RNA viruses are characterized by high mutation and recombination rates, which allow a rapid adaptation to new environments. Most of the emerging diseases and host jumps are therefore sustained by these viruses. Rapid evolution may also hinder the understanding of molecular epidemiology, affect the sensitivity of diagnostic assays, limit the vaccine efficacy and favor episodes of immune escape, thus significantly complicating the control of even well-known pathogens. The history of infectious bronchitis virus (IBV) fits well with the above-mentioned scenario. Despite being known since the 1930s, it still represents one of the main causes of disease and economic losses for the poultry industry. A plethora of strategies have been developed and applied over time, with variable success, to limit its impact. However, they have rarely been evaluated objectively and on an adequate scale. Therefore, the actual advantages and disadvantages of IBV detection and control strategies, as well as their implementation, still largely depend on individual sensibility. The present manuscript aims to review the main features of IBV biology and evolution, focusing on their relevance and potential applications in terms of diagnosis and control.

Since their commercialization, vaccines against Porcine circovirus type 2 (PCV2) have been the cornerstone control strategy. Nevertheless, the periodic emergence of new genotype waves and the recent reports of vaccine failure outbreaks have raised the question if widespread vaccination strategies could have driven viral evolution and affected different genotype fitness. To investigate this issue an in-deep analysis, based on a bioinformatics and biostatistics approach, has been implemented. ORF2 sequences from vaccinated and non-vaccinated populations (i.e. domestic pigs before and after vaccine introduction and wild boars) were considered. The action of selective forces on PCV2 strains has been analyzed and compared among groups. Remarkable differences were found in the selective forces acting on viral populations circulating in different “immune environments”. Particularly for PCV2a, a directional selection promoting a change in the viral capsid away from the vaccine specific antigenic determinants has been detected after vaccine introduction. Involved amino acids were previously reported to be part of viral epitopes whose variability is responsible of immune escape. Our findings support a change in PCV2 evolutionary pattern after widespread vaccination introduction and stress once more the compulsoriness of a continuous monitoring of PCV2 epidemiology to promptly act in response to the emergence of possible vaccine-escaping mutants.

Infectious bronchitis virus (IBV) represents one of the poultry industry major threats, particularly in high density producing countries. The emergence and spread of new IBV genotypes have frustrated the various disease control efforts implemented over time. Despite that, few comprehensive and large scale studies have been performed to understand the international and local spreading dynamics of this virus. In the present work, these phenomena were evaluated by implementing a Bayesian phylodynamic approach to reconstruct the epidemiological patterns and population history of the QX genotype (currently renamed GI-19 lineage), the most relevant IBV lineage of the Old-World. Our analysis, based on 807 partial S1 sequences of strains collected from 18 countries between 1993 and 2015, demonstrates that this genotype originated in China well before its first identification. After a prolonged local circulation, it started spreading to other European, Asian and Middle East countries in successive waves, which were mirrored by concomitant fluctuations in viral population size. Interestingly, the within-Europe spread was characterized by a higher estimated migration rate compared with the inter-continental one, potentially reflecting the closer geographic and economic relationships among these countries. Nevertheless, the colonization of new states by the GI-19 lineage appeared to occur mostly by single introduction events in both intra and inter-continental spread, likely because of epidemiological factor and health policy combination which seems to prevent the frequent introduction and mixing of different strains. On the other hand, the within Italy QX circulation reconstruction showed a much more intricate connection network among different locations, evidencing the difficulty in controlling IBV spread especially in highly densely poultry populated areas. The presence of several well supported epidemiological links among distantly related Italian regions testifies that animal transportation and indirect transmission routes rather than local airborne diffusion contribute to the QX success and persistence at local scale. Globally, the spreading dynamics and evolution of the QX genotype were reconstructed from its very origin to nowadays, demonstrating the need of more effective direct control measures, particularly within each country. Unfortunately, the incompleteness of available molecular epidemiology data represents an insurmountable limit which leaves many questions currently unsolved, thus highlighting the compulsoriness of a structured monitoring and data sharing system implementation.

Avian Metapneumovirus (aMPV) has been recognized as a respiratory pathogen of turkey and chickens for a long time. Recently, a crescent awareness of aMPV, especially subtype B, clinical and economic impact has risen among European researchers and veterinarians. Nevertheless, the knowledge of its epidemiology and evolution is still limited. In the present study, the broadest available collection of partial G gene sequences obtained from European aMPV-B strains was analyzed using different phylodynamic and biostatistical approaches to reconstruct the viral spreading over time and the role of different hosts on its evolution. After aMPV-B introduction, approximatively in 1985 in France, the infection spread was relatively quick, involving the Western and Mediterranean Europe until the end of the 1990s, and then spreading westwards at the beginning of the new millennium, in parallel with an increase of viral population size. In the following period, a wider mixing among aMPV-B strains detected in eastern and western countries could be observed. Most of the within-country genetic heterogeneity was ascribable to single or few introduction events, followed by local circulation. This, combined with the high evolutionary rate herein demonstrated, led to the establishment of genetically and phenotypically different clusters among countries, which could affect the efficacy of natural or vaccine-induced immunity and should be accounted for when planning control measure implementation. On the contrary, while a significant strain exchange was proven among turkey, guinea fowl and chicken, no evidence of differential selective pressures or specific amino-acid mutations was observed, suggesting that no host adaptation is occurring.

In future decades, the demand for poultry meat and eggs is predicted to considerably increase in pace with human population growth. Although this expansion clearly represents a remarkable opportunity for the sector, it conceals a multitude of challenges. Pollution and land erosion, competition for limited resources between animal and human nutrition, animal welfare concerns, limitations on the use of growth promoters and antimicrobial agents, and increasing risks and effects of animal infectious diseases and zoonoses are several topics that have received attention from authorities and the public. The increase in poultry production must be achieved mainly through optimization and increased efficiency. The increasing ability to generate large amounts of data (“big data”) is pervasive in both modern society and the farming industry. Information accessibility—coupled with the availability of tools and computational power to store, share, integrate, and analyze data with automatic and flexible algorithms—offers an unprecedented opportunity to develop tools to maximize farm profitability, reduce socio-environmental impacts, and increase animal and human health and welfare. A detailed description of all topics and applications of big data analysis in poultry farming would be infeasible. Therefore, the present work briefly reviews the application of sensor technologies, such as optical, acoustic, and wearable sensors, as well as infrared thermal imaging and optical flow, to poultry farming. The principles and benefits of advanced statistical techniques, such as machine learning and deep learning, and their use in developing effective and reliable classification and prediction models to benefit the farming system, are also discussed. Finally, recent progress in pathogen genome sequencing and analysis is discussed, highlighting practical applications in epidemiological tracking, and reconstruction of microorganisms’ population dynamics, evolution, and spread. The benefits of the objective evaluation of the effectiveness of applied control strategies are also considered. Although human-artificial intelligence collaborations in the livestock sector can be frightening because they require farmers and employees in the sector to adapt to new roles, challenges, and competencies—and because several unknowns, limitations, and open-ended questions are inevitable—their overall benefits appear to be far greater than their drawbacks. As more farms and companies connect to technology, artificial intelligence (AI) and sensing technologies will begin to play a greater role in identifying patterns and solutions to pressing problems in modern animal farming, thus providing remarkable production-based and commercial advantages. Moreover, the combination of diverse sources and types of data will also become fundamental for the development of predictive models able to anticipate, rather than merely detect, disease occurrence. The increasing availability of sensors, infrastructures, and tools for big data collection, storage, sharing, and analysis—together with the use of open standards and integration with pathogen molecular epidemiology—have the potential to address the major challenge of producing higher-quality, more healthful food on a larger scale in a more sustainable manner, thereby protecting ecosystems, preserving natural resources, and improving animal and human welfare and health.