Abstract
Objective: This thesis investigates the contributions of the Global Fund in controlling malaria in Vietnam since 2014, focusing on its multifaceted approaches, strategies, and interventions in malaria prevention, detection, and treatment, as well as overall health system strengthening.
Subject and Methods: The research employs a case study design combined with a desk review of project documents, financial reports, impact assessments, and academic literature. Qualitative methodologies, including key informant interviews and thematic analysis, are used to evaluate the advantages and disadvantages of the Global Fund's interventions.
Key Findings: The study finds that the Global Fund's contributions have significantly enhanced malaria control in Vietnam through increased funding, technical support, and infrastructural improvements. Notable successes include improved diagnostic capabilities, the introduction of rapid diagnostic tests (RDTs), and increased community awareness and engagement. However, challenges such as logistical issues, funding constraints, and the emergence of drug-resistant malaria strains were identified. The research highlights the critical role of international collaboration, government commitment, and community involvement in sustaining malaria control efforts and provides insights into effective public health interventions.
Frontiers in Tropical Diseases
The COVID-19 global pandemic has been going on for more than two years, and the evolution of SARS-CoV-2 with many variants of concern still poses a risk to public health. Sufficient access to qualified and validated testing plays an important role in detecting and alerting trends of the pandemic and provides evidence for making decisions in preventive strategies and policies. Depending on the method of testing and laboratory conditions, validation parameters (i.e., analytical sensitivity, limit of detection, diagnostic sensitivity, analytical specificity, diagnostic specificity, repeatability, reproducibility, robustness, positive predictive value, negative predictive value, applicability, practicability, and time to results) can be very different. With three main types of COVID-19 detection kits available, comprising nucleic acid, serological, and antigen detection, the kind of validation parameters that should be used becomes a complicated consideration and takes time to assess. Our review provides valuable and comprehensive information for laboratories in the assessment and selection of the optimal parameters to validate new COVID-19 test kits.
Applied sciences
A mobile-phone-based diagnostic tool, which most of the population can easily access, could be a game changer in increasing the number of examinations of people with dental caries. This study aimed to apply a deep learning algorithm in diagnosing the stages of smooth surface caries via smartphone images. Materials and methods: A training dataset consisting of 1902 photos of the smooth surface of teeth taken with an iPhone 7 from 695 people was used. Four deep learning models, consisting of Faster Region-Based Convolutional Neural Networks (Faster R-CNNs), You Only Look Once version 3 (YOLOv3), RetinaNet, and Single-Shot Multi-Box Detector (SSD), were tested to detect initial caries lesions and cavities. The reference standard was the diagnosis of a dentist based on image examination according to the International Caries Classification and Management System (ICCMS) classification. Results: For cavitated caries, YOLOv3 and Faster R-CNN showed the highest sensitivity among the four tested models, at 87.4% and 71.4%, respectively. The sensitivity levels of these two models were only 36.9 % and 26% for visually non-cavitated (VNC). The specificity of the four models reached above 86% for cavitated caries and above 71% for VNC. Conclusion: The clinical application of YOLOv3 and Faster R-CNN models for diagnosing dental caries via smartphone images was promising. The current study provides a preliminary insight into the potential translation of AI from the laboratory to clinical practice.
cancer, cancer control, cancer burden, prevention, early detection, screening, treatment, health systems, health policy, review, NCDs, Vietnam
This study aimed to describe mental health service utilization and examine associated factors among students in Vietnam. Data were collected at eight universities in Hanoi, Vietnam, in 2018 using an administered questionnaire. The total number of participants was 9,120 (95.1% response rate). Among stu dents participating in our survey, 12.5% (95% CI: 10.9–14.1) with depression and/or anxiety symptoms used mental health service in the last 12 months. In the multivariable regression models, significant factors associated with mental health ser vice utilization were marital status, types of housemate, men tal health problems, physical activity, smoking status, and alcohol drinking. Our study made recommendations to stake holders for improving mental health services utilization among students in Vietnam. These findings had important implica tions for future research on factors associated with mental health service utilization among university students.
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