Wild Bird Densities and Landscape Variables Predict Spatial Patterns in HPAI Outbreak Risk across The Netherlands

Drivers for a pandemic due to avian influenza and options for One Health mitigation measures

Avian influenza viruses (AIV) remain prevalent among wild bird populations in the European Union and European Economic Area (EU/EEA), leading to significant illness in and death of birds. Transmission between bird and mammal species has been observed, particularly in fur animal farms, where outbreaks have been reported. While transmission from infected birds to humans is rare, there have been instances of exposure to these viruses since 2020 without any symptomatic infections reported in the EU/EEA. However, these viruses continue to evolve globally, and with the migration of wild birds, new strains carrying potential mutations for mammalian adaptation could be selected. If avian A(H5N1) influenza viruses acquire the ability to spread efficiently among humans, large-scale transmission could occur due to the lack of immune defences against H5 viruses in humans. The emergence of AIV capable of infecting mammals, including humans, can be facilitated by various drivers. Some intrinsic drivers are related to virus characteristics or host susceptibility. Other drivers are extrinsic and may increase exposure of mammals and humans to AIV thereby stimulating mutation and adaptation to mammals. Extrinsic drivers include the ecology of host species, such as including wildlife, human activities like farming practices and the use of natural resources, climatic and environmental factors. One Health measures to mitigate the risk of AIV adapting to mammals and humans focus on limiting exposure and preventing spread. Key options for actions include enhancing surveillance targeting humans and animals, ensuring access to rapid diagnostics, promoting collaboration between animal and human sectors, and implementing preventive measures such as vaccination. Effective communication to different involved target audiences should be emphasised, as well as strengthening veterinary infrastructure, enforcing biosecurity measures at farms, and reducing wildlife contact with domestic animals. Careful planning of poultry and fur animal farming, especially in areas with high waterfowl density, is highlighted for effective risk reduction.

Comparison of the Clinical Manifestation of HPAI H5Nx in Different Poultry Types in the Netherlands, 2014-2022

This study describes clinical manifestations of highly pathogenic avian influenza (HPAI) H5N1, H5N8 and H5N6 outbreaks between 2014 and 2018 and 2020 and 2022 in the Netherlands for different poultry types and age groups. Adult duck (breeder) farms and juvenile chicken (broiler and laying pullet) farms were not diagnosed before 2020. Outbreaks in ducks decreased in 2020-2022 vs. 2014-2018, but increased for meat-type poultry. Neurological, locomotor and reproductive tract signs were often observed in ducks, whereas laying- and meat-type poultry more often showed mucosal membrane and skin signs, including cyanosis and hemorrhagic conjunctiva. Juveniles (chickens and ducks) showed neurological and locomotor signs more often than adults. Diarrhea occurred more often in adult chickens and juvenile ducks. Mortality increased exponentially within four days before notification in chickens and ducks, with a more fluctuating trend in ducks and meat-type poultry than in layers. For ducks, a mortality ratio (MR) > 3, compared to the average mortality of the previous week, was reached less often than in chickens. A lower percentage of laying flocks with MR > 3 was found for 2020-2022 vs. 2014-2018, but without significant differences in clinical signs. This study provides a basis for improvements in mortality- and clinical-sign-based early warning criteria, especially for juvenile chickens and ducks.

Risk factors for avian influenza in Danish poultry and wild birds during the epidemic from June 2020 to May 2021

Exploring the risk factors of avian influenza (AI) occurrence helps us to monitor and control the disease. Since late 2020, the number of avian influenza outbreaks in domestic and wild birds has increased in most European countries, including Denmark. This study was conducted to identify potential risk factors for wild birds and poultry during the epidemic in 2020/2021 in Denmark. Using Danish AI surveillance data of actively surveyed poultry and passively surveyed wild birds from June 2020 to May 2021, we calculated geographical attributes for bird locations and assessed the potential risk factors of AI detections using logistic regression analyses. 4% of actively surveyed poultry and 39% of passively surveyed wild birds were detected with AI circulating or ongoing at the time. Of these, 10 and 99% tested positive for the H5/H7 AI subtypes, respectively. Our analyses did not find any statistically significant risk factors for actively surveyed poultry within the dataset. For passively surveyed wild birds, bird species belonging to the Anseriformes order had a higher risk of being AI virus positive than five other taxonomic bird orders, and Galliformes were of higher risk than two other taxonomic bird orders. Besides, every 1 km increase in the distance to wetlands was associated with a 5.18% decrease in the risk of being AI positive (OR (odds ratio) 0.95, 95% CI 0.91, 0.99), when all other variables were kept constant. Overall, bird orders and distance to wetlands were associated with the occurrence of AI. The findings may provide targets for surveillance strategies using limited resources and assist in risk-based surveillance during epidemics.

Vaccination of poultry against highly pathogenic avian influenza - part 1. Available vaccines and vaccination strategies

Several vaccines have been developed against highly pathogenic avian influenza (HPAI), mostly inactivated whole-virus vaccines for chickens. In the EU, one vaccine is authorised in chickens but is not fully efficacious to stop transmission, highlighting the need for vaccines tailored to diverse poultry species and production types. Off-label use of vaccines is possible, but effectiveness varies. Vaccines are usually injectable, a time-consuming process. Mass-application vaccines outside hatcheries remain rare. First vaccination varies from in-ovo to 6 weeks of age. Data about immunity onset and duration in the target species are often unavailable, despite being key for effective planning. Minimising antigenic distance between vaccines and field strains is essential, requiring rapid updates of vaccines to match circulating strains. Generating harmonised vaccine efficacy data showing vaccine ability to reduce transmission is crucial and this ability should be also assessed in field trials. Planning vaccination requires selecting the most adequate vaccine type and vaccination scheme. Emergency protective vaccination is limited to vaccines that are not restricted by species, age or pre-existing vector-immunity, while preventive vaccination should prioritise achieving the highest protection, especially for the most susceptible species in high-risk transmission areas. Model simulations in France, Italy and The Netherlands revealed that (i) duck and turkey farms are more infectious than chickens, (ii) depopulating infected farms only showed limitations in controlling disease spread, while 1-km ring-culling performed better than or similar to emergency preventive ring-vaccination scenarios, although with the highest number of depopulated farms, (iii) preventive vaccination of the most susceptible species in high-risk transmission areas was the best option to minimise the outbreaks' number and duration, (iv) during outbreaks in such areas, emergency protective vaccination in a 3-km radius was more effective than 1- and 10-km radius. Vaccine efficacy should be monitored and complement other surveillance and preventive efforts.

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.

Emergence of Highly Pathogenic Avian Influenza A Virus (H5N1) of Clade 2.3.4.4b in Egypt, 2021-2022

Wild migratory birds have the capability to spread avian influenza virus (AIV) over long distances as well as transmit the virus to domestic birds. In this study, swab and tissue samples were obtained from 190 migratory birds during close surveillance in Egypt in response to the recent outbreaks of the highly pathogenic avian influenza (HPAI) H5N1 virus. The collected samples were tested for a variety of AIV subtypes (H5N1, H9N2, H5N8, and H6N2) as well as other pathogens such as NDV, IBV, ILT, IBDV, and WNV. Among all of the tested samples, the HPAI H5N1 virus was found in six samples; the other samples were found to be negative for all of the tested pathogens. The Egyptian HPAI H5N1 strains shared genetic traits with the HPAI H5N1 strains that are currently being reported in Europe, North America, Asia, and Africa in 2021-2022. Whole genome sequencing revealed markers associated with mammalian adaption and virulence traits among different gene segments, similar to those found in HPAI H5N1 strains detected in Europe and Africa. The detection of the HPAI H5N1 strain of clade 2.3.4.4b in wild birds in Egypt underlines the risk of the introduction of this strain into the local poultry population. Hence, there is reason to be vigilant and continue epidemiological and molecular monitoring of the AIV in close proximity to the domestic-wild bird interface.

Artificial Intelligence Models for Zoonotic Pathogens: A Survey

Zoonotic diseases or zoonoses are infections due to the natural transmission of pathogens between species (animals and humans). More than 70% of emerging infectious diseases are attributed to animal origin. Artificial Intelligence (AI) models have been used for studying zoonotic pathogens and the factors that contribute to their spread. The aim of this literature survey is to synthesize and analyze machine learning, and deep learning approaches applied to study zoonotic diseases to understand predictive models to help researchers identify the risk factors, and develop mitigation strategies. Based on our survey findings, machine learning and deep learning are commonly used for the prediction of both foodborne and zoonotic pathogens as well as the factors associated with the presence of the pathogens.