Avian Influenza In Wild Birds Research Articles

Avian influenza viruses in wild birds in Canada following incursions of highly pathogenic H5N1 virus from Eurasia in 2021-2022.

We present the results of Canada's Interagency Surveillance Program for Avian Influenza in Wild Birds in the year following the first detection of highly pathogenic avian influenza virus (HPAIV) H5N1 on the continent. The surveillance program tested over 17,000 wild birds, both sick and apparently healthy, which revealed spatiotemporal and taxonomic patterns in HPAIV prevalence and mortality across Canada. The significant shift in the presence and distribution of HPAIV in Canada's wild birds underscores the need for sustained investment in wild bird surveillance and collaboration across One Health partners.

Can the Logarithmized Number of Ducks be an Indicator of the Risk of Outbreaks of Highly Pathogenic Avian Influenza in Wild Birds?

Can the Logarithmized Number of Ducks be an Indicator of the Risk of Outbreaks of Highly Pathogenic Avian Influenza in Wild Birds?

Avian influenza in wild birds and mammals in the United States. Proceeding of The First International Avian Influenza Summit, University of Arkansas- October 16-17, 2023"

Avian influenza in wild birds and mammals in the United States. Proceeding of The First International Avian Influenza Summit, University of Arkansas- October 16-17, 2023"

Using surveillance data for early warning modelling of highly pathogenic avian influenza in Europe reveals a seasonal shift in transmission, 2016–2022

Avian influenza in wild birds and poultry flocks constitutes a problem for animal welfare, food security and public health. In recent years there have been increasing numbers of outbreaks in Europe, with many poultry flocks culled after being infected with highly pathogenic avian influenza (HPAI). Continuous monitoring is crucial to enable timely implementation of control to prevent HPAI spread from wild birds to poultry and between poultry flocks within a country. We here utilize readily available public surveillance data and time-series models to predict HPAI detections within European countries and show a seasonal shift that happened during 2021–2022. The output is models capable of monitoring the weekly risk of HPAI outbreaks, to support decision making.

H5N1 highly pathogenic avian influenza clade 2.3.4.4b in wild and domestic birds: Introductions into the United States and reassortments, December 2021–April 2022

Highly pathogenic avian influenza viruses (HPAIVs) of the A/goose/Guangdong/1/1996 lineage H5 clade 2.3.4.4b continue to have a devastating effect on domestic and wild birds. Full genome sequence analyses using 1369 H5N1 HPAIVs detected in the United States (U.S.) in wild birds, commercial poultry, and backyard flocks from December 2021 to April 2022, showed three phylogenetically distinct H5N1 virus introductions in the U.S. by wild birds. Unreassorted Eurasian genotypes A1 and A2 entered the Northeast Atlantic states, whereas a genetically distinct A3 genotype was detected in Alaska. The A1 genotype spread westward via wild bird migration and reassorted with North American wild bird avian influenza viruses. Reassortments of up to five internal genes generated a total of 21 distinct clusters; of these, six genotypes represented 92% of the HPAIVs examined. By phylodynamic analyses, most detections in domestic birds were shown to be point-source transmissions from wild birds, with limited farm-to-farm spread.

Subtype specific virus enrichment with immunomagnetic separation method followed by NGS unravels the mixture of H5 and H9 avian influenza virus

Wild bird avian influenza type A virus (AIV) surveillance is important for the early detection of highly pathogenic AIVs and for providing early warnings to the poultry industry and veterinary services to implement more effective control measures against these viruses. Some field samples are often found to contain more than two kinds of AIV. Correct determination of the HA/NA subtype and complete nucleotide sequences of the component viruses in those samples are often critical for timely and accurate understanding of the field situation, but it is not easy to define the genomic structure of the constituent viruses unambiguously because AIV has eight segmented genomes. In this study, with immunomagnetic beads incorporating polyclonal antibodies of chicken for subtype-specific viral enrichment, we could selectively decrease the density of one of the two constituent viruses in a sample of different subtypes, H5 and H9, artificially generated; this was represented in the changes of Ct values with subtype specific real-time RT-PCR. Following this, with NGS, we could recover nearly complete genomic sequences and arrange the consensus sequences of gene segments of the constituent viruses confidently with the quantitative variable like genome coverage, linked along the gene segments and associated with the number of viral copies in a sample.

WildHealthNet: Supporting the development of sustainable wildlife health surveillance networks in Southeast Asia

Wildlife and wildlife interfaces with people and livestock are essential surveillance targets to monitor emergent or endemic pathogens or new threats affecting wildlife, livestock, and human health. However, limitations of previous investments in scope and duration have resulted in a neglect of wildlife health surveillance (WHS) systems at national and global scales, particularly in lower and middle income countries (LMICs).Building on decades of wildlife health activities in LMICs, we demonstrate the implementation of a locally-driven multi-pronged One Health approach to establishing WHS in Cambodia, Lao PDR and Viet Nam under the WildHealthNet initiative. WildHealthNet utilizes existing local capacity in the animal, public health, and environmental sectors for event based or targeted surveillance and disease detection. To scale up surveillance systems to the national level, WildHealthNet relies on iterative field implementation and policy development, capacity bridging, improving data collection and management systems, and implementing context specific responses to wildlife health intelligence.National WHS systems piloted in Cambodia, Lao PDR, and Viet Nam engaged protected area rangers, wildlife rescue centers, community members, and livestock and human health sector staff and laboratories. Surveillance activities detected outbreaks of H5N1 highly pathogenic avian influenza in wild birds, African swine fever in wild boar (Sus scrofa), Lumpy skin disease in banteng (Bos javanicus), and other endemic zoonotic pathogens identified as surveillance priorities by local stakeholders. In Cambodia and Lao PDR, national plans for wildlife disease surveillance are being signed into legislation.Cross-sectoral and trans-disciplinary approaches are needed to implement effective WHS systems. Long-term commitment, and paralleled implementation and policy development are key to sustainable WHS networks. WildHealthNet offers a roadmap to aid in the development of locally-relevant and locally-led WHS systems that support the global objectives of the World Organization for Animal Health's Wildlife Health Framework and other international agendas.

Spatiotemporal risk assessment for avian influenza outbreak based on the dynamics of habitat suitability for wild birds.

Highly pathogenic avian influenza (HPAI) has predominantly damaged the poultry industry worldwide. The fundamental prevention and control strategy for HPAI includes early detection and timely intervention enforcement through a systematic surveillance system for wild birds based on the ecological understanding of the dynamics of wild birds' movements. Our study aimed to develop a spatiotemporal risk assessment model for avian influenza (AI) infection in wild birds to empower surveillance information for a contingency strategy. For this purpose, first, we predicted the monthly habitat suitability of seven waterfowl species, using 227,671 Global Positioning System (GPS) tracking records of 562 birds from 2014 to 2018 in the Republic of Korea (ROK). Then, that predicted habitat suitability and 421 coordinates of AI detection sites in wild birds were used to build the risk assessment model. Subsequently, we compared the monthly predicted risk of avian influenza virus (AIv) identification in wild birds between case and non-case poultry farms with HPAI H5N6 outbreak in the ROK between 2016 and 2017. The results reported considerable variation of monthly habitat suitability of seven waterfowls and the impact of predicting AI occurrences in wild birds. The high habitat suitability for spot-billed ducks (contribution rate in November=40.9%) and mallards (contribution rate in January=34.3%) significantly contributed to predicting the average risk of AIv identification in wild birds, with high predictive performance [the monthly mean of area under the curve (AUC)=0.978]. Moreover, our model showed that the averaged risk of identification AI in wild birds was significantly higher in HPAI infected premises, with infected domestic duck holdings exhibiting a significantly higher risk than the chicken farms in November. This study suggests that animal health authority establishes a risk-based HPAI surveillance system grounded on the ecological nature of wild birds to improve the effectiveness of prevention and preparedness of emerging epidemics.

Avian Influenza in Wild Birds and Poultry: Dissemination Pathways, Monitoring Methods, and Virus Ecology.

Avian influenza is one of the largest known threats to domestic poultry. Influenza outbreaks on poultry farms typically lead to the complete slaughter of the entire domestic bird population, causing severe economic losses worldwide. Moreover, there are highly pathogenic avian influenza (HPAI) strains that are able to infect the swine or human population in addition to their primary avian host and, as such, have the potential of being a global zoonotic and pandemic threat. Migratory birds, especially waterfowl, are a natural reservoir of the avian influenza virus; they carry and exchange different virus strains along their migration routes, leading to antigenic drift and antigenic shift, which results in the emergence of novel HPAI viruses. This requires monitoring over time and in different locations to allow for the upkeep of relevant knowledge on avian influenza virus evolution and the prevention of novel epizootic and epidemic outbreaks. In this review, we assess the role of migratory birds in the spread and introduction of influenza strains on a global level, based on recent data. Our analysis sheds light on the details of viral dissemination linked to avian migration, the viral exchange between migratory waterfowl and domestic poultry, virus ecology in general, and viral evolution as a process tightly linked to bird migration. We also provide insight into methods used to detect and quantify avian influenza in the wild. This review may be beneficial for the influenza research community and may pave the way to novel strategies of avian influenza and HPAI zoonosis outbreak monitoring and prevention.

Surveillance system for avian influenza in wild birds and implications of its improvement with insights into the highly pathogenic avian influenza outbreaks in Japan

Since the re-emergence of a highly pathogenic avian influenza (HPAI) in 2004, outbreaks of the viral subtypes HPAI, H5N1, H5N8, and H5N6 in wild birds, poultry, and zoo birds have occurred in Japan. In 2008, a nation-wide avian influenza (AI) surveillance program was started for the early detection of the HPAI virus (HPAIV) and for the assessment of HPAIV infection among wild birds. In this study, we aimed to conduct an overview of the AI surveillance system of wild birds in Japan, including those in the regions and prefectures, to assess its overall performance and develop insights on its improvement. We analyzed past surveillance data in Japan and conducted questionnaire surveys for the officers in 11 regional branches of the Ministry of Environment and the nature conservation divisions of 47 prefectures to acquire details regarding those AI surveillance. We found that the early detection of HPAIV in wild birds was successfully achieved in only one of the five outbreak seasons during the 2008–2019 period in Japan, and the assessment of HPAIV infection had possibly not been adequate in the national surveillance system. In the winter season, AI surveillance in most prefectures were mainly conducted by means of passive surveillance through reported dead birds and active surveillance through collected waterbird feces. Conversely, less than half of the prefectures conducted bird monitoring, patrolling in migratory bird habitats, and AI antigen testing in rescued birds. In areas surrounding HPAI occurrence sites (<10 km), bird monitoring and patrolling efforts were enhanced. However, AI testing efforts in waterbird feces and rescued birds were decreased. The AI surveillance for endangered bird species and in national wildlife protection areas was conducted by the branches of the Ministry of Environment and by the prefectures. Based on our results, we concluded that for maximum efficiency, legislation which specialized in wildlife pathogens should be necessary to prepare adequate national budget and testing capacity for appropriate surveillance system with periodical assessment for surveillance results and the system.

Population genomic transformations induced by isolation of wild bird avian influenza viruses (Orthomyxoviridae) in embryonated chicken eggs.

Isolation and cultivation of wild-type viruses in model organism cells or tissues is standard practice in virology. Oftentimes, the virus host species is distantly related to the species from which the culture system was developed. Thus, virus culture in these tissues and cells basically constitutes a host jump, which can lead to genomic changes through genetic drift and/or adaptation to the culture system. We directly sequenced 70 avian influenza virus (Orthomyxoviridae) genomes from oropharyngeal/cloacal swabs collected from wild bird species and paired virus isolates propagated from the same samples following isolation in specific-pathogen-free embryonated chicken eggs. The data were analyzed using population genetic approaches including evaluation of single nucleotide polymorphism (SNP) frequencies and divergence with pooled-sequencing analyses, consensus sequence placement in neighbor-joining trees, and haplotype reconstruction and networks. We found that propagation of virus in eggs leads to skewed SNP mutation spectra with some SNPs going to fixation. Both synonymous and nonsynonmous SNP frequencies shifted. We found multiple consensus sequences that differed between the swabs and the isolates, with some sequences from the same sample falling into divergent genetic clusters. Twenty of 23 coinfections detected had different dominant subtypes following virus isolation, thus sequences from both the swab and isolate were needed to obtain full subtype data. Haplotype networks revealed haplotype frequency shifts and the appearance or loss of low-frequency haplotypes following isolation. The results from this study revealed that isolation of wild bird avian influenza viruses in chicken eggs leads to skewed populations that are different than the input populations. Consensus sequence changes from virus isolation can lead to flawed phylogenetic inferences, and subtype detection is biased. These results suggest that for genomic studies of wild bird influenza viruses the biological field should move away from chicken egg isolation towards directly sequencing the virus from host samples.

Surveillance system for avian influenza in wild birds and implications for the improvement with insights into highly pathogenic avian influenza outbreaks during 2004-2017 in Japan

Surveillance system for avian influenza in wild birds and implications for the improvement with insights into highly pathogenic avian influenza outbreaks during 2004-2017 in Japan

Avian Influenza in Wild Birds from South America: Review, Implications and Perspectives

Avian influenza viruses (AIVs) have been recorded in a broad variety of hosts, including humans, terrestrial and marine mammals, and domestic and wild birds. Wild aquatic birds are recognized as the chief natural reservoirs of AIV, and their migratory flyways can serve as routes for the dispersion of the virus across countries and continents. Although AIV is one of the most studied pathogens in the world, studies on the ecology and epidemiology of this virus in South America are few and fragmented. In this review, we examine the current state of the art on the epidemiology of AIV in wild birds in South America. Current evidence corroborates that many of the broad epidemiological patterns that have been documented in other continents, such as the role played by Anseriformes and Charadriiformes in the maintenance and spread of AIV, are also true in South America. On the other hand, the fact that AIV prevalence in South American studies appears to be remarkably lower than that observed in other continents, along with the presence of endemic taxa of birds that may be highly susceptible to AIV, indicates that South America may have distinct characteristics that modulate the epidemiology of AIV in unique ways. However, our knowledge on the occurrence of AIV in South America is still limited and there are important gaps in the species and geographic distribution of the sampling effort.

Description and molecular characterization of Haemoproteus macrovacuolatus n. sp. (Haemosporida, Haemoproteidae), a morphologically unique blood parasite of black-bellied whistling duck (Dendrocygna autumnalis) from South America.

During a surveillance programme on avian influenza in wild birds in the east of Colombia, 42% of examined wild black-bellied whistling ducks (Dendrocygna autumnalis) were infected with undescribed Haemoproteus sp., which macrogametocytes possess one or several huge (2.5 μm in largest diameter) conspicuous roundish vacuoles, a unique character of avian haemoproteids. This parasite is named Haemoproteus (Parahaemoproteus) macrovacuolatus and described here using data on the morphology of its gametocytes, host cells and sequences of the complete mitochondrial genome and cytochrome b fragments. Illustrations of blood stages of the new species and DNA sequence information are provided. The phylogenetic analysis identified a closely related lineage C033, reported in South Asian ducks belonging to Dendrocygna. We also found that all Haemoproteus lineages from Passeriformes conformed a monophyletic group. Whereas we cannot exclude that this pattern could be an artefact of the limited taxonomic sampling in non-passeriform birds, thus this finding is worthy of attention. This study adds to our knowledge of the phylogenetic relationships among species of avian haemoproteids and describes a new haemoparasite in a non-passerine host.

MODELING SEASONALITY IN AVIAN INFLUENZA H5N1

The number of cases of H5N1 avian influenza in birds and humans exhibit seasonality which peaks during the winter months. What causes the seasonality in H5N1 cases is still being investigated. This article addresses the question of modeling the periodicity in cumulative number of human cases of H5N1. Three potential drivers of influenza seasonality are investigated: (1) seasonality in bird-to-bird transmission; (2) seasonality caused by wild bird migration or seasonal fluctuation of avian influenza in wild birds; (3) seasonality caused by environmental transmission. A framework of seven models is composed. The seven models involve these three mechanisms and combinations of the mechanisms. Each of the models in the framework is fitted to the cumulative number of humans cases of H5N1. The corrected akaike information criterion (AICc) is used to compare the models and it is found that the model with periodic bird-to-bird transmission rate best explains the data. The best fitted model with the best fitted parameters gives a reproduction number of highly pathogenic avian influenza [Formula: see text]. The best fitted model is a simple SI epidemic model with periodic transmission rate and disease-induced mortality, however, this model is capable of very complex dynamical behavior such as period doubling and chaos.

A global model of avian influenza prediction in wild birds: the importance of northern regions

Avian influenza virus (AIV) is enzootic to wild birds, which are its natural reservoir. The virus exhibits a large degree of genetic diversity and most of the isolated strains are of low pathogenicity to poultry. Although AIV is nearly ubiquitous in wild bird populations, highly pathogenic H5N1 subtypes in poultry have been the focus of most modeling efforts. To better understand viral ecology of AIV, a predictive model should 1) include wild birds, 2) include all isolated subtypes, and 3) cover the host’s natural range, unbounded by artificial country borders. As of this writing, there are few large-scale predictive models of AIV in wild birds. We used the Random Forests algorithm, an ensemble data-mining machine-learning method, to develop a global-scale predictive map of AIV, identify important predictors, and describe the environmental niche of AIV in wild bird populations. The model has an accuracy of 0.79 and identified northern areas as having the highest relative predicted risk of outbreak. The primary niche was described as regions of low annual rainfall and low temperatures. This study is the first global-scale model of low-pathogenicity avian influenza in wild birds and underscores the importance of largely unstudied northern regions in the persistence of AIV.

Estimating transmission of avian influenza in wild birds from incomplete epizootic data: implications for surveillance and disease spread

Summary Estimating disease transmission in wildlife populations is critical to understand host–pathogen dynamics, predict disease risks and prioritize surveillance activities. However, obtaining reliable estimates for free‐ranging populations is extremely challenging. In particular, disease surveillance programs may routinely miss the onset or end of epizootics and peak prevalence, limiting the ability to evaluate infectious processes. We used profile likelihood to estimate the force of infection (FOI) in a low pathogenic avian influenza virus (LPAIv) epizootic model from censored time series of LPAIv prevalence in hatch‐year waterfowl (order Anseriformes) at postbreeding and migration sites in North America. We found a mean LPAIv FOI of 0·12 day−1 [95% CI, 0·00–0·39], corresponding to an incidence rate of 0·11 day−1, with geographic heterogeneity (min–max: 0·02–0·23 day−1) among study sites. These high infection rates indicate that most hatch‐year waterfowl are likely infected with LPAIv early in the fall migration. Comparison of model‐predicted and observed immunity confirmed our assumption of naïve hatch‐year waterfowl and suggested long‐term immunity (&gt;6 months) for adults. Using the mean LPAIv incidence rate, we predict a shorter and lower epizootic curve for highly pathogenic avian influenza virus (HPAIv; 5 weeks with peak prevalence of 28% and 30% mortality) than LPAIv (8 weeks with peak prevalence of 50%). These findings indicate it is harder to detect HPAIv than LPAIv with swabs from live birds, which are commonly used during disease surveillance. Synthesis and applications. Our study highlights the potential of integrating incomplete surveillance data with epizootic models to quantify disease transmission and immunity. This modelling approach provides an important tool to understand spatial and temporal epizootic dynamics and inform disease surveillance. Our findings suggest focusing highly pathogenic avian influenza virus (HPAIv) surveillance on postbreeding areas where mortality of immunologically naïve hatch‐year birds is most likely to occur, and collecting serology to enhance HPAIv detection. Our modelling approach can integrate various types of disease data facilitating its use with data from other surveillance programs (as illustrated by the estimation of infection rate during an HPAIv outbreak in mute swans Cygnus olor in Europe).

Potential risk map for avian influenza A virus invading Japan

AbstractAimOur goal was to use the occurrence of the influenza A virus in wild birds in Japan to create a potential risk map for the spread of avian influenza by migratory birds. Our modelling included a consideration of the multicollinearity and spatial autocorrelation of environmental variables and an examination of the reproducibility of the model results.LocationJapan.MethodsWe used the maximum entropy approach to generate potential distribution models from presence‐only data. Independent variables in the model included environmental factors such as winter temperature and precipitation, host factors such as duck population size and habitat abundance and artificial factors such as size of urban areas and poultry density. We used eigenvector‐based spatial filters to alleviate spatial autocorrelation. To explore the reliability of the model, we compared the risk indices of localities positive in past winters for the influenza A virus in wild birds with those of all localities.ResultsThe model alleviated spatial autocorrelation with a high degree of accuracy. Dabbling duck population, size of urban area, diving duck population and altitude were the variables that were most strongly correlated with the potential distribution of avian influenza. We used the frequency of occurrence of the influenza A virus in five recent years in localities where wild birds were infected to estimate the repeatability of the high‐risk indices; the potential risk indices for avian influenza in wild birds were high in localities where wild birds were infected in past.Main conclusionsThe dabbling duck population in an area appeared to be the best indicator of high risk for the introduction of avian influenza from abroad. Priority monitoring localities for avian influenza carried by wild birds should be designated in western Japan and along the Pacific coast, which we estimated to be high‐risk areas. Poultry farms in these areas should increase their biosecurity to prevent vectors from introducing avian influenza.

Molecular Surveillance of Avian Influenza in Bird Parks of Tehran, Iran

BACKGROUND: Avian influenza (AI) viruses have been isolated from a wide diversity of free-living avian species representing several orders. Since 1998, H9N2 AI outbreaks have been one of the major problems in Iranian poultry industry. In 2006, H5N1 was reported in swans in the north of Iran first , but until now there has been no official report from commercial flocks in Iran. OBJECTIVES: The aim of this study was Molecular Surveillance of Avian Influenza in Bird Parks of Tehran, Iran. METHODS: In this study, 100 fecal samples from different avian species of Public and Bird Parks (The avian species included Pigeon, Duck, Swan, Parrot, Crow and Sparrow) were collected in Tehran, in the central region of Iran during November and December 2009. RNA extraction and RT-PCR have been done according the WHO Instruction for detection of Influenza Type A. RESULTS: In 14% of samples genetic materials (RNA) were detected. Species including duck and sparrow were positive. CONCLUSIONS: This is the first report of AIV detection in this these species in Iran. Due to emergence of new H1N1 influenza and bird flu throughout the world and in regional countries, surveillance programs for monitoring the spread of these viruses need to be redesigned. Surveillance activities for AI in wild birds should be continued to provide further virological (subtype) and epidemiological (Phylogenic Study) information about circulating viruses.

The Ecology of Influenza A Viruses in Wild Birds in Southern Africa

Avian influenza viruses (AIVs) are pathogens of global concern, but there has been little previous research on avian influenza in southern Africa and almost nothing is known about the dynamics of AIVs in the region. We counted, captured and sampled birds regularly at five sites, two in South Africa (Barberspan and Strandfontein) and one in each of Botswana (Lake Ngami), Mozambique (Lake Chuali) and Zimbabwe (Lakes Manyame and Chivero) between March 2007 and May 2009. The South African and Zimbabwean sites were visited every 2 months and the sites in Botswana and Mozambique every 4 months. During each visit we undertook 5-7days of standardised bird counts followed by 5-10days of capturing and sampling water-associated birds. We sampled 4,977 birds of 165 different species and completed 2,503 half-hour point counts. We found 125 positive rRT-PCR cases of avian influenza across all sites. Two viruses (H1N8 and H3N8) were isolated and additional H5, H6 and H7 strains were identified. We did not positively identify any highly pathogenic H5N1. Overall viral prevalence (2.51%) was similar to the lower range of European values, considerable spatial and temporal variation occurred in viral prevalence, and there was no detectable influence of the annual influx of Palearctic migrants. Although waterbirds appear to be the primary viral carriers, passerines may link wild birds and poultry. While influenza cycles are probably driven by the bird movements that result from rainfall patterns, the epidemiology of avian influenza in wild birds in the subregion is complex and there appears to be the possibility for viral transmission throughout the year.