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 of...
| Autores principales: | , , , , |
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| Formato: | Journal Article |
| Lenguaje: | Inglés |
| Publicado: |
Springer
2015
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| Materias: | |
| Acceso en línea: | https://hdl.handle.net/10568/68591 |
| _version_ | 1855535717224022016 |
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| author | Szonyi, Barbara Srinath, I. Esteve-Gassent, M. Lupiani, B. Ivanek, R. |
| author_browse | Esteve-Gassent, M. Ivanek, R. Lupiani, B. Srinath, I. Szonyi, Barbara |
| author_facet | Szonyi, Barbara Srinath, I. Esteve-Gassent, M. Lupiani, B. Ivanek, R. |
| author_sort | Szonyi, Barbara |
| collection | Repository of Agricultural Research Outputs (CGSpace) |
| 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. |
| format | Journal Article |
| id | CGSpace68591 |
| institution | CGIAR Consortium |
| language | Inglés |
| publishDate | 2015 |
| publishDateRange | 2015 |
| publishDateSort | 2015 |
| publisher | Springer |
| publisherStr | Springer |
| record_format | dspace |
| spelling | CGSpace685912024-05-01T08:18:59Z Exploratory spatial analysis of Lyme disease in Texas—What can we learn from the reported cases? Szonyi, Barbara Srinath, I. Esteve-Gassent, M. Lupiani, B. Ivanek, R. health animal health zoonoses 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. 2015-12 2015-10-20T11:11:44Z 2015-10-20T11:11:44Z Journal Article https://hdl.handle.net/10568/68591 en Open Access Springer Szonyi, B., Srinath, I., Esteve-Gassent, M., Lupiani, B. and Ivanek, R. 2015. Exploratory spatial analysis of Lyme disease in Texas—What can we learn from the reported cases? BMC Public Health 15:924. |
| spellingShingle | health animal health zoonoses Szonyi, Barbara Srinath, I. Esteve-Gassent, M. Lupiani, B. Ivanek, R. 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 | health animal health zoonoses |
| url | https://hdl.handle.net/10568/68591 |
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