Advancing Travel Medicine Through Shared Digital Infrastructure and Common Data Standards

1 Title: Advancing Travel Medicine Through Shared Digital Infrastructure and Common Data Standards Authors: Andrés Colubri1,2, Nadja Hedrich3, Juan Leva4, José Muñoz4,5,6, Regina C. LaRocque7, Patricia Schlagenhauf3,8, Andrea Farnham3, and the ISTM Technology Special Interest Group 1 UMass Chan Medical School, Department of Genomics and Computational Biology, Worcester, USA 2 Broad Institute of Harvard and MIT, Cambridge, USA 3 University of Zürich, Epidemiology, Biostatistics and Prevention Institute, Department of Global and Public Health, Zürich, Switzerland 4 Barcelona Institute for Global Health, International Health Department, Barcelona, Spain 5 International Health Department, Hospital Clínic de Barcelona, Barcelona, Spain 6 Facultat de Medicina i Ciències de la Salut, Universitat de Barcelona, Barcelona, Spain 7 Division of Infectious Diseases, Massachusetts General Hospital, Boston, USA 8 WHO Collaborating Centre for Travellers' Health, Department of Global and Public Health, MilMedBiol Competence Centre, Zürich, Switzerland Highlight (≤50 words): Travel medicine needs shared digital standards and resources. We propose a Travel Health Data Commons (THDC) encompassing consensus case definitions, common questionnaires, interoperable data formats, and reusable software modules. This will lower costs, facilitate disease surveillance and response, improve clinical guidance, and spur innovation and collaboration. THDC website is https://travelhealthdatacommons.org. The real-life impact of missing data standards and digital protocols How many international travellers get travellers’ diarrhoea (TD)? Ask ten studies, get ten different answers, ranging anywhere from 30% to 70% [1, 2]. Why the discrepancy? It’s not necessarily the physiopathology of the disease or travellers’ characteristics alone; it’s that the questions we ask, the definitions we use, and the recall windows we study vary widely. The answer also depends on who is asked the questions. Definitions for lay persons and for travel health professionals are by default different. One survey might define diarrhoea as “three or more loose stools in 24 hours,” another as “any change in bowel habits.” Some ask about illness in the past week, others about the entire trip. The result is a shaky evidence base for counselling, chemoprophylaxis, and post-travel care. This TD example illustrates a broader problem: rapid innovation without shared standards. During COVID-19, hundreds of mobile apps and participatory digital systems were built in parallel [3]. Ingenuity flourished, but interoperability did not. In travel medicine, an inherently global and cross-border field, the absence of common questionnaires, data formats, and evaluation frameworks makes signals noisier, comparisons harder, research slower, and surveillance weaker. THDC aims to address this by not imposing one platform, but by agreeing on shared standards that allow many platforms to work together. Our position: not one platform, but shared standards and tools 2 Countries and institutions will (and should) run their own systems, meet their own regulatory requirements, and set their own priorities. The leverage lies between systems: aligned case definitions, core survey elements, interoperable data formats, reference software modules, and evaluation methods that can be adapted locally while staying comparable globally. Rather than a monolith, we propose a commons. Research-driven and clinically oriented groups may collect different data using different tools. However, it is important that they can reuse proven building blocks for their tools and that the shared elements of their respective datasets line up to allow meaningful comparison. Proposal: A Travel Health Data Commons We propose an openly governed Travel Health Data Commons (THDC): a set of shared digital standards and resources that lowers the cost of building trustworthy travel medicine tools while enabling comparability and federated analysis of the health data produced by these tools. The key components of THDC would include: 1. Consensus definitions for common syndromes (e.g., TD, febrile illness, rash), using established severity scales such as the Likert scale. 2. Template questionnaires for pre-travel, during-travel, and post-travel phases, with multilingual translations and short/long forms that can be adapted to local ethics requirements and contexts, while preserving a small set of comparable core items. 3. Pre-trained AI components such as large language models (LLMs) customized for collection of high-quality travel data through conversational interfaces, and for decision support with documented guardrails, performance metrics, and bias checks. 4. Interoperable data and metadata formats (e.g., HL7 FHIR profiles) with standard terminologies (e.g., SNOMED CT, ICD-10, LOINC) to promote Findable, Accessible, Interoperable, and Reusable (FAIR) practices [4]. 5. Reference software modules for consent, survey delivery (offline-first), itinerary parsing (ICS/PNR), data entry (textual or pictorial), de-identification, export utilities, and analytics. 6. Evaluation frameworks covering clinical accuracy, test–retest reliability, usability and accessibility, equity, and privacy safeguards, including specific guidance for AI-mediated data collection and advice. 7. Open governance with transparent versioning, community input, conformance tests, permissive licensing, and geographic and disciplinary diversity including ethical, legal, and data protection expertise as well as representatives of traveller and patient groups. As an illustration, Boxes 1 and 2 below show a core TD case definition and a Minimum Travel Health Data Set (MTHDS) that would be part of the Commons. Box 1. Example of a core TD case definition Primary case (TD core): ≥3 unformed stools in 24 hours and ≥1 accompanying symptom (cramps, urgency, nausea, vomiting, fever, blood/mucus), beginning during travel or within 7 days after return. 3 Severity classes: Mild (no activity interference), Moderate (some interference), Severe (prevents activities or dysentery/fever ≥38.5°C). Outcome fields: self-care vs. medical visit; meds used; duration to last unformed stool. Timing fields: onset date/time; country/city; food/water exposures (last 72h). Rationale: preserves historical comparability while enabling harmonized incidence/severity reporting. Box 2. Example of a Minimum Travel Health Data Set (MTHDS) Traveler & trip: year of birth, sex at birth/gender, pregnancy status, key comorbidities, immunocompromised status; itinerary (ISO-3166 country + admin-1), trip dates, purpose of travel. Pre-travel: immunizations (vaccine name/code + date), chemoprophylaxis/antibiotics (drug name/code + start/stop), counselling delivered. On-trip symptoms (daily/weekly option): fever, diarrhoea (TD core), respiratory symptoms, rash, bites/stings; severity, activity impact, self-care. Care utilization: telemedicine/in-person visit, diagnostics, prescriptions. Post-travel: persistent symptoms at D7/D30; lab results (LOINC), diagnoses (SNOMED/ICD-10). Metadata: instrument name/version, source (self-reported by traveller or clinician-recorded), language, consent scope, timestamps, geolevel. Digital travel health platforms vary in the level of detail they collect. THDC should therefore establish a required core set of variables, with optional extensions for research-oriented systems. Platforms may use different templates as long as their data can be mapped to these core definitions, ensuring comparability, while being able to generate higher-resolution data when needed. What Could Shared Protocols Deliver? Stated simply, interoperability is the ability of information systems to work together. This enables, for example, different providers to access the electronic health records of a patient. In travel medicine, interoperable digital tools would allow for: ● Consistent Data: Comparable estimates of disease incidence and other key parameters, regardless of the collection method. ● Efficiency: Reduced cost and time by reusing core components rather than rebuilding them from scratch each time. 4 ● Global Collaboration: Rapid comparison of studies across regions, strengthening research validity. ● Standardized Benchmarking: A shared environment where digital tools and AI models are tested against the same metrics, providing necessary evidence for regulators. ● Real-Time Surveillance: Immediate cross-border tracking during health crises by aggregating data from clinics, telemedicine, and apps. Ethical, legal, and societal implications The technical interoperability enabled by THDC carries important ethical, legal, and societal implications (ELSI), requiring digital health ethics specialists to be involved from the outset. THDC should embed privacy and security by design through approaches such as role-based access, encryption, and where analyses are carried out across sites, advocating technologies that enhance privacy such as federated learning [5] and differential privacy [6]. But ELSI extends beyond privacy. Participatory surveillance can easily over represent younger, wealthier, or more digitally connected travellers unless equity is explicitly measured and addressed. As AI-driven tools such as LLMs and chatbots become increasingly integrated into clinical practice [7], their performance, biases, and failure modes require explicit evaluation, defined bounds of use, and clear communication to users. A pragmatic path to development and governance The THDC can be established through an open, consensus-driven process modelled on successful international standard-setting efforts such as HL7 FHIR [8] and the WHO guideline development process [9], led under the ISTM banner. The development should be guided by a diverse steering group of clinicians, researchers, public health agencies, and digital health, informatics, and ELSI experts. Our main challenge will be social, not technical: coordinating these stakeholders and agreeing on minimum standards. To succeed, THDC should focus on clear contribution paths and quick pilot successes to sustain momentum, providing tangible benefits to adopters so the standards are seen as helpful rather than an added burden. The THDC steering group will develop and maintain a core set of standards through transparent drafting, public review, and regular versioning, using precise IP/licensing (e.g., permissive open-source license for software; Creative Commons for instruments) to sustain trust. At the same time, THDC must avoid overstandardisation, which can freeze practice and vendor capture. Core definitions and formats should act as a floor, not a ceiling. Pilot implementations across different regions, drawing from existing travel medicine health applications (e.g., Travel Healthy [10], Famba [11, 12], ITIT [13, 14], TOURIST [15]) would function much like FHIR “implementation guides,” validating feasibility and ensuring that definitions, survey items, and data formats work in real clinical and research contexts. A 12-month road map to Version 1.0 Over 12 months, the ISTM Technology Special Interest Group will lay the foundations for Version 1.0 standards by: (1) completing a scoping review of digital/AI tools in travel medicine and adjacent fields 5 (Months 1–4) to map the landscape and lessons from mature governance models, yielding a peerreviewed paper; (2) recruiting an expert panel (Months 3–5) and running 2–3 consensus rounds (Months 6–8) to define core principles, risks, priorities, and best practice evaluation criteria, culminating in a consensus paper; (3) formally establishing the ISTM Technology Consortium with clear IP and collaborative governance (Months 6–10); and (4) presenting outcomes to ISTM leadership with a strategic roadmap (Months 11–12) that specifies guideline drafting, work packages, and shared interoperability assets (e.g., harmonized pre-travel questionnaires, data standards, evaluation frameworks, and an initial ethical and governance charter). Closing the loop: rethinking traveller’s diarrhoea with shared standards With a common TD core definition, severity classes, and the MTHDS, we stop arguing over what “counts” and start speaking a single, decision-ready language. Every study and app would report the same core outputs with instrument/version tags: incidence per 100 traveller-weeks by destination; proportion activity-limiting or severe; median time-to-last unformed stool; care-seeking and antibiotic use; and (in research arms) antibiotic-free recovery and AMR colonization. Clinic counselling shifts from vague ranges (“30–70% get TD”) to concrete expectations (“For a 14-day trip to Region X, the median is 0.6 days of activity-limiting TD; 8% severe; 70% recover without antibiotics”). Public health gains federated, privacy-preserving alerts when severe TD clusters spike; researchers compare like-for-like outcomes without painful harmonization; and stewardship improves because we can finally benchmark antibioticfree recovery across settings. In short, shared standards turn TD from a definitional debate into a measurable, comparable, and improvable outcome, one that travellers, clinicians, and policymakers can act on with confidence. Call to action We believe that the field of travel medicine has a unique opportunity and responsibility to lead the development of shared digital infrastructure for participatory surveillance and mobile health innovation. We therefore invite clinics, public health agencies, researchers, vendors, and traveller communities to join the THDC by completing the online registration form at https://travelhealthdatacommons.org. 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