SPC Applications in Syndromic Surveillance
| dc.contributor.author | Fricker, Ronald D. Jr. | |
| dc.contributor.author | Hegler, Benjamin L. | |
| dc.contributor.author | Dunfee, David A. | |
| dc.contributor.author | Knitt, Matthew C. | |
| dc.contributor.author | Hu, Cecilia X. | |
| dc.date.accessioned | 2014-02-06T00:07:00Z | |
| dc.date.available | 2014-02-06T00:07:00Z | |
| dc.date.issued | 2007 | |
| dc.identifier.citation | Fricker, R.D., Jr., Hegler, B.L., and D.A. Dunfee (2007). SPC Applications in Syndromic Surveillance, 2007 Proceedings of the American Statistical Association [CD-ROM], Alexandria, VA: American Statistical Association, 4035-4044. | |
| dc.identifier.uri | https://hdl.handle.net/10945/38742 | |
| dc.description | 2007 Proceedings of the American Statistical Association [CD-ROM], Alexandria, VA: American Statistical Association, 4035-4044. | en_US |
| dc.description.abstract | syndromic surveillance, biosurveillance, terrorism, disease, detection, statistical process control, CUSUM (MCUSUM) and the multivariate exponentially weighted moving average (MEWMA). Based on our analyses, we found that the CUSUM performed better than the EARS' methods across all of the scenarios we evaluated and, similar to results for the univariate CUSUM and EWMA in classical SPC applications, the directionally sensitive MCUSUM and MEWMA perform very similarly. | en_US |
| dc.rights | defined in Title 17, United States Code, Section 101. Copyright protection is not available for this work in the United States. | en_US |
| dc.title | SPC Applications in Syndromic Surveillance | en_US |
| dc.type | Preprint | en_US |
| dc.contributor.department | Operations Research (OR) | |
| dc.subject.author | Statistical process control, biosurveillance, bioterrorism, early event detection, situational awareness | en_US |
