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Chinese Science Bulletin

, Volume 55, Issue 36, pp 4168–4178 | Cite as

Risk analysis for the highly pathogenic avian influenza in Mainland China using meta-modeling

  • ChunXiang CaoEmail author
  • Min Xu
  • ChaoYi Chang
  • Yong Xue
  • ShaoBo Zhong
  • LiQun Fang
  • WuChun Cao
  • Hao Zhang
  • MengXu Gao
  • QiSheng He
  • Jian Zhao
  • Wei Chen
  • Sheng Zheng
  • XiaoWen Li
Article Geography

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.

Keywords

highly pathogenic avian influenza meta-modeling remote sensing geographical information system Bayesian maximum entropy logistic regression spatiotemporal autocorrelation 

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References

  1. 1.
    Alexander D J. A review of avian influenza in different bird species. Vet Microbiol, 2000, 74: 3–13CrossRefGoogle Scholar
  2. 2.
    Alexander D J. An overview of the epidemiology of avian influenza. Vaccine, 2007, 25: 5637–5644CrossRefGoogle Scholar
  3. 3.
    Swayne D E, Suarez D L. Highly pathogenic avian influenza. Rev Sci Tech, 2000, 19: 463–482Google Scholar
  4. 4.
    Zhu Q Y, Qin E D, Wang W, et al. Fatal Infection with Influenza A (H5N1) Virus in China. New Engl J Med, 2006, 354: 2731–2732CrossRefGoogle Scholar
  5. 5.
    Zhong S B. Application of GIS and remote sensing for study of epidemiology of infectious diseases-case dtudies of hepatitis B and highly pathogenic avian influenza (in Chinese). Dissertation for the Doctoral Degree. Beijing: Graduate University of Chinese Academy of Sciences, 2006. 67–83Google Scholar
  6. 6.
    Chen H, Smith G J, Zhang S Y, et al. Avian flu: H5N1 virus outbreak in migratory waterfowl. Nature, 2005, 436: 191–192CrossRefGoogle Scholar
  7. 7.
    Rogers D J, Randolph S E, Snow R W, et al. Satellite imagery in the study and forecast of malaria. Nature, 2002, 415: 710–715CrossRefGoogle Scholar
  8. 8.
    Xu B, Gong P, Biging G, et al. Snail density prediction for schistosomiasis control using Ikonos and ASTER images. Photog Eng Rem Sens, 2004, 70: 1285–1294Google Scholar
  9. 9.
    Guo J P, Xue Y, Cao C X, et al. Study on the highly pathogenic avian influenza epidemic using land surface temperature from MODIS data. Int Geosci Rem Sens Symp, 2005, 5: 3599–3602Google Scholar
  10. 10.
    Fang L Q, Cao C X, Chen G S, et al. Studies on the spatial distribution and environmental factors of highly pathogenic avian influenza in China using geographic information system technology (in Chinese). Chin J Epidemiol, 2005, 26: 839–842Google Scholar
  11. 11.
    Gilbert M, Chaitaweesub P, Parakamawongsa T, et al. Free-grazing ducks and highly pathogenic avian influenza, Thailand. Emerg Infectious Dis, 2006, 12: 227–234Google Scholar
  12. 12.
    Brownstein J S, Holford T R, Fish D. Effect of climate change on lyme disease risk in North America. Eco Health, 2005, 2: 38–46Google Scholar
  13. 13.
    Gumpertz M L, Graham J M, Ristaino J B. Autologistic model of spatial pattern of Phytophthora epidemic in bell pepper: Effects of soil variables on disease presence. J Agric Biol Environ Stat, 1997, 2: 131–156CrossRefGoogle Scholar
  14. 14.
    Christakos G. Spatiotemporal information systems in soil and environmental sciences. Geoderma, 1998, 85: 141–179CrossRefGoogle Scholar
  15. 15.
    Christakos G. Modern Spatiotemporal Geostatistics. New York: Oxford University Press, 2000. 116–215Google Scholar
  16. 16.
    Christakos G, Bogaert P, Serre M L. Temporal GIS. New York: Springer, 2002. 155–166Google Scholar
  17. 17.
    Wang J F, Christakos G, Han W G, et al. Data-driven exploration of “spatial pattern-time process-driving forces” associations of SARS epidemic in Beijing, China. J Public Health, 2008, 30: 234–244CrossRefGoogle Scholar
  18. 18.
    Woodward M. Epidemiology: Study Design and Data Analysis. Boca Raton: Chapman & Hall/CRC, 1999. 145–190Google Scholar
  19. 19.
    Hosmer D W, Stanley L. Applied Logistic Regression. 2nd ed. New York: Wiley, 2000CrossRefGoogle Scholar
  20. 20.
    Besag J. Spatial interaction and the statistical analysis of lattice systems. J Royal Statist Soc B, 1974, 36: 192–236Google Scholar
  21. 21.
    Cressie N A C. Statist for Spatial Data. New York: Wiley, 1994Google Scholar
  22. 22.
    Kanai K, Ueta M, Germogenov N, et al. Migration routes and important resting areas of Siberian cranes (Grus leucogeranus) between northeastern Siberia and China as revealed by satellite tracking. Biol Conserv, 2002, 106: 339–346CrossRefGoogle Scholar

Copyright information

© Science China Press and Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • ChunXiang Cao
    • 1
    Email author
  • Min Xu
    • 1
    • 3
  • ChaoYi Chang
    • 1
    • 3
  • Yong Xue
    • 1
  • ShaoBo Zhong
    • 1
  • LiQun Fang
    • 2
  • WuChun Cao
    • 2
  • Hao Zhang
    • 1
  • MengXu Gao
    • 1
    • 3
  • QiSheng He
    • 1
    • 3
  • Jian Zhao
    • 1
    • 3
  • Wei Chen
    • 1
    • 3
  • Sheng Zheng
    • 1
    • 3
  • XiaoWen Li
    • 1
  1. 1.State Key Laboratory of Remote Sensing Sciencethe Institute of Remote Sensing Applications of the Chinese Academy of SciencesBeijingChina
  2. 2.Beijing Institute of Microbiology and EpidemiologyState Key Laboratory of Pathogen and BiosecurityBeijingChina
  3. 3.Graduate University of the Chinese Academy of SciencesBeijingChina

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