demand falling. As a result, resource management of ICU beds and ventilators has been a bottleneck in providing adequate healthcare to those in need. Short-term ICU demand forecasts have become a critical tool for hospital administrators. Therefore, using the existing COVID-19 patient data, we build models to predict if a patient's health will deteriorate below safe thresholds to deem admission into ICU in the next 24 to 96 hours. We identify the most important clinical features responsible for the prediction and narrow down the health indicators to focus on, thereby assisting the hospital staff in increasing responsiveness. These models can help the hospital staff better forecast ICU demand in near real-time and triage patients for ICU admissions as per the risk of deterioration. Using a retrospective study with a dataset of 1411 COVID-19 patients from an actual hospital in the USA, we run experiments and find XGBoost performs the best among the models tested when tuning parameters for sensitivity (recall). The most important feature for the four prediction tasks is the maximum respiratory rate, but subsequent features in order of importance vary between models predicting ICU transfer in the next 24 to 48 hours and those predicting ICU transfer in the next 72 to 96 hours. © 2022 IEEE.