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BACKGROUND: Pregnant women are vulnerable against COVID-19 infection due to physiological and immunological changes. COVID-19 in pregnancy affects fetal well-being with a potential for vertical infection. AIM: This study aims to determine the incidence of vertical infection and anti-severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) antibodies in infants born to mothers with positive COVID-19 infection. MATERIALS AND METHODS: Amniotic fluid, swabs of the newborn's nasopharynx and oropharynx, and swabs of the placenta were examined using reverse transcription polymerase chain reaction (RT-PCR) for SARS-CoV-2. Serological examination was performed by Electro-Chemiluminescence Immunoassay on infant's blood. RESULT(S): Four of 33 pregnant women gave birth to infants positive SARS-CoV-2 infection. RT-PCR examination of all amniotic fluid and placental swabs was negative for SARS-CoV-2. Four of 33 infants (12.1%) showed negative polymerase chain reaction (PCR) results but positive SARS-CoV-2 antibodies, another 4 newborns (12.1%) showed positive PCR results, but no SARS-CoV-2 antibodies detected. The remaining 25 babies (75.8%) showed both negative PCR and serologic results. CONCLUSION(S): No evidence of vertical transmission found in this study.Copyright © 2023 Cut Meurah Yeni, Zinatul Hayati, Sarjani M. Ali, Hasanuddin Hasanuddin, Rusnaidi Rusnaidi, Cut Rika Maharani.
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BackgroundViral infections are known triggers of disease flares in idiopathic inflammatory myopathies (IIMs). Reports of post-COVID-19 flares of IIMs have raised suspicion of a possible role of SARS-COV-2 in their onset [1,2]. However, despite rising flare rates in this vulnerable patient group during the pandemic, the risk factors for post-COVID-19 IIMs flares remain unknown [3,4].ObjectivesDisease flares among patients with idiopathic inflammatory myopathies (IIMs) can lead to significant disability, though are poorly explored in the post-COVID-19 period. We analysed risk factors for post-COVID-19 flares in a global sample of IIM patients in a subset analysis as part of the ongoing COVID-19 Vaccination in Autoimmune Diseases (COVAD) study.MethodsA cross-sectional patient self-reporting survey was circulated by the international COVAD study group (157 collaborators, 106 countries) to patients with autoimmune diseases and healthy controls from February-June 2022. Data was collected on demographics, autoimmune disease details, treatment history, comorbidities, COVID-19 history and course and COVID-19 vaccination details. Patients with IIMs who flared post COVID-19 were compared to those who did not using the χ2 test, factors found significant in univariate analysis and deemed clinically important, underwent multivariable analysis (binary logistic regression using the Enter method) with adjustment for age, gender, ethnicity, vaccine type, immunosuppression, autoimmune and non-autoimmune comorbidities, COVID-19 antibody status, and clinical symptoms of COVID-19. Statistical analyses were performed using IBM SPSS version 28.0, with statistical significance considered at p<0.05.Results15,165 respondents completed the survey of whom 1,169 contracted COVID-19. Of these, 207 had IIMs [median (IQR) age 57.0 (47.0-67.0), 71% female, 74.4% Caucasian]. We noted with concern that nearly a third of patients with IIMs (63/207, 30.4%) reported experiencing a flare. A past medical history significant for Asthma, (34.9% vs 6.9%, multivariable OR: 7.1;95%CI: 3.1-16.4, p<0.001) and specific clinical symptoms during COVID-19 including joint pains (multivariable OR: 6.05;95%CI: 1.60-22.9, p=0.008), and difficulty in breathing (multivariable OR: 3.43;95%CI: 1.09-10.8, p=0.036) were found to confer conferred a higher risk of flares (Table 1).Table 1Patient Reported Flares following COVID-19 infection among IIM patientsTotal IIMs (n=207)IIMs with flare after COVID-19 (n=63)IIMs without flare after COVID-19 (n=144)OR (95%CI)PAge (median, IQR) years57.0 (47.0-67.0)53.0 (47.0-62.0)59.0 (47.0-69.0)-0.024GenderMale Female60 (29.0) 147 (71.0)7 (11.1) 56 (88.9)53 (36.8) 91 (63.2)0.2 (0.09-0.5)< 0.001ComorbiditiesAsthma ILD32 (15.5) 31 (15.0)22 (34.9) 11 (17.5)10 (6.9) 20 (13.9)7.1 (3.1-16.4) 1.3 (0.5-2.9)<0.001 00.508Clinical features in previous COVID-19 infectionFatigue Myalgia Arthralgia Difficulty in breathing134 (64.7) 94 (45.4) 56 (27.1) 41 (19.8)52 (82.5) 44 (69.8) 36 (57.1) 27 (42.9)82 (56.9) 50 (34.7) 20 (13.9) 14 (9.7)3.5 (1.7-7.4) 4.3 (2.3-8.2) 8.2 (4.1-16.4) 6.9 (3.3-14.6)<0.001 <0.001 <0.001 <0.001ConclusionWe observed a high frequency of patients with IIM experiencing post-COVID-19 disease flares. A past history of Asthma and those with certain acute COVID-19 symptoms were at higher risk.References[1]Saud A, Naveen R, Aggarwal R, Gupta L. COVID-19 and Myositis: What We Know So Far. Curr Rheumatol Rep 2021;23:63.[2]Gokhale Y, Patankar A, Holla U, Shilke M, Kalekar L, Karnik ND, et al. Dermatomyositis during COVID-19 Pandemic (A Case Series): Is there a Cause Effect Relationship? J Assoc Physicians India 2020;68:20–4.[3]Gupta L, Lilleker JB, Agarwal V, Chinoy H, Aggarwal R. COVID-19 and myositis - unique challenges for patients. Rheumatology (Oxford) 2021;60:907–10.[4]Naveen R, Sundaram TG, Agarwal V, Gupta L. Teleconsultation experience with the idiopathic inflammatory myopathies: a prospective observational cohort study during the COVID-19 pandemic. Rheumatol Int 2021;41:67–76.Acknowledgements:NIL.Disclosure of InterestsSa dia Sasha Ali: None declared, Naveen Ravichandran: None declared, Parikshit Sen: None declared, Jessica Day Grant/research support from: JD has received research funding from CSL Limited., Mrudula Joshi: None declared, Sreoshy Saha: None declared, Rohit Aggarwal Consultant of: RA has a consultancy relationship with and/or has received research funding from the following companies: Bristol Myers-Squibb, Pfizer, Genentech, Octapharma, CSL Behring, Mallinckrodt, AstraZeneca, Corbus, Kezar, Abbvie, Janssen, Alexion, Argenx, Q32, EMD-Serono, Boehringer Ingelheim, and Roivant., Grant/research support from: RA has a consultancy relationship with and/or has received research funding from the following companies: Bristol Myers-Squibb, Pfizer, Genentech, Octapharma, CSL Behring, Mallinckrodt, AstraZeneca, Corbus, Kezar, Abbvie, Janssen, Alexion, Argenx, Q32, EMD-Serono, Boehringer Ingelheim, and Roivant., Vikas Agarwal: None declared, Hector Chinoy Speakers bureau: Speaker for UCB, and Biogen. HC was supported by the National Institution for Health Research Manchester Biomedical Research Centre Funding Scheme., Grant/research support from: Has received grant support from Eli Lilly and UCB, consulting fees from Novartis, Eli Lilly, Orphazyme, Astra Zeneca, Oliver Distler Speakers bureau: OD has consultancy relationships with and/or has received research funding from or has served as a speaker for the following companies in the area of potential treatments for systemic sclerosis and its complications in the last three years: Abbvie, Acceleron, Alcimed, Amgen, AnaMar, Arxx, Baecon, Blade, Bayer, Boehringer Ingelheim, ChemomAb, Corbus, CSL Behring, Galapagos, Glenmark, GSK, Horizon (Curzion), Inventiva, iQvia, Kymera, Lupin, Medac, Medscape, Mitsubishi Tanabe, Novartis, Roche, Roivant, Sanofi, Serodapharm, Topadur and UCB. Patent issued "mir-29 for the treatment of systemic sclerosis” (US8247389, EP2331143)., Consultant of: OD has consultancy relationships with and/or has received research funding from or has served as a speaker for the following companies in the area of potential treatments for systemic sclerosis and its complications in the last three years: Abbvie, Acceleron, Alcimed, Amgen, AnaMar, Arxx, Baecon, Blade, Bayer, Boehringer Ingelheim, ChemomAb, Corbus, CSL Behring, Galapagos, Glenmark, GSK, Horizon (Curzion), Inventiva, iQvia, Kymera, Lupin, Medac, Medscape, Mitsubishi Tanabe, Novartis, Roche, Roivant, Sanofi, Serodapharm, Topadur and UCB. Patent issued "mir-29 for the treatment of systemic sclerosis” (US8247389, EP2331143)., Grant/research support from: OD has consultancy relationships with and/or has received research funding from or has served as a speaker for the following companies in the area of potential treatments for systemic sclerosis and its complications in the last three years: Abbvie, Acceleron, Alcimed, Amgen, AnaMar, Arxx, Baecon, Blade, Bayer, Boehringer Ingelheim, ChemomAb, Corbus, CSL Behring, Galapagos, Glenmark, GSK, Horizon (Curzion), Inventiva, iQvia, Kymera, Lupin, Medac, Medscape, Mitsubishi Tanabe, Novartis, Roche, Roivant, Sanofi, Serodapharm, Topadur and UCB. Patent issued "mir-29 for the treatment of systemic sclerosis” (US8247389, EP2331143)., Carlo Vinicio Caballero: None declared, Carlos Enrique Toro Gutierrez: None declared, Dey Dzifa: None declared, Ashima Makol: None declared, Ai Lyn Tan Speakers bureau: Has received honoraria for advisory boards and speaking for Abbvie, Gilead, Janssen, Lilly, Novartis, Pfizer, and UCB., Consultant of: has received honoraria for advisory boards and speaking for Abbvie, Gilead, Janssen, Lilly, Novartis, Pfizer, and UCB., Samuel Katsuyuki Shinjo: None declared, Vishwesh Agarwal: None declared, Latika Gupta: None declared.
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Introduction: Due to the COVID-19 outbreak, many chronic patients and elective surgical procedures have been postponed to create spaces for the hospitalization of COVID-19 patients, raising issues related to this change. The objective of this study is to assess the effect of the COVID-19 pandemic on the demand for blood products transfusion. Materials ant methods: The study presents the results of a retrospective study of blood transfusions in COVID-19 patients admitted to the Constanta County Emergency Clinical Hospital. The period of study was January-December 2021. We compared the transfusion requirement for each type of blood component in COVID 19 patients versus patients with non-COVID pathology. Results and discussions: During 2021, we transfused 282 COVID-19 patients;150 patients had only Covid pneumonia (of which 19 patients with severe forms needed intensive care in ICU-Covid), and 132 patients had various co-morbidities. The maximum blood requests was registered in the period February - April 2021, with a peak of 63 patients in April 2021. The main co-morbidities in patients with Covid 19 were: severe anemia in patients with malignant hemopathies. Anemia at admission in patients with Covid pneumonia is reported in more than 40% of patients. Moderate anemia (Hb <11 g/dL) is considered as an independent risk factor for the severe course of COVID-19 infection and mortality in these patients. The transfusion requirement in these patients was greater than 1.43 RBC (units/patient), 0.81 Plasma units/patient, 0.40 Platelets concentrate units + single donor platelet concentrate units/patient, in accordance with the associated pathology. Conclusion(s): The most requested product was packed red blood cells, the correction of anaemia being an important factor in preventing the severe course of the disease. The platelet requirement was 0.15 units/patient, thrombocytopenia being present in patients with severe evolution of the infection (hospitalized in ICU-COVID). The most requested blood groups were O+ and A+. COVID-19 transfusion data will help plan and prepare for the use of blood resources during the pandemic.Copyright © 2022 Sevigean Ali et al., published by Sciendo.
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The unprecedented outbreak of Covid-19 and the suspension of classes while continuing teaching created disruption and a situation that added considerable stress not only to the management of technical and vocational institutions but also to teachers, trainers and students and their ability to cope with the situation. The shift to online teaching platforms rather than face-to-face learning caused emotional and physical consequences that affect the ability of teachers and trainers to achieve course objectives. This paper identifies and examines the emotional and physical consequences resulting from the use of online teaching platforms on teachers, trainers and students, in addition to examining the quality of online teaching platforms in achieving course objectives. The research involves designing, testing, and distributing questionnaires to a sample of teachers, trainers, and students as well as meeting with the Dean of the College of Technological Studies. The findings of this research revealed that teachers and trainers are more vulnerable to stress, and this can have a significant effect on teachers and trainers psychological and physical health and triggers emotional and physical consequences. In respect to students' perception towards the effectiveness of applying online teaching platforms, the majority of students were disagreed that online teaching platforms helped in gaining the required skills, understanding cases studies and understanding the course topics. Thus, the management of the College of Technological Studies must ensure that teachers and trainers are well equipped with the required knowledge, skills and attitudes to overcome and/or reduce the consequences resulting from the use of online teaching platforms. Copyright for this article is retained by the author(s).
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Background and Purpose: A significant part of the "post-acute COVID-19 syndrome" that may significantly aggravate patients' clinical history is pulmonary fibrosis (PF), a pathological result of chronic and acute interstitial lung illnesses linked to impaired wound repair. Despite being inconclusive, the information that is currently available suggests that more than a third of COVID-19 hospital patients experience aberrant lung fibrosis after leaving the hospital. The current study's goal is to ascertain if pulmonary fibrosis and COVID-19 susceptibility are related. Material(s) and Method(s): The Al-Amal Hospital provided data on coronavirus infections. Regarding Pulmonary Fibrosis, Age, and Gender in the Najaf Province in 2022. The results were evaluated using the Statistical Analysis System application's Chi-squared test (SPSS). Result(s): In the study results of our study were as follows, where it was found that (11.21%) of the total patients in the age group 18-25 are prone to suffering from pulmonary fibrosis, while (20%) of the age group were 25-36, and also found that (29.08%, 45.74% and 31.19%) for the following age groups, respectively: 36-47y, 47-57y and 57-67y. Finally, it was found that 117 (26.77%) patients out of 320 suffer from pulmonary fibrosis symptoms of the age group 67-77 years, where it formed a significant difference compared with the rest of the age groups. Conclusion(s): There is a link between infection with COVID 19 and pulmonary fibrosis, among other conditions. However, our study shows that severe COVID-19 is linked with considerable respiratory symptoms and morbidity, in-cluding dyspnea, which was reported by many survivors. There is an urgent need for more research to understand the connection more generally and to identify therapies that might help prevent similar lung infections in the future.Copyright © 2023, Colegio de Farmaceuticos de la Provincia de Buenos Aires. All rights reserved.
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Background: This study investigates the clinical characteristics of the first confirmed cases of Coronavirus disease-2019 (COVID-19) in Bahrain. Methods: This is a retrospective, cross-sectional study including the first 247 confirmed cases in Bahrain. Demographic, clinical, and laboratory data were extracted from electronic medical records. Results: Mean Standard Deviation (SD) age of patients was 44.15 (16.5) years. More males were affected by the disease (61%;151/274). Mean (SD) of the duration between confirmation and discharge was 9.8 (5.1) days. Of 247 patients, 4 deaths were reported (1.6%);17.5% (24/137) showed a temperature of >37- on admission, with 4% (6/148) yielding an oxygen saturation of 94% or less. Leukopenia was reported in 36.8% of patients (63/171). One quarter of patients (25.5%) received oseltamivir, 24.7% received hydroxychloroquine sulfate (24.7%), and 1.2% received steroids. Conclusion: In this study, the authors have captured the epidemiological and clinical profiles of the first cases of COVID-19 pertaining to the first wave of the pandemic in Bahrain. The early strict measures may have contributed to the lower incidence as well as lower morbidity and mortality of COVID-19 infection in Bahrain. Major gaps in our knowledge of the clinical spectrum of COVID-19 and its prognosis, outcomes, and associated risk factors indicate the need for further research.
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The healthcare industry, as well as business and society, have been revolutionized by Artificial Intelligence (AI) and Machine Learning (ML). Currently, microbiology, biochemistry, genetics, structural biology, and immunological concepts have all seen significant advances. In contrast, the fields of bioinformatics have seen considerable expansion in order to handle this massive data influx. The field of bioinformatics, which tries to use computational methods for a better understanding of biological sciences, sits at the crossroads of data science and wet lab. Several innovative databases and computational techniques have been proposed in this sector to advance immunology research, with many of them relying on artificial intelligence and machine learning to anticipate complicated immune system activities, such as epitope identification for lymphocytes. Models based on machine learning skilled on specific proteins have provided inexpensive and quick-to-implement strategies for the discovery of effective viral treatments in the recent decade. Given a target biomolecule, these models can predict inhibitor candidates using structural data. The emergence of the coronavirus COVID-19 has resulted in significant network data traffic and resource optimization demands, rendering standard network designs incapable of dealing calmly with COVID-19's consequences. Researchers are encouraged by the use of Machine Learning (ML) and Artificial Intelligence (AI) in previous epidemics, which offers a novel strategy to combating the latest COVID-19 pandemic. © 2023 Scrivener Publishing LLC.
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Social media has become a source of information for many people because of its freedom of use. As a result, fake news spread quickly and easily, regardless of its credibility, especially over the past decade. The vast amount of information being shared has fraudulent practices that negatively affect readers' cognitive abilities and mental health. In this study, we aim to introduce a new Arabic COVID-19 dataset for fake news related to COVID-19 from Twitter and Facebook. Afterward, we applied two pre-Trained models of classification AraBERT and BERT base Arabic. As a result, AraBERT models obtained better accuracy than BERT base Arabic in two datasets. © 2022 IEEE.
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Herein, we present an experimental and theoretical drug–drug interaction study between nitazoxanide (NTZ) and azithromycin (AZT) in an aqueous solution. Interaction was studied by using UV/Vis, fluorescence, attenuated total reflectance-fourier transform infrared (ATR-FTIR), and circular dichroism (CD) spectroscopy, while molecular docking studies were performed to establish the interaction computationally. A bright yellow color was observed when the two drugs interacted, giving a hyperchromic band at 420 nm. The rate of absorbance was linearly increased by increasing drug concentrations and in a time-dependent manner. Stability of the interaction complex (i.e., NTZ: AZT) was measured at variable temperatures (25–80°C), pH (5.0–10.0) and ionic strength (0.05–2.0 M NaCl), and not only proved stable but also retained antimicrobial potential with reduced cellular toxicity. Mole ratio and Job's method of continuous variations were used to establish the binding stoichiometry and found to be 2:1. The calculated binding constant (kb = 8,400 M−1) and Gibb's free energy (ΔG° = −22.4 KJ/mol) also suggested an energetically favorable interaction. FTIR spectra of NTZ: AZT complex in comparison with two drugs alone revealed significant interaction which was nicely complemented by molecular docking studies. Interaction was also successfully demonstrated in presence of carrier protein HSA and by spiking the two drugs in real samples of human plasma and urine. © 2023 The Chemical Society Located in Taipei & Wiley-VCH GmbH.
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Seven human coronaviruses have been identified so far: four seasonal coronaviruses (HCoV-229E, HCoV-OC43, HCoV-NL63, HCoV-HKU1) and three novel coronaviruses (SARS-CoV, MERS-CoV, SARS-CoV-2). While seasonal coronaviruses cause only mild symptoms, novel coronaviruses cause severe and potentially fatal infections. All known coronaviruses originated in animals. Bats are considered as an origin for the majority of coronaviruses capable of infecting humans;however, rodents are proposed as natural hosts for HCoV-OC43 and HCoV-HKU1. Different animal species could serve as intermediate hosts including alpacas (HCoV-229E), livestock (HCoV-OC43), civet cats (SARS-CoV), camels (MERS-CoV), and pangolins (SARS-CoV-2). In Croatia, SARS-CoV-2 was detected in humans, pet animals, wildlife, and the environment. The COVID-19 pandemic has highlighted the role of the 'One Health' approach in the surveillance of zoonotic diseases.Copyright © 2022, University Hospital of Infectious Diseases. All rights reserved.
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In the originally published version of this manuscript, 5 authors were inadvertently omitted: Dr Saad Islam, MBChB, Barts Health NHS Trust, Orthopaedics Dr Adil Hasnain MD, Barts Health NHS Trust, Orthopaedics Mr Shahanoor Ali, MBChB, Barts Health NHS Trust, Orthopaedics Mr Hassan Raja, MBChB, Barts Health NHS Trust, Orthopaedics Mr Konstantinos Tsitskaris, MD MSc FRCS(ortho), Barts Health NHS Trust, Orthopaedics This error has now been corrected.Copyright © The Author(s) 2022. Published by Oxford University Press on behalf of BJS Society Ltd. All rights reserved.
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Background: Coronavirus disease 2019 (COVID-19) is a rapidly spreading global emergency, causing significant damage to the global economy and health care. Knowledge and awareness are crucial elements in stimulating self-imposed preventive measures. Objectives: We evaluated the knowledge and awareness about COVID-19 and the practice of hygiene measures to prevent the spread of coronavirus disease. Methods: A prospective observational study was conducted in Karachi, Pakistan, between March 01 and March 25, 2020, using a non-probability consecutive sampling technique. All individuals aged 18 years or above were included in the study. The individuals who had no formal education were excluded from the study. A self-reported questionnaire assessing knowledge, awareness, and practices was distributed among the participants. Results: The mean age +or- SD of the study population was 29.11 +or- 7.8 years. In our study, 424 (98.6%) participants knew that a virus causes COVID-19, and most were knowledgeable about the disease's transmission mode. Higher education status and the medical profession were associated with the better practice of preventive measures. Conclusions: We recommend that knowledge about COVID-19 and preventive measures be spread across the country via electronic media.
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There is a tremendous demand on the critical care resources due to the extensive spread of the ongoing coronavirus pandemic and the large number of patients requiring critical care. The efficacy of a device directly influences how long a patient lives since patients are often receiving critical care. Smart infusion pump is a medical device that can drip fluids into the patient's body. This device is considered as one of the most safety-critical medical devices due to the way it functions and the risks it presents. The main objective of this work is to develop an affordable infusion pump usin g embedded technology. The main tactic is to develop equipment that can identify air bubbles in infusion pump tubing since even a little one might obstruct blood flow and result in mortality. This method may provide consumers an accurate result, making it the greatest method for identifying bubbles and saving lives.
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Despite numerous recommendations concerning individual and social preventive measures, including quarantine, wearing a mask, physical distancing, and handwashing, vaccination with effective and safe vaccines is still the most effective measure to break the chain of coronavirus SARS-Co2 transmission;still, vaccine hesitancy is a significant barrier to achieve high vaccination coverage against infectious diseases. An observational cross-sectional study was conducted among students of different universities (medical and non-medical) in Baghdad city Iraq using an online structured google form questionnaire from October 20 to November 20, 2021, and a final number of 658 students were included in the study. Causes of acceptance and rejection of the coronavirus vaccine were tested through the questionnaire. Of the total 658 participants, 557(84.7%) had received the vaccine before the start of the study and only 101 (15.3%) were not vaccinated;of them, more than half, 58(57.4%) were willing to, and the remaining 43(42.6%) refused to receive COVID-19 vaccination. Accordingly, the acceptance rate of the vaccine among the total participants was 93.5%, and the rejection rate was only 6.5%. The most chosen cause of vaccine acceptance was that they believed the vaccine protected them, their families and the community against COVID-19 infection and its complications with 63.5%. The most chosen rejection cause was fear of side effects of the vaccine, with 62% of the rejecting participants, followed by 28% having doubts about the vaccine's efficiency in protecting against COVID-19 infection. In this study, although the majority of the participants were willing to be vaccinated, still around one-third of them were under pressure from the government obligations and did not accept the vaccine due to their own convictions;education programs should be designed and directed to remove barriers to negative vaccine beliefs and perception to increase the vaccine coverage in the community. © 2022 by the authors.
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Background The transmission dynamics of influenza were affected by public health and social measures (PHSMs) implemented globally since early 2020 to mitigate the COVID-19 pandemic. We aimed to assess the effect of COVID-19 PHSMs on the transmissibility of influenza viruses and to predict upcoming influenza epidemics. Methods For this modelling study, we used surveillance data on influenza virus activity for 11 different locations and countries in 2017-22. We implemented a data-driven mechanistic predictive modelling framework to predict future influenza seasons on the basis of pre-COVID-19 dynamics and the effect of PHSMs during the COVID-19 pandemic. We simulated the potential excess burden of upcoming influenza epidemics in terms of fold rise in peak magnitude and epidemic size compared with pre-COVID-19 levels. We also examined how a proactive influenza vaccination programme could mitigate this effect. Findings We estimated that COVID-19 PHSMs reduced influenza transmissibility by a maximum of 17.3% (95% CI 13.3-21.4) to 40.6% (35.2-45.9) and attack rate by 5.1% (1.5-7.2) to 24.8% (20.8-27.5) in the 2019-20 influenza season. We estimated a 10-60% increase in the population susceptibility for influenza, which might lead to a maximum of 1-5-fold rise in peak magnitude and 1-4-fold rise in epidemic size for the upcoming 2022-23 influenza season across locations, with a significantly higher fold rise in Singapore and Taiwan. The infection burden could be mitigated by additional proactive one-off influenza vaccination programmes. Interpretation Our results suggest the potential for substantial increases in infection burden in upcoming influenza seasons across the globe. Strengthening influenza vaccination programmes is the best preventive measure to reduce the effect of influenza virus infections in the community. Copyright (C) 2022 The Author(s). Published by Elsevier Ltd.
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The extensive existence about COVID-19 diseases has led to global initiatives to regulate and manage the virus with the goal of eradicating it. Machine Learning (ML) is one key for analyzing and combating COVID-19 in line with research. This is a hotly debated topic right now. Even though numerous studies are in line with medical literature, there is a requirement to follow maintain with fast-increasing quantity of papers on ML applications connected to COVID-19. Day-to-day information on the COVID-19 virus's transmission is critical for assessing the virus's global behavior. As a result, in the state of COVID-19, this paper examines forecasting methods for COVID-19 affected instances utilizing existing machine learning methods. Most of the ML algorithms used in the early detection and diagnosis of contagion are guided learning methods. The prognosis features reported by ML models are in line with medical literature findings. Many of the relevant studies are still in their early phases. One of the limitations of machine learning approaches is the use of unbalanced datasets exposed to bias in selection. © 2023 Author(s).
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Objective: The current study was conducted to determine whether people will keep practicing physical distancing behavior as part of their daily lives after the end of the COVID-19 pandemic. Material(s) and Method(s): A structured questionnaire was prepared online using "Question Pro" software for surveys, and the study was conducted electronically. The questionnaire for the study had two components, the first was related to the partic-ipant's demographics, and the other was about physical distancing questions. There were 16 questions in total. Result(s): Women were more fearful/careful and would want to limit socializing than men. The religious aspect is one primary reason people will be willing to avoid physical distancing. Physical distancing was more acceptable to people with higher education levels. This physical distancing trend might affect the public transportation and tourism industry. Conclusion(s): This study showed that the female gender and population with higher education are willing to follow better ad-herence to SOPs of the COVID-19 pandemic.Copyright © 2023, Khyber Medical College. All rights reserved.
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Tuberculosis (TB), one of the deadliest contagious diseases, is a major concern worldwide. Long-term treatment, a high pill burden, limited compliance, and strict administration schedules are all variables that contribute to the development of MDR and XDR tuberculosis patients. The rise of multidrug-resistant strains and a scarcity of anti-TB medications pose a threat to TB control in the future. As a result, a strong and effective system is required to overcome technological limitations and improve the efficacy of therapeutic medications, which is still a huge problem for pharmacological technology. Nanotechnology offers an interesting opportunity for accurate identification of mycobacterial strains and improved medication treatment possibilities for tuberculosis. Nano medicine in tuberculosis is an emerging research field that provides the possibility of efficient medication delivery using nanoparticles and a decrease in drug dosages and adverse effects to boost patient compliance with therapy and recovery. Due to their fascinating characteristics, this strategy is useful in overcoming the abnormalities associated with traditional therapy and leads to some optimization of the therapeutic impact. It also decreases the dosing frequency and eliminates the problem of low compliance. To develop modern diagnosis techniques, upgraded treatment, and possible prevention of tuberculosis, the nanoparticle-based tests have demonstrated considerable advances. The literature search was conducted using Scopus, PubMed, Google Scholar, and Elsevier databases only. This article examines the possibility of employing nanotechnology for TB diagnosis, nanotechnology-based medicine delivery systems, and prevention for the successful elimination of TB illnesses.