Utility of the Brixia CXR score, C-Reactive Protein and Absolute Neutrophil Count in Predicting the Need for Invasive Mechanical Ventilation, Length of Hospital Stay, and Mortality in Moderate to Severe COVID-19 Patients

Background: The Brixia Chest X-ray (CXR) score, C-reactive protein (CRP), and the absolute neutrophil count (ANC) have been useful to predict outcomes in Coronavirus disease 2019 (COVID-19 patients). We studied the utility of the Brixia CXR score, CRP, and ANC in predicting the outcomes in terms of the need for invasive mechanical ventilation, length of stay, and mortality in moderate-severe COVID-19 patients. Material(s) and Method(s): This was a single-centre, retrospective, study on 122 COVID-19 patients. Brixia CXR score, CRP, and ANC on admission to the hospital and the fifth day of hospital stay were noted along with the need for invasive mechanical ventilation (IMV), prolonged length of stay (LOS) >= 14 days, and mortality. Result(s): 122 patients were included for analysis. The median and interquartile range (IQR) for baseline CRP was 81.50 (39-151) mg/L and 11.0 (4-30) mg/L (p < 0.001) on the fifth day. The median and IQR for baseline Brixia score was 10.0 (7-13), and on the fifth day was 7 (4-11) (p <0.001). The receiver operating characteristic curve (ROC) showed that the baseline CRP >= 52.5mg/L predicted both the need for IMV, with an area under the curve (AUC) of 0.628, and prolonged LOS with an AUC of 0.608. The ROC curve depicted that the baseline ANC >8500/muL predicted IMV requirement with an AUC of 0.657. The fifth day CRP >= 32 mg/L, ANC >= 11,000/ muL and Brixia CXR score >= 7 predicted a higher mortality in hospitalized patients. Conclusion(s): Baseline CRP (> 52.5mg/L) predicts the need for IMV and a prolonged LOS, but not mortality. Baseline ANC (> 8500/muL) predicted the need for IMV. CRP, Brixia CXR score, and ANC on the fifth day were not useful to predict LOS or mortality, though there was a significant reduction in CRP and Brixia CXR score on the fifth day compared to baseline after treatment. The fifth day CRP >= 32 mg/L, ANC >= 11,000/ muL and Brixia CXR score >= 7 predicted a higher mortality.Copyright © 2023, College of Anaesthesiologists of Sri Lanka. All rights reserved.

A Deep Net Model for Covid-19 Detection Based on ROC Analysis Using Radiographs

The European Centre of Disease Prevention & Control's analytical statistics show that the new corona virus (Covid-19) is rapidly spreading amongst millions of people & causing the deaths of thousands of them. Despite the daily increase in cases, there are still a finite quantity of Covid-19 test kits available. The use of an automatic recognition system is crucial for the diagnosis and control of Covid-19. Three important Inception-ResNetV2, InceptionV3, & ResNet50 models of convolutional neural networks are utilized to detect the Corona Virus in lung X-ray radiography. The ResNet50 version has the best result & accuracy rate of the present system. As compared to the current models, a novel procedures and ensuring on the CNN model delivers better specific, sensitivities, and precision. By using confusion matrix and ROC assessment, fivefold validation data is utilized to analyze the current models and compare them to the proposed system. © 2023 IEEE.

Deep Learning based Face Mask Detection system with Automatic Indigation

The COVID-19 pandemic has quickly had an impact on our day-to-day lives, as well as on the movement of goods and people around the world. It has recently been common practice to shield one's face by using a mask. In the not too distant future, many businesses that provide public services will need their clients to correctly wear masks in order for them to receive those services. As a result, the detection of face masks has evolved into an important mission in the service of worldwide society. In this post, a relatively straightforward approach to achieving this goal is presented using basic machine learning tools like TensorFlow, Keras, OpenCV, and Scikit-Learn. The suggested method accurately locates the face inside the image before determining whether or not it is covered by a mask. While doing a surveillance task, it is capable of detecting a mask as well as a moving face. To properly detect the presence of masks without over-fitting, we look into numerous options for optimizing the values of the parameters in the Sequential Convolutional Neural Network model. © 2022 IEEE.

Comparative Study of Molecular Docking, Structural, Electronic, and Fukui Function Studies on Favipiravir and its Newly Designed Derivatives (Potential Inhibitors) for COVID-19 Protease

Favipiravir is an antiviral medication currently being trialed as a COVID-19 treatment. These results motivate us to develop new species (possibly drugs) from favipiravir, perform comparative molecular docking, and reexamine their biological and pharmacological activities. Detailed quantum chemical research on favipiravir and its newly designed derivatives has been carried out with the help of DFT/B3LYP/6–311 + + G (d, p). In the present work, the structure of favipiravir has been modified and 12 new species have been modeled (all species are inherently stable because no virtual frequency is found during the vibration analysis). Reactivity of all species using various descriptors (local) such as Fukui function, local softness, electrophilicity, and global, i.e., electronegativity, hardness, HOMO–LUMO gap, etc. of the same are calculated and discussed. In silico studies such as molecular docking of all species and complete quantum chemistry studies suggest that four of them may mitigate the effects of the COVID-19 protease. © 2023 Wiley-VCH GmbH.

Assessment of Air Quality Before and During COVID-19-Induced Lockdown in Jaipur, India

Air pollution is increasing at a frightening pace due to emissions from industrial plants and manufacturing activities and other anthropogenic activities affecting living beings, property, and environment. This study aims to monitor the impact of COVID-19-induced lockdown and unlock down phases on the air quality of Jaipur city, Rajasthan, India by assessing the change in ambient air quality during pre-COVID-19 (January 2018–December 2019) and COVID-19 (January 2020–December 2021) phases by evaluating air quality parameters (PM10, PM2.5, NO2, O3, Benzene and o-Xylene) using ground station data. Outcome of the study revealed that the ambient air quality improved significantly during lockdown phases (March–May 2020) as the percentage change in concentration of studied parameters declined by more than 100% at different sites. However, the concentrations tend to escalate with the introduction of unlock down phases (June–December 2020) and the onset of winter season (October–December 2020) aggravated the conditions. The AQI touched moderate and poor category many times during study period. Student's t-test was conducted on the dataset. Results revealed significant difference in the concentration of air pollutants between pre-covid and covid period.

A research study to understand the impact of pandemic on healthcare workers

The Covid-19 pandemic has shaken up the entire human race as it has led to more than 2.9 million deaths globally, as reported by Johns Hopkins University's Covid-19 Dashboard on April 2021. This pandemic has shaken the entire world and we are still not 'out of woods' yet. Globally, 136 mn patients have been affected by this pandemic and the healthcare infrastructure is in overdrive now. Healthcare workers are our first responders in these adverse times and the irony is that this is also significantly affecting them. A question, which needs consideration is, if our healthcare workers i.e. frontline doctors and nursing staff are succumbed to this situation, then who will save the humankind. This question needs to be answered by looking from the research perspective as to why healthcare workers and care providers are most vulnerable in these pandemic situations and why there is so much mortality in that group. We have tried to understand the key reasons behind this high mortality rate by qualitative review.

A rapid One-Pot RNA isolation method for simplified clinical detection of SARS-COV-2 infection in India

BackgroundWith the rapid increase in COVID-19 cases and the discovery of new viral variants within India over multiple waves, the expensive reagents and time-consuming sample pretreatment required for qPCR analysis have led to slower detection of the disease. The vast Indian population demands an inexpensive and competent sample preparation strategy for rapid detection of the disease facilitating early and efficient containment of the disease. MethodsIn this study, we have surveyed the spread of COVID-19 infection over Faridabad, Haryana, India for 6 months. We also devised a simple single-step method for total RNA extraction using a single tube and compared its efficacy with the commercially available RNA isolation kits. FindingsOur findings suggest that determining Ct values for samples subjected to the One Pot RNA extraction method was as efficient as the commercially available kits but delivers a subtle advantage in a way, by minimizing the cost, labor and sample preparation time. ConclusionThis novel crude RNA extraction method is stable and capable of operating in developing countries like India for low resource settings, without the use of expensive reagents and instruments. Additionally, this method can be further adapted to pooling samples strategies owing to its high sensitivity.

EVALUATION OF BONE MARROW & PERIPHERAL BLOOD SMEAR FINDINGS IN SARS-COV-2 PATIENTS, CENTRAL INDIA

This study was done to assess the morphological changes in peripheral blood smears during COVID-19 infection .We aimed to examine the characteristics of the cells detected in the peripheral blood smear and bone marrow at the time of diagnosis in COVID-19 patients. Clinical features, laboratory data, peripheral blood smear of 35patients diagnosed with COVID-19 by PCR was evaluated at diagnosis. Peripheral smear samples of the patients were compared with the age and sex-matched 35 healthy controls. The relationship between the laboratory values of all patients and the duration of hospitalization was analyzed. Peripheral smear shows neutrophilic leucocytosis, lymphopenia and thrombocytopenia while Bone marrows were normocellular to hypercellular, most showing maturing trilineage hematopoiesis with myeloid left shift. In 09 out of 35 evaluable bone marrows, hemophagocytic histiocytes were identified.

Strategic shift in marketing communication during COVID-19

During COVID-19, several disruptions were reported, activities got halted, and the focus of marketing shifted towards social media due to engagements of the clients towards various available platforms. The use of the internet and social media increased during and after the pandemic. Digital communications attracted customers towards contactless access and the availability of required services. Interactions among various stakeholders including companies, suppliers, and customers increased during these times for hassle-free and uninterrupted services. A paradigm shift was observed in advertising patterns, customer relationship management, service management, and digital tools and media engagements during the pandemic. A strategic shift, observed during the pandemic, has been explored and covered in this chapter. A theoretical framework of hassle-free uses of digital tools in the pandemic has also been developed and included using various social media platforms. © 2022, IGI Global.

Disease Prediction Using Machine Learning (Health Buddy)

This is a paper on disease prediction using machine learning through a python graphical user interface application. The motivation behind this application is the pandemic (Covid- Situation) faced by the whole world and also the idea to robotize the current manual framework of initial diagnosis by the assistance of mechanized supplies and undeniable PC programming so that their important information/data can be put away for a more drawn out period and also for a more useful purpose. This paper introduces the field of diseases prediction, the treatment for the disease, and consulting with the doctors nearby through efficient programming using machine learning. It describes the need for a system of an online artificial doctor, which will not only help them in predicting and understanding the diseases, but it will also advise them of certain medicines that are necessary for controlling or curing those diseases. © 2022 IEEE.

Sudden loss of smell and taste: clinical predictors of coronavirus disease 2019 infection.

OBJECTIVES: This study aimed: to evaluate the association between coronavirus disease 2019 infection and olfactory and taste dysfunction in patients presenting to the out-patient department with influenza-like illness, who underwent reverse transcription polymerase chain reaction testing for coronavirus; and to determine the sensitivity, specificity, and positive and negative predictive values of olfactory and taste dysfunction and other symptoms in these patients. METHODS: Patients presenting with influenza-like illness to the study centre in September 2020 were included in the study. The symptoms of patients who tested positive for coronavirus on reverse transcription polymerase chain reaction testing were compared to those with negative test results. RESULTS: During the study period, 909 patients, aged 12-70 years, presented with influenza-like illness; of these, 316 (34.8 per cent) tested positive for coronavirus. Only the symptoms of olfactory and taste dysfunction were statistically more significant in patients testing positive for coronavirus than those testing negative. CONCLUSION: During the pandemic, patients presenting to the out-patient department with sudden loss of sense of smell or taste may be considered as positive for coronavirus disease 2019, until proven otherwise.

Role of a Digital Human Anatomy Museum in Teaching- Learning during the COVID-19 Era

Introduction: The museum of human Anatomy plays a prominent role in exploring the structural organization of the human body. However, in the current pandemic era, it has been observed that the entry to Anatomy museum was restricted. The students rarely visit the museum and prefer to browse the internet for learning videos and explanations of the dissected human specimens. Aim: The present project was undertaken to develop the Anatomy museum as an innovative online educational tool through the digitalization of human body specimens. Materials and Methods: High-resolution pictures of 100 core specimens were captured, categorized according to the organ systems, and stored in a database along with the relevant explanation and voiceovers. A database of the digitalized anatomy exhibits and the online management platform was then built as a website. The website was made accessible to the student community and the public. Results: The efforts of digitalizing the human specimens of the Anatomy Museum were well appreciated and encouraged by the students and the public alike. The reflections recorded from the students were subjected to thematic analysis and theme were identified. Conclusion: The study concludes by stating that the digitalized human Anatomy museum is an excellent educational tool for teaching and learning Anatomy. The students from various streams of Health and Allied Sciences will be immensely benefitted from the digitalized Anatomy Museum, especially in these pandemic times.

Assessing knowledge, attitude, and practices towards ivermectin pre-exposure prophylaxis for COVID-19 among health care workers

Background: Health care workers (HCWs) are more likely to be at high risk of SARS-CoV-2 infection due to their direct and/or indirect participation in treatment facilities. Here, we aimed to evaluate the knowledge, attitude, and practices of ivermectin pre-exposure prophylaxis (PEP) in HCWs. Materials and Methods: In this observational study HCWs who were directly/indirectly involved in the medication of COVID-19 patients were selected. The study questionnaire included demographic data;knowledge, attitudes, practices, and associated adverse drug reactions (ADR) after using ivermectin as pre-exposure prophylaxis in COVID-19.

Neem (Azadirachta Indica A. Juss) Capsules for Prophylaxis of COVID-19 Infection: A Pilot, Double-Blind, Randomized Controlled Trial

Context center dot SARS-CoV-2 is a global public-health concern. Interventions to prevent infection are urgently needed. The anti-inflammatory and antiviral effects of neem make it a potential agent for COVID-19 prophylaxis. Objective center dot The study intended to evaluate the prophylactic effects of neem capsules for persons at high risk of COVID-19 infection due to contact with COVID-19 positive patients. Design center dot The research team designed a prospective, randomized, double-blind, placebo-controlled, paralleldesign study. Setting center dot The study was conducted at a single center in India. Participants center dot Participants were 190 healthcare workers at the hospital or relatives of patients with COVID-19 infection. Intervention center dot Of the 190 participants, 95 were in the intervention group and 95 in the control group. Participants received 50 mg of a proprietary, patent-pending, neem-leaf extract or a placebo orally in capsules, twice a day for 28 days. Outcome Measures center dot The number of individuals positive for COVID-19 between baseline and follow-up on day 56 was the primary outcome measure. Secondary measures included an evaluation of neem's safety and its effects on quality of life (QOL) and changes in biomarkers. Results center dot The mean age of participants was 36.97 years, and 68.42% were male. Total 13 subjects tested positive during the study. All were asymptomatic. Of the 154 participants who completed the study per-protocol, 11 tested positive, 3 in the intervention group and 8 in the control group. The probability of COVID-19 infection in participants receiving the intervention was 0.45 times that of participants receiving the placebo, a relative risk of 0.45, with the effectiveness of the intervention being around 55%. Treatment-emergent adverse events (TEAEs) in both groups were minimal and were of grade 1 or 2 in severity. Biomarkers and QOL remained stable in both groups. Conclusions center dot The study found a reduced risk of COVID-19 infection in participants receiving neem capsules, which demonstrates its potential as a prophylactic treatment for the prevention of COVID-19 infection. The findings warrant further investigation in clinical trials.

Impact of pandemic on development and demography in different continents and nations

This study has collected information of 145 countries to predict the effect of cases per million (CPM), tests per million (TPM), and proportion of people aged 65 and above (PAO) on the number of deaths per million DPM at the country and continent level. In addition, it evaluates the economic cost of tests, deaths, COVID-19 cases in terms of reduction in GDP growth rate across the countries. This paper uses a different econometrics model, including analysis of variance (ANOVA), regression, and multinomial regression model. The robust regression model with M and MM-estimation was also used due to leverage and residuals in country wise GDP database. A significant difference was found in deaths per million (DPM), TPM, number of COVID-19 cases (CPM), and percentage of people aged 65 and above (PAO) across continents. The DPM is negatively associated with TPM, and it was relatively more effective in reducing DPM in Africa (0.32%) as compared to Asia (0.25%) and Europe (0.28). The results show that a 1% increase in the elderly population causes a 0.62% increase in DPM in Africa, while it caused a 2.31% increase in Europe. The study will be helpful in ascertaining the impact of these indicators in this pandemic and help in policy formation and decision-making strategies to fight the COVID19 pandemic.

Analyzing the implications of COVID-19 pandemic through an intelligent-computing technique

The outbreak of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2 virus or COVID-19) disease was declared pandemic by the World Health Organization (WHO) on March 11, 2020. COVID-19 has already affected more than 211 nations. In such a bleak scenario, it becomes imperative to analyze and identify those regions in Saudi Arabia that are at high risk. A preemptive study done in the context of predicting the possible COVID-19 hotspots would facilitate in the implementation of prompt and targeted countermeasures against SARS-CoV-2, thus saving many lives. Working towards this intent, the present study adopts a decision making based methodology of simulation named Analytical Hierarchy Process (AHP), a multi criteria decision making approach, for assessing the risk of COVID-19 in different regions of Saudi Arabia. AHP gives the ability to measure the risks numerically. Moreover, numerical assessments are always effective and easy to understand. Hence, this research endeavour employs Fuzzy based computational method of decision making for its empirical analysis. Findings in the proposed paper suggest that Riyadh and Makkah are the most susceptible regions, implying that if sustained and focused preventive measures are not introduced at the right juncture, the two cities could be the worst afflicted with the infection. The results obtained through Fuzzy based computational method of decision making are highly corroborative and would be very useful for categorizing and assessing the current COVID-19 situation in the Kingdom of Saudi Arabia. More specifically, identifying the cities that are likely to be COVID-19 hotspots would help the country's health and medical fraternity to reinforce intensive containment strategies to counter the ills of the pandemic in such regions. © 2022 CRL Publishing. All rights reserved.

Comparative study of molecular docking, structural, electronic, vibrational and hydrogen bonding interactions on 4-hydroxy benzo hydrazide (4HBH) and its newly designed derivative [(E)-N′-((1H-Pyrrol-2-YL)methylene) -4-hydroxy benzo hydrazide and its isomers (I, II and III)] (potential inhibitors) for COVID-19 protease

Studies have shown that hydrazides and thier derivatives are used for pharmaceutical and medicinal purposes. At present, the whole world is suffering for COVID-19 virus. There are some vaccines or medicines available to treat this disease all over the world. Today the one fourth of the world's population is under lockdown condition. In this scenario, scientists from the whole world are doing different types of research on this disease. Being a molecular modeller, this inspires us to design new types of species (may be drugs) which may be capable for COVID-19 Protease. In the present effort, we have performed docking studies of title compounds with COVID-19 protein (6LU7) for anti-COVID-19 activity. A comparative quantum chemical calculations of molecular geometries (bond lengths and bond angles) of 4-Hydroxy Benzo Hydrazide (4HBH) and its newly designed derivatve [(E)-N′-((1H-Pyrrol-2-YL)Methylene) -4-Hydroxy Benzo Hydrazide and its isomers (I, II and III)] in the ground state have also been carried out due to its biological importance and compared with the similer type of compound found in literature i.e. benzohydrazide. The optimized geometry and wavenumber of the vibrational bands of the molecules have been calculated by density functional theory (DFT) using Becke's three-parameters hybrid functional (B3LYP/CAM-B3LYP) with 6-311G (d, p) as the basis set. Vibrational wavenumbers are compared with the observed FT-IR and FTRaman spectra of 4-Hydroxy Benzo Hydrazide. TDDFT calculations are also done on the same level of theory and a theoretical UV-vis spectrum of title molecules are also drawn. HOMO-LUMO analysis has been done to describe the way the molecule interacts with other species. Natural bond orbitals (NBO) analysis has been carried out to inspect the intra- and inter- molecular hydrogen-bonding, conjugative and hyper conjugative interactions and their second order stabilization energy. Nonlinear optical (NLO) analysis has been performed to study the non-linear optical properties of the molecule by computing the first hyperpolarizability. The variation of thermodynamic properties with temperature has been studied. QATIM analysis shows that hydrogen bonding occurs in 4HBH, isomer II and III respectively. © 2021 - IOS Press. All rights reserved.

Effect of COVID-19 lockdown on bovine economy in Uttar Pradesh

A study was conducted among 570 farmers spread across 57 districts (out of 75) of Uttar Pradesh from 10 April to 10 May 2020 by telephonic contact using the pre-structured interview schedule to assess the impact of CoVID 19 lockdown on the investment and profitability of major bovines of the state namely cattle and buffalo each with 460 data points. Different indicators for research variables namely investment pattern and profitability were measured by asking direct questions to the randomly selected 10 farmers from each district during the lockdown period and their experiences during last year (2019). The collected data were subjected for descriptive analysis - average, percentage, rank, standard deviation (SI)) and coefficient of variation (CV), and also to the paired t-test to see the significance of difference, if any. Findings of the study showed that all the investments indicators like feed and fodder price, treatment cost, animal handling charges and total cost of milk production of cattle and buffalo enhanced significantly during the lockdown. The magnitude varied as per the nature of the cost components. The price variation was observed across the sample respondents and district. Similarly, for profitability indicators, there was reduction in the magnitude of milk sale (13-15%), selling price of milk (4-5%) and B:C ratio (5.2 -7.3%) significantly owing to lockdown. The perceptions of KVK experts from across the selected districts were also analyzed. During this period. KVKs of the state also disseminated various advisories, instructions. crop and enterprise-specific recommendations.

Molecular epidemiology of a familial cluster of SARS-CoV-2 infection during lockdown period in Sant Kabir Nagar, Uttar Pradesh, India

We report a familial cluster of 24 individuals infected with SARS-CoV-2. The index case had a travel history &spent twenty four days in the house before being tested and was asymptomatic. Physical overcrowding in the house provided a favourable environment for intra-cluster infection transmission. Restriction of movement of family members due to countrywide lockdown limited the spread in community. Among the infected, only 4 individuals developed symptoms. The complete genome sequences of SARS-CoV-2 was retrieved using next-generation sequencing from eight clinical samples which demonstrated a 99.99% similarity with reference to Wuhan strain and the phylogenetic analysis demonstrated a distinct cluster, lying in the B.6.6 pangolin lineage.

SARS-CoV-2 Transmission Risk through Expressed Breast Milk Feeding in Neonates Born to COVID 19 Positive Mothers: A Prospective Observational Study

Background: Mother-to-child transmission of Severe Acute Respiratory Syndrome Corona Virus 2 (SARS-CoV-2) has become a matter of great concern in post-partum wards and neonatal units. With little prior experience of this novel infection, there are contradictory findings in the literature regarding breastfeeding and rooming-in for newborns of mothers with COVID-19 disease. To assess the transmission risk of SARS-CoV-2 in neonates who were fed expressed breast milk of COVID-19 positive mothers. Methods: This prospective study included 16 neonates born to COVID-19 positive mothers. The neonates were nursed in a neonatal unit separate from their mother. Expressed breast milk was fed by health care givers ensuring proper safety measures. Nasal and throat swabs of neonates were tested twice for SARS CoV-2, firstly, at 48 h of life and secondly, before discharge. Results: Pneumonia was present in 3 (20%) mothers, and C-reactive protein was raised in 9 (60 %) mothers. Birth weight was low in 8 (50%) neonates. Respiratory distress syndrome and meconium aspiration syndrome were present in two and one newborns, respectively. Nasal and throat swabs of all 16 newborns tested negative for SARS-CoV-2 infection twice, at 48 h of life and before discharge. Conclusion: Expressed breast milk feeding can be considered safe in neonates born to COVID-19 positive mothers. Even sick mothers with COVID-19 can continue to express breast milk after ensuring proper safety measures.