Identifying West Nile Virus Risk Areas: The Dynamic Continuous-Area Space-Time System Paper by S. C. Ahearn, S. Grady, M. Merlino and C. N. Theophilides. 2002. American Journal of Epidemiology, 157(9):843-854 Presented by Andrea Krutulis, Environmental Studies, GEOG370, February 26, 2008
Identifying High-Risk Areas Problem: To develop an area-based model for NYC to identify areas where virus activity could lead to human infection in order to prepare for control efforts. Previous studies found that there is a correlation between the number of dead birds and human infection. Hypothesis: By interpreting area and space-time data, a system can be developed to spatially monitor risk of human infection.
Relating Bird Mortality to Spatial Risk Site: New York City in 2001 Used data of areas with high numbers of dead birds Developed a dynamic continuous-area space-time system which interpolates data to determine correlations of events in space and time to determine a high risk area of human infection Calibrated their model using data from the previous year (2000) and tested the model in 2001
Results Model was effective in determining high risk areas in New York City up to 13 days before human infection in five of seven cases
Conclusion Concluded that the model was effective for use in the New York City Department of Health for preventative and control efforts of West Nile Virus. Criticism: Difficult to understand