ojphi-07-e9.pdf


ISDS Annual Conference Proceedings 2014. This is an Open Access article distributed under the terms of the Creative Commons Attribution-
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ISDS 2014 Conference Abstracts

An Ecological Analysis of the Impact of Temperature 
Inversion on Emergency Department Visits for 
Respiratory Syndromes and Subsyndromes using 
BioSense 2.0 Frontend Data

Anne Burke*, David Jackson and Allyn K. Nakashima

Bureau of Epidemiology, Utah Department of Health, Salt Lake City, UT, USA

Objective
To determine the association between emergency department (ED) 

visits for the respiratory syndrome and subsyndromes and air quality 
indices (AQI) for fine particle pollution in Salt Lake County, UT 
using frontend BioSense 2.0 data.

Introduction
During the winter months, Utah experiences a temperature 

inversion which traps pollutants, such as fine particle pollution (PM 
2.5), in the Salt Lake Valley. A previous study determined the impact of 
inversion on ED visits for asthma,1 however similar phenomena have 
yet to be examined using the BioSense 2.0 syndromic surveillance 
system. While similar studies utilize a time-stratified case-crossover 
design, the absence of individually identifiable information on the 
dashboard precludes the utilization of this methodology. Using 
BioSense 2.0 frontend data, an ecological study design may allow 
for analyses to determine the impact of inversion on ED visits for 
respiratory syndrome and subsyndromes from submitting facilities in 
Salt Lake County, UT.

Methods
Numbers and proportions of visits were tabulated for the BioSense 

2.0 respiratory syndrome and subsyndromes (asthma, bronchitis and 
bronchiolitis, chest pain, cough, cyanosis and hypoxemia, dyspnea, 
hemoptysis, influenza-like illness (ILI), otitis media, pleurisy, 
pneumonia and lung abscess, respiratory failure, respiratory syncytial 
virus (RSV), and upper respiratory infections) for January 2012 to 
February 2014. Particulate concentration data for PM2.5 in Salt Lake 
County, UT were be obtained from the EPA website and converted to 
AQI for the same dates. Voluntary and mandatory action days were 
identified by PM2.5 (15-25 and >25 g/m3, respectively) and analysis 
of variance (ANOVA) models were performed to determine if the 
proportion of ED visits differed significantly by action day status. The 
CDC’s C2 aberration detection methodology was used to determine 
dates when the number of ED visits for respiratory events exceeded 
the alarm threshold. These days were examined in relation to AQI 
using ANOVA models in order to determine if there was a significant 
association between days exceeding the threshold and air quality. A 
linear regression analysis was conducted to determine the association 
between BioSense 2.0 respiratory syndrome and subsyndromes and 
AQI when controlling for seasonality.

Results
A total of 80 voluntary and 88 mandatory action days occurred 

during this time period. The mean proportion of total visits for all 
respiratory syndromes and subsyndromes except for respiratory 
failure and otitis media increased significantly with more severe action 
day status (p<0.05). Overall, 85 alarms were triggered for respiratory 
syndromes and subsyndromes during this time period. The mean AQI 
was significantly greater on days in which the proportion of ED visits 
exceeded the alarm threshold for ILI, pleurisy, and respiratory failure 

(p<0.05). After adjusting for seasonality, the AQI was significantly 
associated with the proportion of ED visits for RSV, ILI, and the 
respiratory syndrome (p<0.05).

Conclusions
Regardless of analytical technique, the proportion of ED visits for 

the BioSense 2.0 respiratory syndrome and ILI were significantly 
associated with AQI; however, the association of other subsyndomes 
differed by method of analysis and the inclusion of control variables. 
These data suggest that voluntary and mandatory action days were 
associated with higher proportions of respiratory visits for most 
respiratory conditions. Alarm events, on the other hand, were most 
likely to be associated with AQI for ILI, pleurisy, and respiratory 
failure; this data may be useful to ED practices in Salt Lake County. 
RSV and ILI remained significantly associated with AQI when 
controlling for seasonality. The association between these infectious 
conditions and AQI may inform the use of syndromic data to conduct 
disease surveillance during the influenza and RSV seasons. Overall, 
these data suggest that frontend BioSense 2.0 data may serve useful 
to ecological analyses for air quality issues, such inversions in Salt 
Lake County, UT. Because of its scope and differing characteristics 
of respiratory subsyndromes, breaking the respiratory syndrome down 
into its various subsyndromes for analysis may provide more a more 
accurate representation of its association with air quality.

Keywords
BioSense 2.0; Respiratory syndrome; Air pollution

References

1. Beard JD, Beck C, Graham R, Packham SC, Traphagan M, Giles RT,
Morgan JG. Winter temperature inversions and emergency department 
visits for asthma in Salt Lake County, UT, 2003-2008. Environmental 
Health Perspectives 2012;120(10):1385-1390.

*Anne Burke

E-mail: aburke@utah.gov    

Online Journal of Public Health Informatics * ISSN 1947-2579 * http://ojphi.org * (1):e , 201