The investigators hypothesize that sex, age, area of exposure and purpose of travel are associated with different travel-related infections. The investigators also hypothesize that certain infections will have long-term sequelae. Health-data will be collected from travellers from Switzerland and Europe. The project starts with a pilot study for 50 travellers, followed by the recruiting of 10,000 travellers. The data collection will be via a mobile App (ITIT). The ITIT App will collect active data from travellers. The participants will download the App after signing an electronic consent form and completing a baseline questionnaire. Then the travellers will answer a short daily questionnaire about illness symptoms during travel. The ITIT App will also collect passive data (GPS localisation, environmental and weather data). The project will provide real-time data on travel-related infections and profile travel illness by age, sex and purpose of travel and also identify outbreaks.
International travel is growing exponentially. Globally, there will be a projected 1.8 billion traveller arrivals in 2030. Current surveillance of travellers' health is top-down (i.e., clinicians/laboratories report illness) and only a small proportion of illness events are captured. More data are needed on the types of infections acquired by different groups who have varying purposes of travel such as business/corporate travellers, those visiting friends and relatives (VFR), leisure/tourist travellers and mass gathering event (Hajj, Olympics, World Cup) attendees. More data are needed to profile infections in travellers according to age and sex as men and women have different infection susceptibilities. Infectious diseases, in particular the spread of malaria and "arboviral infections",(i.e. viruses such as dengue) pose major threats with changing epidemiology influenced by climate, environmental factors and human mobility. The extent and impact of these infections on travellers' health and their long-term sequelae have scarcely been evaluated. The collected data will allow the profiling of infections in travellers according to purpose of travel and according to age and sex. Men and women have different infection susceptibilities but there is just one study on this theme in the context of travel medicine Infectious diseases, in particular the spread of malaria and "arboviral infections", i.e. viruses such as dengue, chikungunya and Zika pose major threats with changing areas of transmission influenced by climate and mobility. Although airline statistics are available on traveller numbers, the volume of ill, returning, possibly viremic travellers entering areas, where susceptible vectors exist has never been quantified. The situation of a twin presence of viremic travellers and competent Aedes vectors may lead to the onward transmission of arboviral infections. The ITIT project, evaluating in-travel and post-travel illness profiles, coupled with geo-location and meteorological data, will yield the granular data needed for personalized travel medicine. This is important given the heterogenicity and increasing volume of global travellers. The project has the support of the World Health Organization (WHO). Since the data will be collected anonymously via a questionnaire on the designed mobile App and the study is non-interventional, the risk category for this project is minimal (A).
Study Type
OBSERVATIONAL
Enrollment
10,000
No intervention is planned
Epidemiology, Biostatistics and Prevention Institute at the University of Zurich
Zurich, Switzerland
incidence of travel-related infectious diseases
The Likert scale, self-rating of severity is the unit used to evaluate infectious disease symptoms based on 4 health domains (gastrointestinal symptoms, respiratory symptoms, skin infections and rashes, fever, pain and myalgia) combined with the number of travellers reporting symptoms to get the incidence (travelers with illnesses per 100 travellers).
Time frame: 8 weeks
long-term sequelae of arboviral infections and malaria
The quality-of-life scores and health survey SF-12 version scores will be combined to determine the difference in quality of life due to the infections studied.
Time frame: 1 year
change in epidemiology of travel-related infectious diseases
Change in incidence of travel related infectious diseases over time (incidence change/time)
Time frame: 1 year
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