Environmental Data Analysis and Remote Sensing for Early Detection of Dengue and Malaria

Malaria and dengue fever are the two most common mosquito-transmitted diseases, leading to millions of serious illnesses and deaths each year. Because the mosquito vectors are sensitive to environmental conditions such as temperature, precipitation, and humidity, it is possible to map areas currently or imminently at high risk for disease outbreaks using satellite remote sensing. In this paper we propose the development of an operational geospatial system for malaria and dengue fever early warning; this can be done by bringing together geographic information system (GIS) tools, artificial neural networks (ANN) for efficient pattern recognition, the best available ground-based epidemiological and vector ecology data, and current satellite remote sensing capabilities. We use Vegetation Health Indices (VHI) derived from visible and infrared radiances measured by satellite-mounted Advanced Very High Resolution Radiometers (AVHRR) and available weekly at 4-km resolution as one predictor of malaria and dengue fever risk in Bangladesh. As a study area, we focus on Bangladesh where malaria and dengue fever are serious public health threats. The technology developed will, however, be largely portable to other countries in the world and applicable to other disease threats. A malaria and dengue fever early warning system will be a boon to international public health, enabling resources to be focused where they will do the most good for stopping pandemics, and will be an invaluable decision support tool for national security assessment and potential troop deployment in regions susceptible to disease outbreaks

Calculs comparés de biodiversité dans quelques forêts de Provence

La biodiversité de la végétation peut être précisément calculée sous forme de quantités d’information selon la théorie éponyme. Diverses facettes de la richesse floristique, de la répartition des fréquences spécifiques, de la structuration spatiale, peuvent ainsi être définies et recevoir une valeur numérique caractérisant leur diversité. Une application est donnée pour un échantillon de placettes forestières installées en PACA (réseau Sylvipaca du CRPF). Il est ainsi démontré que des éclaircies intensives peuvent procurer une biodiversité aussi forte que celle des témoins laissés en vieillissement. Divers cas correspondant aux principaux peuplements de la région sont ainsi étudiés et commentés. Une synthèse régionale est aussi sommairement esquissée, montrant que la diversité entre peuplements différents est très supérieure à celle rencontrée au sein d’une communauté donnée. L’étude de la biodiversité floristique dite ordinaire montre bien que l’intervention des forestiers, telle qu’usuellement pratiquée dans la région, n’a généralement pas d’impact négatif. Bien au contraire dans les peuplements initialement fermés, la sylviculture provoque une mise en lumière favorisant la biodiversité

Early Detection and Monitoring of Malaria

Global Earth Observation Systems of Systems (GEOSS) are bringing vital societal benefits to people around the globe. In this research article, we engage undergraduate students in the exciting area of space exploration to improve the health of millions of people globally. The goal of the proposed research is to place students in a learning environment where they will develop their problem solving skills in the context of a world crisis (e.g., malaria). Malaria remains one of the greatest threats to public health, particularly in developing countries. The World Health Organization has estimated that over one million die of Malaria each year, with more than 80% of these found in Sub-Saharan Africa. The mosquitoes transmit malaria. They breed in the areas of shallow surface water that are suitable to the mosquito and parasite development. These environmental factors can be detected with satellite imagery, which provide high spatial and temporal coverage of the earth\u27s surface. We investigate on moisture, thermal and vegetation stress indicators developed from NOAA operational environmental satellite data. Using these indicators and collected epidemiological data, it is possible to produce a forecast system that can predict the risk of malaria for a particular geographical area with up to four months lead time. This valuable lead time information provides an opportunity for decision makers to deploy the necessary preventive measures (spraying, treated net distribution, storing medications and etc) in threatened areas with maximum effectiveness. The main objective of the proposed research is to study the effect of ecology on human health and application of NOAA satellite data for early detection of malaria

Calculs comparés de biodiversité dans quelques forêts de Provence

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