GIS-based spatial, temporal, and space-time analysis of haemorrhagic fever with renal syndrome

Abstract

We obtained a list of all reported cases of haemorrhagic fever with renal syndrome (HFRS) in Shenyang, China, during 1990-2003, and used GIS-based scan statistics to determine the distribution of HFRS cases and to identify key areas and periods for future risk-factor research. Spatial cluster analysis suggested three areas were at increased risk for HFRS. Temporal cluster analysis suggested one period was at increased risk for HFRS. Spacetime cluster analysis suggested six areas from 1995 to 1996 and four areas from 1998 to 2003 were at increased risk for HFRS. We also discussed the likely reasons for these clusters. We conclude that GIS-based scan statistics may provide an opportunity to classify the epidemic situation of HFRS, and we can pursue future investigations to study the likely factors responsible for the increased disease risk based on the classification. © 2009 Cambridge University Press.