S. Gao1, D. Mioc1, X. Yi2, F. Anton1, D.J. Coleman1, B. MacKinnon2, E. Oldfield2

1 - Department of Geodesy and Geomatics Engineering, University of New Brunswick, Canada E3B 5A3

2 - New Brunswick Lung Association, Canada E3B 1G5



Infectious disease, which is identified as the world's biggest killer of children and young adults, is given growing concern nowadays. As infectious disease is strongly related with spatial location, taking advantage of the mapping technology to track and study it could provide better decision making. In this paper, we provided a new methodology for thematic mapping of infectious disease which is implemented within Web Map Service.

In this research, Province of New Brunswick (Canada) and Maine State (USA) are our study sites. Since they share a highly traveled territorial border which makes infectious disease easy to spread from one to the other, web-enabled data sharing will greatly enhance infectious disease surveillance and control. Six level administrative/census areas that cover the entire territory of both sides are provided to satisfy different requirements. The original health data and spatial data are heterogeneous, therefore, semantic, syntactic and schematic heterogeneity are considered during data integration process. For storing the data, we have developed a hierarchical spatial data model. The health data are related to the spatial data, and the health data could be rolled up through spatial operation. In this way, it is effective in overcoming data redundancy.

Regarding the mapping variables of the infectious disease, we mainly concentrated on the demographic factor. The dimensions: temporal dimension, data used dimension, gender dimension, age group dimension, geographic level dimension, disease types are considered in the thematic mapping process. We provided two procedures for the querying and calculating the mapping variables. One is pre-defined and more efficient. The other one is dynamic and more flexible. The standard Web Map Service could not support the parameters for our infectious disease mapping variables. Thus, we extended the software capabilities of our server to fit the standard Web Map Service, which improves health data sharing and interoperability.  The web client could be WMS client or our health portal. In the client side, it supports the visualization of infectious disease, and explores the spatio-temporal trends of infectious disease outbreak.