tetano
Editor, Senior Moderator
J Public Health (Oxf). 2013 Apr 25. [Epub ahead of print]
Local implementation of a syndromic influenza surveillance system using emergency department data in Santander, Spain.
Schrell S, Ziemann A, Garcia-Castrillo Riesgo L, Rosenk?tter N, Llorca J, Popa D, Krafft T; on Behalf of the SIDARTHa Project Consortium.
Source
Department of International Health, CAPHRI School of Public Health and Primary Care, Faculty of Health, Medicine and Life Sciences, Maastricht University, Maastricht, MD 6200, The Netherlands.
Abstract
BACKGROUND:
We assessed the local implementation of syndromic surveillance (SyS) as part of the European project 'System for Information on, Detection and Analysis of Risks and Threats to Health' in Santander, Spain.
METHODS:
We applied a cumulative sum algorithm on emergency department (ED) chief complaints for influenza-like illness in the seasons 2010-11 and 2011-12. We fine tuned the algorithm using a receiver operating characteristic analysis to identify the optimal trade-off of sensitivity and specificity and defined alert criteria. We assessed the timeliness of the SyS system to detect the onset of the influenza season.
RESULTS:
The ED data correlated with the sentinel data. With the best algorithm settings we achieved 70/63% sensitivity and 89/95% specificity for 2010-11/2011-12. At least 2 consecutive days of signals defined an alert. In 2010-11 the SyS system alerted 1 week before the sentinel system and in 2011-12 in the same week. The data from the ED is available on a daily basis providing an advantage in timeliness compared with the weekly sentinel data.
CONCLUSIONS:
ED-based SyS in Santander complements sentinel influenza surveillance by providing timely information. Local fine tuning and definition of alert criteria are recommended to enhance validity.
PMID:
23620543
[PubMed - as supplied by publisher]
http://www.ncbi.nlm.nih.gov/pubmed/23620543
Local implementation of a syndromic influenza surveillance system using emergency department data in Santander, Spain.
Schrell S, Ziemann A, Garcia-Castrillo Riesgo L, Rosenk?tter N, Llorca J, Popa D, Krafft T; on Behalf of the SIDARTHa Project Consortium.
Source
Department of International Health, CAPHRI School of Public Health and Primary Care, Faculty of Health, Medicine and Life Sciences, Maastricht University, Maastricht, MD 6200, The Netherlands.
Abstract
BACKGROUND:
We assessed the local implementation of syndromic surveillance (SyS) as part of the European project 'System for Information on, Detection and Analysis of Risks and Threats to Health' in Santander, Spain.
METHODS:
We applied a cumulative sum algorithm on emergency department (ED) chief complaints for influenza-like illness in the seasons 2010-11 and 2011-12. We fine tuned the algorithm using a receiver operating characteristic analysis to identify the optimal trade-off of sensitivity and specificity and defined alert criteria. We assessed the timeliness of the SyS system to detect the onset of the influenza season.
RESULTS:
The ED data correlated with the sentinel data. With the best algorithm settings we achieved 70/63% sensitivity and 89/95% specificity for 2010-11/2011-12. At least 2 consecutive days of signals defined an alert. In 2010-11 the SyS system alerted 1 week before the sentinel system and in 2011-12 in the same week. The data from the ED is available on a daily basis providing an advantage in timeliness compared with the weekly sentinel data.
CONCLUSIONS:
ED-based SyS in Santander complements sentinel influenza surveillance by providing timely information. Local fine tuning and definition of alert criteria are recommended to enhance validity.
PMID:
23620543
[PubMed - as supplied by publisher]
http://www.ncbi.nlm.nih.gov/pubmed/23620543