Risk Factors for the Introduction of Avian Influenza Virus into Commercial Layer Chicken Farms During the Outbreaks Caused by a Low‐Pathogenic H5N2 Virus in Japan in 2005

Nishiguchi, Akiko; Kobayashi, Sota; Yamamoto, Takehisa; Ouchi, Yoshinao; Sugizaki, T; Tsutsui, Toshiyuki

doi:10.1111/j.1863-2378.2007.01074.x

Cited by 44 publications

(46 citation statements)

References 12 publications

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“…Increasing density of poultry is associated with a higher contact rate between susceptible and infected birds and therefore greater risk of spread [29][30][31][32][33][34]. However, no association was found between poultry density and the risk of HPAIV infection in China, suggesting that this unexpected finding was due to a greater proportion of industrialized chicken production at higher poultry densities, with associated higher biosecurity standards and vaccination protocols.…”

Section: Poultry Densitycontrasting

confidence: 47%

Incidence of Avian Flu Shocks on Poor Household Livelihoods of Poultry Farmers in Africa

Ntsefong¹

2017

IJAWB

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Section: Poultry Densitycontrasting

confidence: 47%

Incidence of Avian Flu Shocks on Poor Household Livelihoods of Poultry Farmers in Africa

Ntsefong¹

2017

IJAWB

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“…Causally this factor plays an important role in the spread of infection, both as windborne spread, if the distance between farms is less than 50 meters [27] and mechanical transfer by other routes e.g. human movement between farms [13]. The large effect size and the wide CIs were a concern for this variable, not because the association may not be true, but because of the effect on the model and the estimation process where there are cells with small numbers of observations affecting precision.…”

Section: Discussionmentioning

confidence: 99%

“…Many published articles have quantified different risk factors for various subtypes of avian influenza in commercial poultry farms all over the world [10–23]. Previously published studies have demonstrated that avian influenza introduction, transmission and persistence are associated with poultry trading pattern [12, 20], human and poultry densities [18, 23], movement of human and fomites [10, 12, 14], low biosecurity [10, 13, 21, 22], proximity to water bodies [15, 16, 17, 23], distance from other commercial poultry farms [11, 13, 21], and proximity to roads [15, 16, 19]. These risk factors help to further identify high-risk farms/systems, which could be targeted for interventions such as vaccination or culling.…”

Section: Introductionmentioning

confidence: 99%

A Case-Control Study to Identify Risk Factors Associated with Avian Influenza Subtype H9N2 on Commercial Poultry Farms in Pakistan

et al. 2015

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A 1:1 matched case-control study was conducted to identify risk factors for avian influenza subtype H9N2 infection on commercial poultry farms in 16 districts of Punjab, and 1 administrative unit of Pakistan. One hundred and thirty-three laboratory confirmed positive case farms were matched on the date of sample submission with 133 negative control farms. The association between a series of farm-level characteristics and the presence or absence of H9N2 was assessed by univariable analysis. Characteristics associated with H9N2 risk that passed the initial screening were included in a multivariable conditional logistic regression model. Manual and automated approaches were used, which produced similar models. Key risk factors from all approaches included selling of eggs/birds directly to live bird retail stalls, being near case/infected farms, a previous history of infectious bursal disease (IBD) on the farm and having cover on the water storage tanks. The findings of current study are in line with results of many other studies conducted in various countries to identify similar risk factors for AI subtype H9N2 infection. Enhancing protective measures and controlling risks identified in this study could reduce spread of AI subtype H9N2 and other AI viruses between poultry farms in Pakistan.

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“…On the other hand, tracing of epidemiological movements between farms conducted by the prefecture revealed that there were several companies whose farms were located inside the cluster, and risk materials and pepole, such as live chickens, vehicles and farm crews, had been moving between related farms before movement restriction was in place. Introduction of infected birds and contaminated fomites (egg trays, bird cages and farm equipment) or personnel are important risk factors for spreading the virus [1,12,17]. Therefore, it is thought that the virus was disseminated to contact farms through the movement of risk materials.…”

mentioning

confidence: 99%

Spatial Analysis of Low Pathogenic H5N2 Avian Influenza Outbreaks in Japan in 2005

Nishiguchi

Kobayashi

Ouchi³

et al. 2009

The Journal of Veterinary Medical Science

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ABSTRACT. We conducted a spatial analysis of low pathogenic H5N2 avian influenza (AI) outbreaks, that affected 41 chicken farms in Japan in 2005. A statistically significant (p=0.001) cluster of AI-positive farms was identified in the central part of Ibaraki Prefecture. Inside the AI cluster, the density was high for both chicken farms and chicken population, the proportion of layer finisher type farms was high and the farm size was large. We considered it important to take precautions for AI outbreaks in densely chicken-populated areas and to implement appropriate movement control around the affected farms to prevent transmission among farms located within small distances in the case of AI outbreaks. Spatial scan statistics are applicable in veterinary epidemiology to detection of high risk areas for animal diseases.KEY WORDS: avian influenza, cluster, spatial scan statistic.J. Vet. Med. Sci. 71 (7): [979][980][981][982] 2009 On the 26th of June 2005, a H5N2 subtype of avian influenza (AI) virus was recovered from a layer chicken flock in Ibaraki Prefecture, Japan, that showed a slight decrease in egg production. Nine more virus-positive farms and 32 seropositive farms (by haemagglutination inhibition tests) were detected over the course of 26 weeks. Since the virus strain was low in pathogenicity, with an intravenous pathogenicity index [14] of 0.0, and did not induce any particular clinical signs in the chickens of most flocks [15,16], the disease spread silently and the timing of virus introduction was unclear. This strain was considered to be newly introduced into Japan, taking into account its genetic characteristics and the results of national AI monitoring implemented periodically prior to the outbreaks [9]. Of 41 affected farms, 40 were located in Ibaraki Prefecture, approximately 60 km north of Tokyo. In this prefecture, almost all the poultry raised were chickens; 70% of these were laying hens, and 30% were broilers.When animal disease outbreaks occur, effective steps to explore the risk factors include investigation of the clustering of the affected farms and identification of their location and size. Nevertheless, it is generally difficult to recognize clusters visually when the locations of the cases and noncases (not affected by AI) are irregularly scattered. On the other hand, the Geographic Information System offers an opportunity to explore the associations between potential risk factors and disease incidence in combination with spatial analyses, and complements traditional visual approaches. Among the spatial analyses, spatial scan statistics enable researchers to locate statistically significant geographical clusters (the locations of the clusters and their size) [10]. In public health epidemiology, spatial scan statistics have been applied for detecting disease clusters to enable investigation of risk factors or planning of intervention trials [2,7,9]. On the other hand, few spatial analyses are reported in animal diseases in Japan [13], and there are no reports concerning the clustering ...

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Risk Factors for the Introduction of Avian Influenza Virus into Commercial Layer Chicken Farms During the Outbreaks Caused by a Low‐Pathogenic H5N2 Virus in Japan in 2005

Cited by 44 publications

References 12 publications

Incidence of Avian Flu Shocks on Poor Household Livelihoods of Poultry Farmers in Africa

Incidence of Avian Flu Shocks on Poor Household Livelihoods of Poultry Farmers in Africa

A Case-Control Study to Identify Risk Factors Associated with Avian Influenza Subtype H9N2 on Commercial Poultry Farms in Pakistan

Spatial Analysis of Low Pathogenic H5N2 Avian Influenza Outbreaks in Japan in 2005

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