Because the Coronavirus epidemic spread in Iraq, the COVID-19 epidemic of people quarantined due to infection is our application in this work. The numerical simulation methods used in this research are more suitable than other analytical and numerical methods because they solve random systems. Since the Covid-19 epidemic system has random variables coefficients, these methods are used. Suitable numerical simulation methods have been applied to solve the COVID-19 epidemic model in Iraq. The analytical results of the Variation iteration method (VIM) are executed to compare the results. One numerical method which is the Finite difference method (FD) has been used to solve the Coronavirus model and for comparison purposes. The numerical simulat

Background: Although underdeveloped in Iraq, telehealth was one tool used to continue health service provision during the COVID-19 pandemic. Aim: To assess women’s experiences and satisfaction with gynaecological and obstetric telehealth services in Iraq during the COVID-19 pandemic. Methods: Free telehealth services were provided by 4 obstetrician-gynaecologists associated with private clinics in 2020–2021. All patients who accessed the services between June 2020 and February 2021 were invited to complete a postconsultation survey on their experience and satisfaction with services. Results were analysed using descriptive statistics and logistic regression conducted using SPSS version 25. Results: A total of 151 (30.2%) women re

COVID-19 is a unique viral infectious illness that causes a variety of symptoms and health hazards, particularly to the respiratory system and has been declared a worldwide pandemic. The disease is characterized by a cytokine release in severe conditions. Interleukin-6 (IL-6), a proinflammatory cytokine, mediates an important immunomodulatory process. Also, vitamin D was identified to have a role in the innate immunity of individuals. Our study was designed to find the role of IL-6 and vitamin D in COVID-19 patients, as well as, to see whether there is a link between vitamin D deficiency and cytokine syndrome development. The study included 90 COVID-19 patients and 30 control people from Baghdad, Iraq. The age of the participants was non-s

Background: since December 2019, China and in particularly Wuhan, faced an unprecedented an outbreak challenge of coronavirus disease 2019, caused by the severe acute respiratory syndrome coronavirus 2. Clinical characteristics of Iraqi patients with COVID-19 and risk factors for mortality needed to be shared with the health care providers to improve the overall disease experience. Methods: prospective, single-center study recruited patients with confirmed SARS-CoV-2 infection who were admitted to Al-Shifaa Isolation Center / Baghdad Medical City between the mid of March and the end of April 2020 until had been discharged or had died. Demographic data, information on clinical signs, symptoms, at presentation, treatment, have been collected

This study aims to find the chemosensitive dysfunction incidence in COVID-19-positive patients and its recovery.

We collected the data from sixty-five patients, all COVID-19 positive, quarantined in-hospital between 5 April 2020 and 17 May 2020, by a questionnaire distributed in the quarantine ward.

The COVID-19 pandemic has necessitated new methods for controlling the spread of the virus, and machine learning (ML) holds promise in this regard. Our study aims to explore the latest ML algorithms utilized for COVID-19 prediction, with a focus on their potential to optimize decision-making and resource allocation during peak periods of the pandemic. Our review stands out from others as it concentrates primarily on ML methods for disease prediction.To conduct this scoping review, we performed a Google Scholar literature search using "COVID-19," "prediction," and "machine learning" as keywords, with a custom range from 2020 to 2022. Of the 99 articles that were screened for eligibility, we selected 20 for the final review.Our system