Location: Mosquito and Fly ResearchTitle: Spatio-temporal patterns of Epizootic Hemorrhagic Disease (EHD) occurrence in the Continental USA (1980-2010)) Author
|Linthicum, Kenneth - Ken|
Submitted to: Meeting Abstract
Publication Type: Abstract Only
Publication Acceptance Date: 12/30/2013
Publication Date: N/A
Citation: N/A Interpretive Summary:
Technical Abstract: Background: Statement of the hypothesis or research question. Epizootic Hemorrhagic Disease (EHD) is a Culicoides insect-borne viral disease of wild and domestic ruminants commonly reported in the USA. While the severity of disease varies by geographic location, mortality rates can be as high as 90% in immunologically naïve white-tailed deer populations. To better understand the current distribution and the potential of incursion to southwestern Canada, we examined the spatio-temporal movement of EHD by quantifying disease foci over a period of thirty years (1981-2010). Methods: An explanation of the study design and experimental methods used. International collaboration with the USDA provided definitive EHD event data for the continental USA. The dataset consists of georeferenced virus isolations available at the county level by collection date. To quantify spatio-temporal patterns of the disease, a retrospective space-time permutation model (SaTScan TM) was implemented. Simulations were performed with 999 Monte Carlo replications to test for significance under a variety of maximum spatial cluster sizes based on percent population at risk (1, 5, 7, and 10%). Representation of results was performed using geographic information (GIS) software. Results: A concise summary of the major findings of the experiment or study. Sufficient data must be provided to permit evaluation by the reviewers and public reading the abstracts. Results of the space-time permutation model revealed significant clusters of EHD across a diagonal band spanning from the southeastern USA, northwest towards the Upper Great Plains. The most likely significant cluster was centered in Iowa, with a total of 22 positive counties involved between September and October of 1998. This remained the single most consistent significant cluster throughout all model simulations. Multiple EHD foci were also identified corresponding to the widespread outbreaks of both 2002 and 2007. Clusters identified were generally stable throughout all simulations. Overlapping clusters were observed over multiple years, suggesting that further investigation of these clusters could provide a better understanding of the ecological factors responsible for the spatio-temporal clustering and variability of EHD. Conclusion: Summary of the overall findings and importance of the study. Improved knowledge of the spatio-temporal distribution of EHD is critical to classifying areas of greater disease transmission risk and assisting regulatory authorities in the development of targeted disease surveillance strategies. Results of this study can be used to identify environmental factors associated with disease foci and in the development of an ecologically-based risk model that could be adapted and implemented to other vector-borne diseases of global concern.