Serum interleukin 1ß and sP-selectin as biomarkers of inflammation and thrombosis, could they be predictors of disease severity in COVID 19 Egyptian patients? (a cross-sectional study).

BACKGROUND: Thromboembolism was a chief cause of mortality in 70% of patients with COVID-19. Our objective was to see if serum interleukins 1 beta (IL-1ß) and soluble platelets selectin (sP-selectin) could serve as novel markers of thromboembolism in COVID-19 patients. METHODS: This cross sectional study involved 89 COVID-19 patients who were recruited from 1st of February to 1st of May 2021. Clinical and laboratory data were collected, and chest imaging was performed. The levels of IL-1ß and sP-selectin were assessed in all cases through ELISA kits. Comparisons between groups were done using an unpaired t-test in normally distributed quantitative variables. In contrast, a non-parametric Mann-Whitney test was used for non-normally distributed quantitative variables. RESULTS: Severe COVID-19 infection was associated with higher serum levels of CRP, Ferritin, LDH, D dimer, IL-1ß and sP-selectin (P <  0.001) with significant correlation between levels of IL-1ß and sP-selectin (r 0.37, P <  0.001), D-dimer (r 0.29, P 0.006) and Ferritin (r 0.5, p <  0.001). Likewise, a positive correlation was also found between levels of sP-selectin, D-dimer and Ferritin (r 0.52, P <  0.001) (r 0.59, P <  0.001). Imaging studies revealed that 9 (10.1%) patients developed venous and 14 (15.7%) developed arterial thrombosis despite receiving anticoagulant therapy. Patients with thrombotic events had significantly higher levels of IL-1ß, sP-selectin and LDH serum levels. Meanwhile, there was no statistical significance between CRP, D-dimer or Ferritin levels and the development of thrombotic events. CONCLUSION: IL-1ß and sP-selectin levels can be promising predictors for severe COVID-19 infection and predictable thrombosis.

Do Vaccinations, Despite Mutations, End The Coronavirus Crisis?

The coronavirus disease was announced in 2019 as a pandemic. Despite the wised measures taken by a Governments and herd immunity, many waves of the virus and its mutants continued to brutally confront the world. There has been no misgiving that vaccination is the only or most influential method of combating it, as happened before in many epidemics such as measles, smallpox, and cholera. So governments and the World Health Organization have sought to make vaccines to confront the virus and approved in less than a year. This rapid vaccine development endeavor raised several concerns regarding the vaccines' effectiveness and safety. Since there is not sufficient, time to conduct sufficient clinical studies about vaccines. There are important questions the vaccinations not affect or will this damn virus ever end? We developed regression with a 7th-degree polynomial and offered case studies from 10 nations to back up our conclusions. The countries are the USA, Spain, Qatar, France, Brazil, Colombia, India, Russia, Kuwait, and Egypt. We fitted a model for every country by comparing the number of cases before vaccination and after vaccination for 8 weeks approximately. Our prediction in this article is based on the data sets given by the World Health Organization. Using machine learning is proved that vaccination cuts down on the number of diseased people and deaths despite the mutations by applying the models to many countries. We are concluding with further development for the domain of the proposed model.

Awareness, knowledge, attitudes, and behaviors related to COVID-19 in Libya: a nation-wide online survey.

INTRODUCTION: the World Health Organization declared the COVID-19 outbreak to be a global pandemic in March 2020. However, the pandemic cannot be ended overnight and more social distancing and other self-care measures are needed to protect our communities. Therefore, people´s awareness, knowledge, attitudes, and appropriate behaviors are instrumental to containing the pandemic. The aim of this study was to determine COVID-19 awareness, knowledge, attitudes, and related behaviors in Libya. METHODS: a cross-sectional online survey was conducted from October 10th to November 10th, 2020 in 24 cities in Libya. The participants were non-medical professionals who were living in Libya for at least 2 years and were at least 18 years old. RESULTS: a total of 1018 participants completed the questionnaire, with ages ranging from 18-74 years (Mean ± SD = 33.49±13.24); nearly two-thirds were < 40, and 68.2% were females. Almost half of the participants considered the potential threat of COVID-19 to be low, and one in five reported that they were "Not worried at all" about getting COVID-19. In multivariate analyses, participants who were 40-49 years old, had master´s degrees or higher, and worked in the private sector reflected high mean scores for both knowledge and attitudes, while those who lived in the Eastern or Southern regions had lower mean attitude scores. CONCLUSION: the low levels of awareness as well as the attitudes and behaviors among the public in Libya are worrisome. This study highlighted profound gaps that may put Libyan communities at high risk of a COVID-19 explosion. Therefore, immediate action is needed to address public awareness and attitudes and to improve COVID-19 related behaviors among the Libyan public.

Psychosocial Impact of COVID-19 Pandemic in Libya: A Cross-Sectional Study.

Background: Since the outbreak of COVID-19 were announced in Wuhan, China, the virus has spread in most countries. After one year of restrictive measures applied by governments, it is unclear how this prolonged social distancing has affected the mental health of individuals in Libya. Therefore, the present study aims to assess the levels of perceived stress, depression, sleep disturbance, and self-efficacy associated with the pandemic in Libya and their association with the demographic factors. Methods: A cross-sectional study was conducted between October 10 and November 10, 2020 in 21 cities in Libya using an online survey. The survey collected socio-demographic variables and other important psychological variables using valid scales: namely, the Perceived Stress scale, the PROMIS Depression scale, the PROMIS Sleep Disturbance scale, and self-efficacy 6-item scale. Additionally, data were collected regarding eating and smoking habits, housing and living situations, and the preparedness of the public to manage the upcoming waves of the pandemic. Results: The questionnaire was accessed 746 times, and a total of 683 completed questionnaires were analyzed (response rate of 91.6%), with ages ranging from 18 to 94 years (Mean ± SD = 27.09 ± 10.57). Among the respondents, 58.4% were females and 77% were from the age group 18-29 years. The perceived stress, depression, and sleep disturbance symptoms were high in overall population. For stress, 52.7 and 17.1% of respondents reported moderate and high stress, and for sleep quality 28.8 and 8.1% reported moderate and high sleep disturbance, respectively. For depression, the overall median score was 20 (out of 40). The perceived stress, depression, and sleep disturbance were more prevalent among females and the younger age groups (18-29 years old). The overall self-efficacy median total score was 6.67 (out of 10), with a significantly higher median total score for males than females (7 vs. 6.33, p = 0.001). About 14.5% of the respondents were regular cigarette smokers, and most of them (79.8%) described their smoking habits during the previous month as more than typical. In addition, the reported eating habits of almost half of the respondents (43%) had changed, with about one-third (29.6%) reporting that their eating habits had become less healthy during the pandemic. Conclusion: The findings of this research suggest increased levels of stress, depression, and sleep disturbances as well as COVID-19-related fear during the pandemic, especially among young females. This alarming finding urgently calls for safe and low-barrier interventions to help mentally burdened individuals. This study makes a significant contribution in providing essential data on the psychological and social impacts on the Libyan population due to the COVID-19 pandemic.

Prediction of the final size for COVID-19 epidemic using machine learning: A case study of Egypt.

COVID-19 is spreading within the sort of an enormous epidemic for the globe. This epidemic infects a lot of individuals in Egypt. The World Health Organization states that COVID-19 could be spread from one person to another at a very fast speed through contact and respiratory spray. On these days, Egypt and all countries worldwide should rise to an effective step to investigate this disease and eliminate the effects of this epidemic. In this paper displayed, the real database of COVID-19 for Egypt has been analysed from February 15, 2020, to June 15, 2020, and predicted with the number of patients that will be infected with COVID-19, and estimated the epidemic final size. Several regression analysis models have been applied for data analysis of COVID-19 of Egypt. In this study, we've been applied seven regression analysis-based models that are exponential polynomial, quadratic, third-degree, fourth-degree, fifth-degree, sixth-degree, and logit growth respectively for the COVID-19 dataset. Thus, the exponential, fourth-degree, fifth-degree, and sixth-degree polynomial regression models are excellent models specially fourth-degree model that will help the government preparing their procedures for one month. In addition, we have applied the well-known logit growth regression model and we obtained the following epidemiological insights: Firstly, the epidemic peak could possibly reach at 22-June 2020 and final time of epidemic at 8-September 2020. Secondly, the final total size for cases 1.6676E+05 cases. The action from government of interevent over a relatively long interval is necessary to minimize the final epidemic size.