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PREDICTION OF JAPANESE ENCEPHALITIS VECTORS IN KURNOOL DISTRICT OF ANDHRA PRADESH, INDIA BY USING BAYESIAN NETWORK
被引:1
|作者:
Murty, Upadhyayula Suryanarayana
[1
]
Rao, Mutheneni Srinivasa
[1
]
Arunachalam, Natarajan
[2
]
机构:
[1] Indian Inst Chem Technol CSIR, Div Biol, Bioinformat Grp, Hyderabad 500007, Andhra Pradesh, India
[2] Ctr Res Med Entomol ICMR, Madurai, Tamil Nadu, India
关键词:
SYSTEM;
MODEL;
D O I:
10.1080/08839510903235362
中图分类号:
TP18 [人工智能理论];
学科分类号:
081104 ;
0812 ;
0835 ;
1405 ;
摘要:
Japanese encephalitis (JE), a complex viral disease transmitted by mosquitoes. Determination of vector (mosquito) density is a prerequisite for devising effective control measures against this disease. Bayesian network is a widely used tool that has recently found application in the epidemiological surveillance studies. This article describes the application of Bayesian network tool to predict the Japanese encephalitis vector density using the longitudinal data collected from the Kurnool district of Andhra Pradesh, India, from 2001 to 2006. The entomological parameter from the study area indicates that various contributing factors are responsible for the prevalence of these vectors, making it difficult to estimate the importance of any particular parameter contributing to the increase of vector density. The application of this approach resulted in 73.12% to 95.12% accuracy compared to the test data with the corrected data.
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页码:828 / 834
页数:7
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