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Egypt faces wheat insecurity due to the limited cropped area of agricultural lands and the limited horizontal expansion disproportionate to the population increase. The issue of food security, crop consumption rates, and self-sufficiency is considered one of the most important problems facing countries that seek to improve sustainable agriculture and economic development to eliminate poverty or hunger. This research aims to use data mining classification techniques and decision tree algorithms to predict the food security status of strategic agricultural crops (e.g., wheat) as an Agro intelligence technique. Also, the outputs and extracted information from the prediction process will help decision-makers to take an appropriate decision to improve the self-sufficiency rate of wheat, especially in epidemic crises and hard times such as COVID-19, political, and economic disturbances. On the other hand, the research investigates the patterns of wheat production and consumption for the Egyptian population from 2005 to 2020. This research presents a methodology to predict the food security status of strategic agricultural crops through the case study of wheat in Egypt. The proposed model predicts the food security status of wheat with an accuracy of 92.3% to determine the self-sufficiency ratio of wheat in Egypt during the years from 2015 to 2020. Also, it identifies the factors affecting the food security status of wheat in Egypt, their impact on determining and improving the food security state and its rate of self-sufficiency. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.
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This study was conducted to determine the objective role of antiviral drugs such as arbidol, lopinavir/ritonavir, and others in improving clinical symptoms, decreasing duration of hospitalization, and decreasing duration of viral shedding in patients with mild and moderate COVID-19 infection. A systematic literature search was carried out on Google Scholar and PubMed databases, using the keywords "COVID-19”, "Antiviral”, "Treatment”, and "Symptomatic” in various combinations. Observational studies, cohort and case control studies, and clinical trials published in English with full-text available were included in the study. Data extraction was carried out from selected studies, and all statistical analysis for the study was carried out using Microsoft Excel. The key outcomes studied were time to negative PCR, duration of clinical stay, time to clinical improvement, and occurrence of adverse events. Seven studies were selected for final review after rigorous selection process. Data of total 4734 participants was analyzed, the majority of which were females (n=2810, 59.3%). The majority of participants had mild disease (n=4197, 88.65%). Average time for negative RT-PCR in the included treatment groups was 13.5 days, whereas the average duration of hospitalization was 14.9 days for the treatment groups. Adverse reactions such as ECG changes, gastrointestinal symptoms, secondary bacterial infections, and hepatic and renal dysfunction were scarcely reported in the included studies. There is no clear benefit in terms of duration of hospitalization and time to negative PCR with the use of various antiviral regimens in mild disease;however, these drugs did play a role in limiting disease progression in the participant population. Pending further evidence, the use of these drugs for the management of COVID-19 is not recommend in patients with mild disease. © 2022, The Running Line. All rights reserved.
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PurposeThis study aims to propose priority solutions for mitigating the impact of the Covid-19 pandemic through the Social Safety Net (SSN) based on the Islamic objectives. Design/methodology/approachThe analytic network process method is used in this study. Focus group discussions and in-depth interviews with relevant stakeholders were used to collect data and supplemented by a literature review to explore comprehensive information. FindingsThe findings indicate different opinions among experts, including regulators, practitioners, associations and academics regarding the most important priority solutions to the impact of Covid-19. However, experts agree that the highest priority solution is the SSN program in the lineage sector, specifically the distribution of the Family Hope Program. A program in the field of protecting the mind is the second priority solution. The program in the field of soul and wealth is the third priority solution. Originality/valueThis study contributes to the development of government policy to deal with the socioeconomic impact of Covid-19 based on the Islamic objectives by mapping the SSN through the five elements of protection, namely, faith, soul, mind, lineage and wealth protection based on priority solution.
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Blood cell identification and counting is critical for doctors and physicians nowadays in order to diagnose and treat a variety of disorders. Platelet identification and counting are frequently performed in the context of many types of sickness such as COVID-19 and others. However, it is frequently costly and time intensive. Additionally, it is not widely available. From this vantage point, it is necessary to develop an efficient technical model capable of detecting and counting three fundamental types of blood cells: platelets, red blood cells, and white blood cells. Thus, this study proposes a deep learning-based model based on the YOLOv5 model with a precision of 0.799. The model consists of thre different layers such as backbone, neck and output layer The model is extremely capable of detecting and counting individual blood cells. Doctors, physicians, and other professionals will be able to detect and count blood cells using real-time images. It will significantly minimise the cost and time associated with detecting and counting blood cells by utilizing real-time blood images. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.
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Background: Since the outbreak of the coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in December 2019, it has affected >200 countries, areas, or territories in 6 continents. At present, whether COVID-19 has an effect on thyroid function is unclear. The aim of this study was to evaluate thyroid function in iraqi patients with COVID-19. Methods: Clinical features, laboratory results, and real time PCR were reviewed for 60 patients with laboratory-confirmed COVID-19 without a history of thyroid disease. They were admitted to the Al-Sadr Teaching Hospital;Iraq between September and December 2021. Healthy participants who underwent routine physical checkups and non-COVID-19 patients the study as the control group. Thyroid hormone and (TSH), vitamin C levels were determine and compared between the COVID-19 and control groups. Results: TSH lower than the normal range of the patients with COVID-19 Compared to the control group. The levels of TSH and serum triiodothyronine (T3) of the patients with COVID-19 were significantly lower than those of the healthy control group. The lower the TSH and T3 levels were, with statistical significance (p <0.001). The degree of the decreases in TSH and T3 levels was positively correlated with the severity of the disease. The thyroxine (T4) level of the patients with COVID-19 was not significantly different from the control group. A relationship between ascorbate (vitamin C) and COVID-19 severity is well known. Conclusions: The Changing TSH and TT3 hormones in the blood of people with Coronavirus may have a role in the infection and the life cycle of the virus.
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Aim: To assess the neurological and mental health responses to pandemic Covid-19. Study design: Cohort study Place and duration of study: Department of Medicine, Chandka Medical College Hospital Larkana and Department of Medicine, Khairpur Medical College Hospital Khairpur Mir's from 1st October 2021 to 31st March 2022. Methodology: Two hundred patients who suffered Covid-19 infection and 200 who had any other life event except Covid-19 were enrolled. All patients who were above 18 years of age and were positive for Covid-19 through reverse transcriptase PCR were included in the study.Global Psych trauma Screening was done by enlisting twenty-two items which assessed trauma related symptoms while five items only assessed the factors increasing risks. Result(s): There were 112 (56%) females and 88 (44%) males in Covid-19 patients and 150 (75%) females and 50 (25%) males in non-Covid patients. The mean age of the Covid-19 patients was 49.65+/-15.5 year while of non Covid patients was 39.02+/-12.01 years. A significant increase in post-traumatic stress disorder (PTSD) cases probability was noted in the Covid-19 cases than non Covid-19 related events. Neurological responses showed that patients who had suffered from Covid 19 infections had a generalized weakness with hyposmia formation. Conclusion(s): Covid-19 is related with high level of depression, anxiety, hyposmia and other mental and neurological responses. Copyright © 2022 Lahore Medical And Dental College. All rights reserved.
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Blood cell identification and counting are essential nowadays for healthcare professionals and therapists treating a variety of diseases. Platelet detection and counting are commonly performed for various disorders such as COVID-19 and others. However, it is the most costly and time-consuming. Furthermore, it is not available everywhere. From that standpoint, it is necessary to develop an effective technological model for detecting and counting three fundamental kinds of blood cells: Platelets, Red Blood Cells (RBCs), and White Blood Cells (WBCs). So, a deep learning-based model is proposed in this study comparing two versions of YOLOv5 model such as YOLOv5s and YOLOv5m. It is found that the YOLOv5m model outperforms with 0.799 precision, where YOLOv5s produces 0.797 precision. The study suggests that the YOLOv5m model is highly capable of detecting and counting the blood cells individually. Doctors, physicians, and other clinicians will be capable to identify and quantify blood cells from real-time photos. It will save money and time by identifying and counting blood cells using real-time blood photos. © 2022 ACM.
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Background: The loss of smell and taste in COVID-19 patients is now acknowledged as one of the disease's primary symptoms.
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There is a need for a biomarker for lung injury in COVID-19 patients. In the present study, an attempt was carried out to examine the role of Dickkopf-related protein 1 (DKK1), High-mobility group box 1 protein (HMGB1), angiotensin-converting enzyme 2 (ACE2) as a function for the lung abnormalities in CT-scan (LACTS). To perform the goals, DKK1, HMGB1, and ACE2 were measured in patients and controls using the ELISA technique. In contrast, other parameters were measured spectrophotometrically. The results showed decreased SpO2 and albumin and an increase in the serum biochemical parameters (glucose, urea, creatinine, D-dimer, ACE2, DKK1, and HMGB1) in COVID-19 patients compared with the control group. In COVID-19 patients, the percentages of the lung abnormalities in CT-scan% are 40.67±11.84. The results showed that those patients with LACTS patients are slightly older and have lower SpO2 than the patients without the LACTS group. ACE2 shows a significant correlation with SpO2 (ρ = 0.336, p<0.01) and a negative correlation with albumin (ρ =-0.197, p<0.05). Other parameters showed no significant correlation with the measured biomarkers. In conclusion, COVID-19 patients have higher ACE, DKK1, and HMGB1 indicating the involvement of the pathways of these biomarkers in the disease progression including lung injury. © 2022, Bogor Agricultural University. All rights reserved.
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Background: Health care workers (HCWs) are crucial to maintaining healthcare services during COVID-19 pandemic. One of the greatest risks to healthcare system is the potentially high rate of infections due to COVID-19 among HCWs. Objective: To summarize the epidemiologic characteristics, clinical features, radiologic findings, laboratory data, and outcomes of health care workers diagnosed with coronavirus disease 2019 (COVID-19) in Sohag University Hospitals. Patients and methods: A retrospective study included 101 HCWs who were proved to have COVID-19. HCWs with COVID-19 were categorized to asymptomatic cases, mild cases which included patients with mild clinical symptoms and normal lung computed tomography (CT), and moderate cases which included patients with mild or moderate clinical features and abnormal lung CT. Results: 89.11% of infected HCWs had no definite history of contact with a confirmed case of COVID-19. A considerable percent of the patients presented with non-respiratory symptoms such as GIT, and neurological symptoms. Patients who had a moderate respiratory illness were significantly older than those who had a mild respiratory illness and were more likely to have diabetes. Home isolation was recommended in most cases (n=73). Several cases (n=24) preferred isolation in university undergraduate houses, and 4 patients were treated at isolation hospital, 2 of them needed oxygen therapy. Conclusion: COVID-19 in HCWs exhibited a wide spectrum of disease severity. Symptom-based screening for COVID-19 in HCWs may underestimate the affected number as there is a considerable percent of asymptomatic cases. For HCWs’ safety, the use of protective personal equipment and adherence to proper hand-hygiene practice are important protective tools during this pandemic. Also, there is a growing need for educational and training programs for all levels of HCWs. © 2021, Ain Shams University Faculty of Medicine. All rights reserved.
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The health sector in Bangladesh is yet to develop and provide universal healthcare services. The aim of this study is to investigate whether the applicability of digitization especially medical robots and blockchain technology can help to improve healthcare enterprises in Bangladesh during the ongoing COVID-19 pandemic. The findings indicate that Bangladesh healthcare enterprises are in a vulnerable situation because of unethical work practices of health workers, the need for medical robots, artificial intelligence, and blockchain technology to improve healthcare management. The study suggests that large investment, pro-patient care, corruption-free and ethical services in the healthcare management and service delivery is required, through joint collaboration with the public and the private sectors and also collaborative effort from the foreign sectors to implement the fourth industrial revolution in healthcare enterprises of the country. © 2021 The Author.
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Aim: To assess the knowledge, attitude and practice of the general population after six months of outbreak. Methods: A cross-sectional survey was conducted on the general population in the month of July 2020. In which the general population was randomly selected and assessed for knowledge, attitude and practice about COVID19. The questionnaire was designed to avoid any privacy information and all questions were mandatory to answer. Results: Total of 1200 participants enrolled male 552(46%) and female 648(54%). Age ranges between 20 to 60 years and education status of responders were divided into middle, higher secondary and graduate respectively;they were 192(16%), 420(35%) and 588(49%). Knowledge assessed through symptom & virus transmission questions fever, fatigue and dry cough responded by 768(64%) while rest question knowledge were very poor. Practice questions responses to the virus were very much disturbing and most believe hype created by government and media, admission causes loss of loved ones and doctors are responsible for giving death injections to admitted peoples. Only 768(64%) of respondents regularly sanitize hands and wash with soap. Conclusion: Response to the question in KAP study was very poor despite six month had been passed in outbreak, yet it is necessary to improve the knowledge by arranging online seminars, media talk and strong awareness campaign required to improve knowledge & motivate their attitude toward virus which will resulting good practice to avoid further transmission of infection.
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BACKGROUND: We investigated the clinical characteristics and risk factors for the isolation of multi-drug-resistant (MDR) Gram-negative bacteria (GNB) from critically ill COVID-19 patients. METHODS: We retrospectively matched (1:2) critical COVID-19 patients with one or more MDR GNB from any clinical specimen (cases), with those with no MDR GNB isolates (controls). RESULTS: Seventy-eight cases were identified (4.5 per 1000 intensive care unit (ICU) days, 95% confidence interval (CI) 3.6-5.7). Of 98 MDR GNB isolates, the most frequent species were Stenotrophomonas maltophilia (24, 24.5%), and Klebsiella pneumoniae (23, 23.5%). Two (8.7%) K. pneumoniae, and six (85.7%) Pseudomonas aeruginosa isolates were carbapenem resistant. A total of 24 (24.5%) isolates were not considered to be associated with active infection. Those with active infection received appropriate antimicrobial agents within a median of one day. The case group had significantly longer median central venous line days, mechanical ventilation days, and hospital length of stay (P<0.001 for each). All-cause mortality at 28 days was not significantly different between the two groups (P=0.19). Mechanical ventilation days (adjusted odds ratio 1.062, 95% CI 1.012-1.114; P=0.015), but not receipt of corticosteroids or tocilizumab, was independently associated with the isolation of MDR GNB. There was no association between MDR GNB and 28-day all-cause mortality (adjusted odds ratio 2.426, 95% CI 0.833-7.069; P= 0.104). CONCLUSION: In critically ill COVID-19 patients, prevention of MDR GNB colonization and infections requires minimizing the use of invasive devices, and to remove them as soon as their presence is no longer necessary.