Forest fires cluster detection with space-time scan statistics

Forest fires are defined as uncontrolled fires often occurring in wildland areas, but that can also affect houses or agricultural resources. Causes are both natural (e.g.,lightning phenomena) and anthropogenic (human negligence or arsons).Major environmental factors influencing the fire ignition and propagation are climate and vegetation. Wildfires are most common and severe during drought period and on windy days. Moreover, under water-stress conditions, which occur after a long hot and dry period, the vegetation is more vulnerable to fire. These conditions are common in the United State and Canada, where forest fires represent a big problem. We focused our analysis on the state of Florida, for which a big dataset on forest fires detection is readily available. USDA Forest Service Remote Sensing Application Center, in collaboration with NASA-Goddard Space Flight Center and the University of Maryland, has compiled daily MODIS Thermal Anomalies (fires and biomass burning images) produced by NASA using a contextual algorithm that exploits the strong emission of mid-infrared radiation from fires. Fire classes were converted in GIS format: daily MODIS fire detections are provided as the centroids of the 1 kilometer pixels and compiled into daily Arc/INFO point coverage.

Detection of clusters using space-time scan statistics

This paper aims at detecting spatio-temporal clustering in fire sequences using space?time scan statistics, a powerful statistical framework for the analysis of point processes. The methodology is applied to active fire detection in the state of Florida (US) identified by MODIS (Moderate Resolution Imaging Spectroradiometer) during the period 2003?06. Results of the present study show that statistically significant clusters can be detected and localized in specific areas and periods of the year. Three out of the five most likely clusters detected for the entire frame period are localized in the north of the state, and they cover forest areas; the other two clusters cover a large zone in the south, corresponding to agricultural land and the prairies in the Everglades. In order to analyze if the wildfires recur each year during the same period, the analyses have been performed separately for the 4 years: it emerges that clusters of forest fires are more frequent in hot seasons (spring and summer), while in the southern areas, they are widely present during the whole year. The recognition of overdensities of events and the ability to locate them in space and in time can help in supporting fire management and focussing on prevention measures.

Ageing Prisoners' Disease Burden: Is Being Old a Better Predictor than Time Served in Prison?

Background: The number of older prisoners entering and ageing in prison has increased in the last few decades. Ageing prisoners pose unique challenges to the prison administration as they have differentiated social, custodial and healthcare needs than prisoners who are younger and relatively healthier. Objective: The goal of this study was to explore and compare the somatic disease burden of old and young prisoners, and to examine whether it can be explained by age group and/or time served in prison. Methods: Access to prisoner medical records was granted to extract disease and demographic information of older (>50 years) and younger (≤49 years) prisoners in different Swiss prisons. Predictor variables included the age group and the time spent in prison. The dependent variable was the total number of somatic diseases as reported in the medical records. Results were analysed using descriptive statistics and a negative binomial model. Results: Data of 380 male prisoners from 13 different prisons in Switzerland reveal that the mean ages of older and younger prisoners were 58.78 and 34.26 years, respectively. On average, older prisoners have lived in prison for 5.17 years and younger prisoners for 2.49 years. The average total number of somatic diseases reported by older prisoners was 2.26 times higher than that of prisoners below 50 years of age (95% CI 1.77-2.87, p < 0.001). Conclusion: This study is the first of its kind to capture national disease data of prisoners with a goal of comparing the disease burden of older and younger prisoners. Study findings indicate that older inmates suffer from more somatic diseases and that the number of diseases increases with age group. Results clearly illustrate the poorer health conditions of those who are older, their higher healthcare burden, and raises questions related to the provision of healthcare for inmates growing old in prison. © 2014 S. Karger AG, Basel.

Moderate to vigorous physical activity and sedentary time and cardiometabolic risk factors in children and adolescents.

CONTEXT: Sparse data exist on the combined associations between physical activity and sedentary time with cardiometabolic risk factors in healthy children. OBJECTIVE: To examine the independent and combined associations between objectively measured time in moderate- to vigorous-intensity physical activity (MVPA) and sedentary time with cardiometabolic risk factors. DESIGN, SETTING, AND PARTICIPANTS: Pooled data from 14 studies between 1998 and 2009 comprising 20 871 children (aged 4-18 years) from the International Children's Accelerometry Database. Time spent in MVPA and sedentary time were measured using accelerometry after reanalyzing raw data. The independent associations between time in MVPA and sedentary time, with outcomes, were examined using meta-analysis. Participants were stratified by tertiles of MVPA and sedentary time. MAIN OUTCOME MEASURES: Waist circumference, systolic blood pressure, fasting triglycerides, high-density lipoprotein cholesterol, and insulin. RESULTS: Times (mean [SD] min/d) accumulated by children in MVPA and being sedentary were 30 (21) and 354 (96), respectively. Time in MVPA was significantly associated with all cardiometabolic outcomes independent of sex, age, monitor wear time, time spent sedentary, and waist circumference (when not the outcome). Sedentary time was not associated with any outcome independent of time in MVPA. In the combined analyses, higher levels of MVPA were associated with better cardiometabolic risk factors across tertiles of sedentary time. The differences in outcomes between higher and lower MVPA were greater with lower sedentary time. Mean differences in waist circumference between the bottom and top tertiles of MVPA were 5.6 cm (95% CI, 4.8-6.4 cm) for high sedentary time and 3.6 cm (95% CI, 2.8-4.3 cm) for low sedentary time. Mean differences in systolic blood pressure for high and low sedentary time were 0.7 mm Hg (95% CI, -0.07 to 1.6) and 2.5 mm Hg (95% CI, 1.7-3.3), and for high-density lipoprotein cholesterol, differences were -2.6 mg/dL (95% CI, -1.4 to -3.9) and -4.5 mg/dL (95% CI, -3.3 to -5.6), respectively. Geometric mean differences for insulin and triglycerides showed similar variation. Those in the top tertile of MVPA accumulated more than 35 minutes per day in this intensity level compared with fewer than 18 minutes per day for those in the bottom tertile. In prospective analyses (N = 6413 at 2.1 years' follow-up), MVPA and sedentary time were not associated with waist circumference at follow-up, but a higher waist circumference at baseline was associated with higher amounts of sedentary time at follow-up. CONCLUSION: Higher MVPA time by children and adolescents was associated with better cardiometabolic risk factors regardless of the amount of sedentary time.

Conviction Statistics as an Indicator of Crime Trends in Europe from 1990 to 2006

Convictions statistics were the first criminal statistics available in Europe during the nineteenth century. Their main weaknesses as crime measures and for comparative purposes were identified by Alphonse de Candolle in the 1830s. Currently, they are seldom used by comparative criminologists, although they provide a less valid but more reliable measure of crime and formal social control than police statistics. This article uses conviction statistics, compiled from the four editions of the European Sourcebook of Crime and Criminal Justice Statistics, to study the evolution of persons convicted in European countries from 1990 to 2006. Trends in persons convicted for six offences -intentional homicide, assault, rape, robbery, theft, and drug offences- and up to 26 European countries are analysed. These trends are established for the whole of Europe as well as for a cluster of Western European countries and a cluster of Central and Eastern European countries. The analyses show similarities between both regions of Europe at the beginning and at the end of the period under study. After a general increase of the rate of persons convicted in the early 1990s in the whole of Europe, trends followed different directions in Western and in Central and Eastern Europe. However, during the 2000s, it can be observed, throughout Europe, a certain stability of the rates of persons convicted for intentional homicides, accompanied by a general decrease of the rate of persons convicted for property offences, and an increase of the rate of those convicted for drug offences. The latter goes together with an increase of the rate of persons convicted for non lethal violent offences, which only reached some stability at the end of the time series. These trends show that there is no general crime drop in Europe. After a discussion of possible theoretical explanations, a multifactor model, inspired by opportunity-based theories, is proposed to explain the trends observed.

Robust accelerated failure time regression

Robust estimators for accelerated failure time models with asymmetric (or symmetric) error distribution and censored observations are proposed. It is assumed that the error model belongs to a log-location-scale family of distributions and that the mean response is the parameter of interest. Since scale is a main component of mean, scale is not treated as a nuisance parameter. A three steps procedure is proposed. In the first step, an initial high breakdown point S estimate is computed. In the second step, observations that are unlikely under the estimated model are rejected or down weighted. Finally, a weighted maximum likelihood estimate is computed. To define the estimates, functions of censored residuals are replaced by their estimated conditional expectation given that the response is larger than the observed censored value. The rejection rule in the second step is based on an adaptive cut-off that, asymptotically, does not reject any observation when the data are generat ed according to the model. Therefore, the final estimate attains full efficiency at the model, with respect to the maximum likelihood estimate, while maintaining the breakdown point of the initial estimator. Asymptotic results are provided. The new procedure is evaluated with the help of Monte Carlo simulations. Two examples with real data are discussed.

Trends over time of virological and immunological characteristics in the Swiss HIV Cohort Study.

BACKGROUND: The long-term outcome of antiretroviral therapy (ART) is not assessed in controlled trials. We aimed to analyse trends in the population effectiveness of ART in the Swiss HIV Cohort Study over the last decade. METHODS: We analysed the odds of stably suppressed viral load (ssVL: three consecutive values <50 HIV-1 RNA copies/mL) and of CD4 cell count exceeding 500 cells/μL for each year between 2000 and 2008 in three scenarios: an open cohort; a closed cohort ignoring the influx of new participants after 2000; and a worst-case closed cohort retaining lost or dead patients as virological failures in subsequent years. We used generalized estimating equations with sex, age, risk, non-White ethnicity and era of starting combination ART (cART) as fixed co-factors. Time-updated co-factors included type of ART regimen, number of new drugs and adherence to therapy. RESULTS: The open cohort included 9802 individuals (median age 38 years; 31% female). From 2000 to 2008, the proportion of participants with ssVL increased from 37 to 64% [adjusted odds ratio (OR) per year 1.16 (95% CI 1.15-1.17)] and the proportion with CD4 count >500 cells/μL increased from 40 to >50% [OR 1.07 (95% CI 1.06-1.07)]. Similar trends were seen in the two closed cohorts. Adjustment did not substantially affect time trends. CONCLUSIONS: There was no relevant dilution effect through new participants entering the open clinical cohort, and the increase in virological/immunological success over time was not an artefact of the study design of open cohorts. This can partly be explained by new treatment options and other improvements in medical care.

Analysis of space-time environmental data in complex regions

This thesis develops a comprehensive and a flexible statistical framework for the analysis and detection of space, time and space-time clusters of environmental point data. The developed clustering methods were applied in both simulated datasets and real-world environmental phenomena; however, only the cases of forest fires in Canton of Ticino (Switzerland) and in Portugal are expounded in this document. Normally, environmental phenomena can be modelled as stochastic point processes where each event, e.g. the forest fire ignition point, is characterised by its spatial location and occurrence in time. Additionally, information such as burned area, ignition causes, landuse, topographic, climatic and meteorological features, etc., can also be used to characterise the studied phenomenon. Thereby, the space-time pattern characterisa- tion represents a powerful tool to understand the distribution and behaviour of the events and their correlation with underlying processes, for instance, socio-economic, environmental and meteorological factors. Consequently, we propose a methodology based on the adaptation and application of statistical and fractal point process measures for both global (e.g. the Morisita Index, the Box-counting fractal method, the multifractal formalism and the Ripley's K-function) and local (e.g. Scan Statistics) analysis. Many measures describing the space-time distribution of environmental phenomena have been proposed in a wide variety of disciplines; nevertheless, most of these measures are of global character and do not consider complex spatial constraints, high variability and multivariate nature of the events. Therefore, we proposed an statistical framework that takes into account the complexities of the geographical space, where phenomena take place, by introducing the Validity Domain concept and carrying out clustering analyses in data with different constrained geographical spaces, hence, assessing the relative degree of clustering of the real distribution. Moreover, exclusively to the forest fire case, this research proposes two new methodologies to defining and mapping both the Wildland-Urban Interface (WUI) described as the interaction zone between burnable vegetation and anthropogenic infrastructures, and the prediction of fire ignition susceptibility. In this regard, the main objective of this Thesis was to carry out a basic statistical/- geospatial research with a strong application part to analyse and to describe complex phenomena as well as to overcome unsolved methodological problems in the characterisation of space-time patterns, in particular, the forest fire occurrences. Thus, this Thesis provides a response to the increasing demand for both environmental monitoring and management tools for the assessment of natural and anthropogenic hazards and risks, sustainable development, retrospective success analysis, etc. The major contributions of this work were presented at national and international conferences and published in 5 scientific journals. National and international collaborations were also established and successfully accomplished. -- Cette thèse développe une méthodologie statistique complète et flexible pour l'analyse et la détection des structures spatiales, temporelles et spatio-temporelles de données environnementales représentées comme de semis de points. Les méthodes ici développées ont été appliquées aux jeux de données simulées autant qu'A des phénomènes environnementaux réels; nonobstant, seulement le cas des feux forestiers dans le Canton du Tessin (la Suisse) et celui de Portugal sont expliqués dans ce document. Normalement, les phénomènes environnementaux peuvent être modélisés comme des processus ponctuels stochastiques ou chaque événement, par ex. les point d'ignition des feux forestiers, est déterminé par son emplacement spatial et son occurrence dans le temps. De plus, des informations tels que la surface bru^lée, les causes d'ignition, l'utilisation du sol, les caractéristiques topographiques, climatiques et météorologiques, etc., peuvent aussi être utilisées pour caractériser le phénomène étudié. Par conséquent, la définition de la structure spatio-temporelle représente un outil puissant pour compren- dre la distribution du phénomène et sa corrélation avec des processus sous-jacents tels que les facteurs socio-économiques, environnementaux et météorologiques. De ce fait, nous proposons une méthodologie basée sur l'adaptation et l'application de mesures statistiques et fractales des processus ponctuels d'analyse global (par ex. l'indice de Morisita, la dimension fractale par comptage de boîtes, le formalisme multifractal et la fonction K de Ripley) et local (par ex. la statistique de scan). Des nombreuses mesures décrivant les structures spatio-temporelles de phénomènes environnementaux peuvent être trouvées dans la littérature. Néanmoins, la plupart de ces mesures sont de caractère global et ne considèrent pas de contraintes spatiales com- plexes, ainsi que la haute variabilité et la nature multivariée des événements. A cet effet, la méthodologie ici proposée prend en compte les complexités de l'espace géographique ou le phénomène a lieu, à travers de l'introduction du concept de Domaine de Validité et l'application des mesures d'analyse spatiale dans des données en présentant différentes contraintes géographiques. Cela permet l'évaluation du degré relatif d'agrégation spatiale/temporelle des structures du phénomène observé. En plus, exclusif au cas de feux forestiers, cette recherche propose aussi deux nouvelles méthodologies pour la définition et la cartographie des zones périurbaines, décrites comme des espaces anthropogéniques à proximité de la végétation sauvage ou de la forêt, et de la prédiction de la susceptibilité à l'ignition de feu. A cet égard, l'objectif principal de cette Thèse a été d'effectuer une recherche statistique/géospatiale avec une forte application dans des cas réels, pour analyser et décrire des phénomènes environnementaux complexes aussi bien que surmonter des problèmes méthodologiques non résolus relatifs à la caractérisation des structures spatio-temporelles, particulièrement, celles des occurrences de feux forestières. Ainsi, cette Thèse fournit une réponse à la demande croissante de la gestion et du monitoring environnemental pour le déploiement d'outils d'évaluation des risques et des dangers naturels et anthro- pogéniques. Les majeures contributions de ce travail ont été présentées aux conférences nationales et internationales, et ont été aussi publiées dans 5 revues internationales avec comité de lecture. Des collaborations nationales et internationales ont été aussi établies et accomplies avec succès.