@MastersThesis{Teixeira:2022:FaAmSo,
author = "Teixeira, Ra{\'{\i}}ssa Caroline dos Santos",
title = "An{\'a}lise espa{\c{c}}o-temporal da leptospirose: fatores
ambientais e sociodemogr{\'a}ficos em dois munic{\'{\i}}pios do
baixo Tocantins no Par{\'a}, Brasil",
school = "Instituto Nacional de Pesquisas Espaciais (INPE)",
year = "2022",
address = "S{\~a}o Jos{\'e} dos Campos",
month = "2021-12-17",
keywords = "sa{\'u}de p{\'u}blica, epidemiologia espacial, leptospirose,
geoprocessamento, sensoriamento remoto, public health, spatial
epidemiology, leptospirosis, geoprocessing, remote sensing.",
abstract = "As doen{\c{c}}as de veicula{\c{c}}{\~a}o h{\'{\i}}drica
est{\~a}o presentes em todo o mundo e geralmente no Brasil
s{\~a}o associadas a baixas condi{\c{c}}{\~o}es
socioecon{\^o}micas e de saneamento. O uso de dados ambientais
detect{\'a}veis por sensoriamento remoto aliado a t{\'e}cnicas
de geoprocessamento vem crescendo principalmente na {\'a}rea da
epidemiologia espacial. A leptospirose {\'e} uma doen{\c{c}}a
infecciosa que ainda apresenta desafios para seu controle, uma
preocupa{\c{c}}{\~a}o de sa{\'u}de em pa{\'{\i}}ses em
desenvolvimento com infraestrutura sanit{\'a}ria deficiente,
baixas condi{\c{c}}{\~o}es socioecon{\^o}micas e acesso
limitado {\`a} {\'a}gua limpa. Para melhor compreender os
principais fatores associados {\`a} transmiss{\~a}o da
leptospirose em uma regi{\~a}o end{\^e}mica, este estudo aplicou
t{\'e}cnicas estat{\'{\i}}sticas e de geoprocessamento em dois
munic{\'{\i}}pios do estado do Par{\'a}, Brasil - Abaetetuba e
Barcarena - de 2007 a 2019. Os dados epidemiol{\'o}gicos foram
extra{\'{\i}}dos do Sistema de Informa{\c{c}}{\~o}es de
Agravos de Notifica{\c{c}}{\~a}o (SINAN). Os dados
sociodemogr{\'a}ficos e divis{\~o}es geopol{\'{\i}}ticas foram
obtidos do Instituto Brasileiro de Geografia e
Estat{\'{\i}}stica (IBGE). Os dados ambientais foram adquiridos
por meio do Google Earth Engine e s{\~a}o de tr{\^e}s fontes
principais: NASA Shuttle Radar Topography Mission (SRTM); Japan
Aerospace Exploration Agency's (JAXA) e European Centre for
Medium-Range Weather Forecasts (ECMWF). As vari{\'a}veis
inclu{\'{\i}}ram escoamento superficial, temperatura do solo e
do ar e volume de {\'a}gua do solo, e foram pr{\'e}-processadas
tanto no tempo, em m{\'e}dia di{\'a}ria, quanto no
dom{\'{\i}}nio espacial, como a m{\'e}dia em uma {\'a}rea
circular com raio de 10km em torno de cada caso georreferenciado.
Um total de 56 casos positivos de leptospirose foram estudados,
sendo 51 georreferenciados. A an{\'a}lise descritiva caracterizou
o perfil socioepidemiol{\'o}gico dos infectados pela leptospirose
e as an{\'a}lises espaciais mostraram o comportamento da
doen{\c{c}}a no espa{\c{c}}o. As associa{\c{c}}{\~o}es entre a
incid{\^e}ncia de leptospirose e fatores ambientais e
sociodemogr{\'a}ficos foram analisadas por meio de um modelo de
regress{\~a}o linear generalizado. Os resultados evidenciaram
diferentes tend{\^e}ncias anuais dos casos confirmados nos
munic{\'{\i}}pios, e um padr{\~a}o ondulat{\'o}rio interanual
com periodicidade aproximada de 4 anos. Os resultados indicaram
{\'a}reas de risco principalmente nas {\'a}reas urbanas e uma
autocorrela{\c{c}}{\~a}o espacial positiva com um
{\'{\I}}ndice de Moran de 0,372. A caracteriza{\c{c}}{\~a}o
socioepidemiol{\'o}gica mostrou que homens autodeclarados pardos
de 30 a 59 anos foram os mais afetados. O diagn{\'o}stico
laboratorial (62,50%) e interna{\c{c}}{\~a}o (79,25%)
confirmaram a alta necessidade de atendimento hospitalar. Locais
com sinais de roedores (71%), enchentes (57,14%) e lixo (48,21%)
foram os fatores ambientais mais correlacionados {\`a}
doen{\c{c}}a. Dados de sensoriamento remoto e t{\'e}cnicas de
geoprocessamento foram essenciais para identificar {\'a}reas de
risco. A regress{\~a}o estat{\'{\i}}stica evidenciou a
declividade e o lixo como as vari{\'a}veis mais relacionadas.
Este estudo refor{\c{c}}a a import{\^a}ncia da
integra{\c{c}}{\~a}o dos dados de sensoriamento remoto aos
estudos epidemiol{\'o}gicos, e dos investimentos em saneamento e
infraestrutura para prevenir surtos de doen{\c{c}}as,
especialmente as de veicula{\c{c}}{\~a}o h{\'{\i}}drica.
Estudos como este podem ser utilizados para apoio {\`a}s tomadas
de decis{\~a}o na {\'a}rea da sa{\'u}de e na
distribui{\c{c}}{\~a}o de recursos. ABSTRACT: Waterborne
diseases are present all over the world and are generally
associated in Brazil with poor socioeconomic and sanitation
conditions. The use of environmental remote sensing data combined
with geoprocessing techniques has been growing especially in the
spatial epidemiology. Leptospirosis is an infectious disease that
still poses big challenges to its control; a health concern mainly
in developing countries with deficient sanitary infrastructure,
critical socioeconomic conditions and limited clear water
accessibility. In an effort to better understand the main factors
associated with leptospirosis transmission in an endemic region,
this study applied statistical and geoprocessing techniques in two
municipalities of Par{\'a} state, Brazil - Abaetetuba and
Barcarena from 2007 to 2019. The epidemiological data were
acquired from the Information System for Notifiable Diseases
(SINAN). The sociodemographic and geopolitical divisions datasets
were obtained from the Brazilian Institute of Geography and
Statistics (IBGE). The environmental data were acquired by means
of Google Earth Engine and derived from three main sources: NASA
Shuttle Radar Topography Mission (SRTM); Japan Aerospace
Exploration Agency's (JAXA), and European Centre for Medium-Range
Weather Forecasts (ECMWF). Variables included surface runoff, soil
temperature, air temperature and soil water volume. They were
preprocessed both in time - daily averaged, and in spatial domain
- 10km buffer radius averaged around each georeferenced case. A
total of 56 leptospirosis cases were positively evaluated and 51
were georeferenced. Descriptive analysis characterized the
socio-epidemiological profile of those infected with leptospirosis
and spatial analyzes showed the behavior of the disease on the
space. The associations between leptospirosis incidence and
environmental and sociodemographic factors were analyzed via a
generalized linear regression model. Results evidenced different
annual trends of positive notifications for each municipality, and
an inter-annual sigmoidal pattern with a periodicity of
approximately 4 years, with greater values in the first semester.
Results indicated hotspots primarily in urban areas, and a
positive spatial autocorrelation with a Morans Index of 0.372. The
socio-epidemiological characterization evidenced that
self-declared brown men aging 30 to 59 were most affected.
Laboratory diagnosis (62.50%) and hospitalization (79.25%)
confirmed the high demand for hospital care. Locations with signs
of rodents (71%), flooding (57.14%) and garbage (48.21%) were the
most related environmental factors to the disease transmission.
Remote sensing data and geoprocessing techniques were essential to
identify leptospirosis hotspots. The statistical regression
evidenced the surface gradient (slope) and garbage as the most
correlated variables. This study reinforces the importance of
integrating remote sensing data into epidemiological studies and
the investment in sanitation and infrastructure in order to
promote proper healthcare conditions and prevention towards
diseases outbreaks in general. Studies like this can be used to
support decision-making in the health area and in the resources
distribution.",
committee = "Kampel, Silvana Amaral (presidente), and Kampel, Milton
(orientador), and Guimar{\~a}es, Ricardo Jos{\'e} de Paula Souza
e (orientador), and Monteiro, Antonio Miguel Vieira and Gurgel,
Helen da Costa and Leal, Philipe Riskalla",
englishtitle = "Space-temporal analysis of leptospirosis: environmental and
socio-demographic factors in two municipalities of baixo Tocantins
in Par{\'a}, Brazil",
language = "pt",
pages = "86",
ibi = "8JMKD3MGP3W34T/45U95P2",
url = "http://urlib.net/ibi/8JMKD3MGP3W34T/45U95P2",
targetfile = "publicacao.pdf",
urlaccessdate = "03 maio 2024"
}