Role of AI and ML in Epidemics and Pandemics

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.

Quantile dependencies and connectedness between the gold and cryptocurrency markets: Effects of the COVID-19 crisis

This paper examines the quantile dependence, connectedness, and return spillovers between gold and the price returns of leading cryptocurrencies, using quantile cross-spectral, the return spillovers based the quantile VAR, and quantile connectedness approaches. The results show that the dependencies within cryptocurrencies are highly symmetric and sensitive to different quantile arrangements. Under normal market conditions, we find a high positive dependence within cryptocurrencies and a low positive dependence between cryptocurrencies and gold. The dependence is higher at long term than intermediate- and short- terms before the pandemic during bearish market conditions. In contrast, the degree of dependence decreases at the intermediate- and long-terms during COVID-19 period than before. Moreover, the magnitude of return spillovers is higher at lower quantile (bearish market) than upper quantile (bullish market). Gold serves as a safe haven and diversifier asset for cryptocurrencies during COVID-19 outbreak at both intermediate and long terms. © 2023 Elsevier B.V.

Phytochemistry and Pharmacological Properties of Morus alba Linn. with Reference to its SARS-CoV-2 Inhibiting Potential

Morus alba Linn. is a plant with varieties of phytochemicals and commonly known as Mulberry tree or Nuni (in Assamese). Mulberry is a perennial and woody plant, belongs to the family Moraceae consider as a native plant of China. In Assam, the leaves of mulberry tree are out most important in horticulture department for feeding purpose. A literature survey was done out by using key words such as Morus alba, or mulberry tree or phytoconstituents, or pharmacological activities, or ethnobotany on the search engine namely Scopus, Web of Science, Google Scholars, PubMed. The purpose of this article is to forward a solid review about the plant profile, method of extraction, phytochemicals constituents and pharmacological activities in reference to SARS-CoV-2. All the parts of Morus alba are phytochemically rich but highest number can be found in fruits and leaves. Fruits of Morus alba contains various class of phytochemicals such as alkaloids, anthocyanins, stillbenoids, flavones. Owing to presence of this compounds, it exhibits various pharmacological. Its leaves, fruits and root bark containing flavonoids, anthocyanins, alkaloids and stilbenoids, possess various pharmacological properties. Resveratrol is one of the most important compounds found in M. alba which possess SARS-CoV-2 inhibiting potential. Still there are some gaps remain in exploring whole plants parts and successive studies of toxicity. © 2022 Chemical Publishing Co.. All rights reserved.

Multi-class LDA classifier and CNN feature extraction for student performance analysis during Covid-19 pandemic

In our modern world, education is essential for developing high moral values and excellence in individuals. But the spread of Covid-19 widely affects the student's education, the majority of students have continued their education via online learning platforms. The academic performance of students has been sluggish across the globe during this pandemic. This problem is solved using a multiclass Linear Discriminant Analysis (LDA) and Convolutional Neural Network (CNN) model which predicts the student learning rate and behavior. This research aims to classify the students' performance into low, medium, and high grades in order to assist tutors in predicting the low-ranking students. The student data log is collected from the Kaggle student performance analysis dataset and pre-processed to remove the noise and non-redundance data. By analyzing the pre-processed data, the CNN extracts feature that are based on student interest and subjective pattern sequences. Then extracted features are filtered by the Minimum Redundancy Maximum Relevance(mRMR) method. mRMR selects the best features and dilutes the least one which handles each feature separately. The feature weights are measured by Stochastic Gradient Descent (SGD) and updated for better feature learning by CNN. At the last stage, the Multi-class LDA classifier evaluates the result into categorized classes. Based on the prediction, the tutors can easily find the low ranks of students who need a high preference for improving their academic performance. Experiments showed that the proposed model achieves greater accuracy (96.5%), precision (094), recall (092), F-score (095), and requires less computation time than existing methods.

The impacts of COVID-19 crisis on spillovers between the oil and stock markets: Evidence from the largest oil importers and exporters

This study examines the multiscale spillovers and nonlinear causalities between the crude oil futures market and the stock markets of the United States (US), Canada, China, Russia, and Venezuela before and during the COVID-19 pandemic. Using the wavelet coherency method, we find strong co-movement between the oil futures market and these five stock markets, particularly from March 2020 to May 2020 (initial period of the COVID-19 outbreak) at high frequency. Furthermore, we find positive co-movements at low frequency during the overall COVID-19 period. This finding suggests that the bearish trend of stock markets is associated with a downward movement in oil prices. Using the wavelet-based Granger causality approach, we find that the oil and stock indices have less co-movement on a smaller scale but greater movement on a larger scale across all periods. As an exception, the Russian market is significantly influenced by oil prices, even on a small scale, before the COVID-19 period, but not after the beginning of the pandemic. We also find effects in the opposite direction—the Canadian and U.S. markets influence oil prices on a small scale during the COVID-19 period, an effect that is not visible for the U.S. market in the pre-COVID-19 sample. The results also show a significant bidirectional causality from oil to stock markets and vice versa during Russian-Saudi oil price war at high scale. Furthermore, we find that investors should hold more oil futures than stock shares in their portfolios for all periods. This evidence confirms that oil instruments are important for hedging during normal periods and act as safe-haven assets during crisis periods. We observe that the U.S. and Canadian stock markets were more affected by oil price shocks than were other countries. © 2021 Economic Society of Australia, Queensland

Expanding the Constructs of Grief and Loss in Capturing the Human Experience: Essential Workers in the Meatpacking Industry and the Pandemic

In this unprecedented (Corona Virus Disease) COVID-19 pandemic, psychologists from every country are faced with the challenge of dealing with the myriad grief and losses that are affecting the mental health of many people. Among the many who are suffering are "essential workers" in the United States meatpacking industry, who are forced to make a choice between working in an unsafe environment or becoming unemployed with no benefits. Many of these workers are people of color (POC) who encounter unrecognized challenges related to their contextual factors and intersectional identities. This article will discuss contextual and intersectional grief and losses experienced by these "essential workers" and how the confluence of their intersectional identities intensifies their pandemic grief and loss. Clinical implications include expansion of the definition of grief and loss beyond death to include experiences that are shaped by extensive contextual factors, work, and intersectional identities that have psychological and mental health implications. Special attention will be given to naming losses to identify the grief, followed by meaning-making and meaning-finding to adapt to changes in mourning. Finally, the addition of grief and loss training requirement to APA programs is advocated to further the values of social justice and incorporation of multiculturalism in the field. Public Significance Statement This article spotlights the grief and loss experienced by workers in the meatpacking industry, who were deemed as "essential workers" during the pandemic. For more effective treatment, it suggests that in tandem with pandemic grief and loss, therapists also explore the different types of grief and losses these workers experience based on their specific contexts and multiple identities that may include some dimensions such as race, culture, gender, social class, sexuality, age, and immigration status.

Vertical transmission of novel coronavirus (COVID-19) from mother to newborn: experience from a maternity unit, the Indus Hospital, Karachi

This study reports that a mother admitted with COVID-19 had developed respiratory failure. The baby was born by caesarean section without delayed umbilical cord clamps and without skin to skin contact;and he was immediately placed in isolation. The newborn's nasopharyngeal smear was performed at 16 hours of age, after which the baby was reported to have tested positive for coronavirus at birth. COVID-19 testing is performed on mothers prior to normal delivery or an elective caesarean section due to the potential risk of aerosol exposure. A total of 585 babies were born in the course of this pandemic from 27 April 2020 to 16 June 2020. Information was collected on women who tested positive for the COVID-19 virus. A staggering 66 mothers reported positive, but found a total of asymptomatic. Twenty of the 66 COVID-19 positive mothers received a spontaneous vaginal delivery, of them a pair of twins;while 7 out of 66 mothers delivered by elective caesarean section. That being said, 40 of 66 mothers underwent an emergency caesarean section performed under spinal anesthesia performed in an operating room specifically designed for suspected COVID-19 positive patients. Nasopharyngeal swab PCR was performed in the 67 newborns at birth who were reported negative. All babies remained stable in the COVID-19 isolation unit with their mothers. Direct maternal feeding continued with a mask for the mothers and all babies were discharged at 48 hours of age;and provided with the corresponding aftercare plans. Although there is no concrete understanding yet of the coronavirus and its relationship to vertical transmission, cases have been reported in which the infants of COVID-positive mothers tested positive. Overall, evidence is lacking to fully confirm whether vertical transmission occurs from mother to baby. However, here, in this hospital, they have not seen any cases of newborns contracting the coronavirus because their mother tested positive for COVID-19.

Vertical Transmission of Novel Coronavirus (COVID-19) from Mother to Newborn: Experience from a Maternity Unit, The Indus Hospital, Karachi

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Personal protective equipment for surgeons during COVID-19 pandemic: systematic review of availability, usage and rationing.

BACKGROUND: Surgeons need guidance regarding appropriate personal protective equipment (PPE) during the COVID-19 pandemic based on scientific evidence rather than availability. The aim of this article is to inform surgeons of appropriate PPE requirements, and to discuss usage, availability, rationing and future solutions. METHODS: A systematic review was undertaken in accordance with PRISMA guidelines using MEDLINE, Embase and WHO COVID-19 databases. Newspaper and internet article sources were identified using Nexis. The search was complemented by bibliographic secondary linkage. The findings were analysed alongside guidelines from the WHO, Public Health England, the Royal College of Surgeons and specialty associations. RESULTS: Of a total 1329 articles identified, 95 studies met the inclusion criteria. Recommendations made by the WHO regarding the use of PPE in the COVID-19 pandemic have evolved alongside emerging evidence. Medical resources including PPE have been rapidly overwhelmed. There has been a global effort to overcome this by combining the most effective use of existing PPE with innovative strategies to produce more. Practical advice on all aspects of PPE is detailed in this systematic review. CONCLUSION: Although there is a need to balance limited supplies with staff and patient safety, this should not leave surgeons treating patients with inadequate PPE.