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Comparison of Enzootic Risk Measures for Predicting West Nile Disease, Los Angeles, California, USA, 2004–2010 - Vol. 18 No. 8 - August 2012 - Emerging Infectious Disease journal - CDC

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Comparison of Enzootic Risk Measures for Predicting West Nile Disease, Los Angeles, California, USA, 2004–2010 - Vol. 18 No. 8 - August 2012 - Emerging Infectious Disease journal - CDC

Risk Measures for Predicting Urban West Nile Disease, Los Angeles, California, 2004–2010 
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Viruses articles
Volume 18, Number 8–August 2012

Volume 18, Number 8—August 2012

Research

Comparison of Enzootic Risk Measures for Predicting West Nile Disease, Los Angeles, California, USA, 2004–2010

Jennifer L. Kwan, Bborie K. Park, Tim E. Carpenter, Van Ngo, Rachel Civen, and William K. ReisenComments to Author 
Author affiliations: University of California, Davis, California, USA (J.L. Kwan, B.K. Park, T.E. Carpenter, W.K. Reisen); and Los Angeles County Department of Public Health, Los Angeles, California, USA (V. Ngo, R. Civen)
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Abstract

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.
West Nile virus (WNV; family Flaviviridae, genus Flavivirus) is amplified within a mosquito–bird cycle, with tangential transmission to equids and humans (1). Since the introduction of WNV into Los Angeles, California, USA, in 2003, our research (25) has focused on surveillance indicators for enzootic WNV transmission and prediction of human cases. The Greater Los Angeles County Vector Control District (GLACVCD) serves >6 million of the ≈10 million residents of Los Angeles County and conducts year-round surveillance for WNV activity (6). In addition to having a robust surveillance dataset, Los Angeles County is a suitable location for evaluating environmental risk because the large human population enables the sensitive detection of dead birds (7), increases opportunities for human–vector contact, and experienced 2 outbreaks during the study period (6).
We compared the predictive ability of 3 measures of human risk by using time-series graphs, sensitivity, specificity, positive predictive value (PPV), and concordance between human case onset and states of high risk based on enzootic transmission during 2004–2010. We believed that for operational decision support a successful risk measure should correctly 1) identify periods of low risk when few or no cases occur, 2) predict high or increased risk before human cases occur, and 3) identify periods of high risk concurrent with the occurrence of human cases.
The 3 measures of risk we compared were the California Mosquito-Borne Virus Risk Assessment (CMVRA), the vector index, and the Dynamic Continuous-Area Space-Time (DYCAST) system. The CMVRA (8) calculates risk on the basis of ranks of environmental variables for enzootic transmission and is used by health agencies throughout California to measure risk. At its inception, the CMVRA was evaluated retrospectively for its ability to detect cases of Western equine encephalomyelitis virus (family Togaviridae, genus Alphavirus) and St. Louis encephalitis virus (family Flaviviridae, genus Flavivirus) in California during low-, medium- and high-risk seasons (9). Additional assessment of the ability of CMVRA to track WNV cases in Bakersfield, California, produced impressive results during 2004 and 2007 (10,11).
The second method was the vector index, an estimate of the number of infected mosquitoes collected per trap-night. This index successfully determined human risk in Colorado (12,13) and is used by the Colorado Department of Public Health and Environment (www.cdphe.state.co.us/dc/zoonosis/wnv/wnvsentinel.htmlExternal Web Site Icon).
The third method was the DYCAST (14) system, which provides an assessment of risk in time and space by using reports of dead birds from the California Department of Public Health Dead Bird Hotline. This risk estimate differs from the previous 2 in that the spatial scale is fine (0.44 km2 grid cells), it is computationally more complex, and it does not rely on laboratory test results (15).
Understanding the characteristics of risk estimates to determine the best predictive measure for human cases is needed for several reasons. First, reducing the rate of false-positive results will reduce message fatigue associated with repeated false warnings of high-risk conditions. Second, increasing the proportion of high-risk areas correctly identified (sensitivity) can reduce the costs associated with emergency mosquito control by correctly focusing timely intervention. Third, a qualitative assessment of risk estimates that incorporates different variables for enzootic transmission enables understanding of the ability of different assemblages of surveillance data for predicting human risk. Overall, a better understanding of the tools used in decision support for emergency intervention can only improve the protection of human health.

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