Matched case-control study of the influence of inland waters surrounding poultry farms on avian influenza outbreaks in Japan.
Ontology highlight
ABSTRACT:
SUBMITTER: Shimizu Y
PROVIDER: S-EPMC5818671 | biostudies-literature | 2018 Feb
REPOSITORIES: biostudies-literature
Publications
Matched case-control study of the influence of inland waters surrounding poultry farms on avian influenza outbreaks in Japan.
Shimizu Yumiko Y Hayama Yoko Y Yamamoto Takehisa T Murai Kiyokazu K Tsutsui Toshiyuki T
Scientific reports 20180219 1
To successfully control highly pathogenic avian influenza (HPAI), understanding the risk factors related to the incursion of the virus into poultry farms is essential. In this study, we focused on the presence of inland waters surrounding poultry farms as a potential risk factor of incursion of the virus. To evaluate the influence of inland waters surrounding poultry farms on HPAI outbreaks in Japan, a simple matched case-control study was conducted. The results of the conditional regression ana ...[more]
Similar Datasets
Project description:BackgroundSince 2003, the H5 highly pathogenic avian influenza (HPAI) subtype has caused massive economic losses in the poultry industry in South Korea. The role of inland water bodies in avian influenza (AI) outbreaks has not been investigated. Identifying water bodies that facilitate risk pathways leading to the incursion of the HPAI virus (HPAIV) into poultry farms is essential for implementing specific precautionary measures to prevent viral transmission.ObjectivesThis matched case-control study (1:4) examined whether inland waters were associated with a higher risk of AI outbreaks in the neighboring poultry farms.MethodsRivers, irrigation canals, lakes, and ponds were considered inland water bodies. The cases and controls were chosen based on the matching criteria. The nearest possible farms located within a radius of 3 km of the case farms were chosen as the control farms. The poultry farms were selected randomly, and two HPAI epidemics (H5N8 [2014-2016] and H5N6 [2016-2017]) were studied. Conditional logistic regression analysis was applied.ResultsStatistical analysis revealed that inland waters near poultry farms were significant risk factors for AI outbreaks. The study speculated that freely wandering wild waterfowl and small animals contaminate areas surrounding poultry farms.ConclusionsPet birds and animals raised alongside poultry birds on farm premises may wander easily to nearby waters, potentially increasing the risk of AI infection in poultry farms. Mechanical transmission of the AI virus occurs when poultry farm workers or visitors come into contact with infected water bodies or their surroundings. To prevent AI outbreaks in the future, poultry farms should adopt strict precautions to avoid contact with nearby water bodies and their surroundings.
| S-EPMC9149499 | biostudies-literature
Project description:Low pathogenic avian influenza (LPAI) of subtype H9 outbreaks have been frequently occurring in major commercial hubs of Nepal including Chitwan, a central lowland area, causing substantial economic losses to the farmers. However, the risk factors associated with these outbreaks have been poorly understood, and hence, this case-control study was conducted in Chitwan, Nawalpur, and Makawanpur districts of Nepal from October 2019 to March 2020. A total of 102 farms were selected in which 51 were case farms, and 51 were controls. Case farms were avian influenza (AI)-subtype-H9-confirmed farms through polymerase chain reaction (PCR) assays on poultry samples. Control farms included farms that were AI-negative in the antigen test brought to the National Avian Disease Investigation Laboratory, Chitwan, for diagnosis during the study period. Each farm was visited to collect information using a semi-structured questionnaire. A total of 25 variables representing farm characteristics and biosecurity measures were considered as potential risk factors. The final multivariable model showed that distance of less than 0.5 km from the main road (OR = 4.04, 95% CI = 1.20-13.56, p = 0.023), distance of less than 1 km from a nearest infected farm (OR = 76.42, 95% CI = 7.17-814.06, p = 0.0003), and wild birds coming around the farm (OR = 6.12, 95% CI = 1.99-18.79, p = 0.0015) were risk factors for avian influenza type H9, whereas using apron or separate cloth inside the shed (OR = 0.109, 95% CI = 0.020-0.577, p = 0.0092) was shown to reduce the risk of farms being positive for AI subtype H9. These findings suggest that due consideration should be given to site selection while establishing the farms and the importance of implementing appropriate biosecurity measures, such as using separate cloth inside the shed and preventing the entry of wild birds inside the farm to reduce the potential risk of introduction of avian influenza type H9 to their poultry farms.
| S-EPMC9326661 | biostudies-literature
Project description:The poultry sector contributes four percent to the national GDP of Nepal. However, this sector is under threat with periodic outbreaks of Avian Influenza (AI) subtypes H5 and H9 since 2009. This has been both a public health threat and an economic issue. Since the past few years, outbreaks of AI subtype H9 have caused huge economic losses in major poultry producing areas of Nepal. However, the risk factors associated with these outbreaks have not been assessed. A retrospective case-control study was conducted from April 2018 to May 2019 to understand the risk factors associated with AI subtype H9 outbreaks in Kathmandu valley. Out of 100 farms selected, 50 were "case" farms, confirmed positive to H9 at Central Veterinary Laboratory, Kathmandu, and another 50 farms were "control" farms, matched for farm size and locality within a radius of three km from the case farm. Each farm was visited to collect information using a semi-structured questionnaire. Twelve potential risk factors were included in the questionnaire under the broad categories: birds and farm characteristics, and management and biosecurity status of the farms. Univariable and multivariable logistic regression analysis was conducted and corresponding odds ratios were calculated. Risk factors, associated with AI subtype H9 outbreaks in Kathmandu valley, identified in the final multivariable model were: "farms that have flock size greater than median flock size of study farms (>1500)" (OR = 4.41, 95% CI: 1.53-12.71, p = 0.006), "farms that did not apply rules to wear boots for visitors inside the farms" (OR = 4.32, 95% CI: 1.52-12.29, p = 0.006) and "other commercial farms located within one km periphery" (OR = 10, 95% CI: 1.8-50, p = 0.007). This study showed that outbreaks of AI subtype H9 in Kathmandu valley were associated with a higher population of birds in the farm, poor management practices, and weak biosecurity measures in poultry farms. We suggest improving management practices and increase biosecurity in the farms to reduce incidences of AI subtype H9 outbreaks in Kathmandu valley.
| S-EPMC7117692 | biostudies-literature
Project description:The development of visual tools for the timely identification of spatio-temporal clusters will assist in implementing control measures to prevent further damage. From January 2015 to June 2020, a total number of 1463 avian influenza outbreak farms were detected in Taiwan and further confirmed to be affected by highly pathogenic avian influenza subtype H5Nx. In this study, we adopted two common concepts of spatio-temporal clustering methods, the Knox test and scan statistics, with visual tools to explore the dynamic changes of clustering patterns. Since most (68.6%) of the outbreak farms were detected in 2015, only the data from 2015 was used in this study. The first two-stage algorithm performs the Knox test, which established a threshold of 7 days and identified 11 major clusters in the six counties of southwestern Taiwan, followed by the standard deviational ellipse (SDE) method implemented on each cluster to reveal the transmission direction. The second algorithm applies scan likelihood ratio statistics followed by AGC index to visualize the dynamic changes of the local aggregation pattern of disease clusters at the regional level. Compared to the one-stage aggregation approach, Knox-based and AGC mapping were more sensitive in small-scale spatio-temporal clustering.
| S-EPMC8604947 | biostudies-literature
Project description:Highly pathogenic avian influenza (HPAI) is often controlled through culling of poultry. Compensating farmers for culled chickens or ducks facilitates effective culling and control of HPAI. However, ensuing price shifts can create incentives that alter the disease dynamics of HPAI. Farmers control certain aspects of the dynamics by setting a farm size, implementing infection control measures, and determining the age at which poultry are sent to market. Their decisions can be influenced by the market price of poultry which can, in turn, be set by policy makers during an HPAI outbreak. Here, we integrate these economic considerations into an epidemiological model in which epidemiological parameters are determined by an outside agent (the farmer) to maximize profit from poultry sales. Our model exhibits a diversity of behaviors which are sensitive to (i) the ability to identify infected poultry, (ii) the average price of infected poultry, (iii) the basic reproductive number of avian influenza, (iv) the effect of culling on the market price of poultry, (v) the effect of market price on farm size, and (vi) the effect of poultry density on disease transmission. We find that under certain market and epidemiological conditions, culling can increase farm size and the total number of HPAI infections. Our model helps to inform the optimization of public health outcomes that best weigh the balance between public health risk and beneficial economic outcomes for farmers.
| S-EPMC3851691 | biostudies-literature
Project description:In recent years, different subtypes of highly pathogenic avian influenza (HPAI) viruses caused outbreaks in several poultry types worldwide. Early detection of HPAI virus infection is crucial to reduce virus spread. Previously, the use of a mortality ratio threshold to expedite notification of suspicion in layer farms was proposed. The purpose of this study was to describe the clinical signs reported in the early stages of HPAI H5N8 and H5N6 outbreaks on chicken and Pekin duck farms between 2014 and 2018 in the Netherlands and compare them with the onset of an increased mortality ratio (MR). Data on daily mortality and clinical signs from nine egg-producing chicken farms and seven Pekin duck farms infected with HPAI H5N8 (2014 and 2016) and H5N6 (2017-2018) in the Netherlands were analysed. In 12 out of 15 outbreaks for which a MR was available, MR increase preceded or coincided with the first observation of clinical signs by the farmer. In one chicken and two Pekin duck outbreaks, clinical signs were observed prior to MR increase. On all farms, veterinarians observed clinical signs of general disease. Nervous or locomotor signs were reported in all Pekin duck outbreaks, but only in two chicken outbreaks. Other clinical signs were observed less frequently in both chickens and Pekin ducks. Compared to veterinarians, farmers observed and reported clinical signs, especially respiratory and gastrointestinal signs, less frequently. This case series suggests that a MR with a set threshold could be an objective parameter to detect HPAI infection on chicken and Pekin duck farms at an early stage. Observation of clinical signs may provide additional indication for farmers and veterinarians for notifying a clinical suspicion of HPAI infection. Further assessment and validation of a MR threshold in Pekin ducks are important as it could serve as an important tool in HPAI surveillance programs.
| S-EPMC8048556 | biostudies-literature
Project description:Avian influenza (AI) is a global health obstacle of critical concern as novel viruses are capable of initiating a pandemic. Recent spillover events of AI into human populations have occurred at human-poultry food system interfaces. As Nepal's poultry sector transitions to more intensified commercial production systems, it is important to examine the epidemiology of AI and the knowledge, attitudes and practices (KAP) of poultry sector workers. We conducted a cross-sectional KAP study utilizing a structured survey to interview 150 commercial poultry farmers in Chitwan District, Nepal. All commercial poultry farmers had knowledge of AI previous to the study and the majority farmers were able to identify farm-farm and poultry-human transmission mechanisms of AI. Farmers had more knowledge surrounding poultry AI symptoms as compared to human AI symptoms. Most farmers believe that AI is serious, contagious and a threat to everyone, yet only half believe it can be prevented. Individual-level personal protective equipment (PPE) uptake, such as facemask, glove and boot usage, on the enrolled farms was low and farm-level biosecurity practices varied greatly. Nine commercial poultry farms (6%) self-reported having an HPAI outbreak and 60 farms (40%) self-reported having an LPAI outbreak in the past 5 years. Layer farms had higher odds (OR: 5.4, 95% CI: 2.3-12.8) of self-reported LPAI as compared broiler farms. Poultry sector farmers face multiple obstacles when attempting to report AI to government authorities such as the fear of flock culling and the perceived lack of monetary compensation for culling. Our study provides updated KAP surrounding AI of farmers and self-reported AI farm-level epidemiology in Nepal's highest density commercial poultry production district. Commercial poultry farmers are fairly knowledgeable on AI, but do not take further protective practice efforts to implement their knowledge and prevent AI. Due to the potential role that human-poultry interfaces may play in AI emergence, it is critical to collaborate with the commercial poultry industry when planning and conducting AI pandemic preparedness mechanisms.
| S-EPMC7772628 | biostudies-literature
Project description:Globally, outbreaks of Avian Influenza Virus (AIV) in poultry continue to burden economies and endanger human, livestock and wildlife health. Wild waterbirds are often identified as possible sources for poultry infection. Therefore, it is important to understand the ecological and environmental factors that directly influence infection dynamics in wild birds, as these factors may thereby indirectly affect outbreaks in poultry. In Australia, where large parts of the country experience erratic rainfall patterns, intense rainfalls lead to wild waterfowl breeding events at temporary wetlands and increased proportions of immunologically naïve juvenile birds. It is hypothesized that after breeding, when the temporary wetlands dry, increasing densities of immunologically naïve waterbirds returning to permanent water bodies might strongly contribute to AIV prevalence in wild waterfowl in Australia. Since rainfall has been implicated as an important environmental driver in AIV dynamics in wild waterbirds in southeast Australia and wild waterbirds are identified globally to have a role in virus spillover into poultry, we hypothesise that rainfall events have an indirect effect on AIV outbreaks in poultry in southeast Australia. In this study we investigated this hypothesis by examining the correlation between the timing of AIV outbreaks in poultry in and near the Murray-Darling basin in relation to temporal patterns in regional rainfall since 1970. Our findings support our hypothesis and suggest that the risk of AIV outbreaks in poultry increases after a period of high rainfall, with peak AIV risk two years after the onset of the high-rainfall period. This is presumably triggered by increased rates of waterbird breeding and consequent higher proportions of immunologically naïve juvenile waterbirds entering the population directly after major rainfall events, which subsequently aggregate near permanent water bodies when the landscape dries out.
| S-EPMC8439068 | biostudies-literature
Project description:Highly pathogenic avian influenza (H5N1) among wild birds emerged simultaneously with outbreaks in domestic poultry in South Korea during November 2010-May 2011. Phylogenetic analysis showed that these viruses belonged to clade 2.3.2, as did viruses found in Mongolia, the People's Republic of China, and Russia in 2009 and 2010.
| S-EPMC3309593 | biostudies-literature
Project description:Poultry can become infected with low pathogenic avian influenza (LPAI) viruses via (in)direct contact with infected wild birds or by transmission of the virus between farms. This study combines routinely collected surveillance data with genetic analysis to assess the contribution of between-farm transmission to the overall incidence of LPAI virus infections in poultry. Over a 10-year surveillance period, we identified 35 potential cases of between-farm transmission in the Netherlands, of which 10 formed geographical clusters. A total of 21 LPAI viruses were isolated from nine potential between-farm transmission cases, which were further studied by genetic and epidemiological analysis. Whole genome sequence analysis identified close genetic links between infected farms in seven cases. The presence of identical deletions in the neuraminidase stalk region and minority variants provided additional indications of between-farm transmission. Spatiotemporal analysis demonstrated that genetically closely related viruses were detected within a median time interval of 8 days, and the median distance between the infected farms was significantly shorter compared to farms infected with genetically distinct viruses (6.3 versus 69.0 km; p < 0.05). The results further suggest that between-farm transmission was not restricted to holdings of the same poultry type and not related to the housing system. Although separate introductions from the wild bird reservoir cannot be excluded, our study indicates that between-farm transmission occurred in seven of nine virologically analysed cases. Based on these findings, it is likely that between-farm transmission contributes considerably to the incidence of LPAI virus infections in poultry.
| S-EPMC6850361 | biostudies-literature