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

The global distribution and diversity of wild-bird-associated pathogens: An integrated data analysis and modeling study

BACKGROUND

Wild birds are significant vectors in global pathogen transmission, but the diversity and spatial distribution of the pathogens detected in them remain unclear. Understanding the transmission dynamics and hotspots of wild-bird-associated pathogens (WBAPs) is crucial for early disease prevention.

METHODS

We compiled an up-to-date dataset encompassing all WBAPs by conducting an extensive search of publications from 1959 to 2022, mapped their diversity and global distribution, and utilized three machine learning algorithms to predict geospatial hotspots where zoonotic and emerging WBAPs were prevalent.

FINDINGS

Based on 1,834 selected studies, a total of 760 pathogens associated with 1,438 wild bird species were identified, including 387 emerging and 212 zoonotic pathogens. Migratory birds exhibited higher pathogen richness (593 species) but a lower proportion of zoonotic pathogens (27.2%) compared to resident birds (303 species and 39.3%, both p < 0.01). When comparing different ecological groups, waterfowl had the highest richness of zoonotic pathogens (128 species), followed by songbirds (76 species). The distribution of WBAPs was significantly influenced by the habitat suitability index of wild birds, mammalian richness, and climatic factors. The potential geographical hotspots of zoonotic and emerging WBAPs were widely distributed in tropical areas of Asia, Africa, and South America, with zoonotic WBAPs having a wider distribution in South America.

CONCLUSIONS

Our study illustrates that the geographical hotspots of WBAPs are more widespread than reported, especially in low-income areas, and that the identification, surveillance, and prevention of WBAP infections should be prioritized.

FUNDING

This work was funded by the National Key Research and Development Program of China.

Perpetuation of Avian Influenza from Molt to Fall Migration in Wild Swan Geese (Anser cygnoides): An Agent-Based Modeling Approach

Wild waterfowl are considered to be the reservoir of avian influenza, but their distinct annual life cycle stages and their contribution to disease dynamics are not well understood. Studies of the highly pathogenic avian influenza (HPAI) virus have primarily focused on wintering grounds, where human and poultry densities are high year-round, compared with breeding grounds, where migratory waterfowl are more isolated. Few if any studies of avian influenza have focused on the molting stage where wild waterfowl congregate in a few selected wetlands and undergo the simultaneous molt of wing and tail feathers during a vulnerable flightless period. The molting stage may be one of the most important periods for the perpetuation of the disease in waterfowl, since during this stage, immunologically naïve young birds and adults freely intermix prior to the fall migration. Our study incorporated empirical data from virological field samplings and markings of Swan Geese (Anser cygnoides) on their breeding grounds in Mongolia in an integrated agent-based model (ABM) that included susceptible-exposed-infectious-recovered (SEIR) states. Our ABM results provided unique insights and indicated that individual movements between different molting wetlands and the transmission rate were the key predictors of HPAI perpetuation. While wetland extent was not a significant predictor of HPAI perpetuation, it had a large effect on the number of infections and associated death toll. Our results indicate that conserving undisturbed habitats for wild waterfowl during the molting stage of the breeding season could reduce the risk of HPAI transmission.

Geospatial and Temporal Analysis of Avian Influenza Risk in Thailand: A GIS-Based Multi-Criteria Decision Analysis Approach for Enhanced Surveillance and Control

Avian influenza (AI) is a viral infection that profoundly affects global poultry production. This study aimed to identify the spatial and temporal factors associated with AI in Thailand, using a geographic information system (GIS)-based multi-criteria decision analysis (MCDA) approach. We discovered that high-risk areas for AI were primarily concentrated in the central and lower northern regions of the country, with fewer occurrences in the northeastern and southern regions. Model validation using historical outbreak data showed moderate agreement (AUC = 0.60, 95% CI = 0.58-0.61). This study provides valuable insights for planning national AI surveillance programs and aiding in disease prevention and control efforts. The efficiency and effectiveness of disease surveillance at the national level can be improved using this GIS-based MCDA, in conjunction with temporal risk factor analysis.

Ecological drivers for poultry farms predisposed to highly pathogenic avian influenza virus infection during the initial phase of the six outbreaks between 2010-2021: a nationwide study in South Korea

Background

Highly pathogenic avian influenza (HPAI) has caused substantial economic losses worldwide. An understanding of the environmental drivers that contribute to spillover transmission from wild birds to poultry farms is important for predicting areas at risk of introduction and developing risk-based surveillance strategies. We conducted an epidemiological study using data from six HPAI outbreak events in South Korea.

Materials and methods

An aggregate-level study design was implemented using third-level administrative units in South Korea. Only regions with high natural reservoir suitability were included. The incidence of HPAI at chicken and duck farms during the initial phase (30 and 45 days after the first case) of each outbreak event was used as the outcome variable, assuming that cross-species transmission from wild birds was the dominant exposure leading to infection. Candidate environmental drivers were meteorological factors, including temperature, precipitation, humidity, and altitude, as well as the proportion of protected area, farm density, deforestation level, and predator species richness. Logistic regression models were implemented; conditional autoregression models were used in cases of spatial autocorrelation of residuals.

Results

Lower temperature, higher farm density, and lower predator species richness were significantly associated with a higher risk of HPAI infection on chicken farms. Lower temperature, higher proportion of protected area, and lower predator species richness were significantly associated with a higher risk of HPAI infection on duck farms.

Conclusion

The predicted dominant transmission routes on chicken and duck farms were horizontal and spillover, respectively. These results reveal a potential protective effect of predator species richness against HPAI outbreaks. Further studies are required to confirm a causal relationship.

Assessment of the spatiotemporal risk of avian influenza between waterfowl and poultry farms during the annual cycle: A spatial prediction study focused on seasonal distribution changes in resident waterfowl in South Korea

Previous studies and efforts to prevent and manage avian influenza (AI) outbreaks have mainly focused on the wintering season. However, outbreaks of AI have been reported in the summer, including the breeding season of waterfowl. Additionally, the spatial distribution of waterfowl can easily change during the annual cycle due to their life-cycle traits and the presence of both migrants and residents in the population. Thus, we assessed the spatiotemporal variation in AI exposure risk in poultry due to spatial distribution changes in three duck species included in both major residents and wintering migrants in South Korea, the mandarin, mallard and spot-billed duck, during wintering (October-March), breeding (April-June) and whole annual seasons. To estimate seasonal ecological niche variations among the three duck species, we applied pairwise ecological niche analysis using the Pianka index. Subsequently, seasonal distribution models were projected by overlaying the monthly ranges estimated by the maximum entropy model. Finally, we overlaid each seasonal distribution range onto a poultry distribution map of South Korea. We found that the mandarin had less niche overlap with the mallard and spot-billed duck during the wintering season than during the breeding season, whereas the mallard had less niche overlap with the mandarin and spot-billed duck during the breeding season than during the wintering season. Breeding and annual distribution ranges of the mandarin and spot-billed duck, but not the mallard, were similar or even wider than their wintering ranges. Similarly, the mandarin and spot-billed duck showed more extensive overlap proportions between poultry and their distributional ranges during both the breeding and annual seasons than during the wintering season. These results suggest that potential AI exposure in poultry can occur more widely in the summer than in winter, depending on sympatry with the host duck species. Future studies considering the population density and variable pathogenicity of AI are required.

Dynamics of the Emerging Genogroup of Infectious Bursal Disease Virus Infection in Broiler Farms in South Korea: A Nationwide Study

Infectious bursal disease (IBD), caused by IBD virus (IBDV), threatens the health of the poultry industry. Recently, a subtype of genogroup (G) 2 IBDV named G2d has brought a new threat to the poultry industry. To determine the current status of IBDV prevalence in South Korea, active IBDV surveillance on 167 randomly selected broiler farms in South Korea from August 2020 to July 2021 was conducted. The bursas of Fabricius from five chickens from each farm were independently pooled and screened for IBDV using virus-specific RT-PCR. As a result, 86 farms were found to be infected with the G2d variant, 13 farms with G2b, and 2 farms with G3. Current prevalence estimation of IBDV infection in South Korea was determined as 17.8% at the animal level using pooled sampling methods. G2d IBDV was predominant compared to other genogroups, with a potentially high-risk G2d infection area in southwestern South Korea. The impact of IBDV infection on poultry productivity or Escherichia coli infection susceptibility was also confirmed. A comparative pathogenicity test indicated that G2d IBDV caused severe and persistent damage to infected chickens compared with G2b. This study highlights the importance of implementation of regular surveillance programs and poses challenges for the comprehensive prevention of IBDV infections.

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

Highly pathogenic avian influenza viruses’ (HPAIVs) transmission from wild birds to poultry occurs globally, threatening animal and public health. To predict the HPAI outbreak risk in relation to wild bird densities and land cover variables, we performed a case-control study of 26 HPAI outbreaks (cases) on Dutch poultry farms, each matched with four comparable controls. We trained machine learning classifiers to predict outbreak risk with predictors analyzed at different spatial scales. Of the 20 best explaining predictors, 17 consisted of densities of water-associated bird species, 2 of birds of prey, and 1 represented the surrounding landscape, i.e., agricultural cover. The spatial distribution of mallard (Anas platyrhynchos) contributed most to risk prediction, followed by mute swan (Cygnus olor), common kestrel (Falco tinnunculus) and brant goose (Branta bernicla). The model successfully distinguished cases from controls, with an area under the receiver operating characteristic curve of 0.92, indicating accurate prediction of HPAI outbreak risk despite the limited numbers of cases. Different classification algorithms led to similar predictions, demonstrating robustness of the risk maps. These analyses and risk maps facilitate insights into the role of wild bird species and support prioritization of areas for surveillance, biosecurity measures and establishments of new poultry farms to reduce HPAI outbreak risks.

Bridging the Local Persistence and Long-Range Dispersal of Highly Pathogenic Avian Influenza Virus (HPAIv): A Case Study of HPAIv-Infected Sedentary and Migratory Wildfowls Inhabiting Infected Premises

The past two decades have seen the emergence of highly pathogenic avian influenza (HPAI) infections that are characterized as extremely contagious, with a high fatality rate in chickens, and humans; this has sparked considerable concerns for global health. Generally, the new variant of the HPAI virus crossed into various countries through wild bird migration, and persisted in the local environment through the interactions between wild and farmed birds. Nevertheless, no studies have found informative cases associated with connecting local persistence and long-range dispersal. During the 2016–2017 HPAI H5N6 epidemic in South Korea, we observed several waterfowls with avian influenza infection under telemetric monitoring. Based on the telemetry records and surveillance data, we conducted a case study to test hypotheses related to the transmission pathway between wild birds and poultry. One sedentary wildfowl naturally infected with HPAI H5N6, which overlapped with the home range of one migratory bird with H5-specific antibody-positive, showed itself to be phylogenetically close to the isolates from a chicken farm located within its habitat. Our study is the first observational study that provides scientific evidence supporting the hypothesis that the HPAI spillover into poultry farms is caused by local persistence in sedentary birds, in addition to its long-range dispersal by sympatric migratory birds.