Exploratory spatial analysis of Lyme disease in Texas –what can we learn from the reported cases?

BMC Public Health

Research Article

Indumathi Srinath¹  Renata Ivanek²  Blanca Lupiani³  Maria Esteve-Gassent³  Barbara Szonyi⁴ 

[1] Center for Agribusiness Excellence, Tarleton State University, Stephenville, TX, USA;Department of Veterinary Integrative Biosciences, College of Veterinary Medicine and Biomedical Sciences, Texas A&M University, College Station, TX, USA;Department of Veterinary Integrative Biosciences, College of Veterinary Medicine and Biomedical Sciences, Texas A&M University, College Station, TX, USA;Department of Veterinary Pathobiology, College of Veterinary Medicine and Biomedical Sciences, Texas A&M University, College Station, TX, USA;International Livestock Research Institute (ILRI), Box 5689, Addis Ababa, Ethiopia;Department of Veterinary Integrative Biosciences, College of Veterinary Medicine and Biomedical Sciences, Texas A&M University, College Station, TX, USA;

关键词: Borrelia burgdorferi;    Exploratory spatial data analysis;    Lyme disease;    Texas;   

DOI  :  10.1186/s12889-015-2286-0

 received in 2015-04-09, accepted in 2015-09-15,  发布年份 2015

来源: Springer

【 摘 要 】

BackgroundLyme 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.MethodsWe 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 DiscussionThere 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.ConclusionsThese 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.

【 授权许可】

CC BY   
© Szonyi et al. 2015