
Editorial
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In the northeastern United States,
To compare the incidence of
The 1999 New York epidemic of human West Nile virus (WN) encephalitis and meningitis was preceded by a crow die-off also caused by WN infection. As one component of the subsequently developed national surveillance system, crow mortality data were collected to detect WN activity before humans might become infected. However, predicting areas at risk for human WN disease likely requires assessment of multiple factors, including the intensity and timing of crow epizootics. To identify early season measures of WN activity in crows associated with subsequent WN disease in humans, county-level crow mortality data from seven northeastern states were analyzed. A predictive model was developed based on analysis of 2000 surveillance data and then assessed for 2001. To characterize the intensity of early season WN activity in crows, 15 variables were constructed from surveillance data of 52 counties that tested at least four crows during the early season (defined as June 17-July 28, 2000). County values for each variable were dichotomized at the 75th percentile into "high" and "low" activity. Multivariate analysis indicated that "high" early season activity of two variables - density of reported dead crow sightings (reported dead crows/area) and [(WN-infected crows/tested crows) × (human population)] - were associated with report of at least one human WN disease case (for each variable: adjusted odds ratio, 6.9; 95% confidence interval, 1.2-40.6). An assessment of this model using 2001 surveillance data from 61 counties yielded similar findings. With emphasis on early season WN activity, crow surveillance may allow timely targeting of interventions to protect the public health.
The distribution of human risk for West Nile virus was determined by spatial analysis of the initial case distribution for the New York City area in 1999 using remote sensing and geographic information system technologies. Cluster analysis revealed the presence of a statistically significant grouping of cases, which also indicates the area of probable virus introduction. Within the cluster, habitat suitability for potentially infective adult mosquitoes was measured by the amount of vegetation cover using satellite imagery. Logistic regression analysis revealed satellite-derived vegetation abundance to be significantly and positively associated with the presence of human cases. The logistic model was used to estimate the spatial distribution of human risk for West Nile virus throughout New York City. Accuracy of the resulting risk map was cross-validated using virus-positive mosquito sample sites. These new epidemiological methods aid in rapid entry point identification and spatial prediction of human risk of infection for introduced vector-borne pathogens.
This work was designed to study the infection process of
To evaluate the vector competence of
This report describes the isolation of