@InProceedings{SilvaPiGuCaSoGoGu:2017:AnCeEp,
               author = "Silva, Laryssa de Cassia Tork da and Pinheiro, Alcione Ferreira 
                         and Guimar{\~a}es, Luis Henrique Rocha and Catete, 
                         Cl{\'{\i}}stenes Pamplona and Soffiatti, Nelson Fernando Lisboa 
                         and Gon{\c{c}}alves, Nelson Veiga and Guimar{\~a}es, Ricardo 
                         Jos{\'e} de Paula Souza e",
                title = "An{\'a}lise do cen{\'a}rio epidemiol{\'o}gico da mal{\'a}ria 
                         no munic{\'{\i}}pio de Melga{\c{c}}o-PA a partir da 
                         aplica{\c{c}}{\~a}o do geoprocessamento",
            booktitle = "Anais...",
                 year = "2017",
               editor = "Gherardi, Douglas Francisco Marcolino and Arag{\~a}o, Luiz 
                         Eduardo Oliveira e Cruz de",
                pages = "6482--6489",
         organization = "Simp{\'o}sio Brasileiro de Sensoriamento Remoto, 18. (SBSR)",
            publisher = "Instituto Nacional de Pesquisas Espaciais (INPE)",
              address = "S{\~a}o Jos{\'e} dos Campos",
             abstract = "In recent years, geotechnologies have become important tools for 
                         analyzing the epidemiological distribution of events. Thus, based 
                         on the use of geoprocessing, this study aims to promote a 
                         spatiotemporal analysis of malaria in Melga{\c{c}}o-PA between 
                         2009 and 2013. First, the epidemiological summary was debugged by 
                         the probable location of the infection of malaria cases in the 
                         System Epidemiological Surveillance of Malaria (Malaria-Sivep). 
                         Following was held georeferencing of 23 localities, where 1,129 
                         cases occurred, using a Global Positioning Receiver (GPS). 
                         Thereafter, the data were aggregated to the IBGE cartographic 
                         databases and the Landsat-TM images. Finally, visual expressions 
                         were created by applying the kernel density estimator for each 
                         year of the period studied. The most affected regions were the 
                         municipal seat and rural localities of the municipality, Ilha do 
                         Laguna and Cidade. It was not observed the existence of a definite 
                         pattern of distribution, because despite the existence of 
                         clusters, the cases were found in several areas of the county. 
                         However, most of the geo-referenced probable infection points were 
                         distributed at the margins of flooded areas, with steady water, 
                         which is favorable to the dissemination of anopheles vectors. This 
                         flooded area is habited by a low income population, predominantly 
                         living in wood dwellings, facilitating the entrance of mosquitos 
                         and therefore allowing the vector-man contact. This study allowed 
                         the dimensioning of the epidemiological scenario of this disease, 
                         indicating the location of housing, low conditions of living , and 
                         housing as main variables responsible for the risk of acquiring 
                         the disease.",
  conference-location = "Santos",
      conference-year = "28-31 maio 2017",
                 isbn = "978-85-17-00088-1",
                label = "60208",
             language = "pt",
         organisation = "Instituto Nacional de Pesquisas Espaciais (INPE)",
                  ibi = "8JMKD3MGP6W34M/3PSMD27",
                  url = "http://urlib.net/ibi/8JMKD3MGP6W34M/3PSMD27",
           targetfile = "60208.pdf",
                 type = "Sa{\'u}de",
        urlaccessdate = "27 abr. 2024"
}