Different environmental gradients associated to the spatiotemporal and genetic pattern of the H5N8 highly pathogenic avian influenza outbreaks in poultry in Italy

Abstract

Comprehensive understanding of the patterns and drivers of avian influenza outbreaks is pivotal to inform surveillance systems and heighten nations' ability to quickly detect and respond to the emergence of novel viruses. Starting in early 2017, the Italian poultry sector has been involved in the massive H5N8 highly pathogenic avian influenza epidemic that spread in the majority of the European countries in 2016/2017. Eighty-three outbreaks were recorded in northeastern Italy, where a densely populated poultry area stretches along the Lombardy, Emilia-Romagna and Veneto regions. The confirmed cases, affecting both the rural and industrial sectors, depicted two distinct epidemic waves. We adopted a combination of multivariate statistics techniques and multi-model regression selection and inference, to investigate how environmental factors relate to the pattern of outbreaks diversity with respect to their spatiotemporal and genetic diversity. Results showed that a combination of eco-climatic and host density predictors were associated with the outbreaks pattern, and variation along gradients was noticeable among genetically and geographically distinct groups of avian influenza cases. These regional contrasts may be indicative of a different mechanism driving the introduction and spreading routes of the influenza virus in the domestic poultry population. This methodological approach may be extended to different spatiotemporal scale to foster site-specific, ecologically informed risk mitigating strategies.

High altitude Relieves transmission risks of COVID-19 through meteorological and environmental factors: Evidence from China

“…For instance, the Ensemble Empirical Mode Decomposition (EEMD) analysis indicated the limited seasonal modulations on COVID-19 evolution ( Huang et al, 2021 ). It has been also reported that high altitudes can influence the occurrence and intensity of influenza A (H1N1, H5N1, H5N8) ( da Costa et al, 2018 ; Scolamacchia et al, 2021 ), and decrease COVID-19 infection ( Segovia-Juarez et al, 2020 ; Stephens et al, 2021 ). The high altitude at 4500 m down-regulates the expression of ACE2, thereby probably protecting them against COVID-19 replication in host cells ( Mendes et al, 2019 ).…”

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

“…In contrast, the higher and dryer eastern and southern parts of the Netherlands with generally sandy soils, have a lower risk of HPAI outbreak. Nevertheless, in contrast to previous studies [ 17 , 18 , 19 , 32 , 33 ], only one land cover variable, i.e., cover by agriculture, was selected in the final model, indicating that densities of wild bird species were better predictors of the HPAIV infection risk in our study. Previous studies mostly tried to explain the variation in the occurrence of HPAIV introductions with environmental variables, such as distance to waterways and vegetation index [ 18 , 19 , 33 ].…”

“…Nevertheless, in contrast to previous studies [ 17 , 18 , 19 , 32 , 33 ], only one land cover variable, i.e., cover by agriculture, was selected in the final model, indicating that densities of wild bird species were better predictors of the HPAIV infection risk in our study. Previous studies mostly tried to explain the variation in the occurrence of HPAIV introductions with environmental variables, such as distance to waterways and vegetation index [ 18 , 19 , 33 ]. Others also included surveillance or telemetry data to track the movements of a selection of wild bird species in a certain time period [ 17 , 29 , 32 , 34 , 35 , 36 ], but most studies did not include detailed count data on wild bird species distribution to analyze HPAIV introductions on poultry farms.…”

“…Such data have proven valuable in many previous spatiotemporal analyses. For example, it has been shown in many studies that the presence of wetlands is vital as they are an important habitat for many waterfowl species [ 32 , 33 , 35 ]. In the current study, the original land cover classes were aggregated into five major classes, which decreased the resolution of land cover classification in the analyses, and may have reduced sensitivity of these variables for the prediction of farm outbreak probability.…”

Contexts matter: Epidemiology and control of avian and swine influenza in contrasted settings

“…For instance, the relative importance of short‐ and long‐distance transmission events during the 2016–2017 H5N8 epidemic in Italy was thus assessed (Harvey et al., 2019). A complementary analysis combining environmental factors, spatio‐temporal patterns of outbreaks and viral genetic diversity explored the role played by different transmission routes in driving the spread of the virus (Scolamacchia et al., 2020). Through the analysis of viral genomes, Nirmala et al., (2020) describe the great genetic diversity of influenza A viruses infecting piglets within US farms and discuss the possible evolutionary implications.…”