The reduction of antibiotic use in livestock production, for the different species, has become a critical focus in national action plans across many countries, underscoring the urgent need to tackle this issue to preserve public health and combat antibiotic resistance (Xu et al., 2022; Jacobsen et al., 2023; Bava et al., 2024). Among these efforts, Vietnam's ambitious 2017 livestock plan is notable for its comprehensive regulatory framework aimed at controlling antibiotic use. This framework includes a phased ban on prophylactic antibiotics in animal feed and requires mandatory prescriptions for antibiotic access.

Despite these promising regulations, their actual implementation poses significant challenges, with limited data available on their practical application. A recent study led by Batie and collaborators attempts to fill this knowledge gap by examining how these regulations are understood, accepted, and applied by stakeholders in the veterinary drug value chain in both northern and southern Vietnam (Batie et al., 2024).

The study employed an interesting iterative stakeholder mapping and analysis approach, organizing a focus group in Hanoi with 12 participants and conducting 39 in-depth semi-structured interviews with a diverse range of stakeholders. These included government authorities, national research bodies, international partners, and private sector representatives. The qualitative analysis aimed to map the veterinary drug value chain, assess stakeholders' technical and social capital regarding regulations, and identify key factors influencing regulatory compliance.

This research convincingly unveiled a complex network of 30 stakeholder categories and identified ten crucial factors that affect the implementation of regulations. These factors include stakeholders’ perceptions and understanding of the regulations, the availability of technical guidance, economic conflicts of interest, management inconsistencies, and hurdles such as technical and financial constraints, informal distribution channels, international influence, and consumer demand for safety. Additionally, the collective drive to reduce antibiotic resistance emerged as an influential factor.

The comprehensive analysis reveals a pressing insight: although Vietnam's regulatory measures are essential for reducing antibiotic usage, their effectiveness is compromised by barriers such as inadequate local stakeholder involvement and various resource limitations. The study emphasizes the necessity for deeper engagement of local stakeholders in developing and refining these regulations. Furthermore, incorporating innovations from small producers into mainstream practices could be vital in overcoming current challenges.

Nonetheless, the study acknowledges several limitations. Most interviews were conducted online owing to the health crisis—a much-needed format for time and budget constraints, albeit with some drawbacks such as reduced direct observations and potential information loss (Namey et al., 2019). The sensitivity of the subject may have led participants to withhold their true opinions, although the researchers attempted to mitigate this bias by interviewing multiple respondents from each category and gathering diverse perspectives. Notably, the study struggled to engage informal stakeholders, which could have enriched the description of the informal value chain. Constraints of time and resources meant that only a single representative from some stakeholder categories was interviewed, suggesting that interviewing additional parties, such as another veterinary district station, might have clarified roles within the drug value chain. The stakeholder identification was initially influenced by the researchers’ familiarity with the Vietnamese context; however, the iterative process helped address this limitation by recruiting new participants based on existing participants' knowledge. Additionally, translation issues may have introduced misunderstandings, potentially leading to an incomplete representation of the veterinary drug value chain, which reflects the situation as of data collection in 2021.

For Vietnam to meet its policy objectives and contribute to the global endeavor against antibiotic resistance, it is crucial to reconcile stakeholder discrepancies and promote collaborative innovation. By fostering an inclusive environment for all parties, Vietnam can not only enhance regulatory adherence but also strengthen its commitment to sustainable and responsible livestock farming practices.

The study is thoughtfully designed and skillfully executed. Additionally, the authors have made further improvements based on feedback from the journal. Readers will find the article both informative and engaging, providing valuable insights. I highly recommend this original article on the regulatory framework for controlling antibiotic use in Vietnam's livestock production systems.

References

Batie, C., Duy, N. V., Khue, N. T. M., Peyre, M., Bordier, M., Dien, N. T., et al. (2024). Understanding the implementation of antimicrobial resistance policies in Vietnam: a multilayer analysis of the veterinary drug value chain. medRxiv, 2024.06.27.24309573, ver. 2 peer-reviewed and recommended by Peer Community in Animal Science. https://doi.org/10.1101/2024.06.27.24309573   

Bava, R., Castagna, F., Lupia, C., Poerio, G., Liguori, G., Lombardi, R., et al. (2024). Antimicrobial Resistance in Livestock: A Serious Threat to Public Health. Antibiotics 13, 551. https://doi.org/10.3390/antibiotics13060551

Jacobsen, A. B. J. E., Ogden, J., and Ekiri, A. B. (2023). Antimicrobial resistance interventions in the animal sector: scoping review. Front. Antibiot. 2. https://doi.org/10.3389/frabi.2023.1233698 

Namey, E., Guest, G., O’Regan, A., Godwin, C. L., Taylor, J., and Martinez, A. (2019). How Does Mode of Qualitative Data Collection Affect Data and Cost? Findings from a Quasi-experimental Study. Field Methods. https://doi.org/10.1177/1525822X19886839 

Xu, C., Kong, L., Gao, H., Cheng, X., and Wang, X. (2022). A Review of Current Bacterial Resistance to Antibiotics in Food Animals. Front Microbiol 13, 822689. https://doi.org/10.3389/fmicb.2022.822689 

The adaptability of livestock to changing environments is based in particular on their genetic characteristics but also on the farming conditions to which they are subjected. However, this last point is poorly documented and little is known about its contribution to environmental challenges. The study by Quéméner and colleagues [1] addresses this question by assessing the effect of two hygiene conditions (good vs poor) on the distribution of cell populations present in adipose and muscle tissues of pigs divergently selected for feed efficiency [2].

The working hypothesis is that degraded housing conditions would be at the origin of an hyper stimulation of the immune system that can influence the homeostasis of adipose tissue and skeletal muscle and consequently modulate the cellular content of these tissues. Cellular compositions are thus interesting intermediate phenotypes for quantifying complex traits. The study uses pigs divergently selected for residual feed intake (RFI+ and RFI-) to assess whether there is a genetic effect associated with the observed phenotypes. 

The study characterized different stromal cell populations based on the expression of surface markers: CD45 to separate hematopoietic lineages and markers associated with the stem properties of mesenchymal cells: CD56, CD34, CD38 and CD140a. The authors observed that certain subpopulations are differentially enriched according to the hygiene condition (good vs poor) in adipose and skeletal tissue (CD45-CD56-) sometimes with an associated (genetic) lineage effect. This pioneering study validates a number of tools for characterizing cell subpopulations present in porcine adipose and muscle tissue. It confirms that housing conditions can have an effect on intermediate phenotypes such as intra-tissue cell populations. This pioneering work will pave the way to better understand the effects of livestock systems on tissue biology and animal phenotypes and to characterize the nature and function of progenitor cells present in muscle and adipose tissue.

[1] Quéméner A, Dessauge F, Perruchot MH, Le Floc’h N, Louveau I. 2022. The impact of housing conditions on porcine mesenchymal stromal/stem cell populations differ between adipose tissue and skeletal muscle. bioRxiv 2021.06.08.447546, ver. 3 peer-reviewed and recommended by Peer Community in Animal Science. https://doi.org/10.1101/2021.06.08.447546 

[2] Gilbert H, Bidanel J-P, Gruand J, Caritez J-C, Billon Y, Guillouet P, Lagant H, Noblet J, Sellier P. 2007. Genetic parameters for residual feed intake in growing pigs, with emphasis on genetic relationships with carcass and meat quality traits. Journal of Animal Science 85:3182–3188. https://doi.org/10.2527/jas.2006-590.

As the world slowly (or not so slowly) warms, the ability to regulate heat becomes even more pertinent for livestock kept in enclosed areas. Trees are not always present on land grazed by sheep, and when the pasture has some forestation, the coverage will provide varying degrees of shade. In this study by Ginane et al. (2025), ewes kept in enclosures with different levels of tree cover were observed at different times over a period of three years to investigate the extent to which the animals chose to spend time in the shade. By using fields with very different provision of shade (approximately 1, 40, and 81% shade, respectively), the authors wanted to test the hypothesis that ewes would actively seek out tree shade when the combined temperature and humidity increased – especially if the conditions reached levels associated with heat stress. Even at the lowest provision of shade, which consisted of a single tree in the paddock, all ewes could fit within the shade cast by the tree; but if the distribution of ewes or groups of ewes were random, i.e. independent of shade, the likelihood of these ewes being in the shade by chance was effectively 1%. By factoring in the element of chance, the authors found that mean shade use was greater than the tree canopy cover for the low and medium shade treatments, whereas it didn’t differ from chance for the densely forested treatment. Across treatments, all ewes spent just under 60% of the observation time grazing, and the ewes with the low and medium level of shade actively selected shade for foraging activity, whereas the ewes with over 80% canopy cover avoided it. Across treatments, shade was used primarily for resting and ruminating.

Tree cover affected the availability of forage in a negative manner, with more biomass available for ewes in the low shade treatment and significantly less in the high treatment, although this did not translate into significant differences in live weight or body condition score. Using this information, Ginane et al. (2025) calculated the optimal level of tree cover to be somewhere between the low and medium cover, at roughly 30 trees per hectare – preferably spread out over the area to offer different locations of shade and to encourage a natural spread of manure.

This longitudinal study of shade use by ewes provides novel and useful information on the positive and negative effects of tree cover in paddocks used to rear ewes with lambs. The authors raise the limitation of the study themselves, and they would have liked to also include observations on non-sunny days, to be able to eliminate place preferences independently of shade availability. But the clever calculation of active shade-selection makes this study easily applicable for use in the assessment of paddock suitability for pregnant ewes.

References

Cécile Ginane, Mickaël Bernard, Véronique Deiss, Donato Andueza, Camille Béral (2025) Shade use, welfare and performance of ewes grazing in temperate silvopastures differing in tree density. Zenodo, ver.4 peer-reviewed and recommended by PCI Animal Science https://doi.org/10.5281/zenodo.15001481

The identification of reliable estimates of growth potential and resilience over the fattening period in large populations is a challenge in actual swine breeding conditions. To overcome this drawback, the study by Revilla et al. 2021 in the frame of precision livestock farming aimed to propose an innovative modelling approach, in addition to previous studies from the same group (Revilla et al. 2019), to enhance the quality of the quantification of pig resilience during the entire fattening period. 

The authors developed a model that quantifies an “individual pig resilience indicator” based on longitudinal data, for instance body weight, recorded routinely by a commercially available automatic feeding system. Revilla and co-workers considered in their study two mainly commercialised pure pig breeds these being Piétrain including Piétrain Français NN Axiom line (Pie NN) free from halothane-sensitivity (ryanodine receptor gene, RYR1) and Piétrain Français Axiom line positive to this gene and Duroc. Therefore, the authors investigated the potential of improving resilience of swine livestock through inclusion for the first time of an “individual pig resilience indicator” in breeding objectives. A database of 13 093 boars (approximately 11.1 million of weightings) belonging to Pie (n= 5 841), Pie NN (n = 5 032) and Duroc (n= 2 220) finished under ad libitum feeding, high sanitary level and controlled temperature was used to develop robust models.

The authors checked the three datasets (for each pig breed)​ independently to explore the variation and gaps (a data pre-treatment procedure) to ensure high quality data for the modelling approach. Then, they applied the Gompertz model and linear interpolation on body weight data to quantify individual deviations from the expected production, allowing the creation of the ABC index. For the modelling, the authors applied a two-step mathematical model approach by first establishing a theoretical growth curve of each animal, while the second step aimed to build the actual perturbed growth curve. The heritability of the index ranged from 0.03 to 0.04, with similar heritability between Piétrain and Duroc breeds. Moreover, moderate genetic relationships were computed between the proposed index and important phenotypic traits in swine production likely BF100: backfat thickness at 100kg; LD100: longissimus dorsi thickness at 100kg; ADG: average daily gain during control and FCR: feed conversion ratio.

Developing models able to capture perturbations during the fattening period is a challenge in swine breeding industry. The model and methodology proposed by the authors in this innovative work (although preliminary and with low heritabilities) would help overcome such limit and facilitate a real implementation at large scale in pig breeding system. The modelling approach further offers an opportunity to develop a selection criterion to improve resilience in swine breeding conditions. 

To explore the full potential of this modelling approach, a larger database and other factors such as breed, behaviour and feeding behaviour of the animals, rearing practices, management and environment conditions, age… etc. are worthy to consider. In the future, more in depth measurements of behaviour that can be computed for example using computer vision should be desirable to increase the robustness of the proposed model.

References

Revilla, M., Friggens, N.C., Broudiscou, L.P., Lemonnier, G., Blanc, F., Ravon, L., Mercat, M.J., Billon, Y., Rogel-Gaillard, C., Le Floch, N. and Estellé, J. (2019). Towards the quantitative characterisation of piglets’ robustness to weaning: a modelling approach. Animal, 13(11), 2536-2546. https://doi.org/10.1017/S1751731119000843 

Revilla M, Lenoir G, Flatres-Grall L, Muñoz-Tamayo R, Friggens NC (2021). Quantifying growth perturbations over the fattening period in swine via mathematical modelling. bioRxiv, 2020.10.22.349985, ver. 5 peer-reviewed and recommended by Peer Community in Animal Science. https://doi.org/10.1101/2020.10.22.349985 

Epidemics such as PRRSv-like virus in pig farms has tremendous impact on the competitiveness of swine production. However, its control requires an understanding of the complex interaction between pathogen transmission, disease impact, population dynamics and management. By using mechanistic epidemiological modelling, Sicard et al. (2023) open up a very interesting field of possibilities. This article describes work aimed at assessing the consequences of infections, taking into account the interaction between clinical outcomes and population dynamics. This study shows how this interaction can influence transmission dynamics at the herd level. It highlights the need to further explore this direction, integrating both disease impacts in breeding practices and structural changes in population dynamics, such as pig crossbreeding and grouping methodologies.
The provision of a new tool making it possible to model herd management practices and the transmission of a virus, such as PRRS, in time and space is a major contribution to understanding the dynamics of this category of diseases. It opens up the possibility of being able to represent specific herd structures and evaluate transmission dynamics using real data. This work improves our understanding of disease spread across herds, taking into account herd management.

Reference

Sicard V, Picault S, Andraud M (2023) Pig herd management and infection transmission dynamics: a challenge for modellers. bioRxiv, 2023.05.17.541128. ver. 2 peer-reviewed and recommended by Peer Community in Animal Science. https://doi.org/10.1101/2023.05.17.541128