Open Access
March 2012 Measuring the vulnerability of the Uruguayan population to vector-borne diseases via spatially hierarchical factor models
Hedibert F. Lopes, Alexandra M. Schmidt, Esther Salazar, Mariana Gómez, Marcel Achkar
Ann. Appl. Stat. 6(1): 284-303 (March 2012). DOI: 10.1214/11-AOAS497

Abstract

We propose a model-based vulnerability index of the population from Uruguay to vector-borne diseases. We have available measurements of a set of variables in the census tract level of the 19 Departmental capitals of Uruguay. In particular, we propose an index that combines different sources of information via a set of micro-environmental indicators and geographical location in the country. Our index is based on a new class of spatially hierarchical factor models that explicitly account for the different levels of hierarchy in the country, such as census tracts within the city level, and cities in the country level. We compare our approach with that obtained when data are aggregated in the city level. We show that our proposal outperforms current and standard approaches, which fail to properly account for discrepancies in the region sizes, for example, number of census tracts. We also show that data aggregation can seriously affect the estimation of the cities vulnerability rankings under benchmark models.

Citation

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Hedibert F. Lopes. Alexandra M. Schmidt. Esther Salazar. Mariana Gómez. Marcel Achkar. "Measuring the vulnerability of the Uruguayan population to vector-borne diseases via spatially hierarchical factor models." Ann. Appl. Stat. 6 (1) 284 - 303, March 2012. https://doi.org/10.1214/11-AOAS497

Information

Published: March 2012
First available in Project Euclid: 6 March 2012

zbMATH: 1235.92043
MathSciNet: MR2951538
Digital Object Identifier: 10.1214/11-AOAS497

Keywords: Areal data , Bayesian inference , model comparison , spatial interpolation , spatial smoothing

Rights: Copyright © 2012 Institute of Mathematical Statistics

Vol.6 • No. 1 • March 2012
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