After a request from the European Commission, EFSA's Panel on Animal Health and Welfare summarised the main characteristics of 36 vector-borne diseases (VBDs) in 36 web-based storymaps. The risk of introduction in the EU through movement of livestock or pets was assessed for each of the 36 VBDs individually, using a semiquantitative Method to INTegrate all relevant RISK aspects (MINTRISK model), which was further modified to a European scale into the EFSA-VBD-RISK-model. Only eight of the 36 VBD-agents had an overall rate of introduction in the EU (being the combination of the rate of entry, vector transmission and establishment) which was estimated to be above 0.001 introductions per year. These were Crimean-Congo haemorrhagic fever virus, bluetongue virus, West Nile virus, Schmallenberg virus, Hepatozoon canis, Leishmania infantum, Bunyamwera virus and Highlands J. virus. For these eight diseases, the annual extent of spread was assessed, assuming the implementation of available, authorised prevention and control measures in the EU. Further, the probability of overwintering was assessed, as well as the possible impact of the VBDs on public health, animal health and farm production. For the other 28 VBD-agents for which the rate of introduction was estimated to be very low, no further assessments were made. Due to the uncertainty related to some parameters used for the risk assessment or the instable or unpredictability disease situation in some of the source regions, it is recommended to update the assessment when new information becomes available. Since this risk assessment was carried out for large regions in the EU for many VBD-agents, it should be considered as a first screening. If a more detailed risk assessment for a specific VBD is wished for on a national or subnational level, the EFSA-VBD-RISK-model is freely available for this purpose. Acknowledgements: The Panel wishes to thank the hearing experts: Ann Lindberg, Clazien Devos, Herman Van Roermond and Marieta Braks, and EFSA staff member: Julia Illenberger for the preparatory work on this scientific output.
Background This study examines the impact of climate, socio-economic and demographic factors on the incidence of dengue in regions of the United States and Mexico. We select factors shown to predict dengue at a local level and test whether the association can be generalized to the regional or state level. In addition, we assess how different indicators perform compared to per capita gross domestic product (GDP), an indicator that is commonly used to predict the future distribution of dengue. Methods A unique spatial-temporal dataset was created by collating information from a variety of data sources to perform empirical analyses at the regional level. Relevant regions for the analysis were selected based on their receptivity and vulnerability to dengue. A conceptual framework was elaborated to guide variable selection. The relationship between the incidence of dengue and the climate, socio-economic and demographic factors was modelled via a Generalized Additive Model (GAM), which also accounted for the spatial and temporal auto-correlation. Results The socio-economic indicator (representing household income, education of the labour force, life expectancy at birth, and housing overcrowding), as well as more extensive access to broadband are associated with a drop in the incidence of dengue; by contrast, population growth and inter-regional migration are associated with higher incidence, after taking climate into account. An ageing population is also a predictor of higher incidence, but the relationship is concave and flattens at high rates. The rate of active physicians is associated with higher incidence, most likely because of more accurate reporting. If focusing on Mexico only, results remain broadly similar, however, workforce education was a better predictor of a drop in the incidence of dengue than household income. Conclusions Two lessons can be drawn from this study: first, while higher GDP is generally associated with a drop in the incidence of dengue, a more granular analysis reveals that the crucial factors are a rise in education (with fewer jobs in the primary sector) and better access to information or technological infrastructure. Secondly, factors that were shown to have an impact of dengue at the local level are also good predictors at the regional level. These indices may help us better understand factors responsible for the global distribution of dengue and also, given a warming climate, may help us to better predict vulnerable populations on a larger scale.
However, the relation between socioeconomic status and cervical cancer survival, investigated on a small area basis, has not been reported before in this country. Such small area analysis can highlight large differences not apparent at a regional level, and its use is demonstrated here. MethodsThe survival details, age, occupation, and address of the 564 Sheffield residents registered with the Trent Cancer Registry with cervical cancer (ICD code: 180) from 1971 to 1984 were extracted. Eight cases from the earlier years were duplicates, leaving 556 to be studied. The electoral ward of residence was obtained from the address at registration using the electoral register.Only 30% ofcases had sufficient information recorded for the occupational social class to be ascertained. An alternative approach using area of residence to derive another measure of social class allowed 99% of cases to be classified, thus permitting 548 cases to be studied. The 29 Sheffield electoral wards were ranked in ascending order according to the percentage of semiskilled and unskilled workers in the 1981 census small area statistics (range 7-41%). They were then divided into quintiles of 6, 6, 5, 6, and 6 wards to collect together areas of approximately equivalent socioeconomic status and similar numbers of women.
Background: Dengue is one of the important vector-borne diseases in the world today; it infects tens of millions of people each year and has been on the rise since the 1950s. In this study, we develop a set of indicators that help us examine the impact of socio-economic and demographic factors on the occurrence of dengue in regions of the United States and Mexico. Methods: We assess the relationship between dengue occurrence in humans, climate factors (temperature and minimum quarterly rainfall), socio-economic factors (such as household income, regional rates of education, housing overcrowding, life expectancy, and medical resources), and demographic factors (such as migration flows, age structure of the population, and population density). Areas at risk of dengue are first selected based on the predicted presence of at least one of the two mosquito vectors responsible for dengue’s transmission: Aedes aegypti and Aedes albopictus. In those regions where the vectors had a high probability of presence, we assess the impact of the composite socio-economic indicators (derived through factor analysis to account for collinearity), and three composite demographic indicators (also derived from factor analysis) on the regional distribution of dengue cases, controlling for climate and spatial correlation. Results: We found that an increase of one unit in one of our socio-economic indicators representing labour force with at least secondary education, better broadband access, and rooms per inhabitant, a higher proportions of active physicians is related to a drop in the occurrence of dengue, whereas the demographic indicators such as population density, age structure of the population and population growth showed no significant impact after taking climate into account. More importantly, our socio-economic indicator can also explain differences in the occurrence of dengue across Mexico, whereas simpler measures, such as regional GDP could not. Conclusions: These results suggest that the set of indicators developed is a better indicator than GDP at predicting the distribution of dengue, by capturing information that is much more tailored to poverty related conditions which aid dengue transmission. Given that data for these indicators are available at a sub-national scale for OECD countries and selected OECD non-member economies, these indices may help us better understand factors responsible for the global distribution of dengue and also, given a warming climate, may help us to better predict vulnerable populations.
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