Surveillance of global, travel-related illness using a novel app: a multivariable, cross-sectional study.

Introduction: Current traveller health surveillance is 'top-down'. Mobile-based surveillance could capture infection symptoms in real time. We aimed to evaluate the spectrum of illness in travellers using a mobile app-based system.
Methods: This study (ClinicalTrials.gov NCT04672577) used an application called Infection Tracking in Travellers (ITIT) that records travel-related illness symptoms with associated geolocation and weather data. The free ITIT app is available in 14 languages. Participants were recruited globally from April 2022 to July 2023. Participants >18 years of age travelled internationally and provided electronic consent. Incentives included the provision of travel health information imported from the WHO website. Symptoms were recorded with daily pop-up questionnaires and symptom severity was assessed using a Likert scale. Two post-travel questionnaires were administered. Logistic mixed models examined factors relating to symptom presence, and a random forest model examined symptom impact.
Results: 609 participants were recruited until July 2023. Participants had an average age of 37 years (18-79), and an average travel duration of 26 days (2-281). Most participants were travelling for leisure/tourism (401; 66%), followed by 'visiting friends and relatives' (99; 16%) and business travel (80; 13%). All continents were visited by at least one traveller. Of 470 registered trips, symptoms were reported on 163 trips (35%). Gastrointestinal symptoms were reported on 87 trips (19%) and respiratory symptoms on 81 trips (17%). The most important factors in predicting the presence of symptoms were duration of travel, travelling in winter and high humidity. Diarrhoea, headache and nausea were symptoms with most impact on daily activities. Post-travel questionnaires showed that 12% of surveyed participants experienced symptoms with several episodes of self-treatment. Two diagnoses were recorded: Lyme disease and amoebic dysentery.
Conclusion: The digital tool ITIT successfully captures the spectrum of travel-related illness. This detailed epidemiology is crucial for outbreak detection and for the formulation of travel medicine guidelines.
Trial Registration Number: NCT04672577.
Competing Interests: Competing interests: None declared.
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