901 resultados para Population of Models
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Context: The stellar population of the 30 Doradus star-forming region in the Large Magellanic Cloud contains a subset of apparently single, rapidly rotating O-type stars. The physical processes leading to the formation of this cohort are currently uncertain.
Aims: One member of this group, the late O-type star VFTS 399, is found to be unexpectedly X-ray bright for its bolometric luminosity-in this study we aim to determine its physical nature and the cause of this behaviour.
Methods: To accomplish this we performed a time-resolved analysis of optical, infrared and X-ray observations.
Results: We found VFTS 399 to be an aperiodic photometric variable with an apparent near-IR excess. Its optical spectrum demonstrates complex emission profiles in the lower Balmer series and select He i lines-taken together these suggest an OeBe classification. The highly variable X-ray luminosity is too great to be produced by a single star, while the hard, non-thermal nature suggests the presence of an accreting relativistic companion. Finally, the detection of periodic modulation of the X-ray lightcurve is most naturally explained under the assumption that the accretor is a neutron star.
Conclusions: VFTS 399 appears to be the first high-mass X-ray binary identified within 30 Dor, sharing many observational characteristics with classical Be X-ray binaries. Comparison of the current properties of VFTS 399 to binary-evolution models suggests a progenitor mass 25 M⊙ for the putative neutron star, which may host a magnetic field comparable in strength to those of magnetars. VFTS 399 is now the second member of the cohort of rapidly rotating "single" O-type stars in 30 Dor to show evidence of binary interaction resulting in spin-up, suggesting that this may be a viable evolutionary pathway for the formation of a subset of this stellar population.
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RAMOS, Ana Maria de Oliveira et al. Project Pró-Natal: population-based study of perinatal and infant mortality in Natal, Northeast Brazil. Pediatric and Developmental Pathology, v.3, n.1, p.29-35, 2000
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[EN] Because of the extensive migrations of marine turtles through the ocean, many aspects of their biology have been unknown for a long time. However, much information has been recently gained from genetic studies and population monitoring of female turtles at their nesting sites. In contrast, still very little is known on the genetic diversity, population structure and dispersal patterns of the male breeding population, mainly because of the difficulty of capturing and monitoring them at sea. The aim of this study is to assess the genetic patterns of the male breeding population of the loggerhead turtle, Caretta caretta, using a non invasive approach and compare them to the female breeding population.
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Thesis (Ph.D.)--University of Washington, 2016-08
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Le rapide déclin actuel de la biodiversité est inquiétant et les activités humaines en sont la cause directe. De nombreuses aires protégées ont été mises en place pour contrer cette perte de biodiversité. Afin de maximiser leur efficacité, l’amélioration de la connectivité fonctionnelle entre elles est requise. Les changements climatiques perturbent actuellement les conditions environnementales de façon globale. C’est une menace pour la biodiversité qui n’a pas souvent été intégrée lors de la mise en place des aires protégées, jusqu’à récemment. Le mouvement des espèces, et donc la connectivité fonctionnelle du paysage, est impacté par les changements climatiques et des études ont montré qu’améliorer la connectivité fonctionnelle entre les aires protégées aiderait les espèces à faire face aux impacts des changements climatiques. Ma thèse présente une méthode pour concevoir des réseaux d’aires protégées tout en tenant compte des changements climatiques et de la connectivité fonctionnelle. Mon aire d’étude est la région de la Gaspésie au Québec (Canada). La population en voie de disparition de caribou de la Gaspésie-Atlantique (Rangifer tarandus caribou) a été utilisée comme espèce focale pour définir la connectivité fonctionnelle. Cette petite population subit un déclin continu dû à la prédation et la modification de son habitat, et les changements climatiques pourraient devenir une menace supplémentaire. J’ai d’abord construit un modèle individu-centré spatialement explicite pour expliquer et simuler le mouvement du caribou. J’ai utilisé les données VHF éparses de la population de caribou et une stratégie de modélisation patron-orienté pour paramétrer et sélectionner la meilleure hypothèse de mouvement. Mon meilleur modèle a reproduit la plupart des patrons de mouvement définis avec les données observées. Ce modèle fournit une meilleure compréhension des moteurs du mouvement du caribou de la Gaspésie-Atlantique, ainsi qu’une estimation spatiale de son utilisation du paysage dans la région. J’ai conclu que les données éparses étaient suffisantes pour ajuster un modèle individu-centré lorsqu’utilisé avec une modélisation patron-orienté. Ensuite, j’ai estimé l’impact des changements climatiques et de différentes actions de conservation sur le potentiel de mouvement du caribou. J’ai utilisé le modèle individu-centré pour simuler le mouvement du caribou dans des paysages hypothétiques représentant différents scénarios de changements climatiques et d’actions de conservation. Les actions de conservation représentaient la mise en place de nouvelles aires protégées en Gaspésie, comme définies par le scénario proposé par le gouvernement du Québec, ainsi que la restauration de routes secondaires à l’intérieur des aires protégées. Les impacts des changements climatiques sur la végétation, comme définis dans mes scénarios, ont réduit le potentiel de mouvement du caribou. La restauration des routes était capable d’atténuer ces effets négatifs, contrairement à la mise en place des nouvelles aires protégées. Enfin, j’ai présenté une méthode pour concevoir des réseaux d’aires protégées efficaces et j’ai proposé des nouvelles aires protégées à mettre en place en Gaspésie afin de protéger la biodiversité sur le long terme. J’ai créé de nombreux scénarios de réseaux d’aires protégées en étendant le réseau actuel pour protéger 12% du territoire. J’ai calculé la représentativité écologique et deux mesures de connectivité fonctionnelle sur le long terme pour chaque réseau. Les mesures de connectivité fonctionnelle représentaient l’accès général aux aires protégées pour le caribou de la Gaspésie-Atlantique ainsi que son potentiel de mouvement à l’intérieur. J’ai utilisé les estimations de potentiel de mouvement pour la période de temps actuelle ainsi que pour le futur sous différents scénarios de changements climatiques pour représenter la connectivité fonctionnelle sur le long terme. Le réseau d’aires protégées que j’ai proposé était le scénario qui maximisait le compromis entre les trois caractéristiques de réseau calculées. Dans cette thèse, j’ai expliqué et prédit le mouvement du caribou de la Gaspésie-Atlantique sous différentes conditions environnementales, notamment des paysages impactés par les changements climatiques. Ces résultats m’ont aidée à définir un réseau d’aires protégées à mettre en place en Gaspésie pour protéger le caribou au cours du temps. Je crois que cette thèse apporte de nouvelles connaissances sur le comportement de mouvement du caribou de la Gaspésie-Atlantique, ainsi que sur les actions de conservation qui peuvent être prises en Gaspésie afin d’améliorer la protection du caribou et de celle d’autres espèces. Je crois que la méthode présentée peut être applicable à d’autres écosystèmes aux caractéristiques et besoins similaires.
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Thesis (Master's)--University of Washington, 2016-08
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RAMOS, Ana Maria de Oliveira et al. Project Pró-Natal: population-based study of perinatal and infant mortality in Natal, Northeast Brazil. Pediatric and Developmental Pathology, v.3, n.1, p.29-35, 2000
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La possibilité d’estimer l’impact du changement climatique en cours sur le comportement hydrologique des hydro-systèmes est une nécessité pour anticiper les adaptations inévitables et nécessaires que doivent envisager nos sociétés. Dans ce contexte, ce projet doctoral présente une étude sur l’évaluation de la sensibilité des projections hydrologiques futures à : (i) La non-robustesse de l’identification des paramètres des modèles hydrologiques, (ii) l’utilisation de plusieurs jeux de paramètres équifinaux et (iii) l’utilisation de différentes structures de modèles hydrologiques. Pour quantifier l’impact de la première source d’incertitude sur les sorties des modèles, quatre sous-périodes climatiquement contrastées sont tout d’abord identifiées au sein des chroniques observées. Les modèles sont calés sur chacune de ces quatre périodes et les sorties engendrées sont analysées en calage et en validation en suivant les quatre configurations du Different Splitsample Tests (Klemeš, 1986;Wilby, 2005; Seiller et al. (2012);Refsgaard et al. (2014)). Afin d’étudier la seconde source d’incertitude liée à la structure du modèle, l’équifinalité des jeux de paramètres est ensuite prise en compte en considérant pour chaque type de calage les sorties associées à des jeux de paramètres équifinaux. Enfin, pour évaluer la troisième source d’incertitude, cinq modèles hydrologiques de différents niveaux de complexité sont appliqués (GR4J, MORDOR, HSAMI, SWAT et HYDROTEL) sur le bassin versant québécois de la rivière Au Saumon. Les trois sources d’incertitude sont évaluées à la fois dans conditions climatiques observées passées et dans les conditions climatiques futures. Les résultats montrent que, en tenant compte de la méthode d’évaluation suivie dans ce doctorat, l’utilisation de différents niveaux de complexité des modèles hydrologiques est la principale source de variabilité dans les projections de débits dans des conditions climatiques futures. Ceci est suivi par le manque de robustesse de l’identification des paramètres. Les projections hydrologiques générées par un ensemble de jeux de paramètres équifinaux sont proches de celles associées au jeu de paramètres optimal. Par conséquent, plus d’efforts devraient être investis dans l’amélioration de la robustesse des modèles pour les études d’impact sur le changement climatique, notamment en développant les structures des modèles plus appropriés et en proposant des procédures de calage qui augmentent leur robustesse. Ces travaux permettent d’apporter une réponse détaillée sur notre capacité à réaliser un diagnostic des impacts des changements climatiques sur les ressources hydriques du bassin Au Saumon et de proposer une démarche méthodologique originale d’analyse pouvant être directement appliquée ou adaptée à d’autres contextes hydro-climatiques.
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Sardines and other Microfilidae have very important ecological role in marine ecosystems because they are first consumers in marine food chain and they are the main food of valuable species as tuna. So decries in their population will decline fishing of these spices. There are 10 genus of Clupeidae in south of Iran and Sardinella is the one of the most abundant of them. In this study we investigated about morphological and genetically differences in population of 3 species: Sardinella sindensis, Sardinella abella, Dussomieria acuta. About 65 specimens of Sardinella sindensis, 61 specimens of Sardinella albella and 63 specimens of, Dussomieria acuta from three regions of their distribution: Jask (Oman Sea), Qeshm (Hormoz) and Lengeh (Pearsian Gulf) have been collected. Morphological research of their characters and statistical studies were done. To determine the genetically structure of specie's population we sequenced 500 bp of mitochondrial control region. Genetical studies determine meaningful difference in alleles and heterozigosity frequency of Sardinella sindensis. This must be the result of divergence in population of this species. Morphological investigation of Sardinella albella shows the meaningful difference. But detailed studies diffused it. Genetical studies show a meaningful variance in allele and heterosigosity frequency. This may be an aspect of sardine tendency to live in estuaries. Morphological research of Dussomieria acuta in Jask and Lengeh show a meaningful variance in these regions. Such a situation might be result of Monsoon, upwelling and better weather which occur in Oman Sea in spite of Persian Gulf.
Epidemiology and genetic architecture of blood pressure: a family based study of Generation Scotland
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Hypertension is a major risk factor for cardiovascular disease and mortality, and a growing global public health concern, with up to one-third of the world’s population affected. Despite the vast amount of evidence for the benefits of blood pressure (BP) lowering accumulated to date, elevated BP is still the leading risk factor for disease and disability worldwide. It is well established that hypertension and BP are common complex traits, where multiple genetic and environmental factors contribute to BP variation. Furthermore, family and twin studies confirmed the genetic component of BP, with a heritability estimate in the range of 30-50%. Contemporary genomic tools enabling the genotyping of millions of genetic variants across the human genome in an efficient, reliable, and cost-effective manner, has transformed hypertension genetics research. This is accompanied by the presence of international consortia that have offered unprecedentedly large sample sizes for genome-wide association studies (GWASs). While GWAS for hypertension and BP have identified more than 60 loci, variants in these loci are associated with modest effects on BP and in aggregate can explain less than 3% of the variance in BP. The aims of this thesis are to study the genetic and environmental factors that influence BP and hypertension traits in the Scottish population, by performing several genetic epidemiological analyses. In the first part of this thesis, it aims to study the burden of hypertension in the Scottish population, along with assessing the familial aggregation and heritialbity of BP and hypertension traits. In the second part, it aims to validate the association of common SNPs reported in the large GWAS and to estimate the variance explained by these variants. In this thesis, comprehensive genetic epidemiology analyses were performed on Generation Scotland: Scottish Family Health Study (GS:SFHS), one of the largest population-based family design studies. The availability of clinical, biological samples, self-reported information, and medical records for study participants has allowed several assessments to be performed to evaluate factors that influence BP variation in the Scottish population. Of the 20,753 subjects genotyped in the study, a total of 18,470 individuals (grouped into 7,025 extended families) passed the stringent quality control (QC) criteria and were available for all subsequent analysis. Based on the BP-lowering treatment exposure sources, subjects were further classified into two groups. First, subjects with both a self-reported medications (SRMs) history and electronic-prescription records (EPRs; n =12,347); second, all the subjects with at least one medication history source (n =18,470). In the first group, the analysis showed a good concordance between SRMs and EPRs (kappa =71%), indicating that SRMs can be used as a surrogate to assess the exposure to BP-lowering medication in GS:SFHS participants. Although both sources suffer from some limitations, SRMs can be considered the best available source to estimate the drug exposure history in those without EPRs. The prevalence of hypertension was 40.8% with higher prevalence in men (46.3%) compared to women (35.8%). The prevalence of awareness, treatment and controlled hypertension as defined by the study definition were 25.3%, 31.2%, and 54.3%, respectively. These findings are lower than similar reported studies in other populations, with the exception of controlled hypertension prevalence, which can be considered better than other populations. Odds of hypertension were higher in men, obese or overweight individuals, people with a parental history of hypertension, and those living in the most deprived area of Scotland. On the other hand, deprivation was associated with higher odds of treatment, awareness and controlled hypertension, suggesting that people living in the most deprived area may have been receiving better quality of care, or have higher comorbidity levels requiring greater engagement with doctors. These findings highlight the need for further work to improve hypertension management in Scotland. The family design of GS:SFHS has allowed family-based analysis to be performed to assess the familial aggregation and heritability of BP and hypertension traits. The familial correlation of BP traits ranged from 0.07 to 0.20, and from 0.18 to 0.34 for parent-offspring pairs and sibling pairs, respectively. A higher correlation of BP traits was observed among first-degree relatives than other types of relative pairs. A variance-component model that was adjusted for sex, body mass index (BMI), age, and age-squared was used to estimate heritability of BP traits, which ranged from 24% to 32% with pulse pressure (PP) having the lowest estimates. The genetic correlation between BP traits showed a high correlation between systolic (SBP), diastolic (DBP) and mean arterial pressure (MAP) (G: 81% to 94%), but lower correlations with PP (G: 22% to 78%). The sibling recurrence risk ratio (λS) for hypertension and treatment were calculated as 1.60 and 2.04 respectively. These findings confirm the genetic components of BP traits in GS:SFHS, and justify further work to investigate genetic determinants of BP. Genetic variants reported in the recent large GWAS of BP traits were selected for genotyping in GS:SFHS using a custom designed TaqMan® OpenArray®. The genotyping plate included 44 single nucleotide polymorphisms (SNPs) that have been previously reported to be associated with BP or hypertension at genome-wide significance level. A linear mixed model that is adjusted for age, age-squared, sex, and BMI was used to test for the association between the genetic variants and BP traits. Of the 43 variants that passed the QC, 11 variants showed statistically significant association with at least one BP trait. The phenotypic variance explained by these variant for the four BP traits were 1.4%, 1.5%, 1.6%, and 0.8% for SBP, DBP, MAP, and PP, respectively. The association of genetic risk score (GRS) that were constructed from selected variants has showed a positive association with BP level and hypertension prevalence, with an average effect of one mmHg increase with each 0.80 unit increases in the GRS across the different BP traits. The impact of BP-lowering medication on the genetic association study for BP traits has been established, with typical practice of adding a fixed value (i.e. 15/10 mmHg) to the measured BP values to adjust for BP treatment. Using the subset of participants with the two treatment exposure sources (i.e. SRMs and EPRs), the influence of using either source to justify the addition of fixed values in SNP association signal was analysed. BP phenotypes derived from EPRs were considered the true phenotypes, and those derived from SRMs were considered less accurate, with some phenotypic noise. Comparing SNPs association signals between the four BP traits in the two model derived from the different adjustments showed that MAP was the least impacted by the phenotypic noise. This was suggested by identifying the same overlapped significant SNPs for the two models in the case of MAP, while other BP traits had some discrepancy between the two sources
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Background: Depression is a major health problem worldwide and the majority of patients presenting with depressive symptoms are managed in primary care. Current approaches for assessing depressive symptoms in primary care are not accurate in predicting future clinical outcomes, which may potentially lead to over or under treatment. The Allostatic Load (AL) theory suggests that by measuring multi-system biomarker levels as a proxy of measuring multi-system physiological dysregulation, it is possible to identify individuals at risk of having adverse health outcomes at a prodromal stage. Allostatic Index (AI) score, calculated by applying statistical formulations to different multi-system biomarkers, have been associated with depressive symptoms. Aims and Objectives: To test the hypothesis, that a combination of allostatic load (AL) biomarkers will form a predictive algorithm in defining clinically meaningful outcomes in a population of patients presenting with depressive symptoms. The key objectives were: 1. To explore the relationship between various allostatic load biomarkers and prevalence of depressive symptoms in patients, especially in patients diagnosed with three common cardiometabolic diseases (Coronary Heart Disease (CHD), Diabetes and Stroke). 2 To explore whether allostatic load biomarkers predict clinical outcomes in patients with depressive symptoms, especially in patients with three common cardiometabolic diseases (CHD, Diabetes and Stroke). 3 To develop a predictive tool to identify individuals with depressive symptoms at highest risk of adverse clinical outcomes. Methods: Datasets used: ‘DepChron’ was a dataset of 35,537 patients with existing cardiometabolic disease collected as a part of routine clinical practice. ‘Psobid’ was a research data source containing health related information from 666 participants recruited from the general population. The clinical outcomes for 3 both datasets were studied using electronic data linkage to hospital and mortality health records, undertaken by Information Services Division, Scotland. Cross-sectional associations between allostatic load biomarkers calculated at baseline, with clinical severity of depression assessed by a symptom score, were assessed using logistic and linear regression models in both datasets. Cox’s proportional hazards survival analysis models were used to assess the relationship of allostatic load biomarkers at baseline and the risk of adverse physical health outcomes at follow-up, in patients with depressive symptoms. The possibility of interaction between depressive symptoms and allostatic load biomarkers in risk prediction of adverse clinical outcomes was studied using the analysis of variance (ANOVA) test. Finally, the value of constructing a risk scoring scale using patient demographics and allostatic load biomarkers for predicting adverse outcomes in depressed patients was investigated using clinical risk prediction modelling and Area Under Curve (AUC) statistics. Key Results: Literature Review Findings. The literature review showed that twelve blood based peripheral biomarkers were statistically significant in predicting six different clinical outcomes in participants with depressive symptoms. Outcomes related to both mental health (depressive symptoms) and physical health were statistically associated with pre-treatment levels of peripheral biomarkers; however only two studies investigated outcomes related to physical health. Cross-sectional Analysis Findings: In DepChron, dysregulation of individual allostatic biomarkers (mainly cardiometabolic) were found to have a non-linear association with increased probability of co-morbid depressive symptoms (as assessed by Hospital Anxiety and Depression Score HADS-D≥8). A composite AI score constructed using five biomarkers did not lead to any improvement in the observed strength of the association. In Psobid, BMI was found to have a significant cross-sectional association with the probability of depressive symptoms (assessed by General Health Questionnaire GHQ-28≥5). BMI, triglycerides, highly sensitive C - reactive 4 protein (CRP) and High Density Lipoprotein-HDL cholesterol were found to have a significant cross-sectional relationship with the continuous measure of GHQ-28. A composite AI score constructed using 12 biomarkers did not show a significant association with depressive symptoms among Psobid participants. Longitudinal Analysis Findings: In DepChron, three clinical outcomes were studied over four years: all-cause death, all-cause hospital admissions and composite major adverse cardiovascular outcome-MACE (cardiovascular death or admission due to MI/stroke/HF). Presence of depressive symptoms and composite AI score calculated using mainly peripheral cardiometabolic biomarkers was found to have a significant association with all three clinical outcomes over the following four years in DepChron patients. There was no evidence of an interaction between AI score and presence of depressive symptoms in risk prediction of any of the three clinical outcomes. There was a statistically significant interaction noted between SBP and depressive symptoms in risk prediction of major adverse cardiovascular outcome, and also between HbA1c and depressive symptoms in risk prediction of all-cause mortality for patients with diabetes. In Psobid, depressive symptoms (assessed by GHQ-28≥5) did not have a statistically significant association with any of the four outcomes under study at seven years: all cause death, all cause hospital admission, MACE and incidence of new cancer. A composite AI score at baseline had a significant association with the risk of MACE at seven years, after adjusting for confounders. A continuous measure of IL-6 observed at baseline had a significant association with the risk of three clinical outcomes- all-cause mortality, all-cause hospital admissions and major adverse cardiovascular event. Raised total cholesterol at baseline was associated with lower risk of all-cause death at seven years while raised waist hip ratio- WHR at baseline was associated with higher risk of MACE at seven years among Psobid participants. There was no significant interaction between depressive symptoms and peripheral biomarkers (individual or combined) in risk prediction of any of the four clinical outcomes under consideration. Risk Scoring System Development: In the DepChron cohort, a scoring system was constructed based on eight baseline demographic and clinical variables to predict the risk of MACE over four years. The AUC value for the risk scoring system was modest at 56.7% (95% CI 55.6 to 57.5%). In Psobid, it was not possible to perform this analysis due to the low event rate observed for the clinical outcomes. Conclusion: Individual peripheral biomarkers were found to have a cross-sectional association with depressive symptoms both in patients with cardiometabolic disease and middle-aged participants recruited from the general population. AI score calculated with different statistical formulations was of no greater benefit in predicting concurrent depressive symptoms or clinical outcomes at follow-up, over and above its individual constituent biomarkers, in either patient cohort. SBP had a significant interaction with depressive symptoms in predicting cardiovascular events in patients with cardiometabolic disease; HbA1c had a significant interaction with depressive symptoms in predicting all-cause mortality in patients with diabetes. Peripheral biomarkers may have a role in predicting clinical outcomes in patients with depressive symptoms, especially for those with existing cardiometabolic disease, and this merits further investigation.
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International audience
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International audience
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As the number of fungal pathogen outbreaks become more frequent worldwide across taxa, so have the number of species extirpations and communities persisting with the pathogen. This phenomenon raises questions, such as: “what leads to host extinction during an outbreak?” and “how are hosts persisting once the pathogen establishes?.” But the data on host populations and communities across life stages before and after pathogen arrival rarely exist to answer these questions. Over the past three to four decades, the amphibian-killing fungus Batrachochytrim dendrobatidis (Bd) spread in a wave-like manner across Central America, leading to rapid species extirpations and population declines. I collected data on tadpole and adult amphibians in El Copé, Panama before, during, and after the Bd outbreak to answer these questions. I used Bayesian statistical approaches to account for imperfect host and pathogen detection of marked and unmarked individuals. In the tadpole community, within 11 months of Bds arrival, density and occupancy rapidly declined. Species losses were phylogenetically correlated, with glass frogs disappearing first, and tree frogs and poison-dart frogs remaining. I found that tadpole communities resembled one another more strongly after the outbreak than they did before Bd invasion. I found no tadpoles within 22 months of the outbreak and limited signs of recovery within 10 years. In contrast, at the same site, for a population of male glass frogs, Espadarana prosopleon, I found that 10 years post-outbreak, the population was consistently half its historic abundance, and that the lack of recruits to the population explained why the population had not rebounded, rather than high pathogen-induced mortality. And finally, examining the entire amphibian community, I found high pathogen prevalence, low infection intensities, and high survival rates of uninfected and infected hosts. Bd transmission risk, i.e., the probability a susceptible host becomes infected, did not relate to host density, pathogen prevalence, or infection intensity– Bd transmission risk was uniform across the study area. My results are especially relevant to conservation biologists aiming to predict the future impacts of Bd outbreaks, those trying to manage persisting populations, and those interested in reintroducing species back into wild amphibian communities.
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The objective of this study was to estimate the spatial distribution of work accident risk in the informal work market in the urban zone of an industrialized city in southeast Brazil and to examine concomitant effects of age, gender, and type of occupation after controlling for spatial risk variation. The basic methodology adopted was that of a population-based case-control study with particular interest focused on the spatial location of work. Cases were all casual workers in the city suffering work accidents during a one-year period; controls were selected from the source population of casual laborers by systematic random sampling of urban homes. The spatial distribution of work accidents was estimated via a semiparametric generalized additive model with a nonparametric bidimensional spline of the geographical coordinates of cases and controls as the nonlinear spatial component, and including age, gender, and occupation as linear predictive variables in the parametric component. We analyzed 1,918 cases and 2,245 controls between 1/11/2003 and 31/10/2004 in Piracicaba, Brazil. Areas of significantly high and low accident risk were identified in relation to mean risk in the study region (p < 0.01). Work accident risk for informal workers varied significantly in the study area. Significant age, gender, and occupational group effects on accident risk were identified after correcting for this spatial variation. A good understanding of high-risk groups and high-risk regions underpins the formulation of hypotheses concerning accident causality and the development of effective public accident prevention policies.