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1.
JMIR Ment Health ; 9(9): e37354, 2022 Sep 07.
Article in English | MEDLINE | ID: covidwho-2022367

ABSTRACT

BACKGROUND: An anticipated surge in mental health service demand related to COVID-19 has motivated the use of novel methods of care to meet demand, given workforce limitations. Digital health technologies in the form of self-tracking technology have been identified as a potential avenue, provided sufficient evidence exists to support their effectiveness in mental health contexts. OBJECTIVE: This literature review aims to identify current and potential physiological or physiologically related monitoring capabilities of the Apple Watch relevant to mental health monitoring and examine the accuracy and validation status of these measures and their implications for mental health treatment. METHODS: A literature review was conducted from June 2021 to July 2021 of both published and gray literature pertaining to the Apple Watch, mental health, and physiology. The literature review identified studies validating the sensor capabilities of the Apple Watch. RESULTS: A total of 5583 paper titles were identified, with 115 (2.06%) reviewed in full. Of these 115 papers, 19 (16.5%) were related to Apple Watch validation or comparison studies. Most studies showed that the Apple Watch could measure heart rate acceptably with increased errors in case of movement. Accurate energy expenditure measurements are difficult for most wearables, with the Apple Watch generally providing the best results compared with peers, despite overestimation. Heart rate variability measurements were found to have gaps in data but were able to detect mild mental stress. Activity monitoring with step counting showed good agreement, although wheelchair use was found to be prone to overestimation and poor performance on overground tasks. Atrial fibrillation detection showed mixed results, in part because of a high inconclusive result rate, but may be useful for ongoing monitoring. No studies recorded validation of the Sleep app feature; however, accelerometer-based sleep monitoring showed high accuracy and sensitivity in detecting sleep. CONCLUSIONS: The results are encouraging regarding the application of the Apple Watch in mental health, particularly as heart rate variability is a key indicator of changes in both physical and emotional states. Particular benefits may be derived through avoidance of recall bias and collection of supporting ecological context data. However, a lack of methodologically robust and replicated evidence of user benefit, a supportive health economic analysis, and concerns about personal health information remain key factors that must be addressed to enable broader uptake.

2.
Concurrency and Computation: Practice and Experience ; 2022.
Article in English | Scopus | ID: covidwho-2013446

ABSTRACT

The Internet of Things (IoT) has appreciably influenced the technology world in the context of interconnectivity, interoperability, and connectivity using smart objects, connected sensors, devices, data, and appliances. The IoT technology has mainly impacted the global economy, and it extends from industry to different application scenarios, like the healthcare system. This research designed anti-corona virus-Henry gas solubility optimization-based deep maxout network (ACV-HGSO based deep maxout network) for lung cancer detection with medical data in a smart IoT environment. The proposed algorithm ACV-HGSO is designed by incorporating anti-corona virus optimization (ACVO) and Henry gas solubility optimization (HGSO). The nodes simulated in the smart IoT framework can transfer the patient medical information to sink through optimal routing in such a way that the best path is selected using a multi-objective fractional artificial bee colony algorithm with the help of fitness measure. The routing process is deployed for transferring the medical data collected from the nodes to the sink, where detection of disease is done using the proposed method. The noise exists in medical data is removed and processed effectively for increasing the detection performance. The dimension-reduced features are more probable in reducing the complexity issues. The created approach achieves improved testing accuracy, sensitivity, and specificity as 0.910, 0.914, and 0.912, respectively. © 2022 John Wiley & Sons, Ltd.

3.
Clinical medicine insights. Circulatory, respiratory and pulmonary medicine ; 16, 2022.
Article in English | EuropePMC | ID: covidwho-1989661

ABSTRACT

BACKGROUND Severe cases of coronavirus disease 2019 (COVID-19) are characterized by progressive respiratory failure and the development of acute respiratory distress syndrome (ARDS), with high mortality rates for patients requiring mechanical ventilation. Levels of the vascular growth factor Angiopoietin 2 (Ang2) in plasma have been strongly correlated with increased ARDS risk in patients with pneumonia or sepsis. The intent of this study was to determine whether LY3127804, an anti-Ang2 monoclonal antibody, could reduce the need for mechanical ventilation among patients admitted to the hospital with pneumonia and presumed or confirmed COVID-19. METHODS Patients admitted to hospital with confirmed pneumonia, presumed or confirmed COVID-19, and infiltrates on chest imaging and/or oxygen saturation of ≤ 95% on room air were stratified by age group (< 65 years and ≥ 65 years), sex, and site and randomly assigned 1:1 within each stratum to receive either LY3127804 (20 mg/kg) or placebo on Day 1 and possibly on Day 15. The primary end point for this study was number of days in which a patient did not require a ventilator over the 28-day study period. RESULTS Interim analysis assessed study futility after 95 randomized patients had 28-day data available and showed no benefit of LY3127804 in reducing the number of ventilator days over placebo. The study was subsequently terminated. CONCLUSION LY3127804 treatment did not decrease the need for ventilator usage in patients hospitalized with pneumonia and presumed or confirmed COVID-19. ClinicalTrials.gov identifier NCT04342897

4.
Gastroenterology ; 162(7):S-600, 2022.
Article in English | EMBASE | ID: covidwho-1967347

ABSTRACT

Introduction Despite the global impact of the COVID-19 pandemic, vaccine hesitancy remains common in the general public. Adults who were on immunosuppressive medications were among the earlier groups recommended by the Centers for Disease Control and Prevention to receive the COVID-19 vaccine. It is unclear whether similar vaccine hesitancy is seen in patients with inflammatory bowel disease (IBD), especially those who are on immunosuppressive medications. We sought to examine rate of vaccine hesitancy in patients with IBD as well as associated demographic and socioeconomic risk factors. Methods We performed a retrospective chart review in November 2021 of 1383 patients with IBD seen at University of Maryland Medical Center, a tertiary referral medical center, between November 2020 and October 2021. Data obtained from patients' charts included demographics;disease characteristics including disease phenotype, number of years since diagnosis, number of IBD-related surgeries;and IBD therapy including biologics, thiopurines or methotrexate, corticosteroids, and mesalamine. Information on COVID vaccination and routinely recommended vaccines were also collected which included annual influenza vaccine, Prevnar/ Pneumovax, and Shingrix. Those with no recorded COVID-19 vaccine were contacted by nurses for updated vaccine status. Results 72% (990/1383) of patients in this cohort were on a biologic, 17% (232/1383) were on corticosteroids, and 16% (224/1383) were on thiopurine or methotrexate, indicating a cohort of patients with moderate to severe disease phenotype. Fifty-seven percent (792/1383) of patients received either the Pfizer, Moderna, or Johnson & Johnson vaccine. In a multivariate regression analysis, COVID vaccination was found to be positively associated with a number of factors including older age (p-value= 4.92e-4), female sex (p=1.61e-3), Asian and Caucasian races (p=9.13e-3, 6.47e-06), number of years since diagnosis (p=2.73e-2), number of clinic visits in the past 12 months (p= 2.66e-10), and biologic use (p=4.41e-4). This remained the case while controlling for IBD disease type;marital status;insurance (Commercial vs Medicaid vs Medicare);and tobacco, alcohol, and substance use history. Patients who received other routinely recommended vaccines (influenza, Prevnar/Pneumovax, Shingrix) were not more likely to receive COVID- 19 vaccine. Discussion Although majority of patients in this cohort were on an immunosuppressive medication, COVID-19 vaccination rate is only recorded to be at 57%. Number of clinic visits, presumably more education and conversation with healthcare providers, had a positive impact on COVID-19 vaccination. In this cohort, younger adults, males, and African Americans were less likely to receive COVID-19 vaccine. Healthcare providers need to recognize these potential risk factors for COVID-19 vaccine hesitancy.

5.
Drug Deliv Transl Res ; 12(12): 3007-3016, 2022 Dec.
Article in English | MEDLINE | ID: covidwho-1943385

ABSTRACT

To address the unprecedented global public health crisis due to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), we designed and developed a novel antiviral nano-drug, called SNAT (Smart Nano-Enabled Antiviral Therapeutic), comprised of taxoid (Tx)-decorated amino (NH2)-functionalized near-atomic size positively charged silver nanoparticles (Tx-[NH2-AgNPs]) that are stable for over 3 years. Using a hamster model, we tested the preclinical efficacy of inhaled SNAT on the body weight, virus titer, and histopathology of lungs in SARS-CoV-2-infected hamsters, including biocompatibility in human lung epithelium and dermal fibroblasts using lactase dehydrogenase (LDH) and malondialdehyde (MDA) assays. Our results showed SNAT could effectively reverse the body weight loss, reduce the virus load in oral swabs, and improve lung health in hamsters. Furthermore, LDH assay showed SNAT is noncytotoxic, and MDA assay demonstrated SNAT to be an antioxidant, potentially quenching lipid peroxidation, in both the human cells. Overall, these promising pilot preclinical findings suggest SNAT as a novel, safer antiviral drug lead against SARS-CoV-2 infection and may find applications as a platform technology against other respiratory viruses of epidemic and pandemic potential.


Subject(s)
COVID-19 , Metal Nanoparticles , Cricetinae , Animals , Humans , SARS-CoV-2 , COVID-19/drug therapy , Disease Models, Animal , Silver , Antiviral Agents/pharmacology , Antiviral Agents/therapeutic use
6.
4th International Conference on Communications and Cyber-Physical Engineering, ICCCE 2021 ; 828:311-324, 2022.
Article in English | Scopus | ID: covidwho-1877774

ABSTRACT

India is one of the best countries which follows the conventional education system and forces the student to learn the subjects by attending the classes directly. The normal education system in the country has changed at the starting of February 2020, when the government confirmed the first case of coronavirus infection in India. The schools were suspended suddenly and the situation continued for a few months. But the government found a solution that the students who are not permitted to go to class can pick an online training framework. This research is mainly for comparing the pre and post covid education system and evaluation of the student performance using machine learning techniques such as Artificial Neural Network (ANN), Logistic Regression, and Naïve Bayes. The prediction algorithms are focus on the attributes such as understandability of subject topics, internal assessment, level of concentration, language proficiency, and percentage of marks in the main exam during regular class and online class. The prediction model compares the attributes and predicts either the regular class or the online class increases the student’s performance. The dataset for research is collected mainly from graduation and post-graduation students through Google form due to the pandemic. ANN is the model that gave a higher accuracy rate of 0.95. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

7.
2022 International Conference on Sustainable Computing and Data Communication Systems, ICSCDS 2022 ; : 1479-1483, 2022.
Article in English | Scopus | ID: covidwho-1874303

ABSTRACT

In the pandemic situation, people are quickly affected in our day-to-day life. Wearing the mask is being normal nowadays for controlling the spread of COVID-19. The government and public sectors will ask the public/customers to wear masks to control the spread of COVID-19. Mask detection has become an essential task to help society's well-being to protect our life. This paper provides a simplified approach to detect face masks using basic ML packages in PYTHON like tensor Flow, Keras, OpenCV. This paper helps to analyze an image to detect the face correctly and then identifies whether there is a mask on the face or not. It is a surveillance task to perform the security to create awareness among the people. This method attains the accuracy of scanning face up to 96.88% and 92.39% respectively. This detection is based on two datasets, one is about without wearing a mask and with wearing a mask. This mechanism helps to detect the mask on people's faces in real-time scenarios. © 2022 IEEE.

9.
Pandemic Outbreaks in the 21st Century: Epidemiology, Pathogenesis, Prevention, and Treatment ; : 111-122, 2021.
Article in English | Scopus | ID: covidwho-1803302

ABSTRACT

Middle East respiratory syndrome coronavirus (MERS-CoV) is a zoonotic coronavirus transferred to humans from infected dromedary camels. The origins of MERS-CoV are unknown, but based on the analysis of different virus genomes, it is thought to have originated in bats and then been transmitted to camels in the distant past. The chapter briefly covers the major MERS-CoV outbreaks, mode of transmission, route of infection in humans, virus structure, and life cycle, with a particular emphasis on the molecular mechanism of pathogenesis, diagnostics, vaccines, treatment, and control strategies. © 2021 Elsevier Inc. All rights reserved.

10.
Emerg Med J ; 39(8): 575-582, 2022 Aug.
Article in English | MEDLINE | ID: covidwho-1788973

ABSTRACT

BACKGROUND: To identify the population-level impact of a national pulse oximetry remote monitoring programme for COVID-19 (COVID Oximetry @home (CO@h)) in England on mortality and health service use. METHODS: We conducted a retrospective cohort study using a stepped wedge pre-implementation and post-implementation design, including all 106 Clinical Commissioning Groups (CCGs) in England implementing a local CO@h programme. All symptomatic people with a positive COVID-19 PCR test result from 1 October 2020 to 3 May 2021, and who were aged ≥65 years or identified as clinically extremely vulnerable were included. Care home residents were excluded. A pre-intervention period before implementation of the CO@h programme in each CCG was compared with a post-intervention period after implementation. Five outcome measures within 28 days of a positive COVID-19 test: (i) death from any cause; (ii) any ED attendance; (iii) any emergency hospital admission; (iv) critical care admission and (v) total length of hospital stay. RESULTS: 217 650 people were eligible and included in the analysis. Total enrolment onto the programme was low, with enrolment data received for only 5527 (2.5%) of the eligible population. The period of implementation of the programme was not associated with mortality or length of hospital stay. The period of implementation was associated with increased health service utilisation with a 12% increase in the odds of ED attendance (95% CI: 6% to 18%) and emergency hospital admission (95% CI: 5% to 20%) and a 24% increase in the odds of critical care admission in those admitted (95% CI: 5% to 47%). In a secondary analysis of CO@h sites with at least 10% or 20% of eligible people enrolled, there was no significant association with any outcome measure. CONCLUSION: At a population level, there was no association with mortality before and after the implementation period of the CO@h programme, and small increases in health service utilisation were observed. However, lower than expected enrolment is likely to have diluted the effects of the programme at a population level.


Subject(s)
COVID-19 , COVID-19/epidemiology , Hospitalization , Humans , Oximetry , Patient Acceptance of Health Care , Retrospective Studies
12.
Open Forum Infectious Diseases ; 8(SUPPL 1):S319, 2021.
Article in English | EMBASE | ID: covidwho-1746562

ABSTRACT

Background. As of May 2, 2021, U.S. nursing homes (NHs) have reported >651,000 COVID-19 cases and >132,000 deaths to CDC's National Healthcare Safety Network. Since U.S. COVID-19 vaccination coverage is increasing, we investigate the role of vaccination in controlling future COVID-19 outbreaks. Methods. We developed a stochastic, compartmental model of SARS-CoV-2 transmission in a theoretical 100-bed NH with a staff of 99 healthcare personnel (HCP) in a community of 20,000 people. We modeled admission and discharge of residents (parameterized with Centers for Medicare & Medicaid Services data), assuming the following: temporary replacement of HCP when tested positive;daily visits to NH residents;isolation of COVID-19 positive residents;personal protective equipment (PPE) use by HCP;and symptom-based testing of residents and staff plus weekly asymptomatic testing of HCP and facility-wide outbreak testing once a COVID-19 case is identified. We systematically varied coverage of an mRNA vaccine among residents and HCP, and in the community. Simulations also varied PPE adherence, defined as the percentage of time in the facility that HCP properly used recommended PPE (25%, 50% or 75% of the time). Infection was initialized in the community with 40 infectious cases, and initial infection in the NH was allowed after 14 days of vaccine dose 1. Simulations were run for 6 months after dose 2 in the NH. Results were summarized over 1000 simulations. Results. At 60% community coverage, expected cumulative symptomatic resident cases over 6 months were ≤5, due to low importation of COVID-19 infection from the community, with further reduction at higher coverage among HCP (Figure 1). Uncertainty bounds narrowed as NH resident coverage or PPE adherence increased. Results were similar if testing of staff and residents stopped. Probability of an outbreak within 4 weeks of dose 2 remained below 5% with high community coverage (Figure 2). An outbreak is defined as an occurrence of 2 or more cases within 4 weeks of dose 2. Probability of no outbreak was calculated by counting how many simulations out of a total of 1000 simulations had ≤1 symptomatic case in NH residents or HCP within 4 weeks after dose 2 was administered in the nursing home. The first vaccine dose in residents and HCP was assumed to be given on day 1, and the second dose 28 days later. A probability value and its 90%-confidence interval (CI) at a given community and HCP coverage was calculated by pooling model outputs for 9 sets (3 PPE adherence values X 3 resident coverage levels) of model simulations. Simulations were performed assuming no asymptomatic testing or facility-wide outbreak testing. Conclusion. Results suggest that increasing community vaccination coverage leads to fewer infections in NH residents. Testing asymptomatic residents and staff may have limited value when vaccination coverage is high. High adherence to recommended PPE may increase the likelihood that future COVID-19 outbreaks can be contained.

13.
Open Forum Infectious Diseases ; 8(SUPPL 1):S417-S418, 2021.
Article in English | EMBASE | ID: covidwho-1746399

ABSTRACT

Background. CURE ID is an internet-based data repository (https://cure.ncats. io/explore) developed collaboratively by FDA and NCATS/NIH. It is designed to capture real-world clinical outcome data to advance drug repurposing and to inform future clinical trials for infectious diseases with high unmet medical need. It also serves as a repository of clinical trials automatically pulled from https://www.clinicaltrials.gov into the CURE ID platform, where they were then manually curated, with the intention of keeping the infectious diseases community updated on the various clinical trials underway. The current study is a descriptive analysis of various therapeutics in clinical trials against COVID-19 on the CURE ID platform. Methods. Using clinicaltrials.gov we selected those trials addressing therapeutics for COVID-19 and reviewed the drugs used, the current status of the trials, and the phases of development. Results. As of May 2021, we identified 2,154 clinical trials and 933 drugs from clinicaltrials.gov that met the inclusion criteria. Hydroxychloroquine (n=251) was the most commonly investigated agent, followed by convalescent plasma (n=147), azithromycin (n=98), ivermectin (n=68), mesenchymal Stem Cells (n=63), tocilizumab (n=58), remdesivir (n=53) and favipiravir (n=51). At the time of our analysis, the majority (45%) of the clinical trials were in the recruiting phase, 12% were in the active phase, and 13% of the studies were completed. The majority (31%) of trials were in phase two, followed by phase three (21%) and phase one (10%). The vast majority of the agents were repurposed (92%), while only 8% of the agents were new molecular entities. Remdesivir was the only drug approved for marketing for treatment of certain patients with COVID-19 at the time of our analysis. Conclusion. Several repurposed and novel drugs are being investigated to treat COVID-19 in clinical trials. CURE ID provides a broad view of the various drugs being researched and serves to keep the scientific community informed. Such a platform may help prevent duplication of efforts and help the scientific community with more coordinated research efforts and larger platform trials that can robustly answer scientific questions during a pandemic.

15.
JMIR Form Res ; 6(1): e30863, 2022 Jan 07.
Article in English | MEDLINE | ID: covidwho-1662511

ABSTRACT

BACKGROUND: Continuous telemonitoring of vital signs in a clinical or home setting may lead to improved knowledge of patients' baseline vital signs and earlier detection of patient deterioration, and it may also facilitate the migration of care toward home. Little is known about the performance of available wearable sensors, especially during daily life activities, although accurate technology is critical for clinical decision-making. OBJECTIVE: The aim of this study is to assess the data availability, accuracy, and concurrent validity of vital sign data measured with wearable sensors in volunteers during various daily life activities in a simulated free-living environment. METHODS: Volunteers were equipped with 4 wearable sensors (Everion placed on the left and right arms, VitalPatch, and Fitbit Charge 3) and 2 reference devices (Oxycon Mobile and iButton) to obtain continuous measurements of heart rate (HR), respiratory rate (RR), oxygen saturation (SpO2), and temperature. Participants performed standardized activities, including resting, walking, metronome breathing, chores, stationary cycling, and recovery afterward. Data availability was measured as the percentage of missing data. Accuracy was evaluated by the median absolute percentage error (MAPE) and concurrent validity using the Bland-Altman plot with mean difference and 95% limits of agreement (LoA). RESULTS: A total of 20 volunteers (median age 64 years, range 20-74 years) were included. Data availability was high for all vital signs measured by VitalPatch and for HR and temperature measured by Everion. Data availability for HR was the lowest for Fitbit (4807/13,680, 35.14% missing data points). For SpO2 measured by Everion, median percentages of missing data of up to 100% were noted. The overall accuracy of HR was high for all wearable sensors, except during walking. For RR, an overall MAPE of 8.6% was noted for VitalPatch and that of 18.9% for Everion, with a higher MAPE noted during physical activity (up to 27.1%) for both sensors. The accuracy of temperature was high for VitalPatch (MAPE up to 1.7%), and it decreased for Everion (MAPE from 6.3% to 9%). Bland-Altman analyses showed small mean differences of VitalPatch for HR (0.1 beats/min [bpm]), RR (-0.1 breaths/min), and temperature (0.5 °C). Everion and Fitbit underestimated HR up to 5.3 (LoA of -39.0 to 28.3) bpm and 11.4 (LoA of -53.8 to 30.9) bpm, respectively. Everion had a small mean difference with large LoA (-10.8 to 10.4 breaths/min) for RR, underestimated SpO2 (>1%), and overestimated temperature up to 2.9 °C. CONCLUSIONS: Data availability, accuracy, and concurrent validity of the studied wearable sensors varied and differed according to activity. In this study, the accuracy of all sensors decreased with physical activity. Of the tested sensors, VitalPatch was found to be the most accurate and valid for vital signs monitoring.

16.
International Journal of Pharmaceutical Sciences Review and Research ; 70(2):109-112, 2021.
Article in English | EMBASE | ID: covidwho-1579149

ABSTRACT

The WHO has set Defined Daily Dose which represent the average daily dose of an antibiotic in a standard patient. The DDD mai nly focuses on population-based parameters & assumes that patients as well as hospitals are homogenous entities. DOTs are very useful in order to classify antibiotic days based on patient-level exposure. DOTs merely mean the number of days that a patient is on an antibiotic, irrespective of dose. DOTs signifies that the underlying assumptions about antibiotic dosing was appropriate. Additionally, when patients receive more than one antibiotic, supplementary DOT may be counted. The 300-bed tertiary care medical center serves adults and paediatrics. An all-time Microbiology Consultant and a Clinical Pharmacology trainee used to go for round daily and used to collect data for ASP for the period of 3 months that is April to June,2021. In this study we have compared DOT of some important antibiotics for a specific period of time for both COVID and NON COVID patient. ASP-focused antibiotics were antibiotics routinely evaluated by the ASP team for appropriateness during therapy and the potential to optimize their appropriate use through policies, protocols, formulary restrictions, or clinician education. ASP-focused antibiotics included meropenem, linezolid, pip-taz, poly b, colistin, teicoplanin. In this study we have compared the DDD for 2 specific period of time for better understanding the consumption of those antibiotics. In conclusion, following the initiation of an ASP, significant decreases in utilization, increases in cost savings occurred. In our study we have reduced the consumption and DDD of linezolid which is clinically significant. When it comes to DOTs;We have reduced the DOTs of piptaz and teicoplanin for covid patient And Reduced the DOTs of meropenem and teicoplanin for non-covid patient which is clinically and statistically significant.

17.
RNA Biol ; 19(1): 1-11, 2022.
Article in English | MEDLINE | ID: covidwho-1569455

ABSTRACT

The role for circulating miRNAs as biomarkers of the COVID-19 disease remains uncertain. We analysed the circulating miRNA profile in twelve COVID-19 patients with moderate-severe disease. This analysis was conducted by performing next generation sequencing (NGS) followed by real-time polymerase chain reaction (RT-qPCR). Compared with healthy controls, we detected significant changes in the circulating miRNA profile of COVID-19 patients. The miRNAs that were significantly altered in all the COVID-19 patients were miR-150-5p, miR-375, miR-122-5p, miR-494-3p, miR-3197, miR-4690-5p, miR-1915-3p, and miR-3652. Infection assays performed using miRNA mimics in HEK-293 T cells determined miR-150-5p to have a crucial role in SARS-CoV-2 infection and this was based on the following data: (i) miR-150-5p mimic lowered in vitro SARS-CoV-2 infection; (ii) miR-150-5p inhibitor reversed the effects of miR-150-5p mimic on SARS-CoV-2 infection of cells; and (iii) a novel miRNA recognition element (MRE) was identified in the coding strand of SARS-CoV-2 nsp10, the expression of which could be inhibited by miR-150-5p mimic. Our findings identified crucial miRNA footprints in COVID-19 patients with moderate-severe disease. A combination of co-transfection and Western blotting experiments also determined the ability of miR-150-5p to inhibit SARS-CoV-2 infection via directly interacting with MRE in the coding strand of nsp10. Our investigation showed that a sharp decline in the miR-150-5p plasma levels in COVID-19 patients may support enhanced SARS-CoV-2 infection. Furthermore, this study provides insight into one possible mechanism by which COVID-19-induced changes to miR-150-5p levels may promote SARS-CoV-2 infection via modulating nsp10 expression.


Subject(s)
COVID-19/metabolism , Gene Expression Regulation, Viral , MicroRNAs/metabolism , SARS-CoV-2/metabolism , Viral Regulatory and Accessory Proteins/biosynthesis , Animals , COVID-19/genetics , Cell Line, Tumor , Chlorocebus aethiops , HEK293 Cells , Humans , MicroRNAs/genetics , SARS-CoV-2/genetics , Vero Cells , Viral Regulatory and Accessory Proteins/genetics
18.
21st International Conference on Computational Science and Its Applications (ICCSA) ; 12950:580-588, 2021.
Article in English | Web of Science | ID: covidwho-1549315

ABSTRACT

In this paper, we present an analysis of Covid-19 data during the first 138 days in Senegal. The data come from the website of the Ministry of Health and Social Action. We build a database with R and Python scripts helping to carry out data analysis for answering questions that support decision-makers. We compute the basic reproduction rate with the collected data using the SIRD model approach (susceptible, infected, recovered, death). Results show that there are two phases in the evolution of infected cases, 4.75% are between the first day of the Covid-19 outbreak and the 50th day, 95.25% are between the 51st day and the 138th day corresponding to the period of the reopening of airports. The average value of the basic reproduction rate during the first 138 days is 2.77. We observed a strong correlation between infected cases and community infected cases. The obtained results could help decision-makers to evaluate the statistical evolution of infected persons.

19.
BMJ Qual Saf ; 31(8): 590-598, 2022 08.
Article in English | MEDLINE | ID: covidwho-1537962

ABSTRACT

INTRODUCTION: Hospital admissions in many countries fell dramatically at the onset of the COVID-19 pandemic. Less is known about how care patterns differed by patient groups. We sought to determine whether areas with higher levels of socioeconomic deprivation or larger ethnic minority populations saw larger falls in emergency and planned admissions in England. METHODS: We conducted a national observational study of hospital care in the English National Health Service (NHS) in 2019-2020. Weekly volumes of elective (planned) and emergency admissions in 2020 compared with 2019 were calculated for each census area. Multiple linear regression analysis was used to estimate the reductions in volumes for areas in different quintiles of socioeconomic deprivation and ethnic minority populations after controlling for national time trends and local area composition. RESULTS: Between March and December 2020, there were 35.5% (3.0 million) fewer elective admissions and 22.0% (1.2 million) fewer emergency admissions with a non-COVID-19 primary diagnosis than in 2019. Areas with the largest share of ethnic minority populations experienced a 36.7% (95% CI 24.1% to 49.3%) larger reduction in non-primary COVID-19 emergency admissions compared with those with the smallest. The most deprived areas experienced a 10.1% (95% CI 2.6% to 17.7%) smaller reduction in non-COVID-19 emergency admissions compared with the least deprived. These patterns are not explained by differential prevalence of COVID-19 cases by area. CONCLUSIONS: Even in a healthcare system founded on the principle of equal access for equal need, the impact of COVID-19 on NHS hospital care for non-COVID patients has not been spread evenly by ethnicity and deprivation in England. While we cannot conclusively determine the mechanisms behind these differences, they risk exacerbating prepandemic health inequalities.


Subject(s)
COVID-19 , COVID-19/epidemiology , Ethnicity , Hospitals , Humans , Minority Groups , Pandemics , Socioeconomic Factors , State Medicine
20.
1st International Conference on Smart Technologies Communication and Robotics, STCR 2021 ; 2021.
Article in English | Scopus | ID: covidwho-1537776

ABSTRACT

Since the outbreak of Coronavirus disease (Covid-19) in the late 2019, humanity has been traumatized by a profound impact in multiple domains. People are obliged to use face masks and gloves to protect themselves from anything that came into physical contact due to rapid and effective spread of the infection. So, masks must be worn for protection the elements, but how about the issues that workers in industries are facing? The tools in the industries are one of the most utilized items having a higher risk of spreading illness. The proposed robot is designed and constructed with the goal of reducing the spread of this disease in institutions, workplace, and industrial environments. The Bot is coupled with contactless temperature sensing and mask detection feature with a Face recognition-based attendance system. It also serves as personal assistance powered with Wolfram Alpha, Open Weather, Wiki-Powered and packed with much more factors to serve day-to-day office and industrial needs. © 2021 IEEE.

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