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Volume 19, Number 8—August 2013
Research

Emergency Department Visit Data for Rapid Detection and Monitoring of Norovirus Activity, United States

Brian RhaComments to Author , Sherry Burrer, Soyoun Park, Tarak Trivedi, Umesh D. Parashar, and Benjamin A. Lopman
Author affiliations: Centers for Disease Control and Prevention, Atlanta, Georgia, USA (B. Rha, S. Burrer, S. Park, T. Trivedi, U.D. Parashar, B.A. Lopman); McKing Consulting Corporation, Atlanta (S. Park)

Main Article

Table 2

Parameters of linear regression models of the association between norovirus outbreaks and BioSense emergency department diarrhea subsyndrome visit data, by state, United States, January 2007–April 2010*

State no. Total no. emergency department visits/mo Norovirus,† β1, × 10−4 (95% CI) p value‡ R
1 273,218 2.86 (1.72 to 4.00) <0.0001 0.858
137,584 6.91 (4.60 to 9.22) <0.0001 0.809
66,597 3.79 (2.74 to 4.83) <0.0001 0.832
21,684 7.06 (0.73 to 13.40) 0.0298 0.637
5,214 2.18 (1.57 to 2. 78) <0.0001 0.800
6§¶ 836 0.53 (−8.77 to 9.84) 0.9082 0.133

*Emergency department chief complaint–based visits for diarrhea subsyndrome as a monthly proportion of all visits regressed on norovirus surveillance data, rotavirus antigen test data, and time variable. Intercept for each model p<0.0001.
†Suspected and confirmed norovirus outbreaks.
‡By t test.
¶Time variable not significant in model (p>0.05).
§Proportion of rotavirus tests positive variable not significant in model (p>0.05).

Main Article

Page created: July 18, 2013
Page updated: July 18, 2013
Page reviewed: July 18, 2013
The conclusions, findings, and opinions expressed by authors contributing to this journal do not necessarily reflect the official position of the U.S. Department of Health and Human Services, the Public Health Service, the Centers for Disease Control and Prevention, or the authors' affiliated institutions. Use of trade names is for identification only and does not imply endorsement by any of the groups named above.
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