2015
DOI: 10.1590/1413-812320152012.01672015
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Análise espaço-temporal da leishmaniose visceral no estado do Maranhão, Brasil

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Cited by 16 publications
(16 citation statements)
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“…We used a Bayesian model to better define the risk factors for the spread of VL in São Paulo State, integrating data on its vector and hosts, and to predict the distribution and dispersion of the disease over time and space. As we already cited above, zoonotic VL has been spreading in other regions of Brazil outside of São Paulo [ 77 , 24 , 38 ] and in other countries as well [ 21 ]. Extension of our model to other scenarios can offer further insights into the factors influencing the spread of leishmaniasis and other diseases elsewhere.…”
Section: Discussionmentioning
confidence: 99%
“…We used a Bayesian model to better define the risk factors for the spread of VL in São Paulo State, integrating data on its vector and hosts, and to predict the distribution and dispersion of the disease over time and space. As we already cited above, zoonotic VL has been spreading in other regions of Brazil outside of São Paulo [ 77 , 24 , 38 ] and in other countries as well [ 21 ]. Extension of our model to other scenarios can offer further insights into the factors influencing the spread of leishmaniasis and other diseases elsewhere.…”
Section: Discussionmentioning
confidence: 99%
“…Among all the Federal states in Brazil, Maranhão, a state in northeastern Brazil has recorded the highest number of cases of HVL. Between 2000 and 2009, 5389 cases of HLV were registered, with the highest incidence in the Regional health unit of Caxias, which reported 36.1 cases per 100,000 inhabitants [ 36 ].…”
Section: Resultsmentioning
confidence: 99%
“…Many difficulties permeate spatial studies because official data such those available in the SINAN are not always complete due to underreporting [ 31 , 36 ]; little information or incomplete data may leave researchers without denominators to compute the rates and the independent variables to explain the spatial causes possibly associated with morbidity and mortality [ 10 , 38 ]. The techniques used in spatial analysis tools still need to be explored in order to improve their potential to benefit health services [ 26 ].…”
Section: Discussionmentioning
confidence: 99%