County Based Analysis of West Nile Virus in Texas: Distribution Patterns and Drivers

Background:

West Nile Virus (WNV) was first detected in New York City in 1999, since then it has spread westwards. WNV is transmitted by infected mosquitoes that acquire the virus by feeding on infected birds. Humans and horses are incidental hosts

Human transmission is dependent on prevalence and feeding patterns of mosquitoes. Local ecology and human behavior influences exposure to mosquitoes. Identification of high risk areas will help to implement prevention strategies We looked into epidemiology and patterns of WNV disease transmission in all counties of Texas from 2012 to 2014

Methods:

County-level human WNV cases were analyzed using tabulate data from surveillance reports of Texas Health Services (2012-2014) along with climatic and demographic data. Total number of WNV cases in Texas 2002-2014 were obtained from Center for diseases control. Non-spatial and spatial data were combined for analysis using ArcGIS to find correlation and trends . Variables included avian cases, equine, human, human West Nile neuroinvasive disease, presumptive viremic blood donors, precipitation, temperature and population density. Getis-Ord procedures were used to detect statistically significant CA-CDI hot spots using population density and WNV cases. Relationship between population density and WNV cases were plotted and Pearson correlation calculated using Minitab software.

Results:

Hotspot analysis using human cases and population density showed distinguishable patterns. Counties with high population density had higher number of viremic blood donors and West Nile neuroinvasive disease. There is clustering of human and equine cases. Lower precipitation was the most important variable predictor; precipitation and temperature alone could explain the pattern of spatial variability. Time-series analysis showed WNV cases increase with time, resulting in high mortality.

Conclusion:

Preventive techniques must be implemented with special focus on areas with high population density and at risk areas based on precipitaion and temperature. Monitoring equine populations susceptible to WNV disease within close proximity to urban population might be useful for predicting disease risk in humans.