Background Every year, many thousands of travellers return to the United Kingdom (UK) from visits to other countries and some will become unwell due to infections acquired abroad. Many imported infections have similar clinical presentations, such as fever and myalgia, so diagnostic testing is an important tool to improve patient management and outcomes. The aim of this study was to examine the demographics, travel history, presenting symptoms and diagnostic outcomes of referrals to the UK’s specialist diagnostic Rare & Imported Pathogens Laboratory (RIPL) for the period 2015–2020. Methods Anonymised clinical and laboratory data was extracted from RIPL’s Laboratory Information Management System (LIMS) and cleaned prior to descriptive analysis of the data. Travel history data was mapped to one of eight world regions, while symptom data was categorised into presenting syndromes. Diagnostic data was categorised as either positive, equivocal or negative. Results During the period 2015–2020, RIPL received 73 951 samples from 53 432 patients suspected of having infections that are rare in the UK. The most common age group for unwell returning travellers was 30–39 years and the most commonly reported travel destination was Southern and SE Asia. Dengue virus was the most diagnosed infection overall, followed by chikungunya, Zika, leptospirosis and spotted fever group Rickettsia. Dengue virus was among the top three most frequent diagnoses for all world regions except Europe and represented 62.5% of all confirmed/probable diagnoses. Conclusions None of the top five infections diagnosed by RIPL in travellers are vaccine-preventable, therefore understanding traveller demographics, destination-specific risk factors and encouraging preventative behaviours is the best available strategy to reduce the number of returning travellers who become infected. Prompt referral of acute samples with a detailed travel history, including purpose of travel and activities undertaken as well as dates and destinations can be a valuable tool in designing public health interventions and diagnostic algorithms.
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