Padrões e determinantes do uso e cobertura da terra e doenças transmitidas por vetores na região metropolitana de Santarém - PA
Date
2019-04-29Author
http://lattes.cnpq.br/7180510909867481
https://orcid.org/0000-0002-2691-6020
CORRÊA, Jéssica Ariana de Jesus
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This thesis aims to analyze and characterize the relationships between land use and land cover and vector - borne diseases, particularly dengue, leishmaniasis and malaria in the Metropolitan Region of Santarém. For this, functional landscape analysis was used as a methodological framework, using landscape composition metrics and statistical analysis. Three main analyzes were carried out: (1) the spatial patterns of land use and land cover and the factors that determined these patterns were identified between 2004 and 2014. (2) a typology of land use and land use patterns was proposed and it was identified in which patterns occurred the cases of the diseases, in two moments in time, 2012 and 2014, finally it was verified if there are correlations between these patterns and the diseases. (3) it was verified whether and how determinants of land use and land cover influence the number of disease cases between 2012 to 2016. Data from the TerraClass project for the years 2004, 2010, 2012 and 2014 were used to identify the standards and logistic regression analysis to verify the factors that determined these patterns. The determinants were rainfall accumulated in the driest and rainy quarter season, surface temperature, environmental protection areas, human settlements, official roads and highways, population, and extension of water bodies (rivers and lakes), declivity, altitude. The typology of land use pattern and land cover was obtained using a rules-based model and the association with the diseases was performed through statistical analysis Odds ratio. Annual data on dengue, malaria and leishmaniasis were obtained from the SIVEP-malaria database, SINAN and CCZ internal control for the period from 2012 to 2016 per probable site of infection. The spatial unit of analysis were 1 x 1 km² cells that received the presence or absence attributes of the response variables and predictor variables totaling 27,841 cells for the entire RMS area. Finally, a logistic regression was performed between the presence of the diseases and biophysical, political and socioeconomic variables to identify the most important factors for the presence of the cases. Land use and cover presented changes in the spatial pattern, being the most important in the agriculture and urban classes with area gains, which evidenced their expansions from 2004 to 2014, while losses to primary forest areas. The patterns can be explained by a combination of biophysical factors, accessibility measures and spatial policies. The pattern most commonly found in the study area was the pattern of forest class cells (PP04) followed by the mandatory presence pattern of primary forest, secondary vegetation and/or pasture (PP14). However, the most significant patterns for the diseases were those that had the urban class (PP03, PP09 and PP10) and vegetation (PP16). Regarding the determinant factors, although the majority were presented differently among the diseases, in common had surface temperature, presence of settlements, units of conservation and presence of roads, being the latter the most significant being the chances of the presence of diseases higher in cells with presence of roads.
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