A multi-data source surveillance system to detect a bioterrorism attack during the G8 Summit in Scotland

Epidemiology and Infection

Volumn 136, Issue 7, 2008, Pages 876-885

  Meyer, N ^a,b   McMenamin, Jim ^b   Robertson, C ^c   Donaghy, M ^b   Allardice, G ^c   Cooper, D ^d  

^a European Programme for Intervention Epidemiology Training (EPIET)   (Sweden)

^b HEALTH PROTECTION SCOTLAND   (United Kingdom)

^c UNIVERSITY OF STRATHCLYDE   (United Kingdom)

^d PUBLIC HEALTH ENGLAND   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

ABSENTEEISM; ALGORITHM; ARTICLE; BIOLOGICAL WARFARE; CLINICAL STUDY; CLUSTER ANALYSIS; EPIDEMIC; FAX; GASTROENTERITIS; HEALTH SURVEY; HUMAN; INFECTION; INFORMATION PROCESSING; INFORMATION SERVICE; LABORATORY TEST; LINEAR REGRESSION ANALYSIS; MEDICAL INFORMATION SYSTEM; NEUROLOGIC DISEASE; POLICE; PRACTICE GUIDELINE; RESPIRATORY TRACT DISEASE; TELECONSULTATION; UNITED KINGDOM; WORKSHOP;

ALGORITHMS; AUTOMATIC DATA PROCESSING; BIOTERRORISM; DEVELOPED COUNTRIES; DISEASE OUTBREAKS; HUMANS; SCOTLAND; SENTINEL SURVEILLANCE;

EID: 44049100809     PISSN: 09502688     EISSN: 14694409     Source Type: Journal    
DOI: 10.1017/S0950268807009132     Document Type: Article

References (23)

1. HMSO. Report on the 1996 outbreak of E. coli O157 in Central Scotland. Edinburgh: HMSO, 1997.
2. McGuigan CC, et al. Lethal outbreak of infection with Clostridium novyi type A and other spore-forming organisms in Scottish injecting drug users. Journal of Medical Microbiology 2002; 51: 971-977.
3. Cotruvo JA, et al. (eds). Waterborne Zoonoses: Identification, Causes and Control. Section IV, Epidemiological data, cases studies, and outbreaks, 2004, pp. 186-190. (http://www.who.int/ water_sanitation_health/diseases/zoonosessect4.pdf).
4. Fleischauer AT, et al. The validity of chief complaint and discharge diagnosis in emergency department-based syndromic surveillance. Academic Emergency Medicine 2004; 11: 1262-1267.
5. Dafni UG, et al. Algorithm for statistical detection of peaks - Syndromic Surveillance System for the Athens 2004 Olympic Games. Morbidity and Mortality Weekly Report 2004; 53 (Suppl.): 86-94.
6. Jorm LR, et al. Watching the Games: Public health surveillance for the Sydney 2000 Olympic Games. Journal of Epidemiology and Community Health 2003; 57: 102-108.
7. Osaka K, Takahashi H, Ohyama T. Testing a symptom-based surveillance system at high-profile gatherings as a preparatory measure for bioterrorism. Epidemiology and Infection 2002; 129: 429-434.
8. Pavlin JA, et al. Innovative surveillance methods for rapid detection of disease outbreaks and bioterrorism: Results of an interagency workshop on health indicator surveillance. American Journal of Public Health 2003; 93: 1230-1235.
9. Centers for Disease Control and Prevention. Syndrome definitions for diseases associated with critical bioterrorism-associated agents 2003 (http://www.bt.cdc.gov/surveillance/syndromedef/index.asp). Accessed 30 May 2005.
10. National, Health Service Information Authority. The clinical terms version 3 (the Read Codes): Incorporation of earlier versions of the Read Codes (the Superset). Birmingham, England: National Health Service Information Authority, 2000.
11. Manchester Triage Group. Emergency triage. Plymouth, UK: BMJ Publishing Group, 1997.
12. CSAGS. Guidance in the Confidentiality and Security Advisory Group for Scotland (CSAGS) report (http://www.show.scot.nhs.uk/sehd/ publications/ppcr/ppcr.pdf). Accessed 30 May 2005.
13. Rogerson PA, Yamada I. Approaches to syndromic surveillance when data consist of small regional counts. Morbidity and Mortality Weekly Report 2004; 53 (Suppl.): 79-85.
14. Hawkins D, Olwell D. Cumulative Sum Charts and Charting for Quality Improvement. New York: Springer, 1998.
15. Farrington CP, et al. A statistical algorithm for early detection of outbreaks of infectious disease. Journal of the Royal Statistical Society Series A 1996; 159: 547-563.
16. Hutwagner L, et al. The bioterrorism preparedness and response Early Aberration Reporting System (EARS). Journal of Urban Health 2003; 80 (Suppl. 1): I89-96.
17. Hutwagner L, et al. Epidemiological investigations of statistical aberrations in syndrome surveillance. Confidential Draft, U.S. Centers for Disease Control, Atlanta, USA.
18. Steiner-Sichel L, et al. Field investigations of emergency department syndromic surveillance, signals - New York City. Morbidity and Mortality Weekly Report 2004; 53: 184-189.
19. O'Brien SJ, Christie P. Do CuSums have a role in routine communicable disease surveillance? Public Health 1997; 111: 255-258.
20. Rolfhamre P, Ekdahl L. An evaluation and comparison of three commonly used statistical models for automatic detection of outbreaks in epidemiological data of communicable diseases. Epidemiology and Infection 2006; 134: 863-871.
21. Centers for Disease Control and Prevention. Framework for evaluating public health surveillance systems for early detection of outbreaks: Recommendations from the CDC Working Group. Morbidity and Mortality Weekly Report 2001; 50 (RR-13).
22. Begier EM, et al. The national Capitol Region's emergency department syndromic surveillance system: Do chief complaint and discharge diagnosis yield different results? Emerging Infectious Diseases 2003; 9: 393-396.
23. Epsino JU, Wagner MM. Accuracy of ICD-9-coded chief complaints and diagnoses for the detection of acute respiratory illness. Proceedings of the Annual Symposium/American Medical Informatics Assocation, 3-7 Nov. 2001. Washington, DC.