No abstract

Porcine reproductive and respiratory syndrome (PRRS) is among the most devastating diseases affecting the pig industry. Despite vaccines having been available for decades, the remarkable genetic variability of this virus, leading to poor cross-protection, has limited their efficacy, and other measures must be adopted to effectively control the viral circulation. Some recent studies have investigated the factors involved in viral spreading and persistence, at least at the local level. However, despite the topic's relevance, no statistically grounded evidence is currently available evaluating the variables more involved in porcine reproductive and respiratory syndrome virus (PRRSV) epidemiological success at a broader scale, such as the European scale. In the present study, an extensive phylodynamic and phylogeographic analysis was performed on more than 1000 ORF5 sequences to investigate the history, dynamics and spreading patterns of PRRSV within European borders. Moreover, several potential predictors, representative of swine population features and trade, human population, economy and geographic characteristics, were evaluated through a specifically designed generalized linear model (GLM) to assess their weight on viral migration rate between countries over time. Although pig stock density, mean PRRSV strain genetic diversity, investments in agriculture (including a likely role of vaccination) and farmer education were involved to a certain extent, the major determinant was proven to be by far the live pig trade. Providing a robust depiction of PRRSV European molecular epidemiology patterns and determinants, the present study could contribute to a more rational allocation of limited resources based on an effective prioritization of control measures.

The species Carnivore protoparvovirus 1 includes viruses, e.g. canine parvovirus (CPV-2) and feline panleukopenia virus (FPV), which are among the most relevant for pets, causing extremely severe clinical signs and high fatality rate in dogs and cats. Moreover, a broad range of wild hosts, including endangered ones, were proven to be susceptible. Currently, no data on CPV-2 molecular epidemiology and strain characterization are available in Ethiopia, also considering the frequent contacts between domestic and wild populations. In the present study, a molecular epidemiology survey was performed on 92 fecal samples collected from domestic (n = 84) and stray (n = 8) dogs in southwestern Ethiopia in 2021. Approximately, 10% of the samples tested positive and the complete VP2 sequences of 5 strains were obtained, classified within the CPV-2a (n = 1) and CPV-2c (n = 4) antigenic variants. In most instances, the closest genetic relatives were strains of Chinese origin, which is fully compatible with the intense relationships that have been developing between the two countries, involving human being travels and their pets as well. Considering the clinical relevance of this infection and the risk it poses to local domestic and wild carnivore populations, especially endangered ones, much stronger monitoring and surveillance activity on foreign incoming animals should be performed. More strict constraints on animal introduction, e.g. compulsory vaccination, should also be considered.

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.

Porcine circovirus type 2 (PCV2) is one of the most relevant infectious agents affecting domestic pigs. Recently, a surprising PCV2 genetic heterogenicity has been reported in Africa. Nevertheless, the knowledge of the epidemiology of PCV2 in African countries, in both domestic and wild species, is limited and sparse. Having this in mind, in the present study, the PCV2 circulation and its molecular epidemiology in Southwestern Ethiopia have been investigated by collecting 64 samples from domestic pigs, wild boars, and warthogs. PCV2 genome presence was detected and quantified using qPCR and ORF2 sequencing was attempted on positive samples. Ten samples, 8 wild boars, 1 domestic pig, and 1 warthog, tested PCV2 positive. Complete ORF2 sequences were obtained from 5 wild boars; 4 of those were classified as PCV2d and 1 as PCV2b. Both PCV2b and PCV2d were related to strains of Asian origin, most commonly from China. The role of this country in the exportation of PCV2 strains in Ethiopia, and Africa in general, might be supported by the crescent economic relationship between the two continents. The obtained evidence also testifies to the inadequacy and/or poor application of biosecurity measures separating wild and domestic animals. Further, extensive and systematic studies should be performed to more deeply characterize the molecular epidemiology of PCV2 in this region, in order to improve our understanding of these ecological niches in the evolution and dispersal of PCV2.