Skip all navigation and jump to content Jump to site navigation
NASA Logo - Goddard Space Flight Center

+ NASA Homepage

    
Goddard Space Flight Center
About MODIS News Data Tools /images2 Science Team Science Team Science Team

   + Home
ABOUT MODIS
MODIS Publications Link
MODIS Presentations Link
MODIS Biographies Link
MODIS Science Team Meetings Link
 

 

 

Cao, CX; Xu, M; Chang, CY; Xue, Y; Zhong, SB; Fang, LQ; Cao, WC; Zhang, H; Gao, MX; He, QS; Zhao, JA; Chen, W; Zheng, S; Li, XW (2010). Risk analysis for the highly pathogenic avian influenza in Mainland China using meta-modeling. CHINESE SCIENCE BULLETIN, 55(36), 4168-4178.

Abstract
A logistic model was employed to correlate the outbreak of highly pathogenic avian influenza (HPAI) with related environmental factors and the migration of birds. Based on MODIS data of the normalized difference vegetation index, environmental factors were considered in generating a probability map with the aid of logistic regression. A Bayesian maximum entropy model was employed to explore the spatial and temporal correlations of HPAI incidence. The results show that proximity to water bodies and national highways was statistically relevant to the occurrence of HPAI. Migratory birds, mainly waterfowl, were important infection sources in HPAI transmission. In addition, the HPAI outbreaks had high spatiotemporal autocorrelation. This epidemic spatial range fluctuated 45 km owing to different distribution patterns of cities and water bodies. Furthermore, two outbreaks were likely to occur with a period of 22 d. The potential risk of occurrence of HPAI in Mainland China for the period from January 23 to February 17, 2004 was simulated based on these findings, providing a useful meta-model framework for the application of environmental factors in the prediction of HPAI risk.

DOI:
10.1007/s11434-010-4225-x

ISSN:
1001-6538

FirstGov logo Privacy Policy and Important Notices NASA logo

Curator: Brandon Maccherone
NASA Official: Shannell Frazier

NASA Home Page Goddard Space Flight Center Home Page