Journal of travel medicine
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The international flight network creates multiple routes by which pathogens can quickly spread across the globe. In the early stages of infectious disease outbreaks, analyses using flight passenger data to identify countries at risk of importing the pathogen are common and can help inform disease control efforts. A challenge faced in this modelling is that the latest aviation statistics (referred to as contemporary data) are typically not immediately available. Therefore, flight patterns from a previous year are often used (referred to as historical data). We explored the suitability of historical data for predicting the spatial spread of emerging epidemics. ⋯ The use of historical flight data as a proxy in epidemic models is an acceptable practice, except in rare, large epidemics that lead to substantial disruptions to international travel.
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This article delves into the innovative integration of AI-driven chatbots in travel medicine, proposing a decalogue for creating effective, personalized health assistance tools with a practical example (a custom GPT, with OpenAI GPT-4).
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Observational Study
Escalating climate-related health risks for Hajj pilgrims to Mecca.
Global temperatures are on the rise, leading to more frequent and severe heatwaves with associated health risks. Heat-related illnesses (HRIs) are an increasing threat for travellers to hot climate destinations. This study was designed to elucidate the interplay between increasing ambient temperatures, incidence of HRIs and the effectiveness of mitigation strategies during the annual Hajj mass gathering over a 40-year period. ⋯ The study underscores the escalating climate-related health risks in Mecca over the study period. The mitigation measures' efficacy in such a globally representative setting emphasizes the findings' generalizability and the importance of refining public health interventions in the face of rising temperatures.
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Overall effectiveness of infection in preventing reinfection with SARS-CoV-2 JN.1 variant was estimated at 1.8% (95% CI: −9.3to 12.6%), and demonstrated rapid decline over time since the previous infection, decreasing from 82.4% (95% CI: 40.9 to 94.7%) within 3 to less than 6 months, to a negligible level after one year.
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Comparative Study
Discrepancies in dengue burden estimates: A comparative analysis of reported cases and Global Burden of Disease Study, 2010-2019.
Dengue is a significant mosquito-borne disease. Several studies have utilized estimates from the Global Burden of Disease (GBD) study to assess the global, regional or national burden of dengue over time. However, our recent investigation suggests that GBD's estimates for dengue cases in Taiwan are unrealistically high. The current study extends the scope to compare reported dengue cases with GBD estimates across 30 high-burden countries and territories, aiming to assess the accuracy and interpretability of the GBD's dengue estimates. ⋯ This study reveals substantial discrepancies between GBD estimates and reported dengue cases, underscoring the imperative for comprehensive analysis in areas with pronounced disparities. The failure of GBD estimates to represent the considerable annual fluctuations in dengue outbreaks highlights the critical need for improvement in disease burden estimation methodologies for dengue.