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  • Open Access

    ARTICLE

    Prostate cancer temporal and regional trends in Brazil

    MEHRSA JALALIZADEH1,#, HEVELINE RAYANE MOURA ROESCH1,#, FERNANDO KORKES2, QUOC DIEN-TRINH3, LEONARDO OLIVEIRA REIS1,4,*

    Oncology Research, Vol.32, No.10, pp. 1565-1573, 2024, DOI:10.32604/or.2024.052179 - 18 September 2024

    Abstract Objectives: The Brazilian Unified Health System (Sistema Único de Saúde−SUS) is the universal public healthcare system of Brazil that maintains a nationwide database of its patients. Our primary objective was to analyze regional and temporal trends, while our secondary goal was to establish correlations between states’ health economy status and their prostate cancer (PCa) epidemiology. Methods: We analyzed Brazil’s nationwide data on prostate cancer (PCa) incidence, mortality, and care gathered between 2013 and 2021 by the Information Technology Department of SUS (DATA-SUS), updated monthly using the International Classification of Diseases (ICD-10) code. Results: In the period,… More >

  • Open Access

    ARTICLE

    Prospect Theory Based Individual Irrationality Modelling and Behavior Inducement in Pandemic Control

    Wenxiang Dong, H. Vicky Zhao*

    CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.1, pp. 139-170, 2024, DOI:10.32604/cmes.2024.047156 - 16 April 2024

    Abstract Understanding and modeling individuals’ behaviors during epidemics is crucial for effective epidemic control. However, existing research ignores the impact of users’ irrationality on decision-making in the epidemic. Meanwhile, existing disease control methods often assume users’ full compliance with measures like mandatory isolation, which does not align with the actual situation. To address these issues, this paper proposes a prospect theory-based framework to model users’ decision-making process in epidemics and analyzes how irrationality affects individuals’ behaviors and epidemic dynamics. According to the analysis results, irrationality tends to prompt conservative behaviors when the infection risk is low More >

  • Open Access

    ARTICLE

    Sleep Quality and Emotional Adaptation among Freshmen in Elite Chinese Universities during Prolonged COVID-19 Lockdown: The Mediating Role of Anxiety Symptoms

    Xinqiao Liu*, Linxin Zhang, Xinran Zhang

    International Journal of Mental Health Promotion, Vol.26, No.2, pp. 105-116, 2024, DOI:10.32604/ijmhp.2023.042359 - 08 March 2024

    Abstract Under the effects of COVID-19 and a number of ongoing lockdown tactics, anxiety symptoms and poor sleep quality have become common mental health issues among college freshmen and are intimately related to their emotional adaptation. To explore this connection, this study gathered data from a sample of 256 freshmen enrolled in an elite university in China in September 2022. The association between sleep quality, anxiety symptoms, and emotional adaptation was clarified using correlation analysis. Additionally, the mediating function of anxiety symptoms between sleep quality and emotional adaptation was investigated using a structural equation model. The… More >

  • Open Access

    ARTICLE

    Do Public Health Events Promote the Prevalence of Adjustment Disorder in College Students? An Example from the COVID-19 Pandemic

    Rong Fu*, Luze Xie

    International Journal of Mental Health Promotion, Vol.26, No.1, pp. 21-30, 2024, DOI:10.32604/ijmhp.2023.041730 - 05 February 2024

    Abstract COVID-19, as one of the most serious sudden public health problems in this century, is a serious threat to people’s mental health. College students, as a vulnerable group, are more likely to develop mental health problems. When the body is unable to adapt to new changes in the environment, the main mental health problem that arises is adjustment disorder. The aim of this study was to assess the prevalence and influencing factors of adjustment disorder among college students during the COVID-19 outbreak in China. Cross-sectional data collected by web-based questionnaires were obtained through convenience sampling… More >

  • Open Access

    REVIEW

    Social Media-Based Surveillance Systems for Health Informatics Using Machine and Deep Learning Techniques: A Comprehensive Review and Open Challenges

    Samina Amin1, Muhammad Ali Zeb1, Hani Alshahrani2,*, Mohammed Hamdi2, Mohammad Alsulami2, Asadullah Shaikh3

    CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.2, pp. 1167-1202, 2024, DOI:10.32604/cmes.2023.043921 - 29 January 2024

    Abstract Social media (SM) based surveillance systems, combined with machine learning (ML) and deep learning (DL) techniques, have shown potential for early detection of epidemic outbreaks. This review discusses the current state of SM-based surveillance methods for early epidemic outbreaks and the role of ML and DL in enhancing their performance. Since, every year, a large amount of data related to epidemic outbreaks, particularly Twitter data is generated by SM. This paper outlines the theme of SM analysis for tracking health-related issues and detecting epidemic outbreaks in SM, along with the ML and DL techniques that… More >

  • Open Access

    VIEWPOINT

    Future of the current anticoronaviral agents: A viewpoint on the validation for the next COVIDs and pandemics

    AMGAD M. RABIE*

    BIOCELL, Vol.47, No.10, pp. 2133-2139, 2023, DOI:10.32604/biocell.2023.030057 - 08 November 2023

    Abstract Despite the global decline in the severity of the coronavirus disease 2019 (COVID-19) cases, the disease still represents a major concern to the relevant scientific and medical communities. The primary concern of drug scientists, virologists, and other concerned specialists in this respect is to find ready-to-use suitable and potent anticoronaviral therapies that are broadly effective against the different species/strains of the coronaviruses in general, not only against the current and previous coronaviruses (e.g., the recently-appeared severe acute respiratory syndrome coronavirus 2 “SARS-CoV-2”), i.e., effective antiviral agents for treatment and/or prophylaxis of any coronaviral infections, including More > Graphic Abstract

    Future of the current anticoronaviral agents: A viewpoint on the validation for the next COVIDs and pandemics

  • Open Access

    ARTICLE

    Effect of Online Social Networking on Emotional Status and Its Interaction with Offline Reality during the Early Stage of the COVID-19 Pandemic in China

    Xiaolin Lu1,*, Xiaolei Miao2

    International Journal of Mental Health Promotion, Vol.25, No.9, pp. 1041-1052, 2023, DOI:10.32604/ijmhp.2023.030232 - 10 August 2023

    Abstract Background: During the early stages of the COVID-19 pandemic in China, social interactions shifted to online spaces due to lock-downs and social distancing measures. As a result, the impact of online social networking on users’ emotional status has become stronger than ever. This study examines the association between online social networking and Internet users’ emotional status and how offline reality affects this relationship. Methods: The study utilizes cross-sectional online survey data (n = 3004) and Baidu Migration big data from the first 3 months of the pandemic. Two dimensions of online networking are measured: social… More > Graphic Abstract

    Effect of Online Social Networking on Emotional Status and Its Interaction with Offline Reality during the Early Stage of the COVID-19 Pandemic in China

  • Open Access

    ARTICLE

    The Mediating Role of Religious Beliefs in the Relationship between Well-Being and Fear of the Pandemic

    Van-Son Huynh1, Thanh-Thao Ly1, My-Tien Nguyen-Thi1,*, Xuan Thanh Kieu Nguyen2, Gallayaporn Nantachai3,4, Vinh-Long Tran-Chi1

    International Journal of Mental Health Promotion, Vol.25, No.9, pp. 1019-1031, 2023, DOI:10.32604/ijmhp.2023.029235 - 10 August 2023

    Abstract Religion is one of the social entities that has had a significant impact on the pandemic. The study’s goals are to investigate the relationship between well-being and fear of COVID-19, as well as to test whether religious beliefs mediate the effect of wellbeing on fear of COVID-19. The sample comprised of 433 participants in Vietnam. Independent Sample t-Test, One-way ANOVA, mediation analysis were used to analyze the data. In the levels of well-being, individuals who engage in religious services daily have higher levels than those hardly and never attend, and people from the age of 18 More >

  • Open Access

    ARTICLE

    Blockchain and IIoT Enabled Solution for Social Distancing and Isolation Management to Prevent Pandemics

    Muhammad Saad1, Maaz Bin Ahmad1,*, Muhammad Asif2, Muhammad Khalid Khan1, Toqeer Mahmood3, Elsayed Tag Eldin4,*, Hala Abdel Hameed5,6

    CMC-Computers, Materials & Continua, Vol.76, No.1, pp. 687-709, 2023, DOI:10.32604/cmc.2023.038335 - 08 June 2023

    Abstract Pandemics have always been a nightmare for humanity, especially in developing countries. Forced lockdowns are considered one of the effective ways to deal with spreading such pandemics. Still, developing countries cannot afford such solutions because these may severely damage the country’s economy. Therefore, this study presents the proactive technological mechanisms for business organizations to run their standard business processes during pandemic-like situations smoothly. The novelty of this study is to provide a state-of-the-art solution to prevent pandemics using industrial internet of things (IIoT) and blockchain-enabled technologies. Compared to existing studies, the immutable and tamper-proof contact… More >

  • Open Access

    ARTICLE

    Statistical Time Series Forecasting Models for Pandemic Prediction

    Ahmed ElShafee1, Walid El-Shafai2,3, Abeer D. Algarni4,*, Naglaa F. Soliman4, Moustafa H. Aly5

    Computer Systems Science and Engineering, Vol.47, No.1, pp. 349-374, 2023, DOI:10.32604/csse.2023.037408 - 26 May 2023

    Abstract COVID-19 has significantly impacted the growth prediction of a pandemic, and it is critical in determining how to battle and track the disease progression. In this case, COVID-19 data is a time-series dataset that can be projected using different methodologies. Thus, this work aims to gauge the spread of the outbreak severity over time. Furthermore, data analytics and Machine Learning (ML) techniques are employed to gain a broader understanding of virus infections. We have simulated, adjusted, and fitted several statistical time-series forecasting models, linear ML models, and nonlinear ML models. Examples of these models are… More >

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