Risk factors for highly pathogenic H7N1 avian influenza virus infection in poultry during the 1999–2000 epidemic in Italy

Investigating the uses of machine learning algorithms to inform risk factor analyses: The example of avian infectious bronchitis virus (IBV) in broiler chickens

Infectious bronchitis virus (IBV) is a contagious coronavirus causing respiratory and urogenital disease in chickens and is responsible for significant economic losses for both the broiler and table egg layer industries. Despite IBV being regularly monitored using standard epidemiologic surveillance practices, knowledge and evidence of risk factors associated with IBV transmission remain limited. The study objective was to compare risk factor modeling outcomes between a traditional stepwise variable selection approach and a machine learning-based random forest Boruta algorithm using routinely collected IBV antibody titer data from broiler flocks. IBV antibody sampling events (n = 1111) from 166 broiler sites between 2016 and 2021 were accessed. Ninety-two geospatial-related and poultry-density variables were obtained using a geographic information system and data sets from publicly available sources. Seventeen and 27 candidate variables were screened to potentially have an association with elevated IBV antibody titers according to the manual selection and machine learning algorithm, respectively. Selected variables from both methods were further investigated by construction of multivariable generalized mixed logistic regression models. Six variables were shortlisted by both screening methods, which included year, distance to urban areas, main roads, landcover, density of layer sites and year, however, final models for both approaches only shared year as an important predictor. Despite limited significance of clinical outcomes, this work showcases the potential of a novel explorative modeling approach in combination with often unutilized resources such as publicly available geospatial data, surveillance health data and machine learning as potential supplementary tools to investigate risk factors related to infectious diseases.

A systematic review of mechanistic models used to study avian influenza virus transmission and control

The global spread of avian influenza A viruses in domestic birds is causing increasing socioeconomic devastation. Various mechanistic models have been developed to better understand avian influenza transmission and evaluate the effectiveness of control measures in mitigating the socioeconomic losses caused by these viruses. However, the results of models of avian influenza transmission and control have not yet been subject to a comprehensive review. Such a review could help inform policy makers and guide future modeling work. To help fill this gap, we conducted a systematic review of the mechanistic models that have been applied to field outbreaks. Our three objectives were to: (1) describe the type of models and their epidemiological context, (2) list estimates of commonly used parameters of low pathogenicity and highly pathogenic avian influenza transmission, and (3) review the characteristics of avian influenza transmission and the efficacy of control strategies according to the mechanistic models. We reviewed a total of 46 articles. Of these, 26 articles estimated parameters by fitting the model to data, one evaluated the effectiveness of control strategies, and 19 did both. Values of the between-individual reproduction number ranged widely: from 2.18 to 86 for highly pathogenic avian influenza viruses, and from 4.7 to 45.9 for low pathogenicity avian influenza viruses, depending on epidemiological settings, virus subtypes and host species. Other parameters, such as the durations of the latent and infectious periods, were often taken from the literature, limiting the models' potential insights. Concerning control strategies, many models evaluated culling (n = 15), while vaccination received less attention (n = 6). According to the articles reviewed, optimal control strategies varied between virus subtypes and local conditions, and depended on the overall objective of the intervention. For instance, vaccination was optimal when the objective was to limit the overall number of culled flocks. In contrast, pre-emptive culling was preferred for reducing the size and duration of an epidemic. Early implementation consistently improved the overall efficacy of interventions, highlighting the need for effective surveillance and epidemic preparedness.

Investigation of risk factors for introduction of highly pathogenic avian influenza H5N1 infection among commercial turkey operations in the United States, 2022: a case-control study

Introduction

The 2022-2023 highly pathogenic avian influenza (HPAI) H5N1 outbreak in the United States (U.S.) is the largest and most costly animal health event in U.S. history. Approximately 70% of commercial farms affected during this outbreak have been turkey farms.

Methods

We conducted a case-control study to identify potential risk factors for introduction of HPAI virus onto commercial meat turkey operations. Data were collected from 66 case farms and 59 control farms in 12 states. Univariate and multivariable analyses were conducted to compare management and biosecurity factors on case and control farms.

Results

Factors associated with increased risk of infection included being in an existing control zone, having both brooders and growers, having toms, seeing wild waterfowl or shorebirds in the closest field, and using rendering for dead bird disposal. Protective factors included having a restroom facility, including portable, available to crews that visit the farm and workers having access and using a shower at least some of the time when entering a specified barn.

Discussion

Study results provide a better understanding of risk factors for HPAI infection and can be used to inform prevention and control measures for HPAI on U.S. turkey farms.

Investigation of risk factors for introduction of highly pathogenic avian influenza H5N1 virus onto table egg farms in the United States, 2022: a case-control study

INTRODUCTION

The 2022-2023 highly pathogenic avian influenza (HPAI) H5N1 outbreak in the United States (U.S.) is the most geographically extensive and costly animal health event in U.S. history. In 2022 alone, over 57 million commercial and backyard poultry in 47 U.S. states were affected. Over 75% of affected poultry were part of the commercial table egg production sector.

METHODS

We conducted a case-control study to identify potential risk factors for introduction of HPAI virus onto commercial table egg operations. Univariate and multivariable analyses were conducted to compare farm characteristics, management, and biosecurity factors on case and control farms.

RESULTS

Factors associated with increased risk of infection included being in an existing control zone, sightings of wild waterfowl, mowing or bush hogging vegetation less than 4 times a month, having an off-site method of daily mortality disposal (off-site composting or burial, rendering, or landfill), and wild bird access to feed/feed ingredients at least some of the time. Protective factors included a high level of vehicle washing for trucks and trailers entering the farm (a composite variable that included having a permanent wash station), having designated personnel assigned to specific barns, having a farm entrance gate, and requiring a change of clothing for workers entering poultry barns.

DISCUSSION

Study results improve our understanding of risk factors for HPAI infection and control measures for preventing HPAI on commercial U.S. table egg farms.

Integration of Epidemiological and Genomic Data to Investigate H5N1 HPAI Outbreaks in Northern Italy in 2021-2022

Between October 2021 and April 2022, 317 outbreaks caused by highly pathogenic avian influenza (HPAI) H5N1 viruses were notified in poultry farms in the northeastern Italian regions. The complete genomes of 214 strains were used to estimate the genetic network based on the similarity of the viruses. An exponential random graph model (ERGM) was used to assess the effect of 'at-risk contacts', 'same owners', 'in-bound/out-bound risk windows overlap', 'genetic differences', 'geographic distances', 'same species', and 'poultry company' on the probability of observing a link within the genetic network, which can be interpreted as the potential propagation of the epidemic via lateral spread or a common source of infection. The variables 'same poultry company' (Est. = 0.548, C.I. = [0.179; 0.918]) and 'risk windows overlap' (Est. = 0.339, C.I. = [0.309; 0.368]) were associated with a higher probability of link formation, while the 'genetic differences' (Est. = -0.563, C.I. = [-0.640; -0.486]) and 'geographic distances' (Est. = -0.058, C.I. = [-0.078; -0.038]) indicated a reduced probability. The integration of epidemiological data with genomic analyses allows us to monitor the epidemic evolution and helps to explain the dynamics of lateral spreads casting light on the potential diffusion routes. The 2021-2022 epidemic stresses the need to further strengthen the biosecurity measures, and to encourage the reorganization of the poultry production sector to minimize the impact of future epidemics.

Epidemiological Features of the Highly Pathogenic Avian Influenza Virus H5N1 in a Densely Populated Area of Lombardy (Italy) during the Epidemic Season 2021–2022

In the last two years, there have been three major epidemic seasons in the territory of the European Union and the HPAI epizootic in 2021–2022 is the most severe in recent history. In Italy, the disease was introduced to dense poultry areas with serious economic consequences for the entire sector. In Lombardy, the analysis of the risk factors was carried out, also taking into account the density of domestic birds. In the most affected areas, 66.7% of the outbreaks occurred in the areas with the highest poultry density and the likelihood of an outbreak occurring increased with an increase in the density of birds per km². In cells 10 × 10 km with a density greater than 10,000 birds/km², the probability of outbreak occurrence was over 66.7%. The provinces involved in the last epidemic were the same involved in previous epidemics and, given the risk factors present in the area, it is plausible that the risk remains high also for future epidemic seasons. Therefore, to avoid the repetition of similar events, certain control measures shall be strengthened and vaccination considered as a complementary tool for the control of HPAI virus in risk areas.

Avian influenza overview December 2021 - March 2022

Between 9 December 2021 and 15 March 2022, 2,653 highly pathogenic avian influenza (HPAI) virus detections were reported in 33 EU/EEA countries and the UK in poultry (1,030), in wild (1,489) and in captive birds (133). The outbreaks in poultry were mainly reported by France (609), where two spatiotemporal clusters have been identified since October 2021, followed by Italy (131), Hungary (73) and Poland (53); those reporting countries accounted together for 12.8 of the 17.5 million birds that were culled in the HPAI affected poultry establishments in this reporting period. The majority of the detections in wild birds were reported by Germany (767), the Netherlands (293), the UK (118) and Denmark (74). HPAI A(H5) was detected in a wide range of host species in wild birds, indicating an increasing and changing risk for virus incursion into poultry farms. The observed persistence and continuous circulation of HPAI viruses in migratory and resident wild birds will continue to pose a risk for the poultry industry in Europe for the coming months. This requires the definition and the rapid implementation of suitable and sustainable HPAI mitigation strategies such as appropriate biosecurity measures, surveillance plans and early detection measures in the different poultry production systems. The results of the genetic analysis indicate that the viruses currently circulating in Europe belong to clade 2.3.4.4b. Some of these viruses were also detected in wild mammal species in the Netherlands, Slovenia, Finland and Ireland showing genetic markers of adaptation to replication in mammals. Since the last report, the UK reported one human infection with A(H5N1), China 17 human infections with A(H5N6), and China and Cambodia 15 infections with A(H9N2) virus. The risk of infection for the general population in the EU/EEA is assessed as low, and for occupationally exposed people, low to medium.

Machine learning-driven dynamic risk prediction for highly pathogenic avian influenza at poultry farms in Republic of Korea: Daily risk estimation for individual premises

Highly pathogenic avian influenza (HPAI) is a fatal zoonotic disease that damages the poultry industry and endangers human lives via exposure to the pathogen. A risk assessment model that precisely predicts high-risk groups and occurrence of HPAI infection is essential for effective biosecurity measures that minimize the socio-economic losses of massive outbreaks. However, the conventional risk prediction approaches have difficulty incorporating the broad range of factors associated with HPAI infections at poultry holdings. Therefore, it is difficult to accommodate the complexity of the dynamic transmission mechanisms and generate risk estimation on a real-time basis. We proposed a continuous risk prediction framework for HPAI occurrences that used machine learning algorithms (MLAs). This integrated environmental, on-farm biosecurity, meteorological, vehicle movement tracking, and HPAI wild bird surveillance data to improve accuracy and timeliness. This framework consisted of (i) the generation of 1788 predictors from six types of data and reconstructed them with an outcome variable into a data mart based on a temporal assumption (i.e. infected period and day-ahead forecasting); (ii) training of the predictors with the temporally rearranged outcome variable that corresponded to HPAI H5N6 infected state at each individual farm on daily basis during the 2016-2017 HPAI epidemic using three different MLAs [Random Forest, Gradient Boosting Machine (GBM), and eXtreme Gradient Boosting]; (iii) predicting the daily risk of HPAI infection during the 2017-2018 HPAI epidemic using the pre-trained MLA models for each farm across the country. The models predicted the high risk to 8-10 out of 19 infected premises during the infected period in advance. The GBM MLAs outperformed the 7-day forecasting of HPAI prediction at individual poultry holdings, with an area under the curve (AUC) of receiver operating characteristic of 0.88. Therefore, this approach enhances the flexibility and timing of interventions against HPAI outbreaks at poultry farms.

Avian influenza overview September - December 2021

Between 16 September and 8 December 2021, 867 highly pathogenic avian influenza (HPAI) virus detections were reported in 27 EU/EEA countries and the UK in poultry (316), in wild (523) and in captive birds (28). The detections in poultry were mainly reported by Italy (167) followed by Hungary and Poland (35 each). Tha majority of the detections in wild birds were reported by Germany (280), Netherlands (65) and United Kingdom (53). The observed persistence and continuous circulation of HPAI viruses in migratory and resident wild birds will continue to pose a risk for the poultry industry in Europe for the coming months. The frequent occurrence of HPAI A(H5) incursions in commercial farms (including poultry production types considered at low avian influenza risk) raises concern about the capacity of the applied biosecurity measures to prevent virus introduction. Short-term preparedness and medium- and long-term prevention strategies, including revising and reinforcing biosecurity measures, reduction of the density of commercial poultry farms and possible appropriate vaccination strategies, should be implemented. The results of the genetic analysis indicate that the viruses characterised during this reporting period belong to clade 2.3.4.4b. Some of the characterized HPAI A(H5N1) viruses detected in Sweden, Germany, Poland and United Kingdom are related to the viruses which have been circulating in Europe since October 2020; in North, Central, South and East Europe novel reassortant A(H5N1) virus has been introduced starting from October 2021. HPAI A(H5N1) was also detected in wild mammal species in Sweden, Estonia and Finland; some of these strains characterised so far present an adaptive marker that is associated with increased virulence and replication in mammals. Since the last report, 13 human infections due to HPAI A(H5N6) and two human cases due to LPAI A(H9N2) virus have been reported from China. Some of these A(H5N6) cases were caused by a reassortant virus of clade 2.3.4.4b, which possessed an HA gene closely related to the A(H5) viruses circulating in Europe. The risk of infection for the general population in the EU/EEA is assessed as low, and for occupationally exposed people, low to medium, with large uncertainty due to the high diversity of circulating viruses in the bird populations.

Two-stage algorithms for visually exploring spatio-temporal clustering of avian influenza virus outbreaks in poultry farms

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.

Risk mapping of highly pathogenic avian influenza H5 during 2012-2017 in Taiwan with spatial bayesian modelling: Implications for surveillance and control policies

During 2012-2017, a total of 1,144 highly pathogenic avian influenza (HPAI) H5 outbreaks were reported in Taiwan. We conjectured the current 3-km radius of the post-outbreak containment policy could fail to effectively alleviate the current ongoing epidemics of HPAI H5 in Taiwan. The high intensity of localized transmission of HPAI H5 at certain focal hotspots was identified to follow the spatial distribution of poultry-raising locations through our hotspot analyses on the HPAI H5 outbreak locations from 2015 to 2017. We then applied 3-, 5- and 7-km circular buffer zones to 15,444 registered poultry-raising locations to inspect the characteristics of the poultry-raising neighbourhood. Three spatial regression models using Bayesian inference were established to infer the risks attributable to poultry-raising characteristics in the corresponding buffer areas. The different buffer radii were treated as a sensitivity analysis of the influential range of neighbouring farms on the HPAI H5 outbreak occurrence, so as to evaluate the effective radius for post-outbreak containment. Evidence showed that the risks of outbreak occurrence were associated with increasing numbers of poultry-raising locations in both 3-km (relative risk [RR] 1.005, 95% confidence interval [CI] 1.002-1.008) and 5-km buffer areas (RR 1.005, 95% CI 1.004-1.007), whereas in the 7-km buffer model, no association between densely populated locations and increasing risks of outbreaks was observed (RR 1.000, 95% CI 0.999-1.001). Therefore, an extension to a 7-km radius for the post-outbreak containment policy (rather than a 3-km radius as in the current policy) is recommended to effectively mitigate further spreading of HPAI H5 outbreaks among neighbouring farms. Overall, we demonstrated that the densely populated locations with multiple poultry species raised in proximity as defined with 3-, 5- and 7-km buffer areas facilitated H5 HPAI outbreak diffusion and shaped the scale of HPAI H5 epidemics in Taiwan.

Spatiotemporal reconstruction and transmission dynamics during the 2016-17 H5N8 highly pathogenic avian influenza epidemic in Italy

Effective control of avian diseases in domestic populations requires understanding of the transmission dynamics facilitating viral emergence and spread. In 2016-17, Italy experienced a significant avian influenza epidemic caused by a highly pathogenic A(H5N8) virus, which affected domestic premises housing around 2.7 million birds, primarily in the north-eastern regions with the highest density of poultry farms (Lombardy, Emilia-Romagna and Veneto). We perform integrated analyses of genetic, spatiotemporal and host data within a Bayesian phylogenetic framework. Using continuous and discrete phylogeography, we estimate the locations of movements responsible for the spread and persistence of the epidemic. The information derived from these analyses on rates of transmission between regions through time can be used to assess the success of control measures. Using an approach based on phylogenetic-temporal distances between domestic cases, we infer the presence of cryptic wild bird-mediated transmission, information that can be used to complement existing epidemiological methods for distinguishing transmission within the domestic population from incursions across the wildlife-domestic interface, a common challenge in veterinary epidemiology. Spatiotemporal reconstruction of the epidemic reveals a highly skewed distribution of virus movements with a high proportion of shorter distance local movements interspersed with occasional long-distance dispersal events associated with wild birds. We also show how such inference be used to identify possible instances of human-mediated movements where distances between phylogenetically linked domestic cases are unusually high.

Evaluation of strategies using simulation model to control a potential outbreak of highly pathogenic avian influenza among poultry farms in Central Luzon, Philippines

The Philippines confirmed its first epidemic of Highly Pathogenic Avian Influenza (HPAI) on August 11, 2017. It ended in November of 2017. Despite the successful management of the epidemic, reemergence is a continuous threat. The aim of this study was to conduct a mathematical model to assess the spatial transmission of HPAI among poultry farms in Central Luzon. Different control strategies and the current government protocol of 1 km radius pre-emptive culling (PEC) from infected farms were evaluated. The alternative strategies include 0.5km PEC, 1.5km PEC, 2 km PEC, 2.5 km PEC, and 3 km PEC, no pre-emptive culling (NPEC). The NPEC scenario was further modeled with a time of government notification set at 24hours, 48 hours, and 72 hours after the detection. Disease spread scenarios under each strategy were generated using an SEIR (susceptible-exposed-infectious-removed) stochastic model. A spatial transmission kernel was calculated and used to represent all potential routes of infection between farms. We assumed that the latent period occurs between 1–2 days, disease detection at 5–7 days post-infection, notification of authorities at 5–7 days post-detection and start of culling at 1–3 days post notification. The epidemic scenarios were compared based on the number of infected farms, the total number of culled farms, and the duration of the epidemic. Our results revealed that the current protocol is the most appropriate option compared with the other alternative interventions considered among farms with reproductive ratio (R_i) > 1. Shortening the culling radius to 0.5 km increased the duration of the epidemic. Further increase in the PEC zone decreased the duration of the epidemic but may not justify the increased number of farms to be culled. Nonetheless, the no-pre-emptive culling (NPEC) strategy can be an effective alternative to the current protocol if farm managers inform the government immediately within 24 hours of observation of the presence of HPAI in their farms. Moreover, if notification is made on days 1–3 after the detection, the scale and length of the outbreak have been significantly reduced. In conclusion, this study provided a comparison of various control measures for confronting the spread of HPAI infection using the simulation model. Policy makers can use this information to enhance the effectiveness of the current control strategy.

Ecological factors associated with persistent circulation of multiple highly pathogenic avian influenza viruses among poultry farms in Taiwan during 2015-17

Emergence and intercontinental spread of highly pathogenic avian influenza A (HPAI) H5Nx virus clade 2.3.4.4 has resulted in substantial economic losses to the poultry industry in Asia, Europe, and North America. The long-distance migratory birds have been suggested to play a major role in the global spread of avian influenza viruses during this wave of panzootic outbreaks since 2013. Poultry farm epidemics caused by multiple introduction of different HPAI novel subtypes of clade 2.3.4.4 viruses also occurred in Taiwan between 2015 and 2017. The mandatory and active surveillance detected H5N3 and H5N6 circulation in 2015 and 2017, respectively, while H5N2 and H5N8 were persistently identified in poultry farms since their first arrival in 2015. This study intended to assess the importance of various ecological factors contributed to the persistence of HPAI during three consecutive years. We used satellite technology to identify the location of waterfowl flocks. Four risk factors consistently showed strong association with the spatial clustering of H5N2 and H5N8 circulations during 2015 and 2017, including high poultry farm density (aOR:17.46, 95%CI: 5.91–74.86 and 8.23, 95% CI: 2.12–54.86 in 2015 and 2017, respectively), poultry heterogeneity index (aOR of 12.28, 95%CI: 5.02–31.14 and 2.79, 95%CI: 1.00–7.69, in 2015 and 2017, respectively), non-registered waterfowl flock density (aOR: 6.8, 95%CI: 3.41–14.46 and 9.17, 95%CI: 3.73–26.20, in 2015 and 2017, respectively) and higher percentage of cropping land coverage (aOR of 1.36, 95%CI: 1.10–1.69 and 1.04, 95%CI: 1.02–1.07, in 2015 and 2017, respectively). Our study highlights the application of remote sensing and clustering analysis for the identification and characterization of environmental factors in facilitating and contributing to the persistent circulation of certain subtypes of H5Nx in poultry farms in Taiwan.

Phylodynamic analysis and evaluation of the balance between anthropic and environmental factors affecting IBV spreading among Italian poultry farms

Infectious bronchitis virus (IBV) control is mainly based on wide vaccine administration. Although effective, its efficacy is not absolute, the viral circulation is not prevented and some side effects cannot be denied. Despite this, the determinants of IBV epidemiology and the factors affecting its circulation are still largely unknown and poorly investigated. In the present study, 361 IBV QX (the most relevant field genotype in Italy) sequences were obtained between 2012 and 2016 from the two main Italian integrated poultry companies. Several biostatistical and bioinformatics approaches were used to reconstruct the history of the QX genotype in Italy and to assess the effect of different environmental, climatic and social factors on its spreading patterns. Moreover, two structured coalescent models were considered in order to investigate if an actual compartmentalization occurs between the two integrated poultry companies and the role of a third "ghost" deme, representative of minor industrial poultry companies and the rural sector. The obtained results suggest that the integration of the poultry companies is an effective barrier against IBV spreading, since the strains sampled from the two companies formed two essentially-independent clades. Remarkably, the only exceptions were represented by farms located in the high densely populated poultry area of Northern Italy. The inclusion of a third deme in the model revealed the likely role of other poultry companies and rural farms (particularly concentrated in Northern Italy) as sources of strain introduction into one of the major poultry companies, whose farms are mainly located in the high densely populated poultry area of Northern Italy. Accordingly, when the effect of different environmental and urban parameters on IBV geographic spreading was investigated, no factor seems to contribute to IBV dispersal velocity, being poultry population density the only exception. Finally, the different viral population pattern observed in the two companies over the same time period supports the pivotal role of management and control strategies on IBV epidemiology. Overall, the present study results stress the crucial relevance of human action rather than environmental factors, highlighting the direct benefits that could derive from improved management and organization of the poultry sector on a larger scale.

A review of knowledge discovery process in control and mitigation of avian influenza

In the last several decades, avian influenza virus has caused numerous outbreaks around the world. These outbreaks pose a significant threat to the poultry industry and also to public health. When an avian influenza (AI) outbreak occurs, it is critical to make informed decisions about the potential risks, impact, and control measures. To this end, many modeling approaches have been proposed to acquire knowledge from different sources of data and perspectives to enhance decision making. Although some of these approaches have shown to be effective, they do not follow the process of knowledge discovery in databases (KDD). KDD is an iterative process, consisting of five steps, that aims at extracting unknown and useful information from the data. The present review attempts to survey AI modeling methods in the context of KDD process. We first divide the modeling techniques used in AI into two main categories: data-intensive modeling and small-data modeling. We then investigate the existing gaps in the literature and suggest several potential directions and techniques for future studies. Overall, this review provides insights into the control of AI in terms of the risk of introduction and spread of the virus.

Integration of genetic and epidemiological data to infer H5N8 HPAI virus transmission dynamics during the 2016-2017 epidemic in Italy

Between October 2016 and December 2017, several European Countries had been involved in a massive Highly Pathogenic Avian Influenza (HPAI) epidemic sustained by H5N8 subtype virus. Starting on December 2016, also Italy was affected by H5N8 HPAI virus, with cases occurring in two epidemic waves: the first between December 2016 and May 2017, and the second in July-December 2017. Eighty-three outbreaks were recorded in poultry, 67 of which (80.72%) occurring in the second wave. A total of 14 cases were reported in wild birds. Epidemiological information and genetic analyses were conjointly used to get insight on the spread dynamics. Analyses indicated multiple introductions from wild birds to the poultry sector in the first epidemic wave, and noteworthy lateral spread from October 2017 in a limited geographical area with high poultry densities. Turkeys, layers and backyards were the mainly affected types of poultry production. Two genetic sub-groups were detected in the second wave in non-overlapping geographical areas, leading to speculate on the involvement of different wild bird populations. The integration of epidemiological data and genetic analyses allowed to unravel the transmission dynamics of H5N8 virus in Italy, and could be exploited to timely support in implementing tailored control measures.

Spatial transmission of H5N2 highly pathogenic avian influenza between Minnesota poultry premises during the 2015 outbreak

The spatial spread of highly pathogenic avian influenza (HPAI) H5N2 during the 2015 outbreak in the U.S. state of Minnesota was analyzed through the estimation of a spatial transmission kernel, which quantifies the infection hazard an infectious premises poses to an uninfected premises some given distance away. Parameters were estimated using a maximum likelihood method for the entire outbreak as well as for two phases defined by the daily number of newly detected HPAI-positive premises. The results indicate both a strong dependence of the likelihood of transmission on distance and a significant distance-independent component of outbreak spread for the overall outbreak. The results further suggest that HPAI spread differed during the later phase of the outbreak. The estimated spatial transmission kernel was used to compare the Minnesota outbreak with previous HPAI outbreaks in the Netherlands and Italy to contextualize the Minnesota transmission kernel results and make additional inferences about HPAI transmission during the Minnesota outbreak. Lastly, the spatial transmission kernel was used to identify high risk areas for HPAI spread in Minnesota. Risk maps were also used to evaluate the potential impact of an early marketing strategy implemented by poultry producers in a county in Minnesota during the outbreak, with results providing evidence that the strategy was successful in reducing the potential for HPAI spread.

Scoring biosecurity in European conventional broiler production

Good biosecurity procedures are crucial for healthy animal production. The aim of this study was to quantify the level of biosecurity on conventional broiler farms in Europe, following a standardized procedure, thereby trying to identify factors that are amenable to improvement. The current study used a risk-based weighted scoring system (biocheck.ugent ®) to assess the level of biosecurity on 399 conventional broiler farms in 5 EU member states. The scoring system consisted of 2 main categories, namely external and internal biosecurity, which had 8 and 3 subcategories, respectively. Biosecurity was quantified by converting the answers to 97 questions into a score from 0 to 100. The minimum score, "0," represents total absence of any biosecurity measure on the broiler farm, whereas the maximum score, "100," means full application of all investigated biosecurity measures. A possible correlation between biosecurity and farm characteristics was investigated by multivariate linear regression analysis. The participating broiler farms scored better for internal biosecurity (mean score of 76.6) than for external biosecurity (mean 68.4). There was variation between the mean biosecurity scores for the different member states, ranging from 59.8 to 78.0 for external biosecurity and from 63.0 to 85.6 for internal biosecurity. Within the category of external biosecurity, the subcategory related to "infrastructure and vectors" had the highest mean score (82.4), while the subcategory with the lowest score related to biosecurity procedures for "visitors and staff" (mean 51.5). Within the category of internal biosecurity, the subcategory "disease management" had the highest mean score (65.8). In the multivariate regression model a significant negative correlation was found between internal biosecurity and the number of employees and farm size. These findings indicate that there is a lot of variation for external and internal biosecurity on the participating broiler farms, suggesting that improvements are possible. Since the subcategory "visitors and staff" scored the lowest, better education of broiler farmers and their staff may help to improve overall biosecurity on broiler farms in Europe.

Avian influenza

Previous introductions of highly pathogenic avian influenza virus (HPAIV) to the EU were most likely via migratory wild birds. A mathematical model has been developed which indicated that virus amplification and spread may take place when wild bird populations of sufficient size within EU become infected. Low pathogenic avian influenza virus (LPAIV) may reach similar maximum prevalence levels in wild bird populations to HPAIV but the risk of LPAIV infection of a poultry holding was estimated to be lower than that of HPAIV. Only few non-wild bird pathways were identified having a non-negligible risk of AI introduction. The transmission rate between animals within a flock is assessed to be higher for HPAIV than LPAIV. In very few cases, it could be proven that HPAI outbreaks were caused by intrinsic mutation of LPAIV to HPAIV but current knowledge does not allow a prediction as to if, and when this could occur. In gallinaceous poultry, passive surveillance through notification of suspicious clinical signs/mortality was identified as the most effective method for early detection of HPAI outbreaks. For effective surveillance in anseriform poultry, passive surveillance through notification of suspicious clinical signs/mortality needs to be accompanied by serological surveillance and/or a virological surveillance programme of birds found dead (bucket sampling). Serosurveillance is unfit for early warning of LPAI outbreaks at the individual holding level but could be effective in tracing clusters of LPAIV-infected holdings. In wild birds, passive surveillance is an appropriate method for HPAIV surveillance if the HPAIV infections are associated with mortality whereas active wild bird surveillance has a very low efficiency for detecting HPAIV. Experts estimated and emphasised the effect of implementing specific biosecurity measures on reducing the probability of AIV entering into a poultry holding. Human diligence is pivotal to select, implement and maintain specific, effective biosecurity measures.

Emergence of a highly pathogenic avian influenza virus from a low-pathogenic progenitor

Avian influenza (AI) viruses of the H7 subtype have the potential to evolve into highly pathogenic (HP) viruses that represent a major economic problem for the poultry industry and a threat to global health. However, the emergence of HPAI viruses from low-pathogenic (LPAI) progenitor viruses currently is poorly understood. To investigate the origin and evolution of one of the most important avian influenza epidemics described in Europe, we investigated the evolutionary and spatial dynamics of the entire genome of 109 H7N1 (46 LPAI and 63 HPAI) viruses collected during Italian H7N1 outbreaks between March 1999 and February 2001. Phylogenetic analysis revealed that the LPAI and HPAI epidemics shared a single ancestor, that the HPAI strains evolved from the LPAI viruses in the absence of reassortment, and that there was a parallel emergence of mutations among HPAI and later LPAI lineages. Notably, an ultradeep-sequencing analysis demonstrated that some of the amino acid changes characterizing the HPAI virus cluster were already present with low frequency within several individual viral populations from the beginning of the LPAI H7N1 epidemic. A Bayesian phylogeographic analysis revealed stronger spatial structure during the LPAI outbreak, reflecting the more rapid spread of the virus following the emergence of HPAI. The data generated in this study provide the most complete evolutionary and phylogeographic analysis of epidemiologically intertwined high- and low-pathogenicity viruses undertaken to date and highlight the importance of implementing prompt eradication measures against LPAI to prevent the appearance of viruses with fitness advantages and unpredictable pathogenic properties.

IMPORTANCE

The Italian H7 AI epidemic of 1999 to 2001 was one of the most important AI outbreaks described in Europe. H7 viruses have the ability to evolve into HP forms from LP precursors, although the mechanisms underlying this evolutionary transition are only poorly understood. We combined epidemiological information, whole-genome sequence data, and ultradeep sequencing approaches to provide the most complete characterization of the evolution of HPAI from LPAI viruses undertaken to date. Our analysis revealed that the LPAI viruses were the direct ancestors of the HPAI strains and identified low-frequency minority variants with HPAI mutations that were present in the LPAI samples. Spatial analysis provided key information for the design of effective control strategies for AI at both local and global scales. Overall, this work highlights the importance of implementing rapid eradication measures to prevent the emergence of novel influenza viruses with severe pathogenic properties.

Environmental correlates of H5N2 low pathogenicity avian influenza outbreak heterogeneity in domestic poultry in Italy

Italy has experienced recurrent incursions of H5N2 avian influenza (AI) viruses in different geographical areas and varying sectors of the domestic poultry industry. Considering outbreak heterogeneity rather than treating all outbreaks of low pathogenicity AI (LPAI) viruses equally is important given their interactions with the environment and potential to spread, evolve and increase pathogenicity. This study aims at identifying potential environmental drivers of H5N2 LPAI outbreak occurrence in time, space and poultry populations. Thirty-four environmental variables were tested for association with the characteristics of 27 H5N2 LPAI outbreaks (i.e. time, place, flock type, number and species of birds affected) occurred among domestic poultry flocks in Italy in 2010-2012. This was done by applying a recently proposed analytical approach based on a combined non-metric multidimensional scaling, clustering and regression analysis. Results indicated that the pattern of (dis)similarities among the outbreaks entailed an underlying structure that may be the outcome of large-scale, environmental interactions in ecological dimension. Increased densities of poultry breeders, and increased land coverage by industrial, commercial and transport units were associated with increased heterogeneity in outbreak characteristics. In areas with high breeder densities and with many infrastructures, outbreaks affected mainly industrial turkey/layer flocks. Outbreaks affecting ornamental, commercial and rural multi-species flocks occurred mainly in lowly infrastructured areas of northern Italy. Outbreaks affecting rural layer flocks occurred mainly in areas with low breeder densities in south-central Italy. In savannah-like environments, outbreaks affected mainly commercial flocks of galliformes. Suggestive evidence that ecological ordination makes sense genetically was also provided, as virus strains showing high genetic similarity clustered into ecologically similar outbreaks. Findings were informed by hypotheses about how ecological interactions among poultry populations, viruses and their environments can be related to the observed patterns of H5N2 LPAI occurrence. This may prove useful in enhancing future interventions by developing site-specific, ecologically-grounded strategies.

Risk factors for the introduction of avian influenza virus in breeder duck flocks during the first 24 weeks of laying

A study was carried out in French breeder duck flocks in 2008 and 2009 to identify practices and events related to the introduction of avian influenza viruses (AIVs). The status of flocks was assessed using serological methods for all subtypes of AIV without typing. Flocks managed with both natural mating and artificial insemination were investigated every 4 weeks from the beginning of the laying period up to seroconversion or for a maximum of 6 months. A questionnaire was completed with the farmer during each visit and 20 female ducks were randomly sampled for blood testing. Only flocks that tested seronegative at the first visit were included in the study (n =151 flocks managed with natural mating or artificial insemination). Data were analysed using survival analysis to identify factors influencing the time to seroconversion. Three separate models were constructed: one for the whole sample, one for natural mating flocks, and one for artificial insemination flocks. Factors related to the time to introduction of AIV included the type of production system linked to artificial insemination practices, the neighbourhood, poor disinfection practices, liquid manure management, presence of wildlife, and vehicles entering the building. No clear relationship could be observed in the serological status of male and female ducks in farms keeping male ducks separately from female ducks for artificial insemination. By respecting carefully biosecurity measures, it should be possible to decrease AIV infection of breeder duck flocks.

Risk factors for infectious diseases in backyard poultry farms in the Poyang Lake area, China

Emergence and transmission of infectious diseases have an enormous impact on the poultry industry and present a serious threat to the health of humans and wild birds. Noncommercial poultry operations, such as backyard poultry facilities in China, are potential sources of virus exchange between commercial poultry and wild birds. It is particularly critical in wetland areas where backyard poultry have close contact with commercial poultry and migratory birds, therefore increasing the risk of contracting infectious diseases. To evaluate the transmission risks, a cross-sectional study was undertaken in the Poyang Lake area, China, involving 309 residents in the backyard poultry farms in three counties (Region A, B, and C) of Jiangxi Province. We examined the backyard poultry population, poultry species, presence of poultry deaths from infectious diseases, food sources, and biosecurity practices. Region B ranked highest for biosecurity while region C ranked lowest. The risks of infectious diseases were assessed by adjusted odds ratio based on multivariate logistic regression analysis. Potential risk factors in the three regions of the study site were compared. In Region A, significant factor was contact of poultry with wild birds (OR: 6.573, 95% CI: 2.148–20.115, P=0.001). In Region B, the most significant factor was contact of poultry with neighboring backyard waterfowls (OR: 3.967, 95% CI: 1.555–10.122, P=0.004). In Region C, significant factors were poultry purchase from local live bird markets (OR: 3.740, 95% CI: 1.243–11.255, P=0.019), and contact of poultry with wild birds (OR: 3.379, 95% CI: 1.058–10.791, P=0.040). In summary, backyard poultry was significantly affected by neighboring commercial poultry and close contact with wild birds. The results are expected to improve our understanding of the transmission risks of infectious diseases in a typical backyard poultry environment in rural China, and address the need to improve local farming practices and take preventive measures.

An epidemiologic simulation model of the spread and control of highly pathogenic avian influenza (H5N1) among commercial and backyard poultry flocks in South Carolina, United States

Epidemiologic simulation modeling of highly pathogenic avian influenza (HPAI) outbreaks provides a useful conceptual framework with which to estimate the consequences of HPAI outbreaks and to evaluate disease control strategies. The purposes of this study were to establish detailed and informed input parameters for an epidemiologic simulation model of the H5N1 strain of HPAI among commercial and backyard poultry in the state of South Carolina in the United States using a highly realistic representation of this poultry population; to estimate the consequences of an outbreak of HPAI in this population with a model constructed from these parameters; and to briefly evaluate the sensitivity of model outcomes to several parameters. Parameters describing disease state durations; disease transmission via direct contact, indirect contact, and local-area spread; and disease detection, surveillance, and control were established through consultation with subject matter experts, a review of the current literature, and the use of several computational tools. The stochastic model constructed from these parameters produced simulated outbreaks ranging from 2 to 111 days in duration (median 25 days), during which 1 to 514 flocks were infected (median 28 flocks). Model results were particularly sensitive to the rate of indirect contact that occurs among flocks. The baseline model established in this study can be used in the future to evaluate various control strategies, as a tool for emergency preparedness and response planning, and to assess the costs associated with disease control and the economic consequences of a disease outbreak.

Improving risk models for avian influenza: the role of intensive poultry farming and flooded land during the 2004 Thailand epidemic

Since 1996 when Highly Pathogenic Avian Influenza type H5N1 first emerged in southern China, numerous studies sought risk factors and produced risk maps based on environmental and anthropogenic predictors. However little attention has been paid to the link between the level of intensification of poultry production and the risk of outbreak. This study revised H5N1 risk mapping in Central and Western Thailand during the second wave of the 2004 epidemic. Production structure was quantified using a disaggregation methodology based on the number of poultry per holding. Population densities of extensively- and intensively-raised ducks and chickens were derived both at the sub-district and at the village levels. LandSat images were used to derive another previously neglected potential predictor of HPAI H5N1 risk: the proportion of water in the landscape resulting from floods. We used Monte Carlo simulation of Boosted Regression Trees models of predictor variables to characterize the risk of HPAI H5N1. Maps of mean risk and uncertainty were derived both at the sub-district and the village levels. The overall accuracy of Boosted Regression Trees models was comparable to that of logistic regression approaches. The proportion of area flooded made the highest contribution to predicting the risk of outbreak, followed by the densities of intensively-raised ducks, extensively-raised ducks and human population. Our results showed that as little as 15% of flooded land in villages is sufficient to reach the maximum level of risk associated with this variable. The spatial pattern of predicted risk is similar to previous work: areas at risk are mainly located along the flood plain of the Chao Phraya river and to the south-east of Bangkok. Using high-resolution village-level poultry census data, rather than sub-district data, the spatial accuracy of predictions was enhanced to highlight local variations in risk. Such maps provide useful information to guide intervention.

Biosecurity and bird movement practices in upland game bird facilities in the United States

Since 1996, the emergence of Asian-origin highly pathogenic avian influenza subtype H5N1 has spurred great concern for the global poultry industry. In the United States, there is concern over the potential of a foreign avian disease incursion into the country. Noncommercial poultry operations, such as upland game bird facilities in the United States, may serve as a potential source of avian disease introduction to other bird populations including the commercial poultry industry, backyard flocks, or wildlife. In order to evaluate how to prevent disease transmission from these facilities to other populations, we examined biosecurity practices and bird movement within the upland game bird industry in the United States. Persons that held a current permit to keep, breed, or release upland game birds were surveyed for information on biosecurity practices, flock and release environments, and bird movement parameters. Biosecurity practices vary greatly among permit holders. Many facilities allow for interaction between wild birds and pen-reared birds, and there is regular long-distance movement of live adult birds among facilities. Results suggest that upland game bird facilities should be targeted for biosecurity education and disease surveillance efforts.

Epidemiology and control of low pathogenicity avian influenza infections in rural poultry in Italy

We analyzed the involvement of the rural poultry sector in outbreaks of low pathogenicity avian influenza (AI) in Italy in 2007-2009 and discuss possible measures for improving monitoring and control. A description of how the rural poultry sector is organized also is provided. Data were obtained by the AI surveillance system established in the areas affected by the outbreaks. The surveillance activities identified two H7N3 epidemics, in 2007 and 2009, both of which mainly involved the rural sector, yet these activities did not allow for the prompt eradication of the disease. Additional strategies could be adopted to avoid the persistence of AI within the rural sector, based on the regulation and control of poultry holdings at the top of the production chain.

Transmission between chickens of an H7N1 Low Pathogenic Avian Influenza virus isolated during the epidemic of 1999 in Italy

The transmissibility of an H7N1 Low Pathogenic Avian Influenza (LPAI) virus isolated from a turkey flock during the large epidemic in Italy in 1999, was experimentally studied in chickens. Four group transmission experiments were performed. Infection and transmission were monitored by means of virus isolation on swab samples and antibody detection in serum samples. From the results of these groups, we estimated the mean infectious period at 7.7 (6.7-8.7) days, the transmission rate parameter at 0.49 (0.30-0.75) infections per infectious chicken per day and the basic reproduction ratio at 3.8 (1.3-6.3). These estimates can be used for the development of surveillance and control programmes of LPAI in poultry.

How backyard poultry flocks influence the effort required to curtail avian influenza epidemics in commercial poultry flocks

This paper summarizes the evidence that the contribution of backyard poultry flocks to the on-going transmission dynamics of an avian influenza epidemic in commercial flocks is modest at best. Nevertheless, while disease control strategies need not involve the backyard flocks, an analysis of the contribution of each element of the next generation matrix to the basic reproduction number indicates that models which ignores the contribution of backyard flocks in estimating the effort required of strategies focused one host type (e.g. commercial flocks only) necessarily underestimate the level of effort to an extent that may matter to policy makers.

Identification of risk factors associated with highly pathogenic avian influenza H5N1 virus infection in poultry farms, in Nigeria during the epidemic of 2006-2007

We conducted a matched case-control study to evaluate risk factors for infection with highly pathogenic avian influenza (HPAI) H5N1 virus in poultry farms during the epidemic of 2006-2007 in Nigeria. Epidemiologic data were collected through the use of a questionnaire from 32 case farms and 83 control farms. The frequency of investigated exposure factors was compared between case and control farms by using conditional logistic regression analysis. In the multivariable analysis, the variables for (i) receiving visitors on farm premises (odds ratio [OR]=8.32; 95% confidence interval [CI]=1.87, 36.97; P<0.01), (ii) purchased live poultry/products (OR=11.91; 95% CI=3.11-45.59; P<0.01), and (iii) farm workers live outside the premises (OR=8.98; 95% CI=1.97, 40.77; P<0.01) were identified as risk factors for HPAI in poultry farms. Improving farm hygiene and biosecurity should help reduce the risk for influenza (H5N1) infection in poultry farms in Nigeria.

A quantitative assessment of the risk for highly pathogenic avian influenza introduction into Spain via legal trade of live poultry

Highly pathogenic avian influenza (HPAI) is considered one of the most important diseases of poultry. During the last 9 years, HPAI epidemics have been reported in Asia, the Americas, Africa, and in 18 countries of the European Union (EU). For that reason, it is possible that the risk for HPAI virus (HPAIV) introduction into Spain may have recently increased. Because of the EU free-trade policy and because legal trade of live poultry was considered an important route for HPAI spread in certain regions of the world, there are fears that Spain may become HPAIV-infected as a consequence of the legal introduction of live poultry. However, no quantitative assessment of the risk for HPAIV introduction into Spain or into any other EU member state via the trade of poultry has been published in the peer-reviewed literature. This article presents the results of the first quantitative assessment of the risk for HPAIV introduction into a free country via legal trade of live poultry, along with estimates of the geographical variation of the risk and of the relative contribution of exporting countries and susceptible poultry species to the risk. The annual mean risk for HPAI introduction into Spain was estimated to be as low as 1.36 x 10(-3), suggesting that under prevailing conditions, introduction of HPAIV into Spain through the trade of live poultry is unlikely to occur. Moreover, these results support the hypothesis that legal trade of live poultry does not impose a significant risk for the spread of HPAI into EU member states.

Modelling the spatial spread of H7N1 avian influenza virus among poultry farms in Italy

We analysed the between-farm transmission of the H7N1 highly pathogenic avian influenza virus that disrupted the Italian poultry production in the 1999-2000 epidemic with a SEIR model with a spatial transmission kernel, accounting for the containment measures actually undertaken. We found significant differences in susceptibility between species and a reduction in transmissibility after the first phase. We performed simulations to assess the effectiveness of the implemented and new control measures. The most effective measure was the ban on restocking. An earlier start of pre-emptive culling promotes eradication; restricted pre-emptive culling delays eradication but causes lower losses.