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No. of bitstreams: 4 DISSERTACAO_ALMEIDA_RB.pdf: 8387092 bytes, checksum: 22ff11cc36b2994b7ee02afed7979d24 (MD5) carta de encaminhamento Sep 24 2019.pdf: 548838 bytes, checksum: f3f236954c42637dd13eaf99815e2dda (MD5) Ata da defesa Sep 24 2019.pdf: 326214 bytes, checksum: e40e79e2716b59a348eb9f357fef6c77 (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) Previous issue date: 2019-08-22 CAPES - Coordena????o de Aperfei??oamento de Pessoal de N??vel Superior (92)991964641 This research aimed to understand the social and environmental dynamics of malaria morbidity in Manaus. For this, the theoretical basis was used S.A.U. and their respective subsystems: the natural, the built and the social in an attempt to analyze malaria in an integrated way. The data analyzed were: rainfall, air temperature, relative humidity, cloudiness, wind speed and satellite images with the identification of atmospheric systems in the year of 2015. Year chosen for the application of rhythmic analysis, the year in which Manaus recorded the highest number of autochthonous cases. These data were obtained from INMET and CPTEC. We also used data referring to the maximum, minimum and average level of the Negro River, obtained on the website of the Port of Manaus. Malaria data were obtained by SIVEP-MALARIA. Variables from the 2010 IBGE Census were used, such as environmental sanitation, income, schooling and population. Static techniques such as the Quantil technique were applied to identify standard years with malaria cases. Multiple Regression was applied to analyze climatic and hydrological variability with malaria cases. The Median Technique was applied in the construction of socio-environmental indicators and characterize low, medium-low, medium-high or high vulnerability neighborhoods. The results of the Quantiles identified that the years in which the major epidemics occurred were standard dry years followed by standard years of normal rains that could favorably condition the malaria vector. On the temperature, this one also presented tendency to standard years hotter than usual. The variability of the rainfall dynamics showed that malaria occurs predominantly in July and August, months with lower total rainfall, high temperatures and high humidity, low cloudiness with strong performance in days / months with higher peaks of the disease, as it favored the maturation of vector anopheles. During the March and April months, rainfall, predominance of ITCZ, SACU and lines of instabilities occurred in low cases of the disease. The months that had the highest peaks of the disease were May and August, months in which predominantly the ZCIT and MEC systems, respectively. The rainfall and the river level showed a strong correlation and, therefore, a greater explanatory power in the increase of malaria cases. The ENOS variable did not present a strong correlation or explanatory power. However, it should be remembered that the ENSO directly influences the hydrological dynamics, the rainfall regime and temperature variation, variables that presented significant significance in the explanation of the disease cases, thus, it can be said that the ENSO is indirectly influencing the cases of malaria. On the socio-environmental determinants of malaria, identified after the construction of the indicators, showed a strong spatial relationship with the precariousness of environmental sanitation. Because the districts with the highest incidence of diseases, such as Lago Azul, Puraquequara and Tarum??-A??u, also present problems with the sanitation services, enhancing he formation of environments favorable to the vector. About the methodology, S.A.U. was shown as a theoretical and methodological contribution capable of supporting researches that aim to study socio-environmental problems that relate the natural, constructed and social system of a metropolitan city such as Manaus. Esta pesquisa teve como objetivo compreender a din??mica socioambiental sobre a morbidade da mal??ria em Manaus. Para isso, foi utilizado como fundamenta????o te??rica o S.A.U. e seus respectivos subsistemas: o natural, o constru??do e o social na tentativa de analisar de forma integrada a mal??ria. Os dados trabalhados se referem ao per??odo de 2003 a 2017. Sobre os dados clim??ticos, as vari??veis trabalhadas foram: pluviosidade, temperatura do ar, umidade relativa, nebulosidade, velocidade do vento e imagens de sat??lite com a identifica????o dos sistemas atmosf??ricos atuantes no ano de 2015. Ano escolhido para aplica????o da an??lise r??tmica, ano em que Manaus registou o maior n??mero de casos aut??ctones. Estes dados foram obtidos no INMET e CPTEC. Tamb??m foram utilizados dados referentes ?? cota m??xima, m??nima e m??dia do rio Negro, obtidos no site do Porto de Manaus. Os dados de mal??ria foram obtidos pelo SIVEPMAL??RIA. Foram utilizadas vari??veis do Censo de 2010 do IBGE, como saneamento ambiental, renda, escolaridade e popula????o. Foram aplicadas t??cnicas est??ticas como a T??cnica dos Quantis para identificar os anos-padr??o com os casos de mal??ria. Foi aplicada a Regress??o M??ltipla para analisar a variabilidade clim??tica e hidrol??gica com os casos de mal??ria. A T??cnica das Medianas foi aplicada na constru????o dos indicadores socioambientais e caracterizar os bairros com vulnerabilidade baixa, m??dia-baixa, m??dia-alta ou alta. Os resultados dos Quantis identificaram que os anos em que ocorreram as maiores epidemias, foram anos-padr??o tendentes a seco seguidos de anospadr??o de chuvas habituais possam condicionar de forma favor??vel ao vetor da mal??ria. Sobre a temperatura, esta tamb??m apresentou tend??ncia a anos-padr??o mais quentes ao habitual. A variabilidade da din??mica pluviom??trica mostrou que a mal??ria ocorre predominantemente nos meses julho e agosto, meses com menores totais de chuva, temperaturas e umidades elevadas, a baixa nebulosidade com forte atua????o em dias/meses com maiores picos da doen??a, pois favoreceu a matura????o do vetor anopheles. Durante os meses mar??os e abril, os mais chuvosos, predom??nio da com ZCIT, ZCAS e linhas de instabilidades ocorreram baixos casos da doen??a. Os meses que tiveram os maiores picos da doen??a foram maio e agosto, meses em que atuaram predominantemente os sistemas ZCIT e MEC, respetivamente. A pluviosidade e a cota do rio mostraram forte correla????o e, por conseguinte, maior poder de explica????o no aumento dos casos da mal??ria. A vari??vel ENOS n??o apresentou forte correla????o nem poder de explica????o. Todavia, cabe lembrar que o ENOS influencia diretamente na din??mica hidrol??gica, no regime de chuvas e varia????o da temperatura, vari??veis que apresentaram signific??ncia importante na explica????o dos casos da doen??a, deste modo, pode-se dizer que o ENOS est?? influenciando indiretamente nos casos de mal??ria. Sobre os determinantes socioambientais da mal??ria, identificados ap??s a constru????o dos indicadores, mostraram forte rela????o espacial com as precariedades de saneamento ambiental. Pois os bairros que apresentaram maiores incid??ncias de doen??as, como Lago Azul, Puraquequara e Tarum??-A??u, tamb??m apresentam problemas com os servi??os de saneamento, potencializando na forma????o de ambientes prop??cios ao vetor. Sobre a metodologia, o S.A.U. mostrou-se como um aporte te??rico e metodol??gico capaz de fundamentar pesquisas que visam estudar problemas socioambientais, que relacionam o sistema natural constru??do e social de uma cidade metropolitana como Manaus.