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| Name | Class |
|---|---|
| ETH Zurich | OTHER |
| Swiss Tropical & Public Health Institute | OTHER |
| University Hospital, Geneva | OTHER |
| Center for Primary Care and Public Health (Unisante), University of Lausanne, Switzerland |
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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).
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Arboviral infection or malaria positive cohort |
|
| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| Observational study | Other | No intervention is planned |
|
| Measure | Description | Time Frame |
|---|---|---|
| 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). | 8 weeks |
| Measure | Description | Time Frame |
|---|---|---|
| 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. | 1 year |
| change in epidemiology of travel-related infectious diseases |
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Inclusion Criteria:
Exclusion Criteria:
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International travellers who cross international borders and are traveling for varying purposes such as business/corporate travellers, those visiting friends and relatives (VFR), leisure/tourist travellers and mass gathering events (Hajj, Olympics, World Cup) attendees.
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| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Epidemiology, Biostatistics and Prevention Institute at the University of Zurich | Zurich | 8001 | Switzerland |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 27592821 | Background | Farnham A, Blanke U, Stone E, Puhan MA, Hatz C. Travel medicine and mHealth technology: a study using smartphones to collect health data during travel. J Travel Med. 2016 Sep 4;23(6):taw056. doi: 10.1093/jtm/taw056. Print 2016 Jun. | |
| 31284067 | Background | Findlater A, Moineddin R, Kain D, Yang J, Wang X, Lai S, Khan K, Bogoch II. The use of air travel data for predicting dengue importation to China: A modelling study. Travel Med Infect Dis. 2019 Sep-Oct;31:101446. doi: 10.1016/j.tmaid.2019.07.002. Epub 2019 Jul 5. |
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| OTHER |
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Change in incidence of travel related infectious diseases over time (incidence change/time) |
| 1 year |
| 29196275 | Background | Leta S, Beyene TJ, De Clercq EM, Amenu K, Kraemer MUG, Revie CW. Global risk mapping for major diseases transmitted by Aedes aegypti and Aedes albopictus. Int J Infect Dis. 2018 Feb;67:25-35. doi: 10.1016/j.ijid.2017.11.026. Epub 2017 Nov 28. |
| 30660556 | Background | Ponce C, Dolea C. The World Health Organisation (WHO) and International Travel and Health: New collaborative, evidence-based and digital directions. Travel Med Infect Dis. 2019 Jan-Feb;27:1. doi: 10.1016/j.tmaid.2019.01.012. Epub 2019 Jan 17. No abstract available. |
| 20156059 | Background | Schlagenhauf P, Chen LH, Wilson ME, Freedman DO, Tcheng D, Schwartz E, Pandey P, Weber R, Nadal D, Berger C, von Sonnenburg F, Keystone J, Leder K; GeoSentinel Surveillance Network. Sex and gender differences in travel-associated disease. Clin Infect Dis. 2010 Mar 15;50(6):826-32. doi: 10.1086/650575. |
| 14604928 | Background | Schlagenhauf P, Tschopp A, Johnson R, Nothdurft HD, Beck B, Schwartz E, Herold M, Krebs B, Veit O, Allwinn R, Steffen R. Tolerability of malaria chemoprophylaxis in non-immune travellers to sub-Saharan Africa: multicentre, randomised, double blind, four arm study. BMJ. 2003 Nov 8;327(7423):1078. doi: 10.1136/bmj.327.7423.1078. |
| 23962447 | Background | Tomasello D, Schlagenhauf P. Chikungunya and dengue autochthonous cases in Europe, 2007-2012. Travel Med Infect Dis. 2013 Sep-Oct;11(5):274-84. doi: 10.1016/j.tmaid.2013.07.006. Epub 2013 Aug 17. |
| 41260318 | Derived | Hedrich N, Lovey T, Bernhard J, Grobusch MP, Gautret P, Schlagenhauf P; ITIT Global Network. Real-time illness monitoring in travellers: an international, prospective, digital surveillance study. Travel Med Infect Dis. 2025 Nov-Dec;68:102943. doi: 10.1016/j.tmaid.2025.102943. Epub 2025 Nov 17. |
| 39067885 | Derived | Lovey T, Hedrich N, Grobusch MP, Bernhard J, Schlagenhauf P; ITIT Global Network. Surveillance of global, travel-related illness using a novel app: a multivariable, cross-sectional study. BMJ Open. 2024 Jul 27;14(7):e083065. doi: 10.1136/bmjopen-2023-083065. |
| ID | Term |
|---|---|
| D000076082 | Travel-Related Illness |
| D008288 | Malaria |
| D003715 | Dengue |
| D065632 | Chikungunya Fever |
| D000071243 | Zika Virus Infection |
| D045169 | Severe Acute Respiratory Syndrome |
| D007251 | Influenza, Human |
| D003967 | Diarrhea |
| ID | Term |
|---|---|
| D012816 | Signs and Symptoms |
| D013568 | Pathological Conditions, Signs and Symptoms |
| D011528 | Protozoan Infections |
| D010272 | Parasitic Diseases |
| D007239 | Infections |
| D000096724 | Mosquito-Borne Diseases |
| D000079426 | Vector Borne Diseases |
| D001102 | Arbovirus Infections |
| D014777 | Virus Diseases |
| D018177 | Flavivirus Infections |
| D018178 | Flaviviridae Infections |
| D012327 | RNA Virus Infections |
| D006482 | Hemorrhagic Fevers, Viral |
| D018354 | Alphavirus Infections |
| D014036 | Togaviridae Infections |
| D012141 | Respiratory Tract Infections |
| D018352 | Coronavirus Infections |
| D003333 | Coronaviridae Infections |
| D030341 | Nidovirales Infections |
| D012140 | Respiratory Tract Diseases |
| D009976 | Orthomyxoviridae Infections |
| D012817 | Signs and Symptoms, Digestive |
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| ID | Term |
|---|---|
| D019370 | Observation |
| ID | Term |
|---|---|
| D008722 | Methods |
| D008919 | Investigative Techniques |
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