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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Laurie B. Marczak; Thomas Jaenisch; Robert Reiner; Moritz U. G. Kraemer; +18 Authors

    AbstractDengue is a mosquito-borne viral infection that has spread throughout the tropical world over the past 60 years and now affects over half the world’s population. The geographical range of dengue is expected to further expand due to ongoing global phenomena including climate change and urbanization. We applied statistical mapping techniques to the most extensive database of case locations to date to predict global environmental suitability for the virus as of 2015. We then made use of climate, population and socioeconomic projections for the years 2020, 2050 and 2080 to project future changes in virus suitability and human population at risk. This study is the first to consider the spread of Aedes mosquito vectors to project dengue suitability. Our projections provide a key missing piece of evidence for the changing global threat of vector-borne disease and will help decision-makers worldwide to better prepare for and respond to future changes in dengue risk.

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ COREarrow_drop_down
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Nature Microbiology
    Article . 2019 . Peer-reviewed
    License: CC BY
    Data sources: Crossref
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Nature Microbiology
    Article
    License: CC BY
    Data sources: UnpayWall
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    PubMed Central
    Other literature type . 2019
    Data sources: PubMed Central
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
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    DI-fusion
    Article . 2019 . Peer-reviewed
    Data sources: DI-fusion
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ COREarrow_drop_down
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      Nature Microbiology
      Article . 2019 . Peer-reviewed
      License: CC BY
      Data sources: Crossref
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      Nature Microbiology
      Article
      License: CC BY
      Data sources: UnpayWall
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      PubMed Central
      Other literature type . 2019
      Data sources: PubMed Central
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      DI-fusion
      Article . 2019 . Peer-reviewed
      Data sources: DI-fusion
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
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      This Research product is the result of merged Research products in OpenAIRE.

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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Simon I. Hay; Simon I. Hay; Jörn P. W. Scharlemann; David Benz; +5 Authors

    Les données environnementales télédétectées provenant de satellites en orbite terrestre sont de plus en plus utilisées pour modéliser la distribution et l'abondance des espèces végétales et animales, en particulier celles d'importance économique ou de conservation. Les séries chronologiques de données provenant des capteurs du spectroradiomètre d'imagerie à résolution modérée (MODIS) à bord des satellites Terra et Aqua de la NASA offrent la possibilité de capturer la saisonnalité thermique et végétale de l'environnement, grâce à une analyse de Fourier temporelle, plus précisément qu'auparavant en utilisant les données des capteurs du radiomètre avancé à très haute résolution (AVHRR) de la NOAA. Les données MODIS sont composées sur des intervalles de temps de 8 ou 16 jours qui posent des problèmes uniques pour l'analyse temporelle de Fourier. L'application de techniques standard aux données MODIS peut introduire des erreurs allant jusqu'à 30% dans l'estimation des amplitudes et des phases des harmoniques de Fourier. Nous présentons un nouvel algorithme basé sur la spline qui surmonte les problèmes de traitement des données MODIS composées. L'algorithme est testé sur des données artificielles générées à l'aide de valeurs sélectionnées de manière aléatoire des amplitudes et des phases, et fournit une estimation précise des variables d'entrée dans toutes les conditions. L'algorithme a ensuite été appliqué pour produire des couches qui capturent la saisonnalité dans les données MODIS pour la période de 2001 à 2005. Des images traitées par Fourier temporel mondial de données MODIS de 1 km pour la réflectance infrarouge moyenne, la température de surface du sol (LST) de jour et de nuit, l'indice de végétation à différence normalisée (NDVI) et l'indice de végétation amélioré (EVI) sont présentées pour des applications écologiques et épidémiologiques. La résolution spatiale et temporelle plus fine, combinée à la plus grande précision géolocalisée et spectrale des instruments MODIS, par rapport aux ensembles de données multitemporelles précédents, signifie que ces données peuvent être utilisées avec une plus grande confiance dans la modélisation de la distribution des espèces. Los datos ambientales teledetectados de los satélites en órbita terrestre se utilizan cada vez más para modelar la distribución y abundancia de especies vegetales y animales, especialmente las de importancia económica o ecológica. Las series temporales de datos de los sensores del espectrorradiómetro de imágenes de resolución MODerate (MODIS) a bordo de los satélites Terra y Aqua de la NASA ofrecen el potencial de capturar la estacionalidad térmica y vegetal ambiental, a través del análisis temporal de Fourier, con mayor precisión de lo que era posible anteriormente utilizando los datos del sensor del radiómetro avanzado de muy alta resolución (AVHRR) de la NOAA. Los datos de MODIS se componen en intervalos de tiempo de 8 o 16 días que plantean problemas únicos para el análisis temporal de Fourier. La aplicación de técnicas estándar a los datos MODIS puede introducir errores de hasta el 30% en la estimación de las amplitudes y fases de los armónicos de Fourier. Presentamos un novedoso algoritmo basado en splines que supera los problemas de procesamiento de los datos MODIS compuestos. El algoritmo se prueba en datos artificiales generados utilizando valores seleccionados aleatoriamente de amplitudes y fases, y proporciona una estimación precisa de las variables de entrada en todas las condiciones. Luego se aplicó el algoritmo para producir capas que capturan la estacionalidad en los datos de MODIS para el período de 2001 a 2005. Se presentan imágenes temporales globales procesadas por Fourier de datos MODIS de 1 km para la reflectancia infrarroja media, la temperatura de la superficie terrestre (LST) diurna y nocturna, el índice de vegetación de diferencia normalizada (NDVI) y el índice de vegetación mejorada (EVI) para aplicaciones ecológicas y epidemiológicas. La resolución espacial y temporal más fina, combinada con la mayor precisión geolocalizadora y espectral de los instrumentos MODIS, en comparación con los conjuntos de datos multitemporales anteriores, significa que estos datos pueden utilizarse con mayor confianza en la modelización de la distribución de las especies. Remotely-sensed environmental data from earth-orbiting satellites are increasingly used to model the distribution and abundance of both plant and animal species, especially those of economic or conservation importance. Time series of data from the MODerate-resolution Imaging Spectroradiometer (MODIS) sensors on-board NASA's Terra and Aqua satellites offer the potential to capture environmental thermal and vegetation seasonality, through temporal Fourier analysis, more accurately than was previously possible using the NOAA Advanced Very High Resolution Radiometer (AVHRR) sensor data. MODIS data are composited over 8- or 16-day time intervals that pose unique problems for temporal Fourier analysis. Applying standard techniques to MODIS data can introduce errors of up to 30% in the estimation of the amplitudes and phases of the Fourier harmonics.We present a novel spline-based algorithm that overcomes the processing problems of composited MODIS data. The algorithm is tested on artificial data generated using randomly selected values of both amplitudes and phases, and provides an accurate estimate of the input variables under all conditions. The algorithm was then applied to produce layers that capture the seasonality in MODIS data for the period from 2001 to 2005.Global temporal Fourier processed images of 1 km MODIS data for Middle Infrared Reflectance, day- and night-time Land Surface Temperature (LST), Normalised Difference Vegetation Index (NDVI), and Enhanced Vegetation Index (EVI) are presented for ecological and epidemiological applications. The finer spatial and temporal resolution, combined with the greater geolocational and spectral accuracy of the MODIS instruments, compared with previous multi-temporal data sets, mean that these data may be used with greater confidence in species' distribution modelling. يتم استخدام البيانات البيئية المستشعرة عن بعد من الأقمار الصناعية التي تدور حول الأرض بشكل متزايد لنمذجة توزيع ووفرة كل من الأنواع النباتية والحيوانية، وخاصة تلك ذات الأهمية الاقتصادية أو أهمية الحفظ. توفر السلاسل الزمنية للبيانات من مستشعرات مقياس الطيف التصويري (MODIS) على متن أقمار تيرا وأكوا التابعة لناسا إمكانية التقاط الموسمية الحرارية والنباتية البيئية، من خلال تحليل فورييه الزمني، بشكل أكثر دقة مما كان ممكنًا في السابق باستخدام بيانات مستشعر مقياس الإشعاع المتقدم عالي الدقة (AVHRR) التابع للإدارة الوطنية للمحيطات والغلاف الجوي (NOAA). يتم تكوين بيانات MODIS على فترات زمنية تتراوح بين 8 أو 16 يومًا والتي تشكل مشاكل فريدة لتحليل فورييه الزمني. يمكن أن يؤدي تطبيق التقنيات القياسية على بيانات MODIS إلى حدوث أخطاء تصل إلى 30 ٪ في تقدير سعة ومراحل توافقيات فورييه. نقدم خوارزمية جديدة تستند إلى شريحة تتغلب على مشاكل معالجة بيانات MODIS المركبة. يتم اختبار الخوارزمية على البيانات الاصطناعية التي تم إنشاؤها باستخدام قيم مختارة عشوائيًا لكل من السعة والمراحل، وتوفر تقديرًا دقيقًا لمتغيرات الإدخال في جميع الظروف. ثم تم تطبيق الخوارزمية لإنتاج طبقات تلتقط الموسمية في بيانات MODIS للفترة من 2001 إلى 2005. تمت معالجة صور فورييه الزمنية العالمية لبيانات MODIS لمسافة 1 كم للانعكاس الأوسط للأشعة تحت الحمراء، ودرجة حرارة سطح الأرض ليلاً ونهارًا (LST)، ومؤشر الفرق الطبيعي للغطاء النباتي (NDVI)، ومؤشر الغطاء النباتي المعزز (EVI) للتطبيقات البيئية والوبائية. إن الدقة المكانية والزمانية الدقيقة، جنبًا إلى جنب مع الدقة الجغرافية والطيفية الأكبر لأدوات MODIS، مقارنة بمجموعات البيانات السابقة متعددة الأزمنة، تعني أنه يمكن استخدام هذه البيانات بثقة أكبر في نمذجة توزيع الأنواع.

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ COREarrow_drop_down
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    PLoS ONE
    Article . 2008 . Peer-reviewed
    License: CC BY
    Data sources: Crossref
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    Article
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    PLoS ONE
    Article . 2008
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    PubMed Central
    Other literature type . 2008
    License: CC BY
    Data sources: PubMed Central
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    PLoS ONE
    Article . 2008
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    PLoS ONE
    Article . Peer-reviewed
    License: CC BY
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
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    e-Prints Soton
    Article . 2008 . Peer-reviewed
    Data sources: e-Prints Soton
    https://dx.doi.org/10.60692/k3...
    Other literature type . 2008
    Data sources: Datacite
    https://dx.doi.org/10.60692/s1...
    Other literature type . 2008
    Data sources: Datacite
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    Authors: K. Biomndo; G.D. Shanks; Simon I. Hay; Robert W. Snow; +1 Authors

    The changing epidemiology of clinical malaria since 1965 among hospitalized patients was studied at a group of tea estates in the western highlands of Kenya. These data indicate recent dramatic increases in the numbers of malaria admissions (6.5 to 32.5% of all admissions), case fatality (1.3 to 6%) and patients originating from low-risk, highland areas (34 to 59%). Climate change, environmental management, population migration, and breakdown in health service provision seem unlikely explanations for this changing disease pattern. The coincident arrival of chloroquine resistance during the late 1980s in the subregion suggests that drug resistance is a key factor in the current pattern and burden of malaria among this highland population.

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    Authors: G. R. William Wint; Marius Gilbert; Elisa Palamara; Laura D'Aietti; +8 Authors

    L'élevage contribue directement aux moyens de subsistance et à la sécurité alimentaire de près d'un milliard de personnes et affecte l'alimentation et la santé de nombreux autres. Avec une population sur pied estimée à 1,43 milliard de bovins, 1,87 milliard d'ovins et de caprins, 0,98 milliard de porcins et 19,60 milliards de poulets, des informations fiables et accessibles sur la distribution et l'abondance du bétail sont nécessaires pour de nombreuses raisons. Il s'agit notamment d'analyses des aspects sociaux et économiques du secteur de l'élevage ; des impacts environnementaux de l'élevage tels que la production et la gestion des déchets, les émissions de gaz à effet de serre et les changements d'affectation des terres liés à l'élevage ; et des enquêtes de santé publique et épidémiologiques à grande échelle. La base de données Gridded Livestock of the World (GLW), produite en 2007, a fourni des densités de bétail modélisées du monde, ajustées pour correspondre aux estimations nationales officielles (FAOSTAT) pour l'année de référence 2005, à une résolution spatiale de 3 minutes d'arc (environ 5×5 km à l'équateur). Des améliorations méthodologiques récentes ont considérablement amélioré ces distributions : des statistiques infranationales plus récentes et détaillées sur le bétail ont été collectées ; un nouvel ensemble de variables prédictives à plus haute résolution est utilisé ; et la procédure analytique a été révisée et étendue pour inclure une évaluation plus systématique de la précision du modèle et de la représentation des incertitudes associées aux prédictions. Cet article décrit en détail l'approche actuelle et présente de nouvelles cartes de distribution mondiale à une résolution de 1 km pour les bovins, les porcs et les poulets, ainsi qu'une carte de distribution partielle pour les canards. Ces couches numériques sont mises à la disposition du public via le Géo-Wiki de l'élevage (http://www.livestock.geo-wiki.org), tout comme les cartes des autres types d'élevage au fur et à mesure de leur production. La ganadería contribuye directamente a los medios de vida y la seguridad alimentaria de casi mil millones de personas y afecta a la dieta y la salud de muchas más. Con poblaciones permanentes estimadas de 1.430 millones de vacas, 1.870 millones de ovejas y cabras, 0.980 millones de cerdos y 19.600 millones de pollos, se necesita información confiable y accesible sobre la distribución y abundancia de ganado por muchas razones. Estos incluyen análisis de los aspectos sociales y económicos del sector ganadero; los impactos ambientales de la ganadería, como la producción y gestión de residuos, las emisiones de gases de efecto invernadero y el cambio de uso de la tierra relacionado con la ganadería; e investigaciones epidemiológicas y de salud pública a gran escala. La base de datos Gridded Livestock of the World (GLW), producida en 2007, proporcionó densidades de ganado modeladas del mundo, ajustadas para coincidir con las estimaciones nacionales oficiales (FAOSTAT) para el año de referencia 2005, a una resolución espacial de 3 minutos de arco (aproximadamente 5×5 km en el ecuador). Las mejoras metodológicas recientes han mejorado significativamente estas distribuciones: se han recopilado estadísticas ganaderas subnacionales más actualizadas y detalladas; se utiliza un nuevo conjunto de variables predictoras de mayor resolución; y el procedimiento analítico se ha revisado y ampliado para incluir una evaluación más sistemática de la precisión del modelo y la representación de las incertidumbres asociadas con las predicciones. Este documento describe el enfoque actual en detalle y presenta nuevos mapas de distribución global a una resolución de 1 km para ganado vacuno, cerdos y pollos, y un mapa de distribución parcial para patos. Estas capas digitales se ponen a disposición del público a través de Livestock Geo-Wiki (http://www.livestock.geo-wiki.org), al igual que los mapas de otros tipos de ganado a medida que se producen. Livestock contributes directly to the livelihoods and food security of almost a billion people and affects the diet and health of many more. With estimated standing populations of 1.43 billion cattle, 1.87 billion sheep and goats, 0.98 billion pigs, and 19.60 billion chickens, reliable and accessible information on the distribution and abundance of livestock is needed for a many reasons. These include analyses of the social and economic aspects of the livestock sector; the environmental impacts of livestock such as the production and management of waste, greenhouse gas emissions and livestock-related land-use change; and large-scale public health and epidemiological investigations. The Gridded Livestock of the World (GLW) database, produced in 2007, provided modelled livestock densities of the world, adjusted to match official (FAOSTAT) national estimates for the reference year 2005, at a spatial resolution of 3 minutes of arc (about 5×5 km at the equator). Recent methodological improvements have significantly enhanced these distributions: more up-to date and detailed sub-national livestock statistics have been collected; a new, higher resolution set of predictor variables is used; and the analytical procedure has been revised and extended to include a more systematic assessment of model accuracy and the representation of uncertainties associated with the predictions. This paper describes the current approach in detail and presents new global distribution maps at 1 km resolution for cattle, pigs and chickens, and a partial distribution map for ducks. These digital layers are made publically available via the Livestock Geo-Wiki (http://www.livestock.geo-wiki.org), as will be the maps of other livestock types as they are produced. تساهم الثروة الحيوانية بشكل مباشر في سبل العيش والأمن الغذائي لما يقرب من مليار شخص وتؤثر على النظام الغذائي والصحة للكثيرين غيرهم. مع وجود ما يقدر بنحو 1.43 مليار رأس من الماشية، و 1.87 مليار رأس من الأغنام والماعز، و 0.98 مليار رأس من الخنازير، و 19.60 مليار رأس من الدجاج، هناك حاجة إلى معلومات موثوقة ويمكن الوصول إليها حول توزيع ووفرة الماشية لأسباب عديدة. ويشمل ذلك تحليلات للجوانب الاجتماعية والاقتصادية لقطاع الثروة الحيوانية ؛ والآثار البيئية للثروة الحيوانية مثل إنتاج وإدارة النفايات وانبعاثات غازات الدفيئة والتغيير في استخدام الأراضي المتعلقة بالثروة الحيوانية ؛ والتحقيقات واسعة النطاق في مجال الصحة العامة والأوبئة. قدمت قاعدة بيانات الثروة الحيوانية الشبكية في العالم (GLW)، التي تم إنتاجها في عام 2007، نماذج لكثافة الثروة الحيوانية في العالم، تم تعديلها لتتناسب مع التقديرات الوطنية الرسمية (FAOSTAT) للسنة المرجعية 2005، بدقة مكانية تبلغ 3 دقائق من القوس (حوالي 5×5 كم عند خط الاستواء). عززت التحسينات المنهجية الأخيرة هذه التوزيعات بشكل كبير: تم جمع إحصاءات أكثر حداثة وتفصيلاً عن الثروة الحيوانية على المستوى دون الوطني ؛ وتم استخدام مجموعة جديدة أعلى دقة من متغيرات التنبؤ ؛ وتمت مراجعة الإجراء التحليلي وتوسيعه ليشمل تقييمًا أكثر منهجية لدقة النموذج وتمثيل أوجه عدم اليقين المرتبطة بالتنبؤات. تصف هذه الورقة النهج الحالي بالتفصيل وتقدم خرائط توزيع عالمية جديدة بدقة 1 كم للماشية والخنازير والدجاج، وخريطة توزيع جزئية للبط. تتاح هذه الطبقات الرقمية للجمهور عبر موقع Livestock Geo - Wiki (http://www.livestock.geo-wiki.org)، وكذلك خرائط أنواع الماشية الأخرى عند إنتاجها.

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    Authors: Laurie B. Marczak; Thomas Jaenisch; Robert Reiner; Moritz U. G. Kraemer; +18 Authors

    AbstractDengue is a mosquito-borne viral infection that has spread throughout the tropical world over the past 60 years and now affects over half the world’s population. The geographical range of dengue is expected to further expand due to ongoing global phenomena including climate change and urbanization. We applied statistical mapping techniques to the most extensive database of case locations to date to predict global environmental suitability for the virus as of 2015. We then made use of climate, population and socioeconomic projections for the years 2020, 2050 and 2080 to project future changes in virus suitability and human population at risk. This study is the first to consider the spread of Aedes mosquito vectors to project dengue suitability. Our projections provide a key missing piece of evidence for the changing global threat of vector-borne disease and will help decision-makers worldwide to better prepare for and respond to future changes in dengue risk.

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    Nature Microbiology
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    Nature Microbiology
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    PubMed Central
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    DI-fusion
    Article . 2019 . Peer-reviewed
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      Nature Microbiology
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    Authors: Simon I. Hay; Simon I. Hay; Jörn P. W. Scharlemann; David Benz; +5 Authors

    Les données environnementales télédétectées provenant de satellites en orbite terrestre sont de plus en plus utilisées pour modéliser la distribution et l'abondance des espèces végétales et animales, en particulier celles d'importance économique ou de conservation. Les séries chronologiques de données provenant des capteurs du spectroradiomètre d'imagerie à résolution modérée (MODIS) à bord des satellites Terra et Aqua de la NASA offrent la possibilité de capturer la saisonnalité thermique et végétale de l'environnement, grâce à une analyse de Fourier temporelle, plus précisément qu'auparavant en utilisant les données des capteurs du radiomètre avancé à très haute résolution (AVHRR) de la NOAA. Les données MODIS sont composées sur des intervalles de temps de 8 ou 16 jours qui posent des problèmes uniques pour l'analyse temporelle de Fourier. L'application de techniques standard aux données MODIS peut introduire des erreurs allant jusqu'à 30% dans l'estimation des amplitudes et des phases des harmoniques de Fourier. Nous présentons un nouvel algorithme basé sur la spline qui surmonte les problèmes de traitement des données MODIS composées. L'algorithme est testé sur des données artificielles générées à l'aide de valeurs sélectionnées de manière aléatoire des amplitudes et des phases, et fournit une estimation précise des variables d'entrée dans toutes les conditions. L'algorithme a ensuite été appliqué pour produire des couches qui capturent la saisonnalité dans les données MODIS pour la période de 2001 à 2005. Des images traitées par Fourier temporel mondial de données MODIS de 1 km pour la réflectance infrarouge moyenne, la température de surface du sol (LST) de jour et de nuit, l'indice de végétation à différence normalisée (NDVI) et l'indice de végétation amélioré (EVI) sont présentées pour des applications écologiques et épidémiologiques. La résolution spatiale et temporelle plus fine, combinée à la plus grande précision géolocalisée et spectrale des instruments MODIS, par rapport aux ensembles de données multitemporelles précédents, signifie que ces données peuvent être utilisées avec une plus grande confiance dans la modélisation de la distribution des espèces. Los datos ambientales teledetectados de los satélites en órbita terrestre se utilizan cada vez más para modelar la distribución y abundancia de especies vegetales y animales, especialmente las de importancia económica o ecológica. Las series temporales de datos de los sensores del espectrorradiómetro de imágenes de resolución MODerate (MODIS) a bordo de los satélites Terra y Aqua de la NASA ofrecen el potencial de capturar la estacionalidad térmica y vegetal ambiental, a través del análisis temporal de Fourier, con mayor precisión de lo que era posible anteriormente utilizando los datos del sensor del radiómetro avanzado de muy alta resolución (AVHRR) de la NOAA. Los datos de MODIS se componen en intervalos de tiempo de 8 o 16 días que plantean problemas únicos para el análisis temporal de Fourier. La aplicación de técnicas estándar a los datos MODIS puede introducir errores de hasta el 30% en la estimación de las amplitudes y fases de los armónicos de Fourier. Presentamos un novedoso algoritmo basado en splines que supera los problemas de procesamiento de los datos MODIS compuestos. El algoritmo se prueba en datos artificiales generados utilizando valores seleccionados aleatoriamente de amplitudes y fases, y proporciona una estimación precisa de las variables de entrada en todas las condiciones. Luego se aplicó el algoritmo para producir capas que capturan la estacionalidad en los datos de MODIS para el período de 2001 a 2005. Se presentan imágenes temporales globales procesadas por Fourier de datos MODIS de 1 km para la reflectancia infrarroja media, la temperatura de la superficie terrestre (LST) diurna y nocturna, el índice de vegetación de diferencia normalizada (NDVI) y el índice de vegetación mejorada (EVI) para aplicaciones ecológicas y epidemiológicas. La resolución espacial y temporal más fina, combinada con la mayor precisión geolocalizadora y espectral de los instrumentos MODIS, en comparación con los conjuntos de datos multitemporales anteriores, significa que estos datos pueden utilizarse con mayor confianza en la modelización de la distribución de las especies. Remotely-sensed environmental data from earth-orbiting satellites are increasingly used to model the distribution and abundance of both plant and animal species, especially those of economic or conservation importance. Time series of data from the MODerate-resolution Imaging Spectroradiometer (MODIS) sensors on-board NASA's Terra and Aqua satellites offer the potential to capture environmental thermal and vegetation seasonality, through temporal Fourier analysis, more accurately than was previously possible using the NOAA Advanced Very High Resolution Radiometer (AVHRR) sensor data. MODIS data are composited over 8- or 16-day time intervals that pose unique problems for temporal Fourier analysis. Applying standard techniques to MODIS data can introduce errors of up to 30% in the estimation of the amplitudes and phases of the Fourier harmonics.We present a novel spline-based algorithm that overcomes the processing problems of composited MODIS data. The algorithm is tested on artificial data generated using randomly selected values of both amplitudes and phases, and provides an accurate estimate of the input variables under all conditions. The algorithm was then applied to produce layers that capture the seasonality in MODIS data for the period from 2001 to 2005.Global temporal Fourier processed images of 1 km MODIS data for Middle Infrared Reflectance, day- and night-time Land Surface Temperature (LST), Normalised Difference Vegetation Index (NDVI), and Enhanced Vegetation Index (EVI) are presented for ecological and epidemiological applications. The finer spatial and temporal resolution, combined with the greater geolocational and spectral accuracy of the MODIS instruments, compared with previous multi-temporal data sets, mean that these data may be used with greater confidence in species' distribution modelling. يتم استخدام البيانات البيئية المستشعرة عن بعد من الأقمار الصناعية التي تدور حول الأرض بشكل متزايد لنمذجة توزيع ووفرة كل من الأنواع النباتية والحيوانية، وخاصة تلك ذات الأهمية الاقتصادية أو أهمية الحفظ. توفر السلاسل الزمنية للبيانات من مستشعرات مقياس الطيف التصويري (MODIS) على متن أقمار تيرا وأكوا التابعة لناسا إمكانية التقاط الموسمية الحرارية والنباتية البيئية، من خلال تحليل فورييه الزمني، بشكل أكثر دقة مما كان ممكنًا في السابق باستخدام بيانات مستشعر مقياس الإشعاع المتقدم عالي الدقة (AVHRR) التابع للإدارة الوطنية للمحيطات والغلاف الجوي (NOAA). يتم تكوين بيانات MODIS على فترات زمنية تتراوح بين 8 أو 16 يومًا والتي تشكل مشاكل فريدة لتحليل فورييه الزمني. يمكن أن يؤدي تطبيق التقنيات القياسية على بيانات MODIS إلى حدوث أخطاء تصل إلى 30 ٪ في تقدير سعة ومراحل توافقيات فورييه. نقدم خوارزمية جديدة تستند إلى شريحة تتغلب على مشاكل معالجة بيانات MODIS المركبة. يتم اختبار الخوارزمية على البيانات الاصطناعية التي تم إنشاؤها باستخدام قيم مختارة عشوائيًا لكل من السعة والمراحل، وتوفر تقديرًا دقيقًا لمتغيرات الإدخال في جميع الظروف. ثم تم تطبيق الخوارزمية لإنتاج طبقات تلتقط الموسمية في بيانات MODIS للفترة من 2001 إلى 2005. تمت معالجة صور فورييه الزمنية العالمية لبيانات MODIS لمسافة 1 كم للانعكاس الأوسط للأشعة تحت الحمراء، ودرجة حرارة سطح الأرض ليلاً ونهارًا (LST)، ومؤشر الفرق الطبيعي للغطاء النباتي (NDVI)، ومؤشر الغطاء النباتي المعزز (EVI) للتطبيقات البيئية والوبائية. إن الدقة المكانية والزمانية الدقيقة، جنبًا إلى جنب مع الدقة الجغرافية والطيفية الأكبر لأدوات MODIS، مقارنة بمجموعات البيانات السابقة متعددة الأزمنة، تعني أنه يمكن استخدام هذه البيانات بثقة أكبر في نمذجة توزيع الأنواع.

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    PLoS ONE
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    e-Prints Soton
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      e-Prints Soton
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    Authors: K. Biomndo; G.D. Shanks; Simon I. Hay; Robert W. Snow; +1 Authors

    The changing epidemiology of clinical malaria since 1965 among hospitalized patients was studied at a group of tea estates in the western highlands of Kenya. These data indicate recent dramatic increases in the numbers of malaria admissions (6.5 to 32.5% of all admissions), case fatality (1.3 to 6%) and patients originating from low-risk, highland areas (34 to 59%). Climate change, environmental management, population migration, and breakdown in health service provision seem unlikely explanations for this changing disease pattern. The coincident arrival of chloroquine resistance during the late 1980s in the subregion suggests that drug resistance is a key factor in the current pattern and burden of malaria among this highland population.

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    Authors: G. R. William Wint; Marius Gilbert; Elisa Palamara; Laura D'Aietti; +8 Authors

    L'élevage contribue directement aux moyens de subsistance et à la sécurité alimentaire de près d'un milliard de personnes et affecte l'alimentation et la santé de nombreux autres. Avec une population sur pied estimée à 1,43 milliard de bovins, 1,87 milliard d'ovins et de caprins, 0,98 milliard de porcins et 19,60 milliards de poulets, des informations fiables et accessibles sur la distribution et l'abondance du bétail sont nécessaires pour de nombreuses raisons. Il s'agit notamment d'analyses des aspects sociaux et économiques du secteur de l'élevage ; des impacts environnementaux de l'élevage tels que la production et la gestion des déchets, les émissions de gaz à effet de serre et les changements d'affectation des terres liés à l'élevage ; et des enquêtes de santé publique et épidémiologiques à grande échelle. La base de données Gridded Livestock of the World (GLW), produite en 2007, a fourni des densités de bétail modélisées du monde, ajustées pour correspondre aux estimations nationales officielles (FAOSTAT) pour l'année de référence 2005, à une résolution spatiale de 3 minutes d'arc (environ 5×5 km à l'équateur). Des améliorations méthodologiques récentes ont considérablement amélioré ces distributions : des statistiques infranationales plus récentes et détaillées sur le bétail ont été collectées ; un nouvel ensemble de variables prédictives à plus haute résolution est utilisé ; et la procédure analytique a été révisée et étendue pour inclure une évaluation plus systématique de la précision du modèle et de la représentation des incertitudes associées aux prédictions. Cet article décrit en détail l'approche actuelle et présente de nouvelles cartes de distribution mondiale à une résolution de 1 km pour les bovins, les porcs et les poulets, ainsi qu'une carte de distribution partielle pour les canards. Ces couches numériques sont mises à la disposition du public via le Géo-Wiki de l'élevage (http://www.livestock.geo-wiki.org), tout comme les cartes des autres types d'élevage au fur et à mesure de leur production. La ganadería contribuye directamente a los medios de vida y la seguridad alimentaria de casi mil millones de personas y afecta a la dieta y la salud de muchas más. Con poblaciones permanentes estimadas de 1.430 millones de vacas, 1.870 millones de ovejas y cabras, 0.980 millones de cerdos y 19.600 millones de pollos, se necesita información confiable y accesible sobre la distribución y abundancia de ganado por muchas razones. Estos incluyen análisis de los aspectos sociales y económicos del sector ganadero; los impactos ambientales de la ganadería, como la producción y gestión de residuos, las emisiones de gases de efecto invernadero y el cambio de uso de la tierra relacionado con la ganadería; e investigaciones epidemiológicas y de salud pública a gran escala. La base de datos Gridded Livestock of the World (GLW), producida en 2007, proporcionó densidades de ganado modeladas del mundo, ajustadas para coincidir con las estimaciones nacionales oficiales (FAOSTAT) para el año de referencia 2005, a una resolución espacial de 3 minutos de arco (aproximadamente 5×5 km en el ecuador). Las mejoras metodológicas recientes han mejorado significativamente estas distribuciones: se han recopilado estadísticas ganaderas subnacionales más actualizadas y detalladas; se utiliza un nuevo conjunto de variables predictoras de mayor resolución; y el procedimiento analítico se ha revisado y ampliado para incluir una evaluación más sistemática de la precisión del modelo y la representación de las incertidumbres asociadas con las predicciones. Este documento describe el enfoque actual en detalle y presenta nuevos mapas de distribución global a una resolución de 1 km para ganado vacuno, cerdos y pollos, y un mapa de distribución parcial para patos. Estas capas digitales se ponen a disposición del público a través de Livestock Geo-Wiki (http://www.livestock.geo-wiki.org), al igual que los mapas de otros tipos de ganado a medida que se producen. Livestock contributes directly to the livelihoods and food security of almost a billion people and affects the diet and health of many more. With estimated standing populations of 1.43 billion cattle, 1.87 billion sheep and goats, 0.98 billion pigs, and 19.60 billion chickens, reliable and accessible information on the distribution and abundance of livestock is needed for a many reasons. These include analyses of the social and economic aspects of the livestock sector; the environmental impacts of livestock such as the production and management of waste, greenhouse gas emissions and livestock-related land-use change; and large-scale public health and epidemiological investigations. The Gridded Livestock of the World (GLW) database, produced in 2007, provided modelled livestock densities of the world, adjusted to match official (FAOSTAT) national estimates for the reference year 2005, at a spatial resolution of 3 minutes of arc (about 5×5 km at the equator). Recent methodological improvements have significantly enhanced these distributions: more up-to date and detailed sub-national livestock statistics have been collected; a new, higher resolution set of predictor variables is used; and the analytical procedure has been revised and extended to include a more systematic assessment of model accuracy and the representation of uncertainties associated with the predictions. This paper describes the current approach in detail and presents new global distribution maps at 1 km resolution for cattle, pigs and chickens, and a partial distribution map for ducks. These digital layers are made publically available via the Livestock Geo-Wiki (http://www.livestock.geo-wiki.org), as will be the maps of other livestock types as they are produced. تساهم الثروة الحيوانية بشكل مباشر في سبل العيش والأمن الغذائي لما يقرب من مليار شخص وتؤثر على النظام الغذائي والصحة للكثيرين غيرهم. مع وجود ما يقدر بنحو 1.43 مليار رأس من الماشية، و 1.87 مليار رأس من الأغنام والماعز، و 0.98 مليار رأس من الخنازير، و 19.60 مليار رأس من الدجاج، هناك حاجة إلى معلومات موثوقة ويمكن الوصول إليها حول توزيع ووفرة الماشية لأسباب عديدة. ويشمل ذلك تحليلات للجوانب الاجتماعية والاقتصادية لقطاع الثروة الحيوانية ؛ والآثار البيئية للثروة الحيوانية مثل إنتاج وإدارة النفايات وانبعاثات غازات الدفيئة والتغيير في استخدام الأراضي المتعلقة بالثروة الحيوانية ؛ والتحقيقات واسعة النطاق في مجال الصحة العامة والأوبئة. قدمت قاعدة بيانات الثروة الحيوانية الشبكية في العالم (GLW)، التي تم إنتاجها في عام 2007، نماذج لكثافة الثروة الحيوانية في العالم، تم تعديلها لتتناسب مع التقديرات الوطنية الرسمية (FAOSTAT) للسنة المرجعية 2005، بدقة مكانية تبلغ 3 دقائق من القوس (حوالي 5×5 كم عند خط الاستواء). عززت التحسينات المنهجية الأخيرة هذه التوزيعات بشكل كبير: تم جمع إحصاءات أكثر حداثة وتفصيلاً عن الثروة الحيوانية على المستوى دون الوطني ؛ وتم استخدام مجموعة جديدة أعلى دقة من متغيرات التنبؤ ؛ وتمت مراجعة الإجراء التحليلي وتوسيعه ليشمل تقييمًا أكثر منهجية لدقة النموذج وتمثيل أوجه عدم اليقين المرتبطة بالتنبؤات. تصف هذه الورقة النهج الحالي بالتفصيل وتقدم خرائط توزيع عالمية جديدة بدقة 1 كم للماشية والخنازير والدجاج، وخريطة توزيع جزئية للبط. تتاح هذه الطبقات الرقمية للجمهور عبر موقع Livestock Geo - Wiki (http://www.livestock.geo-wiki.org)، وكذلك خرائط أنواع الماشية الأخرى عند إنتاجها.

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