Exatidão dos dados do sistema de vigilância epidemiológica da malária no estado do Amazonas

The Epidemiological Surveillance System for Malaria (SIVEP-Malaria) is the Brazilian governmental program that registers all information about compulsory reporting of detected cases of malaria by all medical units and medical practitioners. The objective of this study is to point out the main sources of errors in the SIVEP-Malaria database by applying a data cleaning method to assist researchers about the best way to use it and to report the problems to authorities. The aim of this study was to assess the quality of the data collected by the surveillance system and its accuracy. The SIVEP-Malaria data base used was for the state of Amazonas, Brazil, with data collected from 2003 to 2014. A data cleaning method was applied to the database to detect and remove erroneous records. It was observed that the collecting procedure of the database is not homogeneous among the municipalities and over the years. Some of the variables had different data collection periods, missing data, outliers and inconsistencies. Variables depending on the health agents showed a good quality but those that rely on patients were often inaccurate. We showed that a punctilious preprocessing is needed to produce statistically correct data from the SIVEP-Malaria data base. Fine spatial scale and multi-temporal analysis are of particular concern due to the local concentration of uncertainties and the data collecting seasonality observed. This assessment should help to enhance the quality of studies and the monitoring of the use of the SIVEP database.O Sistema de Vigilância Epidemiológica de Malária (SIVEP-Malária) é um programa governamental brasileiro que arquiva automaticamente todas as informações sobre casos de malária registrados em todas as unidades de saúde e consultórios medicos. O objetivo deste estudo foi avaliar a qualidade dos dados coletados pelo sistema de vigilância e sua precisão. Foram utilizados os dados do SIVEP-Malária para o estado do Amazonas, Brasil, de 2003 a 2014. Um método de limpeza de dados foi aplicado para detectar e remover registros errôneos. Observamos que a coleta de dados não é homogênea entre os municipios e ao longo dos anos. Algumas variaveis tinham diferentes padrões de coleta, falta de dados, dados discrepantes e inconsistências. Dados que dependem do agente de saúde possuem boa qualidade mas aqueles que dependem dos pacientes são frequentemente imprecisos. Mostramos que um pre-processamento meticuloso é necessário para produzir dados estatisticamente corretos a partir do SIVEP-Malária. Analises em escala espacial detalhada ou multi-temporais são particularmente afetadas devido à concentração local de incertezas e a sazonalidade observada na coleta de dados. Esta avaliação deve auxiliar a melhorar os estudos e monitoramentos que fazem uso dos dados do SIVEP

Study of the relationship between the hydrological dynamics and malaria in the State of Amazonas in the Brazilian Amazon

Le paludisme trouve dans la région amazonienne des conditions favorables à la transmission de la maladie, par un moustique vecteur qui est essentiellement l’Anophèles darlingi, se reproduisant en milieu aquatique. Ce moustique est connu pour sa grande adaptabilité aux conditions environnementales et en Amazonie, il est réputé être plus spécialement trouvé près des fleuves d’eau blanche (chargée en sédiments). La relation entre la présence du moustique et la couleur des eaux a été peu étudiée à l’échelle régionale. La présente étude a utilisé 11 années d’images MODIS à 250 m de résolution et un pas de temps mensuel, dont il a été extrait un indicateur de réflectance des eaux. D’autre part, ce travail de thèse exploite les données épidémiologiques du système de surveillance épidémiologique brésilien du paludisme. L’objectif principal est d’évaluer les corrélations entre la dynamique saisonnière de la réflectance des eaux et l’incidence parasitaire du paludisme sur différentes zones de l’État d’Amazonas afin notamment de comprendre l’influence de la couleur des eaux sur la présence du vecteur et donc la transmission du paludisme. Les résultats obtenus permettent de montrer que les notifications concernant le paludisme dans l’Etat d’Amazonas sont en effet corrélées aux eaux blanches, mais que les eaux noires ont aussi une corrélation avec l’incidence du paludisme, d’une façon sensiblement différente, à la fois dans le temps et dans l’espace. Ces résultats pourront être utiles à l’amélioration de notre compréhension des risques épidémiologiques dans cette région ainsi qu’à la mise en place de programme de surveillance plus efficaces, même si le facteur étudié, i.e. la couleur des eaux, n’est qu’un facteur parmi beaucoup d’autres qui influent sur le risque d’infection paludéen.Malaria in the Amazon region finds favorable conditions for the transmission of the disease by the mosquito vector Anopheles darlingi, which breeds in water. This mosquito is known for its great adaptability to environmental conditions. In the Amazon it is deemed to be especially found near rivers of white water (loaded with sediments). The relationship between the presence of the mosquito and water color has been little studied regionally. This study used 11 years of MODIS 250 m resolution and a monthly time base, which enable extracting a reflectance index of water. Secondly, this thesis uses the epidemiological data of the Brazilian system of epidemiological surveillance of malaria. The main objective is to evaluate the correlation between the seasonal dynamics of the reflectance of water and parasite incidence of malaria on different areas of the State of Amazonas in particular to understand the influence of water color on the presence of the vector and therefore the transmission of malaria. The results obtained show that notifications of malaria in the state of Amazonas are indeed correlated with white water, but the black water also have a correlation with the incidence of malaria, a substantially different way, since in the former case, the correlation is related to the flood, while in the case of black water, the presence of Anopheles and the flood are disconnected. These results may be useful in improving our understanding of epidemiological risks in the region and the establishment of more effective compliance program, even if the factor of interest, ie the color of the water is one factor among many others that affect the risk of malaria infection

Etude des relations entre la luminosité de l'eau et le paludisme dans l’État d’Amazonas en Amazonie brésilienne

Malaria in the Amazon region finds favorable conditions for the transmission of the disease by the mosquito vector Anopheles darlingi, which breeds in water. This mosquito is known for its great adaptability to environmental conditions. In the Amazon it is deemed to be especially found near rivers of white water (loaded with sediments). The relationship between the presence of the mosquito and water color has been little studied regionally. This study used 11 years of MODIS 250 m resolution and a monthly time base, which enable extracting a reflectance index of water. Secondly, this thesis uses the epidemiological data of the Brazilian system of epidemiological surveillance of malaria. The main objective is to evaluate the correlation between the seasonal dynamics of the reflectance of water and parasite incidence of malaria on different areas of the State of Amazonas in particular to understand the influence of water color on the presence of the vector and therefore the transmission of malaria. The results obtained show that notifications of malaria in the state of Amazonas are indeed correlated with white water, but the black water also have a correlation with the incidence of malaria, a substantially different way, since in the former case, the correlation is related to the flood, while in the case of black water, the presence of Anopheles and the flood are disconnected. These results may be useful in improving our understanding of epidemiological risks in the region and the establishment of more effective compliance program, even if the factor of interest, ie the color of the water is one factor among many others that affect the risk of malaria infection.Le paludisme trouve dans la région amazonienne des conditions favorables à la transmission de la maladie, par un moustique vecteur qui est essentiellement l’Anophèles darlingi, se reproduisant en milieu aquatique. Ce moustique est connu pour sa grande adaptabilité aux conditions environnementales et en Amazonie, il est réputé être plus spécialement trouvé près des fleuves d’eau blanche (chargée en sédiments). La relation entre la présence du moustique et la couleur des eaux a été peu étudiée à l’échelle régionale. La présente étude a utilisé 11 années d’images MODIS à 250 m de résolution et un pas de temps mensuel, dont il a été extrait un indicateur de réflectance des eaux. D’autre part, ce travail de thèse exploite les données épidémiologiques du système de surveillance épidémiologique brésilien du paludisme. L’objectif principal est d’évaluer les corrélations entre la dynamique saisonnière de la réflectance des eaux et l’incidence parasitaire du paludisme sur différentes zones de l’État d’Amazonas afin notamment de comprendre l’influence de la couleur des eaux sur la présence du vecteur et donc la transmission du paludisme. Les résultats obtenus permettent de montrer que les notifications concernant le paludisme dans l’Etat d’Amazonas sont en effet corrélées aux eaux blanches, mais que les eaux noires ont aussi une corrélation avec l’incidence du paludisme, d’une façon sensiblement différente, à la fois dans le temps et dans l’espace. Ces résultats pourront être utiles à l’amélioration de notre compréhension des risques épidémiologiques dans cette région ainsi qu’à la mise en place de programme de surveillance plus efficaces, même si le facteur étudié, i.e. la couleur des eaux, n’est qu’un facteur parmi beaucoup d’autres qui influent sur le risque d’infection paludéen

Satellite based oceanic monitoring around Reunion Island for the years 2003 to 2017

International audienceCoastal waters are structurally and functionally diverse hotspots of marine biodiversity. In La Reunion Island those ecosystems are characterized by frequent disturbances. Severe cyclonic storms, increasing human activity and land-use change cause multiple effects including chemical and biological pollution as well as physical destruction along the coast line. In addition, ongoing climatic changes affects marine ecosystems. In order to characterize the spatial and temporal evolution of the coastal waters around La Reunion Island we investigated optical characteristics of several sea water quality parameters. Those include the diffuse attenuation coefficient at 490 nm (Kd490), particulate organic and inorganic carbon (POC, PIC), chlorophyll a concentration and night time as well as day sea surface temperature (NSST, SST). In this study, water quality indicators were derived from daily satellite imagery data from the Moderate Resolution Imaging Spectroradiometer (MODIS) in a spatial resolution of ≈ 2 km for the years 2003 to 2017. SST around La Reunion increased reaching +1◦C in the south of the research area in 14 years. Water turbidity (Kd490), POC and chlorophyll a show high intercorrelations and indicate the presence of living material (phyto- and zooplankton, bacteria). They exhibit decreasing trends over the course of our investigation. The absolute concentrations as well as the coefficients of variation are elevated along the island’s rainy eastern coastline which indicates the presence of a dynamic oceanic ecosystem. CaCO3 (PIC) concentrations are highest in the shallow waters of the western lagoons where it’s concentration decreased by an average of 0,00009 mol m-3 in the marine reserve. Potential underlying reasons are coral bleaching or macrophytic algae decrease. The ocean productivity is highest in an area of 18 km in diameter around the island. For the years 2003 to 2017, it decreased at the eastern coast while the temperature rose. This phenomenon may influence fishing rates as well as the behavior and migrations of marine megafauna. Future conditions might promote biological invasions. The coastal ecosystems are changing with the climate. It is important to assess and improve the monitoring of the following stages of this phenomenon to help preserve human life quality and native biodiversity

Parallel Acquisition of Airborne and Satellite Nighttime Datasets over Oldenburg

In this paper we describe the first parallel nighttime remote sensing data acquisition from airplane and satellite. DLR planned a nighttime acquisition in June 2022 over Oldenburg with an aircraft from its own research fleet carrying the 3K camera system. In the scope of a science proposal it was possible to obtain nearly in parallel nighttime satellite images from the Jilin-1 satellite imagery products of Changguang Satellite Technology Co., Ltd. provided by HEAD Aerospace. The result of this cooperation is for the first time a direct comparison of a parallel aerial and satellite nighttime acquisition of a city. This paper presents as background the recording of night lights for energy system analysis, the prerequisites and processing of the data sets as well as a comparison of the different types of data. Furthermore, challenges which arose during this unique dataset generation are discussed. After a comparison of the data sets and their results, lessons learned and a summary of the advantages and disadvantages of each dataset concludes the article

Une méthode pour déterminer le sous-ensemble optimal d'attributs pour la classification orientée objet d'images satellitaires

International audienceIn GEOBIA, remote sensing experts benefit from a large spectrum of characteristics to interpret images (spectral information, texture, geometry, spatial relations, etc). However, the quality of a classification is not always increased by inserting a higher number of features. The experts are then used to define classification rules based on a laborious "trial-and-error" process. In this paper, we propose a methodology to automatically determine an optimal subset of features for discriminating features. This process assumes that a reference land cover map is available. The method consists in ranking the features according to their potential for discriminating two classes. This task was performed thanks to the Support Vector Machine-Ranking Feature Extraction (SVM-RFE) algorithm. Then, it consists in training and validating a classification algorithm (SVM), with an increasing number of features: first only the best-ranked feature is included in the classifier, then the two best-ranked features, etc., until all the N features are included. The objective is to analyze how the quality of the classification evolves according to the numbers of features used. The optimal subset of features is finally determined through the analysis of the Akaike information criterion. The methodology was tested on two classes of pastures in a study area located in the Amazon. Two features were considered as sufficient to discriminate both classes

A methodology for determining optimal feature subset for classification in object-based image analysis

International audienc