期刊
EPIDEMIOLOGY AND INFECTION
卷 138, 期 6, 页码 873-883出版社
CAMBRIDGE UNIV PRESS
DOI: 10.1017/S0950268809990884
关键词
Antibiotic resistance; medical informatics; outbreaks; Shigella; surveillance
资金
- Collaborative Group WHONET-Argentina
- INEI
- National Institutes of Health [GM076672, RR025040-02]
- NATIONAL CENTER FOR RESEARCH RESOURCES [R01RR025040] Funding Source: NIH RePORTER
- NATIONAL INSTITUTE OF GENERAL MEDICAL SCIENCES [U01GM076672, R01GM103525] Funding Source: NIH RePORTER
Antimicrobial resistance is a priority emerging public health threat, and the ability to detect promptly outbreaks caused by resistant pathogens is critical for resistance containment and disease control efforts. We describe and evaluate the use of an electronic laboratory data system (WHONET) and a space time permutation scan statistic for semi-automated disease outbreak detection. In collaboration with WHONET-Argentina, the national network for surveillance of antimicrobial resistance, we applied the system to the detection of local and regional outbreaks of Shigella spp. We searched for clusters on the basis of genus, species, and resistance phenotype and identified 19 statistical 'events' in a 12-month period. Of the six known outbreaks reported to the Ministry of Health, four had good or suggestive agreement with SaTScan-detected events. The most discriminating analyses were those involving resistance phenotypes. Electronic laboratory-based disease surveillance incorporating statistical cluster detection methods can enhance infectious disease outbreak detection and response.
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