Epidemic risk analysis after the Wenchuan Earthquake using remote sensing

On 12 May 2008, Wenchuan Earthquake, magnitude 8.0, destroyed thousands of buildings, and resulted in thousands of people being buried in the collapsed buildings. In order to investigate the potential epidemic disease risk after earthquake, a Backward Propagation Neural Network (BPNN) was constructed to assess the potential epidemic risks by applying remote sensing technology to obtain Normalized Difference Vegetation Index (NDVI) and Normalized Difference Water Index (NDWI) values, as well as by using a geographic information system (GIS) to gain ambient epidemic-related spatial factors over the earthquake region. In this study, a relationship was established between the change in environmental factors after earthquake and potential epidemic risks, which was found to be statistically significant. The result might be explained for three change perspectives, namely environmental risks, medical risks and psychological risks. The corresponding strategies for preparedness in case of epidemic disease were given.

[1]  D. Lemonick.  Epidemics After Natural Disasters , 2011 .

[2]  Shu Li,et al.  Psychological Typhoon Eye in the 2008 Wenchuan Earthquake , 2009, PloS one.

[3]  Liu Haijiang,et al.  Monitoring sandy desertification of Otindag Sandy Land based on multi-date remote sensing images , 2008 .

[4]  Xu Bing,et al.  Remote sensing and geographic information systems in the spatial temporal dynamics modeling of infectious diseases. , 2006 .

[5]  Wim Van Biesen,et al.  Epidemiologic aspects of the Bam earthquake in Iran: the nephrologic perspective. , 2006, American journal of kidney diseases : the official journal of the National Kidney Foundation.

[6]  Peng Gong,et al.  Remote sensing and geographic information systems in the spatial temporal dynamics modeling of infectious diseases , 2006, Science in China Series C: Life Sciences.

[7]  Yanping Bai,et al.  Prediction of SARS epidemic by BP neural networks with online prediction strategy , 2005 .

[8]  Significant changes in ocean parameters after the Gujarat earthquake , 2001 .

[9]  U. Kitron,et al.  Spatial analysis of the distribution of Lyme disease in Wisconsin. , 1997, American journal of epidemiology.

[10]  B. Gao.  NDWI—A normalized difference water index for remote sensing of vegetation liquid water from space , 1996 .

[11]  D R Roberts,et al.  Remote sensing as a landscape epidemiologic tool to identify villages at high risk for malaria transmission. , 1994, The American journal of tropical medicine and hygiene.

[12]  R. O. Hayes,et al.  Detection, identification, and classification of mosquito larval habitats using remote sensing scanners in earth-orbiting satellites. , 1985, Bulletin of the World Health Organization.