TOURIST 2: Tracking Of Urgent Risks In Swiss Travelers

New mobile Health (mHealth) technology creates an opportunity to approach travel medicine research in a different way, revolutionising our understanding of risks to travellers. Using mHealth technology, the Epidemiology, Biostatistics and Prevention Institute (EBPI), University of Zurich (UZH), developed a TRAVEL app in collaboration with the Eidgnössische Technische Hochschule (ETH) Zurich.

By using this new technology, an extensive collection of data (prospective collection of individual travel behaviour and experienced health events, mapping the travel itinerary via global positioning system (GPS), linking to publicly available local weather data and data on disease endemicity) can be combined and an unprecedented abundance of information on travel behaviour and experienced risks can be obtained. These data will allow a much better understanding of travel risk profiles using cluster analysis. By simultaneously recording health outcomes, the relationship between travel risk profiles and health events can be assessed. In this study, the investigators will address several major shortcomings in travel health in tropical and subtropical destinations by improving the understanding of poorly assessed and potentially underestimated health threats (e.g. risk of accidents and injury, mental health disorders), and travel risks specific to elderly travellers and travellers with chronic conditions. These findings will directly feed back into individual travel advice given by practitioners in Switzerland and finally world-wide.

New mobile Health (mHealth) technology creates an opportunity to approach travel medicine research in a different way, revolutionising our understanding of risks to travellers. Using mHealth technology, the Epidemiology, Biostatistics and Prevention Institute (EBPI), University of Zurich (UZH), developed a TRAVEL app in collaboration with the Eidgnössische Technische Hochschule (ETH) Zurich.

By using this new technology, an extensive collection of data (prospective collection of individual travel behaviour and experienced health events, mapping the travel itinerary via global positioning system (GPS), linking to publicly available local weather data and data on disease endemicity) can be combined and an unprecedented abundance of information on travel behaviour and experienced risks can be obtained. These data will allow a much better understanding of travel risk profiles using cluster analysis. By simultaneously recording health outcomes, the relationship between travel risk profiles and health events can be assessed. In this study, the investigators will address several major shortcomings in travel health in tropical and subtropical destinations by improving the understanding of poorly assessed and potentially underestimated health threats (e.g. risk of accidents and injury, mental health disorders), and travel risks specific to elderly travellers and travellers with chronic conditions.

1000 clients traveling to Thailand, China, India, Brazil, Peru or Tanzania will be recruited from the Travel Clinics in Zurich and Basel and through advertising at local travel agents and the universities of ETH and UZH from September 2017 until February 2019. After completing an intake at the clinic, participants will be given the option to use their own Smartphone for data collection, or to use a phone owned by the UZH-EBPI during travel. Participants will use a data collection app for questionnaire responses during and after travel including: a daily questionnaire on travel behaviors, daily symptoms questionnaire, and localization tracking, showing the participants' travel path and locations.

Eligibility Criteria:
Inclusion Criteria:

* Informed Consent
* Traveler to Thailand, China, India, Brazil, Peru or Tanzania
* German-speaking (level 3 or higher)
* Literate (able to read and write in German - level 3 or higher)
* Capable of operating Smartphone application for data collection
* Traveling to Thailand, China, India, Brazil, Peru or Tanzania for ≤ 4 weeks

Exclusion Criteria:

- not fulfilling inclusion criteria