: Epidemiology Update and a Review of Strategies to Prevent Spread.

J Clin Med

Division of Infectious Diseases, Department of Medicine, College of Medicine, University of Arizona, Tucson, AZ 85724, USA.

Published: November 2024

AI Article Synopsis

  • Candida auris is a rapidly spreading fungal pathogen that poses serious health risks and has led to considerable illness and death.
  • The review highlights current understanding of its epidemiology and effective strategies to prevent its spread and outbreaks.
  • Future research directions are also explored to better manage and combat this emerging threat.

Article Abstract

Candida auris () has emerged as a fungal pathogen with great propensity to spread rapidly on a global scale. infections have also caused significant morbidity and mortality. Strategies to prevent spread and outbreaks are critical. In this review, an update on the epidemiology of and a discussion of strategies to combat the spread of are presented. Future directions are also discussed.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11595167PMC
http://dx.doi.org/10.3390/jcm13226675DOI Listing

Publication Analysis

Top Keywords

strategies prevent
8
prevent spread
8
epidemiology update
4
update review
4
review strategies
4
spread
4
spread candida
4
candida auris
4
auris emerged
4
emerged fungal
4

Similar Publications

The novel coronavirus (COVID-19) has affected more than two million people of the world, and far social distancing and segregated lifestyle have to be adopted as a common solution in recent years. To solve the problem of sanitation control and epidemic prevention in public places, in this paper, an intelligent disinfection control system based on the STM32 single-chip microprocessor was designed to realize intelligent closed-loop disinfection in local public places such as public toilets. The proposed system comprises seven modules: image acquisition, spraying control, disinfectant liquid level control, access control, voice broadcast, system display, and data storage.

View Article and Find Full Text PDF

Untangling areas of improvement in secondary prevention of ischemic stroke in patients with atrial fibrillation.

Sci Rep

December 2024

Health Services Research and Pharmacoepidemiology Unit, Foundation for the Promotion of Health and Biomedical Research of Valencia Region (FISABIO), Avenida Cataluña, 21, 46020, Valencia, Spain.

Improvement of post-stroke outcomes relies on patient adherence and appropriate therapy maintenance by physicians. However, comprehensive evaluation of these factors is often overlooked. This study assesses secondary stroke prevention by differentiating patient adherence to antithrombotic treatments (ATT) from physician-initiated interruptions or switches.

View Article and Find Full Text PDF

Climate change has caused many challenges to soil ecosystems, including soil salinity. Consequently, many strategies are advised to mitigate this issue. In this context, biochar is acknowledged as a useful addition that can alleviate the detrimental impacts of salt stress on plants.

View Article and Find Full Text PDF

While bacille-calmette-guerin (BCG) vaccination is one of the recommended strategies for preventing tuberculosis (TB), its coverage is low in several countries, including Ethiopia. This study investigated the spatial co-distribution and drivers of TB prevalence and low BCG coverage in Ethiopia. This ecological study was conducted using data from a national TB prevalence survey and the Ethiopian demographic and health survey (EDHS) to map the spatial co-distribution of BCG vaccination coverage and TB prevalence.

View Article and Find Full Text PDF

This study presents a web application for predicting cardiovascular disease (CVD) and hypertension (HTN) among mine workers using machine learning (ML) techniques. The dataset, collected from 699 participants at the Gol-Gohar mine in Iran between 2016 and 2020, includes demographic, occupational, lifestyle, and medical information. After preprocessing and feature engineering, the Random Forest algorithm was identified as the best-performing model, achieving 99% accuracy for HTN prediction and 97% for CVD, outperforming other algorithms such as Logistic Regression and Support Vector Machines.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!