Comparison of enzootic risk measures for predicting West Nile disease, Los Angeles, California, USA, 2004-2010.

In Los Angeles, California, USA, 2 epidemics of West Nile virus (WNV) disease have occurred since WNV was recognized in 2003. To assess which measure of risk was most predictive of human cases, we compared 3 measures: the California Mosquito-Borne Virus Surveillance and Response Plan Assessment, the vector index, and the Dynamic Continuous-Area Space-Time system. A case-crossover study was performed by using symptom onset dates from 384 persons with WNV infection to determine their relative environmental exposure to high-risk conditions as measured by each method. Receiver-operating characteristic plots determined thresholds for each model, and the area under the curve was used to compare methods. We found that the best risk assessment model for human WNV cases included surveillance data from avian, mosquito, and climate sources.

Temporal connections between Culex tarsalis abundance and transmission of western equine encephalomyelitis virus in California.

Definition of targets for vector control requires an understanding of the relationship between vector abundance and the intensity of arbovirus transmission. Using an extensive surveillance dataset with observations from sentinel chicken flocks and mosquito traps paired in time and space, hierarchical autoregressive logistic regression models were developed to predict the probability of seroconversion in chickens for western equine encephalomyelitis virus (WEEV) based on the relative abundance of the principal vector, Culex tarsalis. After adjustments for confounders, the abundance of Cx. tarsalis 29-42 d before the date of chicken sampling was credibly associated with the risk of WEEV transmission in both the Central and Coachella Valleys, and a doubling of relative Cx. tarsalis abundance was associated with a 58% increase in the odds of seroconversion. The critical time windows identified in our study highlight the need for surveillance of vector populations and forecasting models to guide proactive vector control measures before the detection of transmission to sentinel chickens.