Surveillance data for waterborne illness detection: an assessment following a massive waterborne outbreak of Cryptosporidium infection
| Autor: | K. A. Blair, M. E. Proctor, Jeffrey P. Davis |
|---|---|
| Rok vydání: | 1998 |
| Předmět: |
medicine.medical_specialty
Time Factors Epidemiology Population Surveillance Methods Cryptosporidiosis Sensitivity and Specificity Disease Outbreaks Wisconsin Bias Environmental health Medicine Humans Prospective Studies education Retrospective Studies education.field_of_study Data collection biology business.industry 1993 Milwaukee Cryptosporidiosis outbreak Public health Data Collection Urban Health Outbreak Reproducibility of Results Water Workload Cryptosporidium biology.organism_classification Surgery Infectious Diseases Population Surveillance Feasibility Studies business Research Article |
| Zdroj: | Epidemiology and infection. 120(1) |
| ISSN: | 0950-2688 |
| Popis: | Following the 1993 Milwaukee cryptosporidiosis outbreak, we examined data from eight sources available during the time of the outbreak. Although there was a remarkable temporal correspondence of surveillance peaks, the most timely data involved use of systems in which personnel with existing close ties to public health programmes perceived the importance of providing information despite workload constraints associated with an outbreak. During the investigation, surveillance systems which could be easily linked with laboratory data, were flexible in adding new variables, and which demonstrated low baseline variability were most useful. Geographically fixed nursing home residents served as an ideal population with non-confounded exposures. Use of surrogate measurements of morbidity can trigger worthwhile public health responses in advance of laboratory-confirmed diagnosis and help reduce total morbidity associated with an outbreak. This report describes the relative strengths and weaknesses of these surveillance methods for community-wide waterborne illness detection and their application in outbreak decision making. |
| Databáze: | OpenAIRE |
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