Factors affecting Chinese broiler farmers’ main preventive practices in response to highly pathogenic avian influenza

Huang, Ziyan; Zeng, Di; Wang, Jimin

doi:10.1016/j.prevetmed.2016.10.013

Cited by 12 publications

(8 citation statements)

References 27 publications

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“…In conformity with previous empirical studies' findings about animal diseases (Huang et al, ; Toma et al, ), poultry farmers who perceived higher risk of A/H5N1 were more likely to apply biosecurity means to protect poultry from A/H5N1 infection. In addition, poultry farmers who perceived higher efficacy of biosecurity measures were also more confident to adopt biosecurity measures to prevent poultry infection with A/H5N1 (Tiongco et al, ; Valeeva, Asseldonk, & Backus, ).…”

Section: Discussionsupporting

confidence: 89%

“…There have been many relevant studies focused on poultry farmers' preventive behaviours against AI. In the literature that was available, except a qualitative analysis of lay perceptions of A/H5N1 aetiology (Liao, Lam, Dang, et al, ), quantitative research dominates, and these quantitative studies focus on either the poultry farmers' behaviours protecting poultry against A/H5N1 infection (Cui & Liu, ; Huang, Zeng, & Wang, ; Tiongco, Narrod, Scott, Kobayashi, & Omiti, ) or personal protective behaviours against A/H7N9 infection (Cui, Liao, Lam, Liu, & Fielding, ) and A/H5N1 infection (Hossain, Eusufzai, Elahi, & Jamayet, ; Neupane, Khanal, Ghimire, Aro, & Leppin, ; Yu et al, ). However, the preventive behaviours and personal protective behaviours of poultry farmers occur simultaneously because of the dual risks their face.…”

Section: Introductionmentioning

confidence: 99%

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Chinese poultry farmers' decision‐making for avian influenza prevention: a qualitative analysis

Cui

Wang

et al. 2019

Zoonoses and Public Health

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Poultry farmers faced dual risk when mutant avian influenza (AI) virus showed the zoonotic characteristics. A/H5N1 and A/H7N9 were two dominant AI virus strains that have captured the attention of the public over the years for they have been reported to bring about greater loss to poultry and human, respectively. Previous studies mainly used quantitative methods investigating either the means that poultry farmers adopted for protecting their poultry against A/H5N1 infection or the poultry farmers' self‐protective behaviours against A/H7N9 infection. We sought insights into the underlying factors influencing Chinese poultry farmers' protective behaviours in response to the dual risk of AI by a qualitative way. Semi‐structured in‐depth interviews were conducted with 25 Chinese chicken farmers recruited by purposive sampling between November 2016 and May 2017, the peak season of AI. All interviews were audio‐taped, transcribed and analysed using a grounded theory approach. From participants' experiences, we revealed five main themes: Measures adopted for protecting poultry and farmers, Emotional response to the AI epidemic, Perceived risk of AI, Perceived effectiveness of the preventive measures adopted and Perceived self‐efficacy to take preventive measures. The information of AI outbreak directly triggered Chinese chicken farmers' emotional response and thereafter preventive actions. Compared to the perceived risk of poultry infection with A/H5N1 which mainly connected to economic loss, participants perceived much lower risk of human infection with A/H7N9. AI epidemic information played a key role triggering poultry farmers' response behaviours. Chinese poultry farmers weighted more attention on the risk of poultry infection which was highly associated with economic losses. The government should build and improve an early AI warning and information transmission network to poultry farmers. Further reinforcement of related self‐protective and preventive knowledge training towards poultry farmers is necessary.

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Section: Discussionsupporting

confidence: 89%

Section: Introductionmentioning

confidence: 99%

Chinese poultry farmers' decision‐making for avian influenza prevention: a qualitative analysis

Cui

Wang

et al. 2019

Zoonoses and Public Health

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“…To construct strategies to control diseases, the identification of timely risk factors in outbreaks is important (Lewallen & Courtright, 1998). Previous avian influenza epidemiologic studies have identified several risk factors from a variety of settings and countries (Abbas, Wilking, Horeth-Bontgen, & Conraths, 2012;Arriola et al, 2015;Beaudoin et al, 2014;Biswas et al, 2011;Boender et al, 2007;Bui, Gardner, MacIntyre, & Sarkar, 2017;Cao et al, 2010;Chaudhry, Rashid, Thrusfield, Welburn, & Bronsvoort, 2015;Desvaux et al, 2011;Dinh et al, 2006;Fang et al, 2008;Fasina, Rivas, Bisschop, Stegeman, & Hernandez, 2011;Gale et al, 2014;Garber et al, 2016;Gilbert et al, 2006;Henning et al, 2009;Huang, Zeng, & Wang, 2016;Iglesias, Jesus Munoz, Martinez, & de la Torre, 2010;Kung et al, 2007;Liu et al, 2015;Lohiniva et al, 2013;Loth, Gilbert, Osmani, Kalam, & Xiao, 2010;Mannelli, Ferre, & Marangon, 2006;Martin et al, 2011;McQuiston et al, 2005;Metras et al, 2013;Mounts et al, 1999;Musa, Abdu, Sackey, & Oladele, 2013;Nishiguchi et al, 2007;Osmani et al, 2014;Paul et al, 2011;Tenzin, Wangdi, & Rai, 2017;Thomas et al, 2005;Thompson, Sinclair, & Ganzevoort, 2008;…”

Section: Introductionmentioning

confidence: 99%

“…To construct strategies to control diseases, the identification of timely risk factors in outbreaks is important (Lewallen & Courtright, ). Previous avian influenza epidemiologic studies have identified several risk factors from a variety of settings and countries (Abbas, Wilking, Horeth‐Bontgen, & Conraths, ; Arriola et al., ; Beaudoin et al., ; Biswas, Christensen, Ahmed, Barua, et al., ; Biswas, Christensen, Ahmed, Das, et al., ; Biswas et al., ; Boender et al., ; Bui, Gardner, MacIntyre, & Sarkar, ; Cao et al., ; Chaudhry, Rashid, Thrusfield, Welburn, & Bronsvoort, ; Desvaux et al., ; Dinh et al., ; Fang et al., ; Fasina, Rivas, Bisschop, Stegeman, & Hernandez, ; Gale et al., ; Garber et al., ; Gilbert et al., ; Henning et al., ; Huang, Zeng, & Wang, ; Iglesias, Jesus Munoz, Martinez, & de la Torre, ; Kung et al., ; Liu et al., ; Lohiniva et al., ; Loth, Gilbert, Osmani, Kalam, & Xiao, ; Mannelli, Ferre, & Marangon, ; Martin et al., ; McQuiston et al., ; Metras et al., ; Mounts et al., ; Musa, Abdu, Sackey, & Oladele, ; Nishiguchi et al., ; Osmani et al., ; Paul et al., ; Tenzin, Wangdi, & Rai, ; Thomas et al., ; Thompson, Sinclair, & Ganzevoort, ; Tiensin et al., ; Tombari et al., ; Tsukamoto et al., ; Vong et al., ; Wang et al., ; Wang et al., ; Ward, Maftei, Apostu, & Suru, ; Zhang et al., ; Zhou et al., ). However, most risk factor studies are based on the HPAI subtype H5N1.…”

Section: Introductionmentioning

confidence: 99%

Risk factors associated with highly pathogenic avian influenza subtype H5N8 outbreaks on broiler duck farms in South Korea

Kim

et al. 2018

Transbound Emerg Dis

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Highly Pathogenic Avian Influenza (HPAI) subtype H5N8 outbreaks occurred in poultry farms in South Korea in 2014 resulting in significant damage to the poultry industry. Between 2014 and 2016, the pandemic disease caused significant economic loss and social disruption. To evaluate the risk factors for HPAI infection in broiler duck farms, we conducted a retrospective case-control study on broiler duck farms. Forty-three farms with confirmed laboratories on premises were selected as the case group, and 43 HPAI-negative farms were designated as the control group. Control farms were matched based on farm location and were within a 3-km radius from the case premises. Spatial and environmental factors were characterized by site visit and plotted through a geographic information system (GIS). Univariable and multivariable logistic regression models were developed to assess possible risk factors associated with HPAI broiler duck farm infection. Four final variables were identified as risk factors in a final multivariable logistic model: "Farms with ≥7 flocks" (odds ratio [OR] = 6.99, 95% confidence interval [CI] 1.34-37.04), "Farm owner with ≥15 years of raising poultry career" (OR = 7.91, 95% CI 1.69-37.14), "Presence of any poultry farms located within 500 m of the farm" (OR = 6.30, 95% CI 1.08-36.93) and "Not using a faecal removal service" (OR = 27.78, 95% CI 3.89-198.80). This highlights that the HPAI H5N8 outbreaks in South Korea were associated with farm owner education, number of flocks and facilities and farm biosecurity. Awareness of these factors may help to reduce the spread of HPAI H5N8 across broiler duck farms in Korea during epidemics. Greater understanding of the risk factors for H5N8 may improve farm vulnerability to HPAI and other subtypes and help to establish policies to prevent re-occurrence. These findings are relevant to global prevention recommendations and intervention protocols.

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“…In the research in Chapter 6, I accounted for the most important characteristics of study participants, however, some other confounding factors (e.g. personal income [303,304], place of residence [182,305]) were not captured which may also have contributed to differences in KAP towards AI observed among difference groups. In the research in Chapter 7, I controlled for poultry surveillance data, live chicken movements and sociodemographic factors that are related to H7N9 human infections.…”

Section: Confounding Factorsmentioning

confidence: 99%

Spatial risk assessment of the zoonotic influenza A (H7N9) along the live meat chicken market chain in Southeast China

Zhou¹

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Introduction:A new reassortant avian influenza A (H7N9) virus of low pathogenicity to poultry emerged in eastern provinces of China in early 2013. There have been five epidemic waves causing more than 1600 human infections in 29 provinces and municipalities in mainland China till May 2018.Exposure to H7N9 infected live meat chickens at live bird markets (LBMs) within the affected provinces was suggested to be the main risk factor for human infection. Previous studies demonstrated the role of poor biosecurity measures at poultry farms and LBMs and the role of live poultry trade in the dissemination of avian influenza (AI) virus. However, the continued and increasing number of reported human H7N9 cases throughout China indicated that vulnerabilities linked to the live meat chicken market chain remain, that need to be elucidated in order to better design surveillance programmes and health promotion interventions to prevent poultry and human exposure along the live meat chicken market chain. Aims:The overall aim of the research in this thesis is to define the risks of sustained transmission of H7N9 virus along the live meat chicken market chain in eastern China. To meet the aim, studies were sequentially designed with the following specific objectives: 1) identify the effect of market-level risk factors on avian influenza infections in poultry and humans and generate evidence that will inform avian influenza prevention and control programs at LBMs; 2) to understand the role of live poultry movement and live bird market biosecurity in the epidemiology of H7N9 during the emergency; 3) to understand the level of knowledge, attitudes and practices (KAP) on avian influenza of different actors along the live meat chicken market chain and the risk factors associated with their KAP levels; 4) to develop a spatial risk assessment model of the live chicken market chain within the H7N9 high risk area, to provide essential evidence and recommendations for risk-based AI surveillance programs and appropriate enhancements to current prevention and control policies for H7N9 in the study area. Methods:To address each of the specific objectives four studies have been designed. Firstly, we performed a systematic literature review and estimated the pooled odds ratios of biosecurity indicators relating to human and poultry AI infections at market level using a quality effects meta-analysis model. Secondly, we identified the biosecurity risk factors associated with the H7N9 presence in the surveyed LBMs in the affected provinces during the H7N9 emergency response. We also used social network analysis and spatial analysis to quantify the connectivity of counties in Eastern china via live poultry movements and identify highly connected areas associated with human cases. Then, to quantify differences in KAP of AI among different actors (chicken farmers, live chicken vendors and consumers at LBMs) along the live chicken market chain operating within the areas in the Eastern provinces (i.e.ii Shanghai, Jiangsu, and Anhui) identified in the pre...

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Factors affecting Chinese broiler farmers’ main preventive practices in response to highly pathogenic avian influenza

Cited by 12 publications

References 27 publications

Chinese poultry farmers' decision‐making for avian influenza prevention: a qualitative analysis

Chinese poultry farmers' decision‐making for avian influenza prevention: a qualitative analysis

Risk factors associated with highly pathogenic avian influenza subtype H5N8 outbreaks on broiler duck farms in South Korea

Spatial risk assessment of the zoonotic influenza A (H7N9) along the live meat chicken market chain in Southeast China

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