The Role of Data Aggregation in Public Health and Food Safety Surveillance - Biosurveillance: Methods and Case Studies - page 165

Gender = *
GI = *
Resp = *

Vary Gender Vary GI Vary Resp

Gender = M
GI = *
Resp = *

Gender = F
GI = *
Resp = *

Gender =
Unknown
GI = *
Resp = *

Gender = *
GI = Ye s
Resp = *

Gender = *
GI = No
Resp = *

Gender = *
GI = *
Resp = Ye s

Gender = *
GI = *
Resp = No

Vary GI Vary Resp Vary GI Vary Resp Vary GI Vary Resp Vary Resp Vary Resp

Gender = M
GI = Ye s
Resp = *

Gender = M
GI = No
Resp = *

Gender = M
GI = *
Resp = Ye s

Gender = M
GI = *
Resp = No

Gender = F
GI = Ye s
Resp = *

Gender = F
GI = No
Resp = *

Gender = *
GI = Ye s
Resp = Ye s

Gender = *
GI = Ye s
Resp = No

Gender = *
GI = No
Resp = Ye s

Gender = *
GI = No
Resp = No

Figure 9.1
Simple example of a T-Cube structure built for data typical to the public health domain. Components shown in light gray can be pruned for large sav-
ings of memory at a marginal increase of computational costs.