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Exploratory spatial analysis of Lyme disease in Texas –what can we learn from the reported cases?
BACKGROUND: Lyme disease (LD) is a tick-borne zoonotic illness caused by the bacterium Borrelia burgdorferi. Texas is considered a non-endemic state for LD and the spatial distribution of the state’s reported LD cases is unknown. METHODS: We analyzed human LD cases reported to the Texas Department o...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4575478/ https://www.ncbi.nlm.nih.gov/pubmed/26386670 http://dx.doi.org/10.1186/s12889-015-2286-0 |
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author | Szonyi, Barbara Srinath, Indumathi Esteve-Gassent, Maria Lupiani, Blanca Ivanek, Renata |
author_facet | Szonyi, Barbara Srinath, Indumathi Esteve-Gassent, Maria Lupiani, Blanca Ivanek, Renata |
author_sort | Szonyi, Barbara |
collection | PubMed |
description | BACKGROUND: Lyme disease (LD) is a tick-borne zoonotic illness caused by the bacterium Borrelia burgdorferi. Texas is considered a non-endemic state for LD and the spatial distribution of the state’s reported LD cases is unknown. METHODS: We analyzed human LD cases reported to the Texas Department of State Health Services (TX-DSHS) between 2000 and 2011 using exploratory spatial analysis with the objective to investigate the spatial patterns of LD in Texas. Case data were aggregated at the county level, and census data were used as the population at risk. Empirical Bayesian smoothing was performed to stabilize the variance. Global Moran’s I was calculated to assess the presence and type of spatial autocorrelation. Local Indicator of Spatial Association (LISA) was used to determine the location of spatial clusters and outliers. RESULTS AND DISCUSSION: There was significant positive spatial autocorrelation of LD incidence in Texas with Moran’s I of 0.41 (p = 0.001). LISA revealed significant variation in the spatial distribution of human LD in Texas. First, we identified a high-risk cluster in Central Texas, in a region that is thought to be beyond the geographical range of the main vector, Ixodes scapularis. Second, the eastern part of Texas, which is thought to provide the most suitable habitat for I. scapularis, did not appear to be a high-risk area. Third, LD cases were reported from several counties in western Texas, a region considered unsuitable for the survival of Ixodes ticks. CONCLUSIONS: These results emphasize the need for follow-up investigations to determine whether the identified spatial pattern is due to: clustering of misdiagnosed cases, clustering of patients with an out-of state travel history, or presence of a clustered unknown enzootic cycle of B. burgdorferi in Texas. This would enable an improved surveillance and reporting of LD in Texas. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12889-015-2286-0) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-4575478 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-45754782015-09-20 Exploratory spatial analysis of Lyme disease in Texas –what can we learn from the reported cases? Szonyi, Barbara Srinath, Indumathi Esteve-Gassent, Maria Lupiani, Blanca Ivanek, Renata BMC Public Health Research Article BACKGROUND: Lyme disease (LD) is a tick-borne zoonotic illness caused by the bacterium Borrelia burgdorferi. Texas is considered a non-endemic state for LD and the spatial distribution of the state’s reported LD cases is unknown. METHODS: We analyzed human LD cases reported to the Texas Department of State Health Services (TX-DSHS) between 2000 and 2011 using exploratory spatial analysis with the objective to investigate the spatial patterns of LD in Texas. Case data were aggregated at the county level, and census data were used as the population at risk. Empirical Bayesian smoothing was performed to stabilize the variance. Global Moran’s I was calculated to assess the presence and type of spatial autocorrelation. Local Indicator of Spatial Association (LISA) was used to determine the location of spatial clusters and outliers. RESULTS AND DISCUSSION: There was significant positive spatial autocorrelation of LD incidence in Texas with Moran’s I of 0.41 (p = 0.001). LISA revealed significant variation in the spatial distribution of human LD in Texas. First, we identified a high-risk cluster in Central Texas, in a region that is thought to be beyond the geographical range of the main vector, Ixodes scapularis. Second, the eastern part of Texas, which is thought to provide the most suitable habitat for I. scapularis, did not appear to be a high-risk area. Third, LD cases were reported from several counties in western Texas, a region considered unsuitable for the survival of Ixodes ticks. CONCLUSIONS: These results emphasize the need for follow-up investigations to determine whether the identified spatial pattern is due to: clustering of misdiagnosed cases, clustering of patients with an out-of state travel history, or presence of a clustered unknown enzootic cycle of B. burgdorferi in Texas. This would enable an improved surveillance and reporting of LD in Texas. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12889-015-2286-0) contains supplementary material, which is available to authorized users. BioMed Central 2015-09-19 /pmc/articles/PMC4575478/ /pubmed/26386670 http://dx.doi.org/10.1186/s12889-015-2286-0 Text en © Szonyi et al. 2015 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Article Szonyi, Barbara Srinath, Indumathi Esteve-Gassent, Maria Lupiani, Blanca Ivanek, Renata Exploratory spatial analysis of Lyme disease in Texas –what can we learn from the reported cases? |
title | Exploratory spatial analysis of Lyme disease in Texas –what can we learn from the reported cases? |
title_full | Exploratory spatial analysis of Lyme disease in Texas –what can we learn from the reported cases? |
title_fullStr | Exploratory spatial analysis of Lyme disease in Texas –what can we learn from the reported cases? |
title_full_unstemmed | Exploratory spatial analysis of Lyme disease in Texas –what can we learn from the reported cases? |
title_short | Exploratory spatial analysis of Lyme disease in Texas –what can we learn from the reported cases? |
title_sort | exploratory spatial analysis of lyme disease in texas –what can we learn from the reported cases? |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4575478/ https://www.ncbi.nlm.nih.gov/pubmed/26386670 http://dx.doi.org/10.1186/s12889-015-2286-0 |
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