May-June 1999 (CDC, 1999a)
shock, necrotizing fascitis
TABLE 4.6 Nine Patterns—Cont'd
Commercially distributed products
Sexual or parenteral transmission
A large community outbreak of salmonellosis caused by intentional contamination of restaurant salad bars (Torok TJ et al., 1997)
Large community outbreak of cryp-tosporidiosis due to contamination of a filtered public water supply (Hayes EB et al., 1989) Outbreak of West Nile-like viral encephalitis, New York (CDC, 1999b,c)
Cluster of HIV-positive young women, New York, 1997-1998 (Anonymous, 1999)
Salmonellosis, Shigella sp., Escherichia coli 0157, Brucella sp., Staph enterortoxin B. vibrio cholera, B anthracis, toxic alimentary aleukia: T2 Mycotoxin, Clostridium botulinum: botulism, hepatitis A and C. Perfringins E toxin, ricin toxin, heavy metals: iron, mercury, arsenic, Nipah virus, marine toxin: saxitoxin, ciguatoxin, tetrodotoxin, palytoxin, trichinella: trichinosis, norwalk, cyclosporiasis cryptosporidiosis, Shigella sp, camphylobacter, giardiasis, staph enterotoxin B, Escherichia coli 0157, botulism, bioterroristic, ricin toxin, entamoeba histolytica, cyclosporiasis
Malaria, West Nile, yellow fever, dengue, Yersinia pestis-Tularemia, ebola, marburg, hantaviruses, Q fever, Glanders, melioidosis, Lassa, Machupo, Junin, Rift Valley, Crimean-Congo hemorrhagic fever, Hantaan, Alphaviridae: Venezuelan equine encephalitis, eastern equine encephalitis, western equine encephalitis, Chikungunya, Flaviviridea Encephalitis (e.g., Russian spring summer, eastern equine, St Louis, West Nile,Venezuelan), Nipah virus, rabies, Lyme, Rickettsia sp.: Rocky Mountain spotted fever, typhus HIV, Neisseria gonorrhea, Hemophillus ducrei, Treponema pallidum, Chlamydia trachomatis, hepatitis B and C
Reprinted from Journal of Biomedical Informatics, Vol. 36, Michael Wagner, Virginia Dato, John N. Dowling, and Michael Allswede, Representative Threats for Research in Public Health, pp. 177-188, Copyright 2003, with permission from Elsevier.
These analyses must be longitudinal to detect intermittent or ongoing contaminations and must consider that many foods can be stored for relatively long periods before consumption.
The seventh pattern is contamination of the water supply (well or surface water), as illustrated by the example of cryp-tosporidium in Chapter 2. The timeliness requirement may be "anthrax-like,'' as a cohort of individuals can be exposed nearly simultaneously. To achieve the required timeliness of detection, a surveillance system would require in-line monitoring of the water system for contamination, as well as components that correlate the spatial distribution of disease data with the branching anatomy and vulnerabilities of the water supply system, to allow a subtle increase in cases to be noticed as early as possible.
The eighth pattern results from disease transmission through an intermediate, nonhuman vector, such as mosquitoes or even contaminated blood products. Similar to diseases that are contagious and passed from human to human, outbreaks of this type do not have anthrax-like timeliness requirements. Detection of outbreaks in this category, however, requires that a biosurveillance system monitor for the presence of organisms in vectors (e.g., mosquitoes and blood products). It must also be capable of collecting and analyzing data about sick individuals and their exposures to vectors to find clusters of cases that otherwise would not be apparent above the background level of disease.
The ninth and final pattern is that caused by a disease transmitted through sexual or other intimate contact, such as the sharing of needles. This pattern resembles the contagious person-to-person pattern, but the analysis separated this pattern because the data collection enabling the analysis of sexual contact patterns is difficult, requires sensitivity, and may infringe on legal rights.A key detection problem raised by this category is identifying a carrier who is infecting other individuals (either intentionally or unintentionally). The timeliness requirement is not severe, as illustrated by AIDS, but the difficulty in detecting cases and identifying contacts is high.
5.7. Strengths and Limitations of Using Patterns to Reduce Design Complexity
The goal of the above analysis was to identify a set of patterns that would dramatically reduce the complexity of designing biosurveillance systems. By using these patterns, a system designer avoids the paralysis induced by the complexity of developing specifications for hundreds of organisms.
Each of these nine patterns represents an important and different problem in detection. This set of patterns may be more useful to system designers than are priority lists, as in Table 4.2. Table 4.2 does not identify explicitly requirements to detect premonitory cases, building contaminations, or continuous releases; hence, a designer may overlook these requirements if Table 4.2 is used.
Wagner and colleagues noted that five of the nine patterns happen to correspond to organizational divisions within governmental public health (sexually transmitted, communicable, vector-borne, water-borne, foodborne disease). They conjectured that the specialization that has occurred in governmental public health (in response to complexity) over the years might have been shaped by similarities among diseases, especially with respect to the types of data and analyses required to detect and characterize outbreaks of these diseases.
It is worth noting that four of the nine patterns do not correspond to organizational divisions in health departments (large-scale aerosol release, small premonitory release, building contamination, and continuous or intermittent release). This observation suggests that these patterns may require special attention. We note that the Department of Homeland Security is addressing the large-scale aerosol release, and the U.S. Postal Service is addressing the problem of building contamination— at least for the tiny subset of buildings in the United States that they own.
It is also worth noting that designers can benefit from focusing their attention on an even smaller subset of patterns. Two patterns—the communicable person-to-person and the large-scale release pattern—cover many of the design issues raised by the larger set of patterns (Wagner et al., 2003a).
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