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Mathes R.W.,Bureau of Environmental Surveillance and Policy | Ito K.,New York University | Matte T.,York College - The City University of New York
PLoS ONE | Year: 2011

Background: Prospective syndromic surveillance of emergency department visits has been used for near-real time tracking of communicable diseases to detect outbreaks or other unexpected disease clusters. The utility of syndromic surveillance for tracking cardiovascular events, which may be influenced by environmental factors and influenza, has not been evaluated. We developed and evaluated a method for tracking cardiovascular events using emergency department free-text chief complaints. Methodology/Principal Findings: There were three phases to our analysis. First we applied text processing algorithms based on sensitivity, specificity, and positive predictive value to chief complaint data reported by 11 New York City emergency departments for which ICD-9 discharge diagnosis codes were available. Second, the same algorithms were applied to data reported by a larger sample of 50 New York City emergency departments for which discharge diagnosis was unavailable. From this more complete data, we evaluated the consistency of temporal variation of cardiovascular syndromic events and hospitalizations from 76 New York City hospitals. Finally, we examined associations between particulate matter ≤2.5 μm (PM2.5), syndromic events, and hospitalizations. Sensitivity and positive predictive value were low for syndromic events, while specificity was high. Utilizing the larger sample of emergency departments, a strong day of week pattern and weak seasonal trend were observed for syndromic events and hospitalizations. These time-series were highly correlated after removing the day-of-week, holiday, and seasonal trends. The estimated percent excess risks in the cold season (October to March) were 1.9% (95% confidence interval (CI): 0.6, 3.2), 2.1% (95% CI: 0.9, 3.3), and 1.8% (95%CI: 0.5, 3.0) per same-day 10 μg/m3 increase in PM2.5 for cardiac-only syndromic data, cardiovascular syndromic data, and hospitalizations, respectively. Conclusions/Significance: Near real-time emergency department chief complaint data may be useful for timely surveillance of cardiovascular morbidity related to ambient air pollution and other environmental events. © 2011 Mathes et al. Source


Egger J.R.,uite LLC | Konty K.J.,Gotham Center | Wilson E.,Gotham Center | Karpati A.,Gotham Center | And 4 more authors.
Journal of School Health | Year: 2012

Background: The effects of individual school dismissal on influenza transmission have not been well studied. During the spring 2009 novel H1N1 outbreak, New York City implemented an individual school dismissal policy intended to limit influenza transmission at schools with high rates of influenza-like illness (ILI). Methods: Active disease surveillance data collected by the New York City Health Department on rates of ILI in schools were used to evaluate the impact. Sixty-four schools that met the Health Department's criteria for considering dismissal were included in the analysis. Twenty-four schools that met criteria subsequently dismissed all classes for approximately 1 school week. A regression model was fit to these data, estimating the effect of school dismissal on rates of in-school ILI following reconvening, adjusting for potential confounders. Results: The model estimated that, on average, school dismissal reduced the rate of ILI by 7.1% over the entire average outbreak period. However, a large proportion of in-school ILI occurred before dismissal criteria were met. A separate model estimated that school absenteeism rates were not significantly affected by dismissal. Conclusion: Results suggest that individual school dismissal could be considered in situations where schools have a disproportionate number of high-risk students or may be unable to implement recommended preventive or infection control measures. Future work should focus on developing more sensitive indicators of early outbreak detection in schools and evaluating the impact of school dismissal on community transmission. © 2012, American School Health Association. Source


Metzger K.B.,Bureau of Environmental Surveillance and Policy | Ito K.,New York University | Matte T.D.,Bureau of Environmental Surveillance and Policy
Environmental Health Perspectives | Year: 2010

Background: To assess the public health risk of heat waves and to set criteria for alerts for excessive heat, various meteorologic metrics and models are used in different jurisdictions, generally without systematic comparisons of alternatives. We report such an analysis for New York City that compared maximum heat index with alternative metrics in models to predict daily variation in warm-season natural-cause mortality from 1997 through 2006. Materials and methods: We used Poisson time-series generalized linear models and generalized additive models to estimate weather-mortality relationships using various metrics, lag and averaging times, and functional forms and compared model fit. Results: A model that included cubic functions of maximum heat index on the same and each of the previous 3 days provided the best fit, better than models using maximum, minimum, or average temperature, or spatial synoptic classification (SSC) of weather type. We found that goodness of fit and maximum heat index-mortality functions were similar using parametric and nonparametric models. Same-day maximum heat index was linearly related to mortality risk across its range. The slopes at lags of 1, 2, and 3 days were flat across moderate values but increased sharply between maximum heat index of 95°F and 100°F (35-38°C). SSC or other meteorologic variables added to the maximum heat index model moderately improved goodness of fit, with slightly attenuated maximum heat index-mortality functions. Conclusions: In New York City, maximum heat index performed similarly to alternative and more complex metrics in estimating mortality risk during hot weather. The linear relationship supports issuing heat alerts in New York City when the heat index is forecast to exceed approximately 95-100°F. Periodic city-specific analyses using recent data are recommended to evaluate public health risks from extreme heat. Source


King K.L.,Central South University of forestry and Technology | Johnson S.,Bureau of Environmental Surveillance and Policy | Kheirbek I.,Bureau of Environmental Surveillance and Policy | Lu J.W.T.,Olmsted Center | Matte T.,Bureau of Environmental Surveillance and Policy
Landscape and Urban Planning | Year: 2014

Urban forest pollution removal potential has not been well explored at the neighborhood resolution and in relation to neighborhood-level emissions. In NYC's five counties, modeled NO2 removed by the primarily-deciduous urban forest ranges from <1% (New York) to 13% (Richmond) of total emissions; modeled PM10 removal ranges from <4% (New York) to 20% (Richmond). Across a 900m2 grid, average traffic NO2 emissions are over an order of magnitude greater than canopy removal; PM10 canopy removal slightly exceeds average traffic emissions. NO2 and PM10 removal are weakly but significantly inversely correlated in space with traffic emissions at the grid level (r=-0.126, p<0.0001). Land Use Regression modeling of monitored levels of NO2 and PM2.5 reveals an inverse correlation with tree cover in winter (leaf-off) and summer (leaf-on) suggesting that canopy indicators represent lack of pollution sources rather than active pollution removal. Tree canopy deposition likely has at most a small impact on neighborhood air quality relative to emissions. Planners should emphasize a holistic view of the benefits of urban trees when prioritizing urban neighborhoods for tree planting. © 2014 Elsevier B.V. Source


Kheirbek I.,Bureau of Environmental Surveillance and Policy | Ito K.,Bureau of Environmental Surveillance and Policy | Neitzel R.,University of Michigan | Kim J.,Bureau of Environmental Surveillance and Policy | And 5 more authors.
Journal of Urban Health | Year: 2014

Exposure to environmental noise from traffic is common in urban areas and has been linked to increased risks of adverse health effects including cardiovascular disease. Because traffic sources also produce air pollutants that increase the risk of cardiovascular morbidity, associations between traffic exposures and health outcomes may involve confounding and/or synergisms between air pollution and noise. While prior studies have characterized intraurban spatial variation in air pollution in New York City (NYC), limited data exists on the levels and spatial variation in noise levels. We measured 1-week equivalent continuous sound pressure levels (Leq) at 56 sites during the fall of 2012 across NYC locations with varying traffic intensity and building density that are routinely monitored for combustion-related air pollutants. We evaluated correlations among several noise metrics used to characterize noise exposures, including Leq during different time periods (night, day, weekday, weekend), Ldn (day-night noise), and measures of intermittent noise defined as the ratio of peak levels to median and background levels. We also examined correlations between sound pressure levels and co-located simultaneous measures of nitric oxide (NO), nitrogen dioxide (NO2), fine particulate matter (PM2.5), and black carbon (BC) as well as estimates of traffic and building density around the monitoring sites. Noise levels varied widely across the 56 monitoring sites; 1-week L eq varied by 21.6 dBA (range 59.1-80.7 dBA) with the highest levels observed during the weekday, daytime hours. Indices of average noise were well correlated with each other (r∈>∈0.83), while indices of intermittent noise were not well correlated with average noise levels (r∈<∈0.41). One-week Leq correlated well with NO, NO2, and EC levels (r∈=∈0.61 to 0.68) and less so with PM2.5 levels (r∈=∈0.45). We observed associations between 1-week noise levels and traffic intensity within 100 m of the monitoring sites (r∈=∈0.58). The high levels of noise observed in NYC often exceed recommended guidelines for outdoor and personal exposures, suggesting unhealthy levels in many locations. Associations between noise, traffic, and combustion air pollutants suggest the possibility for confounding and/or synergism in intraurban epidemiological studies of traffic-related health effects. The different spatial pattern of intermittent noise compared to average noise level may suggest different sources. © 2014 The New York Academy of Medicine. Source

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