@misc{10481/64985,
year = {2020},
month = {9},
url = {http://hdl.handle.net/10481/64985},
abstract = {In this paper, we propose presenting a solution based on socio-epidemiological variables of
tuberculosis, considering a clustering with spatial/geographical constraints; and, determine a value of
alpha that increases spatial contiguity without significantly deteriorating the quality of the solution based
on the variables of interest, i.e. those of the feature space. For the application of Ward’s hierarchical
clustering method, two dissimilarity matrices were calculated, the first provides the dissimilarities in
the feature space calculated from the socio-epidemiological variables D0 and the second provides the
dissimilarities in the calculated constraints space from the geographical distances D1, together with
an a mixing parameter and the non-uniform weight w assigned to the calculation of the dissimilarity
matrix defined by the standardized incidence ratio (SIR) of TB and that contributed significantly to the
increase in clarity, both from a spatial and socio-epidemiological point of view. The method is shown
to be feasible in epidemiological studies in the joint understanding of factors of different dimensions,
aggregated from a spatial perspective. It is analysis tool that allows making a better understanding of the
socio-epidemiological reality of the municipality.},
publisher = {Mdpi},
keywords = {Ward-like algorithm},
keywords = {Spatial constraints},
keywords = {Measure of risk},
keywords = {Tuberculosis},
keywords = {State of Paraíba, Brazil},
title = {Hierarchical Clustering with Spatial Constraints and Standardized Incidence Ratio in Tuberculosis Data},
doi = {10.3390/math8091478},
author = {Camêlo Aguiar, Dalila and Gutiérrez Sánchez, Ramón and Silva Camêlo, Edwirde Luiz},
}