The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. Vol. XXXVII. Part Bl. Beijing 2008
Centre Latitude
24.928055
22.692492
Radius
1.204827
0.481931
Population Number
1669635
1901586
Observed Cases
49
52
Expected Cases
16.766081
19.095279
LLR
27.824853
9.668875
Relative Risk
3.341264
3.140871
P
0.001
0.001
Table 2. b) Spatial scan statistics results (scale: province)
Hotspot Cluster: 1
Cluster type
Circle
Centre Name
Shuikou Town
Centre Code
45142309
Centre Longitude
106.586283
Centre Latitude
22.478791
Radius
0.156412
Population Number
41485
Observed Cases
2
Expected Cases
0.704587
LLR
2.967778
Relative Risk
5.676992
P
0.001
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Figure 5. Fieldwork response module of PDA client
In the experiment of prototype system, the surveillance
computing program could deal with multi-scale geographical
and disease data, and provide corresponding computing results.
Intelligent disease diagnosis program of PDA client could
accomplish the intelligent diagnosis of several hundred kinds of
diseases. Meanwhile, on the condition of nice internet and
mobile network, collaborative server, PC client and PDA client
could implement the one-to-one, one-to-many, many-to-one,
and many-to-many collaborative work rapidly and accurately.
Table 2. c) Spatial scan statistics results (scale: county)
7. CONCLUSION
a) b)
c)
d)
Figure 4. Intelligent disease diagnosis module of PDA client: a)
choose the symptoms; b) choose the districts and the
exposed time; c) reconfirm the input items; d)
display the results.
The structure design and implementation of a collaborative
epidemical surveillance and response system was discussed in
this paper. This system combined epidemical surveillance
system and response system using collaborative working mode,
and accomplished the surveillance computing program and
intelligent disease diagnosis program based on scan statistics
and Bayesian analysis methods. The prototype system had
completed the architecture design, basic program developing,
equipment testing and practical experiment, and reached a
satisfying result. Before applied in practical applications, the
system has some possible problems to solve or improve, such as:
a) Due to the full-time and long-period system running
demand, tests for the architecture mode and the carrying
capacity of the server are needed.
b) Further improvement to the architecture mode is
required for the optimization of the P2P (Person to Person),
P2C (Person to Computer) and C2C (Computer to Computer)
collaborations.
c) The disease models in the surveillance and response
modules are possibly required to be improved and optimized.
d) A great deal of real disease data are needed for the
precision and validity tests to the system and models.
ACKNOWLEDGEMENTS
This research is partially supported by the National High-tech
R&D Program (863 Program) 2007AA12Z240, the Beijing’s
Natural Science Key Foundation Project No.7061005, and the
National High-tech R&D Program (863 Program)
2006AA12Z109.