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Tackling with Covid-19 dilemma of vaccine distribution needed a stack of analysis and examination. This paper develops a generalizable framework for designing a hub vaccination dispensing network to achieve expand the Covid-19 vaccination coverage for public. Designing a hub location routing network for vaccine distribution is the main concern for this research. The proposed model hinges on maximum coverage and patients' safety by considering high-priority population alongside the cost reduction in an uncertain environment. The hub location model enhances the accessibility of the vaccines to various communities and helps to overcome the challenges. The results of this model were examined through both numerical and case studies in the north of Tehran to demonstrate its application. Furthermore, in order to reduce the costs of vaccine imports, vaccine entry routing can be developed from border and air points to the country in order to be able to perform vaccination in the fastest time and lowest cost in the future. The results concede that increasing the number of outreach dispensing locations per hub dispensing location will not necessarily result in increased coverage.
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Background: There has been a rampant increase in substance abuse in Kashmir valley for the last few years. Department of Psychiatry SKIMS Medical College Srinagar has extended its services to cater to the needs of the substance users in the valley even during the COVID -19 pandemic. In 2021, de-addiction services were also started among prison inmates of central jail Srinagar. This was the first of its kind of services provided in the valley. The management of substance users with Hepatitis infections had also been challenging. Purpose(s): To describe the management of substance users under special circumstances(COVID-19), special settings(Central Jail Srinagar), high-risk groups(substance users with blood-borne infections). Method(s): Semi-structured proformas were used to collect data from special groups of participants a) those who were seeking treatment during COVID-19 times from the De-addiction center, SKIMS Medical College b) Prison in-mates on treatment for substance-use disorders c) substance users who are hepatitis B and/or positive. This included Socio-demographic details, clinical profile, the pattern of substance use, coping strategies, and treatment seeking. Preliminary Findings: More than 25 percent of the prison in-mates are substance dependent and relapse rate is very high. Psychiatric comorbidity like mood disorders and or personality disorders are present among most of the prison-inmates. During COVID-19 times, 90% patients reported average to very high level of importance and value given to their own health and health of family and friends and focussed on treatment of their illness(85%). Substance users with blood-borne infections were associated with highrisk behavior in the form of needle-sharing. Conclusion(s): The findings provide a voice that there is a need for backup plans that cater to the needs of substance users during in-evitable circumstances like the COVID-19 pandemic. Policymakers should focus on prison mental health for the functioning of a better society. Substance users with blood-borne infections should be rigorously treated to prevent them from taking the shape of an epidemic.
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Drug repurposing is an unconventional approach that is used to investigate new therapeutic aids of existing and shelved drugs. Recent advancement in technologies and the availability of the data of genomics, proteomics, transcriptomics, etc., and with the accessibility of large and reliable database resources, there are abundantly of opportunities to discover drugs by drug repurposing in an efficient manner. The recent pandemic of SARS-COV-2, that caused the death of 6,245,750 human beings to date, has tremendously increase the exceptional usage of bioinformatics tools in interpreting the molecular characterizations of viral infections. In this paper, we have employed various bioinformatics tools such as AutoDock-Vina, PyMol etc. We have found a leading drug candidate Cepharanthine (CEP) that has shown better results and effectiveness than recently used antiviral drug candidates such as Favipiravir, IDX184, Remedesivir, Ribavirin and etc. This paper has analyzed CEP's potential therapeutic importance as a drug of choice in managing COVID-19 cases. It is anticipated that proposed study would be beneficial for researchers and medical practitioners in handling SARS-CoV-2 and its variant related diseases. © 2022 IEEE.
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The pandemic caused by the coronavirus SARS-COVID-2 has had devastating impact on the world. It has caused a significant number of deaths across the world. Fast spread and lack of vaccine prompted academia to adopt new, fast and reliable methodologies to design new drugs. A combined approach of direct drug design and indirect drug design has been used for molecular docking. In the study, we found a compound, Vilazodone, with a binding energy of -8.40 kcal/mol. The druglikeness properties of this compound are investigated through SWISS ADMET analysis. In this in-silico study, we confirmed this compound is a potential drug candidate against SARS-CoV-2.However, in-vitro and in-vivo studies are required to prove its efficacy. © 2022 IEEE.
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Drug repurposing is the technique of finding new uses for currently used or under-researched drugs. Because this strategy requires less time and money, it is thought to be a particularly effective drug development strategy. Due to current technological breakthroughs, the accessibility of vast and reliable database resources, as well as data accessibility from genomes, proteomics, transcriptomics, etc., there are numerous opportunities to identify drugs by drug repurposing. The recent SARS-COV-2 epidemic, which has so far claimed 6,245,750 lives, has significantly increased the use of bioinformatics techniques in deciphering the characteristics of viral diseases. Using FDA-approved antiviral drugs that target the COVID-19 spike protein, we have used a bioinformatics approach to drug repurposing to find possible effective inhibitors against the Coronavirus (COVID-19). We used a variety of bioinformatics tools in this study, including AutoDock-Vina, PyMol, and Discovery Studio, to identify a promising drug called Cepharanthine (CEP), which demonstrates successful outcomes and efficacy compared to recently used antiviral drug candidates like arbidol, talampicillin, bromhexine, chloroquine, lycorine, bruceine A, reserpine, indinavir, galidesiver, doxycycline, methisazone, flupentixol, trifluoperazine and fluoxetine. The potential therapeutic value of cepharanthine as a drug for treating COVID-19 has been investigated in this study. It is expected that the proposed study will help medical professionals and researchers cure disorders linked to Severe acute respiratory and variations of it. © 2022 IEEE.
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Hydrocortisone (termed as D1) and dexamethasone (termed as D2) are corticosteroids currently used to treat COVID-19. COVID-19 is a disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Exploring additional chemical properties of drugs used in the treatment protocols for COVID-19 could help scientists alike improve these treatment protocols and potentially even the vaccines (i.e., Janssen, Moderna, AstraZeneca, Pfizer-BioNTech). In this work, the charge-transfer (CT) properties of these two corticosteroids (D1 and D2) with two universal acceptors: 7,8,8-tetracyanoquinodimethane (termed as TCNQ) and fluoranil (termed as TFQ) in five different solvents were investigated. The examined solvents were MeOH, EtOH, MeCN, CH2Cl2, and CHCl3. The CT interactions formed stable corticosteroid CT complexes in all examined solvents. Several spectroscopic parameters were derived, and the oscillator strength (f) and transition dipole moment (µe.g. ) values revealed that the interaction between the investigated corticosteroids with TCNQ acceptor is much stronger than their interaction with TFQ acceptor. The CT interactions were proposed to process via n â π* transition.
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Aim: The knowledge of viral characteristics in addition immune reply to severe respiratory disorder (Sars Syndrome Coronavirus 2 (SARS-CoV-2) contamination still has significant gaps. Methods: In a retrospective longitudinal cohort analysis of 140 cases having PCR-established SARS-CoV-2 disease, researchers analyzed those parameters and demonstrated their correlation with symptom manifestations (mean age, 44 years;54 percent male;48 percent through comorbidities). Breathing models (n = 76) remained obtained for viral culture, serum specimens (n = 32) for IgM/IgG levels, and plasma samples (n = 82) for inflammatory cytokines and chemokines. The illness burden remained connected to the findings of viral culture, serologic tests, also immunological markers. Results: Fifty-eight (58%) cases established viral pneumonia, including 22 (18%) requiring supplementary oxygen and 14 (11%) requiring invasive mechanical ventilation. Twenty of the 77 individuals were positive for viral culture from respiratory samples (24 percent). When the PCR cycle threshold (Ct) value remained more than 31 or greater than 15 days following indication onset, no virus was recovered. Seroconversion happened at a median (IQR) of 13.6 (10-20) days for IgM and 16.1 (14-22) days for IgG;56/63 patients (88.2 percent) seroconverted on day 15 or later. Health hazard appeared linked to quicker seroconversion as well as greater peak IgM and IgG levels. Conclusion: Researchers discovered that viral viability significantly related having such a lower PCR Ct charge in the initial stages of disease. The seriousness of the illness was linked to a greater antibody level. Overcharged pro-inflammatory immune markers provide marks for host-directed immunotherapy, that would have been investigated in randomized precise studies.
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Quinine (QN), chloroquine (CQ), and hydroxychloroquine (HCQ) belong to the 4-aminoquinoline family. QN was used to treat the Spanish Flu, while CQ and HCQ are under consideration for the treatment of COVID-19. This work aimed to investigate the charge-transfer (CT) interaction between QN compound with five acceptor molecules: iodine crystals (A1), 7,7,8,8-tetracyanoquinodimethane (A2), 2,3-dichloro-5,6-dicyano-p-benzoquinone (A3), chloranilic acid (A4), and tetrafluoro-1,4-benzoquinone (A5). The experimental results indicated that QN formed stable and vividly colored CT complexes with these acceptors. Strong color changes occurred upon complexation in both liquid and solid forms. The analytical findings suggest that QN reacted with the A2, A3, A4 and A5 acceptors at a 1:1 molar ratio and a 1:2 ratio with A1 acceptor. The charge migration occurred from QN to A1 via the formation of a tri-iodide complex, while the charge migration occurred from QN to A2, A3, A4, and A5 acceptors through an n → π* interaction.
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Coronavirus disease is an infectious disease caused by the newly discovered coronavirus. Most people infected with the Coronavirus disease have difficulty breathing. Some patients who underwent radiographic tests had changes in their lungs. There are many methods to detect people who have contracted the COVID-19. One alternative method proposed is to perform automatic diagnostics through x-ray images. To perform automation, a model is needed to classify patients with COVID-19 and normal. One of the training methods for creating classifiers is deep learning, but deep learning method needs a huge amount of annotated data. Therefore, the transfer learning method is used by using an existing model, then back again with the desired data. The model used is Xception, InceptionV3 and MobileNetv3. This study produces accuracy of 91% on model trained with Xception, 89% accuracy on model trained with InceptionV3, and 86% accuracy on model trained with MobileNetV3.
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COVID-19 is the disease caused by a novel coronavirus (CoV) named the severe acute respiratory syndrome coronavirus 2 (termed SARS coronavirus 2 or SARS-CoV-2). Since the first case reported in December 2019, infections caused by this novel virus have led to a continuous global pandemic that has placed an unprecedented burden on health, economic, and social systems worldwide. In response, multiple therapeutic options have been developed to stop this pandemic. One of these options is based on traditional corticosteroids, however, chemical modifications to enhance their efficacy remain largely unexplored. Obtaining additional insight into the chemical and physical properties of pharmacologically effective drugs used to combat COVID-19 will help physicians and researchers alike to improve current treatments and vaccines (i.e., Pfizer-BioNTech, AstraZeneca, Moderna, Janssen). Herein, we examined the charge-transfer properties of two corticosteroids used as adjunctive therapies in the treatment of COVID-19, hydrocortisone and dexamethasone, as donors with 2,3-dichloro-5,6-dicyano-p-benzoquinone as an acceptor in various solvents. We found that the examined donors reacted strongly with the acceptor in CH2Cl2 and CHCl3 solvents to create stable compounds with novel clinical potential.
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The current study aims to investigate the influence of budget-hotels' environmental orientation (EO) on their eco-innovation (EI) and environmental performance (EP). Besides empirically testing the said direct relationship, mediating role of EI in the relationship between EO and EP has also been investigated. Moderating effect of competitive intensity (CI) of the firm has also been examined on the link between EI and EP. The requisite data for this study was collected from 422 individuals, working on various managerial positions in the budget-hotels in Pakistan. Correlation, path analysis, structural equation modelling and hierarchical regression were used for the purpose of data analysis. Data analysis using SPSS and AMOS reveals a direct effect of EO on EI and EP. Moreover, the results substantiated that EI mediates between EO and EP. Moderating effect of CI on the link between EI and EP has also been confirmed. The study advocates new mechanisms which would be helpful in protecting natural environment. In the context of budget hotel segment of hospitality industry of Pakistan, the present study makes significant contribution to the literature through knowledge addition regarding the positive association of EO and EI © 2021,Pakistan Journal of Commerce and Social Sciences.All Rights Reserved
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BACKGROUND: Several different types of vaccines have been developed for the prevention of coronavirus disease (COVID-19). Despite several local and systemic side-effects to COVID-19 vaccination reported, the vaccines are still considered the best intervention to tackle the spread of the virus and reduce the severity of COVID-19 infection. However, the reported side-effects continue to have a crucial role in public confidence in the vaccine and its acceptance. This study aimed to investigate the short-term side-effects reported by the healthcare workers (HCWs) in Saudi Arabia after receiving the first dose of the Oxford/AstraZeneca (ChAdOx1 nCoV-19) COVID-19 vaccine. METHODS: A prospective cohort study was conducted among HCWs in the Jazan region of southwestern Saudi Arabia. Healthcare workers who had received the first dose of the COVID-19 vaccine and agreed to participate in the study were followed up for 3 weeks post vaccination through a weekly online survey. Information was collected on local and/or systemic side-effects reported following vaccine administration. Participants' general and demographic information was also collected. RESULTS: A total of 57.2% (250/437) of the HCWs who participated in this study reported at least one side-effect. Injection site pain and redness (80.0%), fever (73.2%), whole-body pain/fatigue (56.4%), and headache (48.8%) were the most commonly reported side-effects. Moreover, 12.4% of the participants who reported side-effects needed to see a physician, and only one female participant was admitted to the hospital. Multivariate regression analyses revealed that nationality (Saudi, adjusted odds ratio (aOR) = 3.65; 95% CI = 2.40, 5.55) and residency (Jazan governorate, aOR = 0.38; 95% CI = 0.15, 0.95) were the significant factors associated with reporting COVID-19 post-vaccination side-effects, while the number of reported side-effects was found to be significantly influenced by occupation (medical, aOR = 0.42; 95% CI = 0.26, 0.66; p < 0.001) and gender (female, aOR = 0.61; 95% CI = 0.38, 0.97; p = 0.038). CONCLUSIONS: Findings of the present study support the safety of the Oxford/AstraZeneca COVID-19 vaccine among HCWs in Saudi Arabia. All the reported side-effects were mild-to-moderate side-effects. The findings may help convince vaccine-hesitant individuals and skeptics to accept the COVID-19 vaccine.
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There is limited data from Arabic-speaking countries on risk factors for depression and anxiety during the COVID-19 pandemic. Country-specific data is necessary given differences in culture, demographics, and COVID-19 infection and mortality rates. The main purpose of the study is to identify the factors associated with symptoms of depression-anxiety in the adult population of Qatar during the first year of the COVID-19 pandemic. We conducted a cross-sectional online survey in Qatar between July and December 2020 after Qatar’s first COVID-19 wave and before the beginning of the second wave. Depression-anxiety was defined as a cut-off of 20 or higher on the Patient Health Questionnaire-Anxiety Depression Scale (PHQ-ADS). Of 1138 participants, 71.0% were female, 69.0% Arabs, 70.0% Non-Qataris, and 77.0% were < 40 years (the median age in Qatar is 32 years). In a fully-adjusted model, six variables were significantly associated with moderate-to-severe levels of depression or anxiety on the PHQ-ADS;Arab ethnicity (OR = 1.67, p = 0.026), never married versus married (OR = 1.69, p = 0.015), prior history of psychiatric disorder versus no history (OR = 1.80, p = 0.009), increased worries due to social media use for COVID-related news/updates (OR = 1.72, p = 0.003), a history of COVID-19 (OR = 1.76, p = 0.039), loneliness (OR = 1.91, p < 0.001), and lower levels of religiosity (OR = 0.96, p = 0.039). These associations also pertained in the reduced model, with the exception of religiosity which was only marginally statistically significant (OR = 0.97, p = 0.055). The potential risk factors identified may assist with anxiety and depression prevention in future COVID-19 waves, and similar national events, and assist with early intervention to treat sufferers.
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Coronavirus infection (SARS-CoV-2), is a pandemic disease declared by the World Health Organization (WHO). This disease reports a high risk of contagion, especially by the transmission of aerosols in health care workers. In this scenario, aerosol exposure is increased in various procedures related to the airway, lungs, and pleural space. For this reason, it is important to have recommendations that reduce the risk of exposure and infection with COVID-19. In this document, a team of international specialists in interventional pulmonology elaborated a series of recommendations, based on the available evidence to define the risk stratification, diagnostic methods and technical considerations on procedures such as bronchoscopy, tracheostomy, and pleural procedures among others. As well as the precautions to reduce the risk of contagion when carrying out pulmonary interventions.
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Finding a cure or vaccine for the coronavirus disease (COVID-19) is the most pressing issue facing the world in 2020 and 2021. One of the more promising current treatment protocols is based on the antibiotic azithromycin (AZM) alone or in combination with other drugs (e.g., chloroquine, hydroxychloroquine). We believe gaining new insight into the charge-transfer (CT) chemistry of this antibiotic will help researchers and physicians alike to improve these treatment protocols. Therefore, in this work, we examine the CT interaction between AZM (donor) and tetracyanoethylene (TCNE, acceptor) in either solid or liquid forms. We found that, for both phases of starting materials, AZM reacted strongly with TCNE to produce a colored, stable complex with 1:2 AZM to TCNE stoichiometry via a nâ¯ââ¯π* transition (AZMâ¯ââ¯TCNE). Even though both methodologies yielded the same product, we recommend the solid-solid interaction since it is more straightforward, environmentally friendly, and cost- and time-effective.
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INTRODUCTION: The COVID-19 pandemic represents a global and nationwide public health crisis. Although protective, socially restrictive measures may cause social isolation, which amounts to an increased ecological risk for mental health disturbance in vulnerable populations. Previous reports have suggested a significant association between the occurrence of public health crises and increased rates of multiple risk factors related to child mental health disturbances, domestic violence, and child-maltreatment. METHODOLOGY: We conducted a retrospective data review of reported child maltreatment cases from the National Family Safety Program during the period of September 2019 to September 2020. A descriptive analysis approach was used to compare rates before and during the COVID-19 pandemic. RESULTS: During COVID-19, abuse was significantly more reported by a family member than by the victims themselves or by a healthcare worker. However, before COVID-19, the offender was less often reported to be known to the victim; was both parents or the mother but was more often described as male, older, single, less educated; and currently unemployed with no significant change observed in their health status (p < 0.001). Interestingly, the predicted type of abuse also significantly differed and was more emotional or sexual than other types (p < 0.001). CONCLUSION: The types of abuse and the characteristics of both abused children and offenders saw significant changes during the COVID-19 pandemic. Sexual and emotional abuses were reported more frequently, and the male gender is considered to feature more commonly in reports prior to the pandemic era than during the pandemic.
Subject(s)
COVID-19 , Child , Humans , Male , Pandemics , Retrospective Studies , SARS-CoV-2 , Saudi ArabiaABSTRACT
Background: Given the devastating impact that COVID-19 can have on the lung, it is reasonable to fear for patients with underlying chronic lung conditions. Recent studies have shown that there is an excess risk of contracting the infection, as well as developing severe symptoms and worst outcomes for some of these conditions. We present a single center experience of the characteristics and outcomes of patients admitted due to with confirmed SARS-CoV-2 infection and chronic lung disease. Methods: Retrospective medical records review of patients with chronic lung conditions (COPD, asthma, interstitial lung disease, pulmonary hypertension, and lung cancer) and SARS-CoV-2 infection between January 1, 2020 and December 1, 2020 at Beth Israel Deaconess Medical Center, Boston, MA. Patients were identified from our institutional database. Demographics, baseline comorbidities, hospital say, ICU admission, and interventions performed were recorded. Results: 12.405 patients were diagnosed with SARS CoV-2 infection at BIDMC. From the total, 961 (7.8%) patients were admitted for further care with an age of 66 years (IQR 52-78), 464 (48.28%) males, and a BMI of 29.8 kg/m2 (IQR 25.8-34.6). Regarding the comorbid conditions, 157 subjects (16.3%) had COPD, 157 (16.3%) asthma, 24 (2.50%) pulmonary hypertension, 14 (1.46%) ILD and 18 (1.87%) lung cancer. We found that patients with COPD (23.57% vs 14.68%, p=0.005) as well as lung cancer (38.89% vs 15.69%, p=0.016) died more often after hospital admission. Additionally, a logistic regression model for mortality showed an OR of 1.8 (95%CI 1.2-2.7, p=0.006) for COPD and an OR of 3.42 (95%CI 1.30-8.96, p=90.012) for lung cancer. Conclusion: Our review showed that patients hospitalized due to SARS CoV-2 infection, and a previous diagnosis of COPD or lung cancer, were more likely to die during the hospital stay. (Table Presented).
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Background: Acute Distress Respiratory Syndrome (ARDS) develops in 42% of patients presenting with COVID19 pneumonia, and 61-81% of those requiring intensive care. Tracheostomy placement is still a subject of controversy due to the poor prognosis of intubated patients and the risk of transmission to health care providers through this highly aerosolizing procedure. In this study we aim to determine the outcomes of tracheostomized patients with ARDS due to COVID-19 and ARDS to non-COVID-19. Methods: We performed a single center retrospective review of patients diagnosed with SARS-CoV-2 and who underwent tracheostomy due to ARDS between January 2020 and November 2020. Patients were identified from our institutional database. Demographics, baseline comorbidities, mortality, intensive care unit (ICU) stay, duration of ventilator requirement, tracheostomy procedure details, complications, and length of stay. Results: The average time from endotracheal intubation to tracheostomy was 25.56 ± 7.58 days and 25.56 ± 6.35 days for SARS-CoV-2 positive and SARS-CoV-2 negative, respectively. In the SARS-CoV-2 positive group, eleven patients (32.4%) were liberated from the ventilator, six (17.6%) were decannulated, and nine (26.5%) remained on MV. In contrast, in the SARS-CoV-2 negative group five patients (27.8%) were liberated from the ventilator, eight (44.4%) were decannulated, and three (16.7%) remained on MV. The median time from tracheostomy to ventilator liberation was 19 days (range 10-41 days) and 32 days (range 24-49 days) for SARS-CoV-2 positive and SARS-CoV-2 negative, respectively. Of patients who were successfully decannulated, the average time to decannulation was 34.17 ± 16.88 days and 42.00 ± 13.01 days for SARS-CoV-2 positive and SARS-CoV-2 negative, respectively. There was no significant difference in mortality between both groups. Conclusions: In patients with ARDS, there are no statistical differences between SARS-CoV-2 positive and SARS-CoV-2 negative patients in terms of mortality, ventilator liberation, and decannulation time.
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The recent COVID-19 pandemic caused by the novel coronavirus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has had a significant impact on human life and the economy around the world. A reverse transcription polymerase chain reaction (RT-PCR) test is used to screen for this disease, but its low sensitivity means that it is not sufficient for early detection and treatment. As RT-PCR is a time-consuming procedure, there is interest in the introduction of automated techniques for diagnosis. Deep learning has a key role to play in the field of medical imaging. The most important issue in this area is the choice of key features. Here, we propose a set of deep learning features based on a system for automated classification of computed tomography (CT) images to identify COVID-19. Initially, this method was used to prepare a database of three classes: Pneumonia, COVID-19, and Healthy. The dataset consisted of 6000 CT images refined by a hybrid contrast stretching approach. In the next step, two advanced deep learning models (ResNet50 and DarkNet53) were fine-tuned and trained through transfer learning. The features were extracted from the second last feature layer of both models and further optimized using a hybrid optimization approach. For each deep model, the Rao-1 algorithm and the PSO algorithm were combined in the hybrid approach. Later, the selected features were merged using the new minimum parallel distance non-redundant (PMDNR) approach. The final fused vector was finally classified using the extreme machine classifier. The experimental process was carried out on a set of prepared data with an overall accuracy of 95.6%. Comparing the different classification algorithms at the different levels of the features demonstrated the reliability of the proposed framework. © 2021 Tech Science Press. All rights reserved.
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Investigating the chemical properties of molecules used to combat the COVID-19 pandemic is of vital and pressing importance. In continuation of works aimed to explore the charge-transfer chemistry of azithromycin, the antibiotic used worldwide to treat COVID-19, the disease resulting from infection with the novel SARS-CoV-2 virus, in this work, a highly efficient, simple, clean, and eco-friendly protocol was used for the facile synthesis of charge-transfer complexes (CTCs) containing azithromycin and three π-acceptors: 7,7,8,8-tetracyanoquinodimethane (TCNQ), 2,3-dichloro-5,6-dicyano-p-benzoquinone (DDQ), and tetrafluoro-1,4-benzoquinone (TFQ). This protocol involves grinding bulk azithromycin as the donor (D) with the investigated acceptors at a 1:1 M ratio at room temperature without any solvent. We found that this protocol is environmentally benign, avoids hazardous organic solvents, and generates the desired CTCs with excellent yield (92-95%) in a straightforward means.