Search

Introduction: The establishment of Aedes albopictus in new areas in Europe has changed the risk of local dengue transmission represented by imported human cases. The risk of transmission is determined by the distribution of travelers arriving from dengue-endemic areas and the distribution of Ae. albopictus as potential vectors of dengue in Spain., Methods: Environmental, entomological, epidemiological, demographic, tourism and travel data were analyzed to produce a series of maps to represent: the distribution of Ae. albopictus across municipalities; the risk of expansion of Ae. albopictus based on a species distribution model; the calculated index of travelers from dengue-endemic areas (IDVZE) per province; the percentage contribution of each municipality to the total number of cases in Spain. The maps were then added using map algebra, to profile the spatial risk of autochthonous dengue in Spain at a municipal level from 2016 to 2018., Results: Ae. albopictus was detected in 983 municipalities. The calculated IDVZE varied from 0.23 to 10.38, with the highest IDVZE observed in Madrid. The overall risk of autochthonous cases oscillated between 0.234 and 115, with the very high risk and high risk areas detected in the Mediterranean region, mainly in the Levantine coast and some parts of the Balearic Islands. Most of the interior of the peninsula was characterized as low risk., Conclusion: Prevention and control measures to mitigate the risk of autochthonous dengue should be prioritized for municipalities in the high risk areas integrating early detection of imported dengue cases and vector control., (Copyright © 2023 The Author(s). Published by Elsevier España, S.L.U. All rights reserved.)

BackgroundQ fever is a bacterial zoonosis caused by Coxiella burnetii. Spain has the highest number of notified human cases in Europe. Small ruminants are a key reservoir for the pathogen, transmission from animals to humans is usually airborne.AimWe aimed at exploring temporal and spatial epidemiological patterns of sporadic and outbreak cases of Q fever in four Spanish regions with the highest number of notified cases.MethodsWe extracted data on Q fever cases in the Canary Islands, Basque Country, La Rioja and Navarre between 2016 and 2022 from the Spanish National Epidemiological Surveillance Network. We calculated standardised incidence ratios (SIR), spatial relative risks (sRR) and posterior probabilities (PP) utilising Besag-York-Mollié models.ResultsThere were 1,059 notifications, with a predominance of males aged 30-60 years. In Basque Country, La Rioja and Navarre area, 11 outbreaks were reported, while no in the Canary Islands. A seasonal increase in incidence rates was observed between March and June. In the Canary Islands, elevated sRR was seen in La Palma, Gran Canaria, Lanzarote and Fuerteventura. In Basque Country, La Rioja and Navarre area, the highest sRR was identified in the south of Biscay province.ConclusionGoats were the main source for humans in outbreaks reported in the literature. Seasonal increase may be related to the parturition season of small ruminants and specific environmental conditions. Local variations in sRR within these regions likely result from diverse environmental factors. Future One Health-oriented studies are essential to deepen our understanding of Q fever epidemiology.

Background: Understanding the patterns of disease importation through international travel is paramount for effective public health interventions and global disease surveillance. While global airline network data have been used to assist in outbreak prevention and effective preparedness, accurately estimating how these imported cases disseminate locally in receiving countries remains a challenge., Objective: This study aimed to describe and understand the regional distribution of imported cases of dengue and malaria upon arrival in Spain via air travel., Methods: We have proposed a method to describe the regional distribution of imported cases of dengue and malaria based on the computation of the "travelers' index" from readily available socioeconomic data. We combined indicators representing the main drivers for international travel, including tourism, economy, and visits to friends and relatives, to measure the relative appeal of each region in the importing country for travelers. We validated the resulting estimates by comparing them with the reported cases of malaria and dengue in Spain from 2015 to 2019. We also assessed which motivation provided more accurate estimates for imported cases of both diseases., Results: The estimates provided by the best fitted model showed high correlation with notified cases of malaria (0.94) and dengue (0.87), with economic motivation being the most relevant for imported cases of malaria and visits to friends and relatives being the most relevant for imported cases of dengue., Conclusions: Factual descriptions of the local movement of international travelers may substantially enhance the design of cost-effective prevention policies and control strategies, and essentially contribute to decision-support systems. Our approach contributes in this direction by providing a reliable estimate of the number of imported cases of nonendemic diseases, which could be generalized to other applications. Realistic risk assessments will be obtained by combining this regional predictor with the observed local distribution of vectors., (©David García-García, Beatriz Fernández-Martínez, Frederic Bartumeus, Diana Gómez-Barroso. Originally published in JMIR Public Health and Surveillance (https://publichealth.jmir.org), 27.05.2024.)

Tuberculosis (TB) remains a global leading cause of death, necessitating an investigation into its unequal distribution. Sun exposure, linked to vitamin D (VD) synthesis, has been proposed as a protective factor. This study aimed to analyse TB rates in Spain over time and space and explore their relationship with sunlight exposure. An ecological study examined the associations between rainfall, sunshine hours, and TB incidence in Spain. Data from the National Epidemiological Surveillance Network (RENAVE in Spanish) and the Spanish Meteorological Agency (AEMET in Spanish) from 2012 to 2020 were utilized. Correlation and spatial regression analyses were conducted. Between 2012 and 2020, 43,419 non-imported TB cases were reported. A geographic pattern (north-south) and distinct seasonality (spring peaks and autumn troughs) were observed. Sunshine hours and rainfall displayed a strong negative correlation. Spatial regression and seasonal models identified a negative correlation between TB incidence and sunshine hours, with a four-month lag. A clear spatiotemporal association between TB incidence and sunshine hours emerged in Spain from 2012 to 2020. VD levels likely mediate this relationship, being influenced by sunlight exposure and TB development. Further research is warranted to elucidate the causal pathway and inform public health strategies for improved TB control.