Introduction: According to international surveys, over half of the travellers face some kind of health issue when travelling. The overwhelming majority of travel-related illnesses can be prevented with pre-travel medical consultations, but the syllabus and content of the consultation have to match the travel habits and culture of the given society.
Aim: This publication explores the specificities and travel habits of Hungarian travellers.
Method: One hundred participants of a travel exhibition completed a survey about their international travel. As the survey was not representative, the data could only be processed through simple statistical methods. However, since the exhibition was presumably attended by those wishing to travel, the conclusions drawn from the results are worth publishing, since no similar survey in Hungary has been published before.
Results: Based on the suitable classification of age groups in travel medicine, 11% of the participants were adolescents / young adults (aged 15-24), 81% adults (25-59) and 8% elderly (60-74). Twenty-eight percent of the participants travel multiple times a year, 40% yearly and 32% of them less frequently; 16% of the adults, 8% of the adolescents and 4% of the elderly age group travel multiple times a year.
Conclusions: The travel destinations of Hungarian travellers have remained practically unchanged since a study was conducted 13 years ago: the vast majority (95%) travelled within Europe, 2% to the United States, and 11% of them elsewhere. Since Hungarians do not travel to endemic areas, only 5% consulted their general practitioners (GPs) prior to travelling, and 29% did when they had to be vaccinated. Forty-two percent of those wishing to travel never consult their GPs, even though 29% of them are aware of some chronic illness. Instead, 51% gather their health information from the internet and only 6% from their doctors. By the contradiction between the poor health status of the majority of Hungarian travellers and the negligence of seeking pre-travel advice, our survey clearly points out the importance of the propagation of doctor's advice before trips, even if the travellers visit exclusively non-endemic countries like the European Union. Orv Hetil. 2018; 159(9): 357-362.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1556/650.2018.30987 | DOI Listing |
Int J Med Microbiol
December 2024
Institute of Medical Microbiology, University Hospital Münster, Münster, Germany; Masanga Medical Research Unit, Masanga Hospital, Masanga, Sierra Leone.
Background: Nasopharyngeal colonization with Staphylococcus aureus is a risk factor for subsequent infection. Isolates from colonization can therefore provide important information on virulence factors and antimicrobial resistance when data from clinical isolates are lacking. The aim of this study was to assess colonization rates, resistance patterns and selected virulence factors of S.
View Article and Find Full Text PDFLung
January 2025
Department of Pulmonary Diseases, University of Groningen, University Medical Centre Groningen, PO Box 30001, 9700 RB, Groningen, The Netherlands.
NPJ Precis Oncol
January 2025
Zentalis Pharmaceuticals, Inc., San Diego, CA, USA.
Upregulation of Cyclin E1 and subsequent activation of CDK2 accelerates cell cycle progression from G1 to S phase and is a common oncogenic driver in gynecological malignancies. WEE1 kinase counteracts the effects of Cyclin E1/CDK2 activation by regulating multiple cell cycle checkpoints. Here we characterized the relationship between Cyclin E1/CDK2 activation and sensitivity to the selective WEE1 inhibitor azenosertib.
View Article and Find Full Text PDFNat Commun
January 2025
Lunenfeld-Tanenbaum Research Institute, Sinai Health System, Toronto, ON, Canada.
Spatial protein expression technologies can map cellular content and organization by simultaneously quantifying the expression of >40 proteins at subcellular resolution within intact tissue sections and cell lines. However, necessary image segmentation to single cells is challenging and error prone, easily confounding the interpretation of cellular phenotypes and cell clusters. To address these limitations, we present STARLING, a probabilistic machine learning model designed to quantify cell populations from spatial protein expression data while accounting for segmentation errors.
View Article and Find Full Text PDFBMC Neurol
January 2025
Department of Neurology, Friedrich-Baur-Institute, Ludwig-Maximilians-University of Munich, Munich, Germany.
Background: Due to improved treatment options, more SMA patients reach childbearing age. Currently, limited data on pregnant SMA patients is available, especially in relation to disease-modifying therapies (DMT). This case report helps to elucidate new approaches for future guidelines in the management of pregnancy and SMA.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!