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COVID-19 Vaccine Uptake And Its’ Associated Factors among general population In Basmaia City in Baghdad 2022
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Abstract<sec><title>Objective

Vaccination is a vital cornerstone of public health, which has saved countless lives throughout history. Therefore, achieving high vaccination uptake rates is essential for successful vaccination programs. Unfortunately, vaccine uptake has been hindered by deferent factors and challenges. The objective of this study is to assess COVID-19 vaccine uptake and associated factors among the general population.

Methods

This study is a descriptive cross-sectional study conducted in Basmaia city, Baghdad from June to October 2022. Data were collected through a semi-structured questionnaire using multi-stage random sampling. Statistical analysis was performed using descriptive statistics, chi-square analysis, Mann-Whitney test, and binary and multivariable logistic regression.

Results

The prevalence of COVID-19 vaccine uptake was 70.4%. The most common reason for getting vaccinated was protection from the disease, while fear of side effects and not needing the vaccine were the main reasons for refusal.

The study found that gender, age, education level, job title, risk perception, knowledge, and attitude towards the vaccine were significantly associated with COVID-19 vaccine uptake. Males were 2.273 times more likely to get vaccinated than females, and older age groups had higher odds of vaccination than younger age groups. Those with higher education levels were also more likely to receive the vaccine. Participants with higher risk perception, knowledge, and positive attitude towards the vaccine were more likely to get vaccinated.

And found that mandatory vaccination policies may negatively impact uptake of subsequent vaccine doses.

Conclusion

The study found a high prevalence of COVID-19 vaccine uptake, with gender, age, education level, and job title being significant factors associated with vaccine uptake. Additionally, mandatory vaccination policies may have a negative impact on the uptake of subsequent vaccine doses. Public health efforts should prioritize addressing these factors to increase vaccine uptake.

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Publication Date
Tue Jan 01 2019
Journal Name
Advances In Public Health
Detection of Antibiotics in Drinking Water Treatment Plants in Baghdad City, Iraq
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Persistence of antibiotics in the aquatic environment has raised concerns regarding their potential influence on potable water quality and human health. This study analyzes the presence of antibiotics in potable water from two treatment plants in Baghdad City. The collected samples were separated using a solid-phase extraction method with hydrophilic-lipophilic balance (HLB) cartridge before being analyzed. The detected antibiotics in the raw and finished drinking water were analyzed and assessed using high-performance liquid chromatography (HPLC), with fluorometric detector and UV detector. The results confirmed that different antibiotics including fluoroquinolones andB-lactams were detected in the raw an

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Publication Date
Tue Jan 30 2024
Journal Name
Iraqi Journal Of Science
A Study of Drinking Water Properties in Some Hospitals in Baghdad City
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One of the bigger problems in drinking water is disinfection by-products (DBPs) that come from chlorinated disinfection. This study’s goal was to evaluate the drinking water in Al-Yarmouk Teaching Hospital, Ibn Sina Hospital and Ibn-Al-Nafis Hospital.  Samples were collected between October 2018 and September 2019. Physical and chemical characteristics of the water were studied, including (temperature, hydrogen ion (pH), total dissolved solids (TDS), electrical conductivity (EC), turbidity, free residual chlorine, total organic carbon (TOC), total trihalomethanes (THMs), total halo acetic acid (THAAs)). Data analysis showed the highest value of study temperature, pH, TDS, EC, turbidity, free residual chlorine and TOC which was

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Publication Date
Thu May 06 2021
Journal Name
International Journal Of Pharmacy Practice
Impact of COVID-19 pandemic on healthcare providers: save the frontline fighters
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Abstract<sec><title>Objectives

The objective of this study was to assess the impact of the COVID-19 pandemic on healthcare providers (HCPs) at personal and professional levels.

Methods

This was a cross-sectional descriptive study. It was conducted using an electronic format survey through Qualtrics Survey Software in English. The target participants were HCPs working in any healthcare setting across Iraq. The survey was distributed via two professional Facebook groups between 7 April and 7 May 2020. The survey items were adopted with modifications from three previous studies of Severe Acute Respiratory Syndrome (SARS) and Avia

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Publication Date
Tue Sep 01 2026
Journal Name
International Journal Of Advances In Applied Sciences
COVID-19 infection detection using convolutional self-attention network with voting classifier
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Early and accurate detection of COVID-19 from chest computed tomography (CT) scans are becoming essential for effective clinical decision-making and disease control. This study is proposing a robust deep learning framework that integrates a convolutional self-attention network (CSAN), gamma correction for image enhancement, and a voting-based ensemble classifier to improving diagnostic performance. The model is being evaluated on a dataset of 2,271 CT images and is achieving an accuracy of 95.12%, sensitivity of 97.25%, specificity of 98.11%, F1-score of 96.46%, and area under the curve (AUC) of 0.977. Experimental results are demonstrating that the proposed method significantly surpasses baseline models, including standalone CSAN,

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Publication Date
Thu May 06 2021
Journal Name
International Journal Of Pharmacy Practice
Impact of COVID-19 pandemic on healthcare providers: save the frontline fighters
...Show More Authors
Abstract<sec><title>Objectives

The objective of this study was to assess the impact of the COVID-19 pandemic on healthcare providers (HCPs) at personal and professional levels.

Methods

This was a cross-sectional descriptive study. It was conducted using an electronic format survey through Qualtrics Survey Software in English. The target participants were HCPs working in any healthcare setting across Iraq. The survey was distributed via two professional Facebook groups between 7 April and 7 May 2020. The survey items were adopted with modifications from three previous studies of Severe Acute Respiratory Syndrome (SARS) and Avia

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Scopus (11)
Crossref (3)
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Publication Date
Sun Oct 03 2021
Journal Name
Journal Of Interdisciplinary Mathematics
Application of topological concepts to the investigation of COVID-19 (modified) symptoms
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We examine 10 hypothetical patients suffering from some of the symptoms of COVID 19 (modified) using topological concepts on topological spaces created from equality and similarity interactions and our information system. This is determined by the degree of accuracy obtained by weighing the value of the lower and upper figures. In practice, this approach has become clearer.

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Publication Date
Fri Oct 20 2023
Journal Name
Al-ameed Journal For Medical Research And Health Sciences
Perceptions of Nursing Students about COVID-19 Transmission: A Multi University Study
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Publication Date
Wed Feb 01 2023
Journal Name
Indonesian Journal Of Electrical Engineering And Computer Science
Diagnose COVID-19 by using hybrid CNN-RNN for Chest X-ray
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<p>Combating the COVID-19 epidemic has emerged as one of the most promising healthcare the world's challenges have ever seen. COVID-19 cases must be accurately and quickly diagnosed to receive proper medical treatment and limit the pandemic. Imaging approaches for chest radiography have been proven in order to be more successful in detecting coronavirus than the (RT-PCR) approach. Transfer knowledge is more suited to categorize patterns in medical pictures since the number of available medical images is limited. This paper illustrates a convolutional neural network (CNN) and recurrent neural network (RNN) hybrid architecture for the diagnosis of COVID-19 from chest X-rays. The deep transfer methods used were VGG19, DenseNet121

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Publication Date
Wed Jan 15 2025
Journal Name
Human Antibodies
State of type 2 diabetic Iraqi patients after hospitalization for COVID-19
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Background

The coronavirus-19 (COVID-19) pandemic, triggered by the severe acute respiratory syndrome coronavirus 2, has affected over 100 million people and killed around 2 million individuals. One of the most common chronic illnesses in the world is diabetes, which greatly raises the risk of hospitalization and death for COVID-19 patients.

Objective

This study aims to analyze the novel coronavirus's general characteristics and shed light on COVID-19 and its management in diabetic individuals by measuring some metabolic and inflammatory factors in type 2 diabetic pa

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Publication Date
Sat Apr 01 2023
Journal Name
Baghdad Science Journal
COVID-19 Diagnosis Using Spectral and Statistical Analysis of Cough Recordings Based on the Combination of SVD and DWT
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Healthcare professionals routinely use audio signals, generated by the human body, to help diagnose disease or assess its progression. With new technologies, it is now possible to collect human-generated sounds, such as coughing. Audio-based machine learning technologies can be adopted for automatic analysis of collected data. Valuable and rich information can be obtained from the cough signal and extracting effective characteristics from a finite duration time interval that changes as a function of time. This article presents a proposed approach to the detection and diagnosis of COVID-19 through the processing of cough collected from patients suffering from the most common symptoms of this pandemic. The proposed method is based on adopt

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