Spatio-temporal epidemiology of highly pathogenic avian influenza (subtype H5N1) in poultry in eastern India

被引：15

作者：

Dhingra, Madhur S. ^{[1
,2
]}

Dissanayake, Ravi ^{[3
]}

Negi, Ajender Bhagat ^{[1
]}

Oberoi, Mohinder ^{[3
]}

Castellan, David ^{[4
]}

Thrusfield, Michael ^{[5
]}

Linard, Catherine ^{[6
,7
]}

Gilbert, Marius ^{[6
,7
]}

机构：

[1] UN, Anim Quarantine & Certificat Serv Stn Kapashera, India Food & Agr Org, Emergency Ctr Transboundary Anim Dis India, New Delhi 110037, India

[2] Coll Med & Vet Med, Sch Biomed Sci, Div Pathway Med, Edinburgh EH16 4SB, Midlothian, Scotland

[3] UN, Reg Support Unit SAARC Countries, FAO, ECTAD, Kathmandu, Nepal

[4] FAO, ECTAD, Reg Off Asia & Pacific FAO RAP, Bangkok 10200, Thailand

[5] Univ Edinburgh, Coll Med & Vet Med, Royal Dick Sch Vet Studies, Vet Clin Sci,Easter Bush Vet Ctr Roslin, Edinburgh EH25 9RG, Midlothian, Scotland

[6] Univ Libre Bruxelles, Biol Control & Spatial Ecol, B-1050 Brussels, Belgium

[7] Fonds Natl Rech Sci FRS FNRS, B-1000 Brussels, Belgium

来源：

SPATIAL AND SPATIO-TEMPORAL EPIDEMIOLOGY | 2014年 / 11卷

关键词：

Eastern India; HPAI H5N1 in poultry; Spatial and temporal clusters; Risk factors; Predictive risk modeling; Disease surveillance;

D O I：

10.1016/j.sste.2014.06.003

中图分类号：

R1 [预防医学、卫生学];

学科分类号：

1004 ; 120402 ;

摘要：

In India, majority outbreaks of highly pathogenic avian influenza (HPAI) H5N1 have occurred in eastern states of West Bengal, Assam and Tripura. This study aimed to identify disease clusters and risk factors of HPAI H5N1 in these states, for targeted surveillance and disease control. A spatial scan statistic identified two significant disease clusters in West Bengal and Assam, occurring during January and November-December 2008, respectively. Key risk factors were identified at sub-district level using bootstrapped logistic regression and boosted regression trees model. With both methods, HPAI H5N1 outbreaks in backyard poultry were associated with accessibility in terms of time taken to access a city with > 50,000 persons, human population density and duck density (P < 0.005). In addition, areas at lower elevation were also identified as high risk by BRT model. It is recommended that risk-based surveillance should be implemented in high duck density areas and all live-bird markets in high-throughput locations. (C) 2014 Elsevier Ltd. All rights reserved.

引用

页码：45 / 57

页数：13

共 62 条

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