ABSTRACT
During the early phase of the COVID-19 pandemic, reverse transcriptase-polymerase chain reaction (RT-PCR) testing faced limitations, prompting the exploration of machine learning (ML) alternatives for diagnosis and prognosis. Providing a comprehensive appraisal of such decision support systems and their use in COVID-19 management can aid the medical community in making informed decisions during the risk assessment of their patients, especially in low-resource settings. Therefore, the objective of this study was to systematically review the studies that predicted the diagnosis of COVID-19 or the severity of the disease using ML. Following the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA), we conducted a literature search of MEDLINE (OVID), Scopus, EMBASE, and IEEE Xplore from January 1 to June 31, 2020. The outcomes were COVID-19 diagnosis or prognostic measures such as death, need for mechanical ventilation, admission, and acute respiratory distress syndrome. We included peer-reviewed observational studies, clinical trials, research letters, case series, and reports. We extracted data about the study's country, setting, sample size, data source, dataset, diagnostic or prognostic outcomes, prediction measures, type of ML model, and measures of diagnostic accuracy. Bias was assessed using the Prediction model Risk Of Bias ASsessment Tool (PROBAST). This study was registered in the International Prospective Register of Systematic Reviews (PROSPERO), with the number CRD42020197109. The final records included for data extraction were 66. Forty-three (64%) studies used secondary data. The majority of studies were from Chinese authors (30%). Most of the literature (79%) relied on chest imaging for prediction, while the remainder used various laboratory indicators, including hematological, biochemical, and immunological markers. Thirteen studies explored predicting COVID-19 severity, while the rest predicted diagnosis. Seventy percent of the articles used deep learning models, while 30% used traditional ML algorithms. Most studies reported high sensitivity, specificity, and accuracy for the ML models (exceeding 90%). The overall concern about the risk of bias was "unclear" in 56% of the studies. This was mainly due to concerns about selection bias. ML may help identify COVID-19 patients in the early phase of the pandemic, particularly in the context of chest imaging. Although these studies reflect that these ML models exhibit high accuracy, the novelty of these models and the biases in dataset selection make using them as a replacement for the clinicians' cognitive decision-making questionable. Continued research is needed to enhance the robustness and reliability of ML systems in COVID-19 diagnosis and prognosis.
ABSTRACT
For decades, societies have been planting the seed of their own destruction. The environmental degradation catastrophe has become so voluminous and complex, seen in many forms and extending across various dimensions of nature. Air pollution, water pollution, and soil pollution have caused tremendous amounts of damage. Species extinction and the loss of various forms of life have been massively increasing at an unprecedented rate. It is calculated that approximately 0.01–0.1% of all known species will become extinct each year. This raises a major concern: Could biodiversity loss affect the wellbeing of nations through hindering economic growth? If so, to what extent? This is the question that this study aims to investigate. The case of COVID-19 has been a powerful example enabling the world to witness how biodiversity loss could affect economic growth, which has posed as an economic threat to all nations. This study, therefore, investigates the relationship between biodiversity and economic growth utilizing a fixed effects panel regression conducted using a selected sample of OECD countries. Findings of this study indicate that biodiversity does in fact hinder GDP growth in the long run. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.
ABSTRACT
Background: Owing to absence of definitive treatment to coronavirus disease 2019 (COVID-19) and vaccine hesitancy, the general population sought information from various sources to prevent or treat the disease. Consequently, self-treatment (ST) was boosted in many parts of the world. Aim: The current study aimed to assess ST knowledge, beliefs and practice during the COVID-19 pandemic among Egyptians. Subjects and Method: A cross-sectional, anonymous online survey was conducted using different social media platforms to recruit participants. The survey assessed the sociodemographic characteristics, past COVID-19 infection and vaccination, exposure to ST, and reasons for ST. Results: A total of 400 participants completed the questionnaire;their mean age was 34.9±11.5, females represented 67.8%, married (63.3%), living in urban areas (76.8%) and had chronic diseases (28%). About 67.5% had received vitamins or minerals, antibiotics or herbals or food supplements either due to ST (59.6%) or non-ST (40.4%). Among the ST group, vitamins were used by (81.9%), antibiotics (45.9%), and herbals and supplements (40.9%). Conclusion: ST may delay medical advice seeking leading to worsening of the patient's health. Efforts to raise public awareness about risks of ST should be done by healthcare members especially in the media. © 2022, Ain Shams University Faculty of Medicine. All rights reserved.
ABSTRACT
Background: Coronavirus 2 is the cause of COVID-19, a hazardous respiratory disease (SARS-CoV-2). More than 80% of hospitalized patients and 30% of COVID-19 survivors may have long-term effects. The most prevalent and incapacitating symptoms of the post-COVID-19 syndrome are thought to be fatigue and cognitive impairment. Objective: The major objective of the current study is to trace fatigue affected post-COVID survivors’ cognitive function. Subjects and Methods: In this study, 84 cases were enlisted, and they were subdivided into two groups. The study group consisted of 42 post-COVID survivors, and the control group consisted of 42 healthy individuals who were age-and sex-matched. Addenbrooke's cognitive examination revised scale, the fatigue rating scale, and the computer-based Cognitive Assessment therapy (Rehacom system) were adopted in the current study to evaluate each case. Results: A clear negative correlation was found between the FSS scores and the ACE-R (r =-0.98, p = 0.001), as well as between the FSS scores and the degree of logical thinking difficulty (r =-0.74, p = 0.001) and the FSS scores and the level of figural memory difficulty (r =-0.93, p = 0.001). Clear positive correlation were detected between the FSS scores and the first quartile response time (r = 0.94, p = 0.001), the third quartile reaction time (r = 0.96, p = 0.001), the acquisition time (r = 0.97, p = 0.001), and the solution time (r = 0.98, p = 0.001). Conclusion: In post-COVID survivors, fatigue has a major impact on cognitive abilities.
ABSTRACT
Purpose This study examined the level of knowledge, attitudes and practices (KAP) of Jordanian dairy employees about coronavirus disease 2019 (COVID-19) characteristics and the effect of precautionary measures on food safety risk during the pandemic. Design/methodology/approach A cross-sectional study was conducted between Dec 17, 2020 and Feb 22, 2021, involving a total of 428 participants across 34 random chosen dairy facilities in Jordan. KAP related to COVID-19 were measured by 46 items, while 13 items were used to examine perceived notions regarding COVID-19 precautionary measures on food safety. Findings The results indicated that 32.2% of the respondents had sufficient knowledge, 60.3% had a good attitude, and 27.1% followed correct practices concerning COVID-19. Moreover, female respondents had higher total KAP scores of COVID-19 characteristics than males. Furthermore, older and more experienced respondents had higher total KAP scores than younger respondents. This study also observed that the total KAP scores were not affected by education, marital status, and job position. Characteristics and measures taken by the dairy industry were at large significantly associated with (p < 0.05) knowledge and practice of employees about COVID-19 attributes. Results of this study suggested that Jordanian dairy workers were not adequately aware about COVID-19. Originality/value No such study on dairy workers has been conducted previously to the best of the authors' knowledge. Moreover, studies which analyse the association of industry response and characteristics on the KAP of employees are very limited.
ABSTRACT
COVID19 chest X-ray has been used as supplementary tools to support COVID19 severity level diagnosis. However, there are challenges that required to face by researchers around the world in order to implement these chest X-ray samples to be very helpful to detect the disease. Here, this paper presents a review of COVID19 chest X-ray classification using deep learning approach. This study is conducted to discuss the source of images and deep learning models as well as its performances. At the end of this paper, the challenges and future work on COVID19 chest X-ray are discussed and proposed. © 2021 Institute of Physics Publishing. All rights reserved.
ABSTRACT
Human safety needs careful attention to minimize the risks of the COVID-19 pandemic, which signifies a crucial political, scientific, political, and public health concern across the globe. The purposes of this study were to assess the knowledge, attitude, communication, commitment, and behavioral practices of universities’ students in UAE towards COVID-19, and the influences of the students' knowledge and attitude towards COVID-19 on their communication, commitment, and behavioral practices using Structural Equation Modelling (SEM). In this cross-sectional study, 995 university students in UAE completed an online-based questionnaire. In general, the respondents had good COVID-19 knowledge (71.4%), attitude (70%), behavioral practices (77.2%), and very good commitment (80.4 %)., while communication was moderate (67.6%), and it has been found a significant relationship between student’s knowledge and attitude coupled with their behavioral patterns towards the epidemics and pandemic of COVID-19. There was a significant correlation between the knowledge and attitude of students with their behavior towards COVID-19. Significant relationships were found between the COVID-19 knowledge and attitude of the students with their commitment/communication and between communication and commitment of the students with their behavioral practices. The latter variable acted as partial mediators in the relationships between the students' knowledge and attitude with their behavioral practices. The results of this study approved that communication and commitment are important variables in COVID-19 management and preparedness to translate the COVID-19 knowledge and attitude into proactive behavioral practices. © 2021, Academy of Strategic Management Journal. All Rights Reserved.
ABSTRACT
Coronavirus disease 2019 (COVID-19) is an infectious disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). In Sudan, several haematological studies were conducted to study the ABO blood group distribution among the population, in which the O blood group was dominant followed by the A blood group. However, there is no systematic study into any correlation between COVID-19 and the population's blood group types, therefore we have intended to study the possible effect of blood group on the acquisition of SARS-CoV-2 infection. A questionnaire-based case-control study was carried out on 557 individuals with COVID-19 in Sudan; factors such as age, blood group, previous malaria infection, history of ailments such as diabetes, hypertension and symptoms suffered were also considered and analysed. More women were infected than men, and individuals between 25 and 35 years were the most affected age group. O Rhesus-positive (O+) blood group was the least affected by the disease while A Rhesus-positive (A+) individuals were the most vulnerable. Fatigue, fever and loss of smell were the major symptoms among the patients, but 13% of SARS-COV-2-positive individuals remained asymptomatic. As the Sudan population is largely constituted of O Rhesus-positive inhabitants (approximately 50%) these results might explain the relatively lower COVID-19 incidence in the country.