Statistics Papers
Document Type
Technical Report
Date of this Version
9-11-2014
Publication Source
Journal of the Royal Statistical Society: Series A (Statistics in Society)
Volume
178
Issue
3
Start Page
641
Last Page
658
DOI
10.1111/rssa.12077
Abstract
Maps of the distribution of epidemiological data often ignore surveillance error or possible correlations between missing information and outcomes. We analyse presence–absence data at the household level (12050 points) of a disease‐carrying insect in Mariano Melgar, Peru, collected as part of the Arequipan Ministry of Health's efforts to control Chagas disease. We construct a Bayesian hierarchical model to locate regions that are vulnerable to under‐reporting due to surveillance error, accounting for variability in participation due to infestation status. The spatial correlation in the data allows us to identify relative inspector sensitivity and to elucidate the relationship between participation and infestation. We show that naive estimates of prevalence would be biased by surveillance error and missingness at random assumptions. We validate our results through simulations and observe how randomized inspector assignments may improve prevalence estimates. Our results suggests that bias due to imperfect observations and missingness at random can be assessed and corrected in prevalence estimates of spatially auto-correlated binary variables.
Copyright/Permission Statement
This is the peer reviewed version of the following article: [Hong, A.E., Barbu, C.M., Small, D.S., & Levy, M.Z. (2014). Mapping the Spatial Distribution of a Disease-Transmitting Insect in the Presence of Surveillance Error and Missing Data. Journal of the Royal Statistical Society: Series A 178, no. 3: pp. 641-658], which has been published in final form at http://dx.doi.org/10.1111/rssa.12077. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Use of Self-Archived Versions.
Keywords
Bayesian hierarchical modelling, spatial analysis, statistical epidemiology, surveillance error
Recommended Citation
Hong, A. E., Barbu, C. M., Small, D. S., & Levy, M. Z. (2014). Mapping the Spatial Distribution of a Disease-Transmitting Insect in the Presence of Surveillance Error and Missing Data. Journal of the Royal Statistical Society: Series A (Statistics in Society), 178 (3), 641-658. http://dx.doi.org/10.1111/rssa.12077
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Date Posted: 25 October 2018
This document has been peer reviewed.