Info

Environmental investigation

Legionnaire's disease, foodborne illness, anthrax 2001

Number ill, number

Screening, contact tracing

All

at risk, spatial

Spatial and temporal analysis

All

distribution

Mathematical modeling

None

The examples are outbreaks discussed in Chapter 2 and additional examples that we discuss in this chapter (in bold type). SARS indicates severe acute respiratory syndrome; ILI, influenza-like illness.

*Includes physicians, nurse practitioners, veterinarians, and pathologists. tAstute observer includes clinicians and lay observers.

*The spatial analysis of the Sverdlovsk outbreak included a meteorological analysis.

diagnosis by ruling in (confirming) or ruling out (excluding) these diseases by further questioning, observation, and testing. The clinician draws on a large set of facts (medical knowledge) about the effects of disease on people or animals to generate and resolve a differential diagnosis. Clinicians acquire this knowledge during professional training and from textbooks of medicine (human or veterinary) and medical journals. The clinician also draws on available information about local disease prevalence, which may come to her attention through health alerts, morbidity and mortality reports, informal collegial consultations, and hospital surveillance information. In Chapter 13, we discuss how researchers have modeled clinical diagnosis mathematically and implemented these models in diagnostic expert systems.

Coroners, medical examiners, hospital pathologists, and veterinarians use a similar reasoning process when performing postmortem examinations to establish the cause of death. We further discuss the role of coroners and medical examiners in biosurveillance in Chapter 11 and the role of veterinarians in biosurveillance in Chapter 7. Postmortem examinations played a role in the detection of mad cow disease and anthrax (1979).

The strength of case detection by clinicians is that sick individuals seek medical care. Furthermore, clinicians are expert at diagnosing illness, which is fundamental to case detection.

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