Modeling and analysis of mosquito and environmental data to predict the risk of Japanese encephalitis

American Society for Photogrammetry and Remote Sensing Annual Conference 2009, ASPRS 2009

Volumn 2, Issue , 2009, Pages 538-544

  Masuoka, Penny ^a   Klein, Terry A ^b   Kim, Heung Chul ^c   Claborn, David M ^d   Achee, Nicole ^a   Andre, Richard ^a   Chamberlin, Judith ^a   Taylor, Kevin ^a   Small, Jennifer ^e   Anyamba, Assaf ^e   Sardelis, Michael ^f   Grieco, John ^a  

^a Uniformed Services University of the Health Sciences   (United States)

^b US Army MEDDAC Korea Unit 15281   (United States)

^c Unit 15247   (United States)

^d MISSOURI STATE UNIVERSITY   (United States)

^e NASA GODDARD SPACE FLIGHT CENTER   (United States)

^f National Center for Medical Intelligence   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

DATA SETS; DISEASE VECTORS; ECOLOGICAL CHARACTERISTICS; ECOLOGICAL NICHE; ENVIRONMENTAL CONDITIONS; ENVIRONMENTAL DATA; GEOGRAPHICAL AREA; LAND COVER; LOW PROBABILITY; MODELING AND ANALYSIS; MODELING PROGRAMS; MOFFETT; MOSQUITO POPULATIONS; NDVI DATA; NORMALIZED DIFFERENCE VEGETATION INDEX; PETERSON; REAL-TIME PREDICTION; REPUBLIC OF KOREA; STUDY AREAS; TEMPERATE CLIMATE;

CLIMATOLOGY; ECOLOGY; PHOTOGRAMMETRY; POPULATION STATISTICS; REMOTE SENSING; VIRUSES;

FORECASTING;

EID: 84868564593     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (11)

1. Elith, J., C.H. Graham, R.P. Anderson, M. Dudik, S. Ferrier, A. Guisan, R.J. Hijamans, F. Huettmann, J.R. Lethwick, A. Lehmann, J. Li, L.G. Lohmann, B.A. Loiselle, G. Manion, C. Moritz, M. Nakamura, Y. Nakazawa, J. McC. Overton, J. Sobéron, S. Williams, M.S. Wisz, and N.E. Zimmermann, 2006. Novel methods improve prediction of species' distributions from occurrence data, Ecography, 29:129-151.
2. Hernandez, P., C. Graham, L. Master and D. Albert, 2006. The effect of sample size and species characteristics on performance of different species distribution modeling methods, Ecography, 29: 773-785.
3. Hijmans, R.J., S.E. Cameron, J.L. Parra, P.G. Jones and A. Jarvis, 2005. Very high resolution interpolated climate surfaces for global land areas, International Journal of Climatology, 25: 1965-1978.
4. Moffett, A., N. Shackelford and S. Sarkar, 2007. Malaria in Africa: Vector species' niche models and relative rick maps, PLoSOne, 2(9): e824. doi:10.1371/journal.pone.0000824.
5. Pandey, B., A. Yamamoto, K. Morita, Y. Kurosawa, S. Rai, S. Adhikari, P. Kandel, and I. Kurane, 2003. Serodiagnosis of Japanese encephalitis among Nepalese patients by particle agglutination assay, Epi. and Infection, 131: 881-885.
6. Peiris, J.S.M., F.P. Amerasinghe, C.K. Arunagiri, L.P. Perera, P.P. Karunaratne, C.B. Ratnayake, T.A. Kulatilaka, and M.R.N. Abeysinghe, 1993. Japanese encephalitis in Sri Lanka: Comparison of vector and virus ecology in different agro-climatic areas, Trans. Royal Soc. Trop. Med. and Hygiene, 87:541-548.
7. Peterson, A.T. and J.J. Shaw, 2003. Lutzomyia vectors for cutaneous leishmaniasis in southern Brazil: ecological niche models, predicted geographic distribuitons, and climate change effects, International Journal of Parasitology, 33: 19-931.
8. Phillips, S.J., M. Dudík, and R.E. Schapire, 2004. A maximum entropy approach to species distribution modeling, In Proceedings of the Twenty-First International Conference on Machine Learning, pp. 655-662.
9. Phillips, S.J., R.P. Anderson, and R.E. Schapire, 2006. Maximum entropy modeling of species geographic distributions, Ecological Modelling, 190:231-259.
10. Straus, J.H. and E.G. Straus, 2002. Viruses and Human Disease, Academic Press: San Diego, 383 pp.
11. Wada, Y., Kawai, S., Oda, T., Miyagi, I., Suenaga, O., Nishigaki, J., and N. Omori, 1969. Dispersal experiment of Culex tritaeniorhynchus in Nagasaki area (preliminary report), Tropical Medicine, 11(1): 37-44.