Objectives: To study the geographical pattern of mortality caused by haematological tumours in Spain at the municipal level using three Bayesian models and to compare their goodness of fit.
Methods: The fitted Bayesian hierarchical models were: (1) the Besag York and Molliè (BYM) model; (2) a model based on zero-inflated Poisson (ZIP) distribution, which allowed a large number of event-free areas; and (3) a mixture of distributions that enabled discontinuities (jumps in the pattern) to be modelled. The three models allow smoothed relative risk maps to be obtained for the all countries. The goodness of fit was evaluated using the deviance information criteria.
Results: The three models yielded similar results. The ZIP model plotted a pattern almost identical with the BYM model. The goodness-of-fit criteria indicate that the mixture model is the one that best fits our data. Haematological tumours display a geographical pattern that could be partly explained by environmental determinants, as many of the highest-risk towns are located in heavily industrialised areas.
Conclusions: The choice of one or another model has scant practical consequences. The pattern of distribution supports the hypothesis that differences in lifestyles, air/industrial pollution and migratory phenomena may determine the pattern of urban mortality due to these tumours.
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http://dx.doi.org/10.1136/jech.2005.041491 | DOI Listing |
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Laboratório de Ecologia e Biogeografia de Plantas, Departamento de Biodiversidade, Setor Palotina, Universidade Federal do Paraná, Rua Pioneiro, 2153, Jardim Dallas, CEP 85950 000, Palotina, Paraná, Brazil.
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Department of Biology, Colorado State University, Fort Collins, Colorado, USA.
Identifying populations at highest risk from climate change is a critical component of conservation efforts. However, vulnerability assessments are usually applied at the species level, even though intraspecific variation in exposure, sensitivity and adaptive capacity play a crucial role in determining vulnerability. Genomic data can inform intraspecific vulnerability by identifying signatures of local adaptation that reflect population-level variation in sensitivity and adaptive capacity.
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Biological invasions are a major threat to biodiversity, ecosystem functioning and nature's contributions to people worldwide. However, the effectiveness of invasive alien species (IAS) management measures and the progress toward achieving biodiversity targets remain uncertain due to limited and nonuniform data availability. Management success is usually assessed at a local level and documented in technical reports, often written in languages other than English, which makes such data notoriously difficult to collect at large geographic scales.
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The Asian long-horned tick, Haemaphysalis longicornis Neumann, 1901, is the competent vector for severe fever with thrombocytopenia syndrome virus (SFTSV). Haemaphysalis longicornis originated mainly in eastern Asia and invaded many areas like Australia, New Zealand, and the Pacific islands, and was recently introduced to eastern parts of the USA. This species is characterized by high adaptability to a wide range of temperatures and can reproduce parthenogenically under stressful conditions.
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