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The rapid expansion of shrimp farming in Ca Mau Province, Vietnam since the early 2000s has converted mangrove forests into aquaculture ponds, resulting in deforestation and degraded mangrove ecosystems. A system dynamics model was developed to assess the interactions and temporal changes among various economic, social, and environmental factors. The analysis was conducted under two development scenarios. In the Business as Usual scenario, shrimp farming will expand to 317,037 hectares in 2050, reducing mangrove coverage to 76,484 hectares and carbon storage to 4.8×106 MgC. However, this expansion is expected to create jobs, producing an output value of 25,153 billion VND and accounting for 25.13% of the province’s workforce. Conversely, the Policy Scenario stabilizes shrimp farming areas at 280,000 hectares, which will have alternative impacts on the environment, society, and economy. By 2050, Ca Mau’s mangrove coverage and carbon storage will reach 88,902 hectares and 5.6×106 MgC, respectively. Besides, the shrimp industry will generate an output value of 22,214 billion VND and account for 23.58% of the province’s workforce. Despite yielding lower economic growth and employment generation, policy interventions are expected to support overall positive developmental progress. Furthermore, a shift in the labor structure is anticipated due to restrictions on shrimp farming areas. The findings provide insights for policymakers to anticipate potential consequences of future development and appropriately adjust policy interventions. Several strategies, such as land use management, economic diversification, and alternative livelihood generation, are needed to balance environmental sustainability with social and economic growth in Ca Mau. Moreover, the methodology presented in this study is not limited to Ca Mau but is also applicable to other areas where the expansion of aquaculture endangers mangrove ecosystems.

This article describes data on eco-shrimp farming households in Ca Mau, Vietnam. The survey was conducted in Tam Giang Dong commune, Nam Can district, Ca Mau province from March 2023 to May 2023 with a total of 120 households engaged in eco-shrimp farming. The non-probability convenience sampling method was used to select respondents. Two responses were removed from the dataset due to uncomplete questionnaires. The dataset includes a structured questionnaire with 52 questions, along with a raw data file of 118 responses. The questionnaire collected data on (a) household demographic information, (b) eco-shrimp farming area and pond types, (c) production characteristics for the 2021–2022 eco-shrimp crop, and (d) farmers’ perspectives on the eco-shrimp farming model. The dataset is available in an Excel file format. It is expected to benefit policymakers and local authorities by providing evidence-based insights into the eco-shrimp production model and the compliance of eco-shrimp farmers with mangrove conservation policies.

Antimicrobials are a core aspect of most livestock production systems, especially in low-and middle-income countries. They underpin the efficient use of scarce feed resources and stabilize returns on capital and labor inputs. Antimicrobial use (AMU) contributes to the production of healthy animals, yet AMU in livestock is linked to antimicrobial resistance (AMR) in animals, humans and the environment.The Vietnamese Platform for Antimicrobial Reduction in Chicken Production was implemented during 2016–2019 and was one of Southeast Asia's first interventions focused on AMU reductions in livestock production. The project targeted small-scale commercial poultry farms in the Mekong Delta region of Vietnam using a “randomized before-and-after controlled” study design. It provided farmers with a locally adapted support service (farmer training plan, advisory visits, biosecurity, and antimicrobial replacement products) to help them reduce their reliance on antimicrobials. A partial budget analysis was performed comparing the control group (status-quo) and intervention group (alternative). The median net farm-level benefit of the intervention strategies with the project's support was VND 6.78 million (interquartile range (IR) VND -71.9–89 million) per farm. Without project support the benefit was reduced to VND 5.1 million (IR VND -69.1–87.2 million) to VND 5.3 million (IR -VND 68.9–87.5 million) depending on the antimicrobial alternative product used. At the project level with a focus on AMU and its reduction, subsequently influence on the resistance reduction, our results showed that achieving resistance reduction benefits with the current knowledge and technologies required investment of at least VND 9.1 million (US$ 395.10) per farm during the project's lifetime. The results highlight the positive net profit for the majority of enrolled farms and a reasonable investments from the project. The recommendation focuses on the implementation of policies on financial support, legislation, and information as potential solutions to facilitate the application of intervention strategies to reduce AMU in poultry production.

In the rapidly evolving landscape of Beyond 5G (B5G) networks, Cell-Free Massive Multiple-Input Multiple-Output (CFmMIMO) systems have emerged as a pivotal solution to address the escalating demands for seamless connectivity and low-latency communication. However, the effective management of radio resources, particularly in the uplink direction, presents formidable challenges in optimizing system performance while ensuring equitable treatment for all users. Existing uplink power control methods often grapple with the intrinsic complexity of the optimization problems they encounter. To mitigate these challenges, this paper introduces a novel approach termed the metaheuristics-based uplink power control scheme tailored explicitly for user-centric CFmMIMO systems. Leveraging advanced metaheuristic optimization techniques, our scheme navigates the intricacies of uplink power control by prioritizing three primary objectives: maximizing the minimum user Spectral Efficiency (SE), maximizing the sum SE, and striking a balance between these two objectives. Through rigorous exploration of potential solutions, our proposed scheme transcends the limitations of conventional methods, offering near-optimal solutions for uplink power control. Numerical simulations corroborate the efficacy of our approach, showcasing enhanced fairness among users and substantial gains in SE compared to traditional methods. This research represents a significant advancement in the practical implementation of user-centric CFmMIMO systems within B5G networks, presenting promising solutions to address the evolving requirements of future wireless communication.

Rice is the most important crop in Vietnam’s agriculture sector for its contribution to economic stability and food security. Improving the efficiency of rice farming and expanding production towards sustainability has become one of the national economic development goals. This study aimed to empirically evaluate technical efficiency of rice farms based on their farming practices using observational data from face-to-face interviews with 152 rice farm households in Long An Province in the Mekong Delta, Vietnam. The data envelopment analysis model was applied to evaluate the technical and scale efficiencies. Results show that except for farmers applying one practice, the average technical efficiency exceeded 81 %. Farmers who adopted more sustainable practices obtained higher technical efficiency and scale efficiency with scores of 90 % and 91 % respectively. Many farmers with different combinations of farming practices operated under increasing returns to scale. The Tobit model was also applied to estimate the determinant factors of technical efficiency. The results of the Tobit model revealed that the farmer’s education level and farming experience had a significant impact on rice farming efficiency. The study also found an inverted U-shaped relationship between education level and efficiency, which indicates that if farmers had higher education levels beyond the threshold point, their farming efficiency will decrease. The significance of adopting sustainable agriculture practices in rice-producing households was emphasized by the positive correlation observed between the number of sustainable agriculture practices applied and efficiency.

The paradigm shift from “connected things” to “connected intelligence” is anticipated to be made possible by the sixth-generation wireless systems, which typically use millimeter wave beamforming to mitigate the significant propagation loss. However, beamforming design in millimeter wave communications poses many different challenges owing to the large antenna arrays with the limitation of radio frequency chains and analog beamforming architectures. To circumvent this problem, deep learning models have recently been utilized as a disruptive method for solving difficult optimization problems in sixth-generation mobile systems, such as maximizing spectral efficiency. However, it is still unclear how to produce high-performance deep learning models which require considering appropriate hyperparameters. This study proposes a metaheuristics-based approach for optimizing hyperparameters that are used to build optimized deep learning models to maximize spectral efficiency. The research results demonstrate that the proposed approach-based models establish higher spectral efficiency than the state-of-the-art approach-based models and the reference model whose hyperparameters are based on empirical trials.

Fluvial floods endure as one of the most catastrophic weather-induced disasters worldwide, leading to numerous fatalities each year and significantly impacting socio-economic development and the environment. Hence, the research and development of new methods and algorithms focused on improving fluvial flood prediction and devising robust flood management strategies are essential. This study explores and assesses the potential application of 1D-Convolution Neural Networks (1D-CNN) for spatial prediction of fluvial flood in the Quang Nam province, a high-frequency tropical cyclone area in central Vietnam. To this end, a geospatial database with 4156 fluvial flood locations and 12 flood indicators was considered. The ADAM algorithm and the MSE loss function were used to train the 1D-CNN model, whereas popular performance metrics, such as Accuracy (Acc), Kappa, and AUC, were used to measure the performance. The results indicated remarkable performance by the 1D-CNN model, achieving high prediction accuracy with metrics such as Acc = 90.7%, Kappa = 0.814, and AUC = 0.963. Notably, the proposed 1D-CNN model outperformed benchmark models, including DeepNN, SVM, and LR. This achievement underscores the promise and innovation brought by 1D-CNN in the realm of susceptibility mapping for fluvial floods.

Vietnam is a low- and middle-income country (LMIC), a primary food producer, and an antimicrobial resistance (AMR) hotspot. AMR is recognized as a One Health challenge since it may transfer between humans, animals and the environment. This study aimed to apply systematic review and meta-analysis to investigate the phenotypic profiles and correlations of antimicrobial-resistant Enterobacteriaceae across three compartments: humans, animals and the environment in Vietnam. A total of 89 articles found in PubMed, Science Direct, and Google Scholar databases were retrieved for qualitative synthesis. E. coli and non-typhoidal Salmonella (NTS) were the most common bacterial species in studies of all compartments (60/89 studies). Among antimicrobials classified as critically important, the resistance levels were observed to be highest to quinolones, 3rd generation of cephalosporins, penicillins, and aminoglycosides. Of 89 studies, 55 articles reported the resistance prevalence of E. coli and NTS in healthy humans, animals and the environment against ciprofloxacin, ceftazidime, ampicillin, gentamicin, sulfamethoxazole-trimethoprim, chloramphenicol was used for meta-analysis. The pooled prevalence was found highest in E. coli against ampicillin 84.0% (95% CI 73.0–91.0%) and sulfamethoxazole-trimethoprim 66.0% (95% CI 56.0–75.0%) while in NTS they were 34.0% (95% CI 24.0–46.0%), 33.0% (95% CI 25.0–42.0%), respectively. There were no significant differences in the pooled prevalence of E. coli and NTS to these antimicrobials across healthy humans, animals and the environment, except for ceftazidime-resistant E. coli (χ2 = 8.29, p = 0.02), chloramphenicol-resistant E.coli (χ2 = 9.65, p

Wastewater from industries has been a serious issue that both manufactures and authorities raise concerns since it brings tremendous demerits to the surrounding environment and human well-being. Therefore, an appropriate treatment method should be applied before being discharged into the environment. In this paper, sugarcane bagasse was modified with citric acid and then used to load the suspension of Fe3O4 nanoparticles to form a nanocomposite of magnetic citric acid-modified sugarcane bagasse. The properties of prepared materials were investigated by a variety of modern methods such as X-ray diffraction (XRD), Fourier transforms infrared spectroscopy (FT-IR), Scanning electron microscopy (SEM), Transmission electron microscopy (TEM) and a Vibrating sample magnetometer (VSM). The adsorptive capacity of prepared materials was investigated with methylene blue as the typical adsorbate. The decolonization effectiveness was increased with increasing contact time and declined with rising initial dye concentration. The higher removal efficiency was observed for the basic medium in comparison with the acidic medium. Additionally, the results showed that more than 12.42 mg/g (98%) of cationic yellow 51, and basic red 46 dyes were removed after 30 min.

This study is devoted to the synthesis of King Orange peel essential oil in water nanoemulsions combined with nanosilver by ultrasonic method supported by mechanical stirring for antibacterial application. The samples were characterized by Gas chromatography-mass spectrometry (GC-MS), Ultraviolet–visible (UV-Vis), Transmission electron microscopy (TEM), and Dynamic light scattering (DLS) methods. According to the above-experimental results, it was found that the emulsions based on orange essential oil (without nanosilver) and the ones combined with nanosilver have the average particle size from 66.2 nm and 42.9 nm, respectively. The obtained nanoemulsions were also tested to examine their antibacterial ability against Escherichia coli (E. coli) by the disc diffusion method. It has been also found that nanoemulsions based on orange essential oil supported by nanosilver have the superior antibacterial ability, compared with individual components of the materials.

In the Mekong Delta region of Vietnam, small-scale chicken farming is common. However, high levels of disease or mortality in such flocks impair economic development and challenge the livelihoods of many rural households. We investigated 61 diseased small-scale flocks (122 chickens) for evidence of infection with 5 bacteria, 4 viruses, and helminths. Serological profiles (ELISA) were also determined against 6 of these pathogens. The aims of this study were the following: (1) to investigate the prevalence of different pathogens and to compare the probability of detection of bacterial pathogens using PCR and culture; (2) to investigate the relationship between detection of organisms in birds' tissues and the observed morbidity and mortality, as well as their antibody profile; and (3) to characterize risk factors for infection with specific viral or bacterial pathogens. We used PCR to test for viral (viruses causing infectious bronchitis [IB], highly pathogenic avian influenza [HPAI], Newcastle disease, and infectious bursal disease [IBD]) and bacterial pathogens (Mycoplasma gallisepticum, Pasteurella multocida, Avibacterium paragallinarum, and Ornithobacterium rhinotracheale [ORT]). The latter two were also investigated in respiratory tissues by conventional culture. Colisepticemic Escherichia coli was investigated by liver or spleen culture. In 49 of 61 (80.3%) flocks, at least one bacterial or viral pathogen was detected, and in 29 (47.5%) flocks, more than one pathogen was detected. A. paragallinarum was detected in 62.3% flocks, followed by M. gallisepticum (26.2%), viruses causing IBD (24.6%) and IB (21.3%), septicemic E. coli (14.8%), ORT (13.1%), and HPAI viruses (4.9%). Of all flocks, 67.2% flocks were colonized by helminths. Mortality was highest among flocks infected with HPAI (100%, interquartile range [IQR]: 81.6–100%) and lowest with flocks infected with ORT (5.3%, IQR: 1.1–9.0%). The results indicated slight agreement (kappa ≤ 0.167) between detection by PCR and culture for both A. paragallinarum and ORT, as well as between the presence of cestodes and ORT infection (kappa = 0.317). Control of A. paragallinarum, viruses causing HPAI, IBD, and IB, M. gallisepticum, and gastrointestinal helminths should be a priority in small-scale flocks.

Abstract The accurate assessment of antimicrobial use (AMU) requires relating quantities of active ingredients (AAIs) with population denominators. These data can be used to prioritize potential sources of selective pressure for antimicrobial resistance and to establish reduction targets. Here, we estimated AMU in Vietnam (human population 93.4 M in 2015), and compared it with European Union (EU) data (population 511.5 M in 2014). We extrapolated AMU data on each key animal species and humans from different published sources to calculate overall AMU (in tonnes) in Vietnam. We then compared these data with published statistics on AMU in the European Union (EU). A total of 3838 t of antimicrobials were used in Vietnam, of which 2751 (71.7%) corresponded to animal use, and the remainder (1086 t; 28.3%) to human AMU. This equates to 261.7 mg and 247.3 mg per kg of human and animal biomass, compared with 122.0 mg and 151.5 mg in the EU. The greatest quantities of antimicrobials (in decreasing order) were used in pigs (41.7% of total use), humans (28.3%), aquaculture (21.9%) and chickens (4.8%). Combined AMU in other species accounted for

Based on the experimental results, this study develops a multi-objective optimization scheme to obtain the set of optimal process parameters for pulsed laser direct cutting of non-oriented silicon steel sheets for manufacturing motor core laminations. The experiments were conducted in the nital solvent, which was the one with the smallest thermal effect of laser cutting among the candidate environments of air, deionized water, alcohol, lubricant oil, sodium chloride solution, and nital solution. The laser was a pulsed Nd:YAG nanosecond laser and the thickness of the silicon steel was 100 μm. The effects of three laser process parameters, laser power (P), cutting speed (v), and pulse repetition rate (f) on the cutting qualities of the heat-affected zone (HAZ), cutting time (TC), and multiple dimensional accuracies of the cut core lamination were examined. The inspected geometric accuracies included the errors in inner and outer core diameters (ED1 and ED2), the error in tooth width (EL), and the roundness of inner and outer diameters (C1 and C2). The developed multi-objective optimization model was a PSI-based ELM-GA scheme consisting of the extreme learning machine (ELM) model for connecting the inputs and the outputs, the preference selection index (PSI) method for obtaining the weighted multi-objective function, and the genetic algorithm (GA) for process optimization. Through employing the predicted optimal process parameter set, the validation experiment showed that the errors between the prediction and the experimental result for the seven qualities of HAZ, ED1, ED2, C1, C2, EL, and TC were 4.04%, 6.25%, 4.02%, 0.48%, 2.14%, 5.09%, and 1.25%, respectively. The HAZ and geometric accuracy of the cut core laminations were qualified for the subsequent lamination assembly. Consequently, the merit of direct formation of ready-for-assembly core laminations without the need for any post-processing renders the proposed laser cutting scheme an economical and effective approach for manufacturing motor core laminations from thin silicon steel sheets. [ABSTRACT FROM AUTHOR]

In recent years, robot manipulator arms have become increasingly prevalent and are playing pivotal roles across various industries. Their ability to replace human labor in arduous and hazardous tasks has positioned them as indispensable assets. Consequently, there has been a surge in research efforts aimed at enhancing their operational performance. The imperative to improve their efficiency and effectiveness has garnered significant attention within the research community. In this study, a novel fault-tolerant control (FTC) scheme for robot manipulators to handle the effects of the unknown input is proposed to aid robots in achieving good tracking performance. In the first step, an extended state observer (ESO) is constructed to approximate both velocities and the unknown input in the robot system. The observer offers estimation information with good accuracy and quick convergence. The estimated signals are then combined with computed torque control (CTC), which is a useful control technique for trajectory tracking of robot manipulator systems, to construct an active FTC to decrease the influences of the unknown input. The proposed algorithm does not require velocity measurement in the design process. In addition, with a novel design approach, the combination of controller and observer provides a novel control signal that delivers higher tracking performance compared to the traditional design approach. The global and asymptotic stability of the suggested technique is proved through the Lyapunov theory. Finally, simulations are implemented on a 2-degree-of-freedom (DOF) robot manipulator to validate the efficiency of the proposed controller–observer method. [ABSTRACT FROM AUTHOR]

In the landscape of wireless communication, smart antennas, or adaptive array antennas, have emerged as vital components, offering heightened gains and spectral efficiency in advanced communication systems such as 5G and beyond. However, augmenting network coverage, capacity, and quality of service remains a pressing concern amid advancing communication technologies and escalating user demands. Array antennas with reduced sidelobe levels, high directivity, and increased beam steering capabilities are sought after to address these challenges. This paper explores convex optimization as a potent tool for array synthesis problems, offering robust performance and solution efficiency. By formulating optimization problems as convex programming, sidelobe reduction challenges can be efficiently addressed. The paper presents a comprehensive investigation into convex optimization-based approaches for array pattern nulling, assessing their performance and computational efficiency in various scenarios. Numerical examples demonstrate the efficacy of the proposed methods in maintaining the main lobe, controlling sidelobe levels, and placing nulls at interfering directions, thereby advancing the state-of-the-art in smart antenna technology. [ABSTRACT FROM AUTHOR]

Abstract Background The Mekong Delta of Vietnam is a hotspot of antimicrobial use (AMU), but there is no information on the quality of the labelling and strength of antimicrobial products used in poultry production. Methods Based on a large random sample of farms, we identified the 20 most used antimicrobial products in the area, and investigated their antimicrobial active ingredient (AAI) content by UPLC‐MS/MS (91 analytical tests). Results Only 17/59 (28.8%) batches contained all AAIs within 10% of the declared strength. Worryingly, 65.0% products provided in their label preparation guidelines for both therapeutic and prophylactic use. Withdrawal times for both meat and eggs were stated in 8/20 (40%) products. Conclusion Results highlight deficiencies in quality and labelling contents that undermine authorities’ efforts to discourage inappropriate use of antimicrobials.

Abstract Background Antimicrobials are used by poultry farmers in Vietnam as a tool to treat and prevent infectious diseases. We aimed to determine the fraction of disease episodes likely to remain untreated due to the administration of antimicrobials on non-susceptible pathogens in chicken flocks in the Mekong Delta of Vietnam. Weekly data on antimicrobial use and clinical signs were collected from 88 randomly chosen chicken flocks over 124 full production cycles (i.e. time between restocking flocks with day-old chicks and sale for slaughter). A naïve Bayes model was trained to infer the probabilities of disease episodes having been caused by each of 24 pathogens, given the observed clinical sign profile, and expert knowledge on their relative incidence. Results A total of 224 disease episodes were observed, of which 44.8% were attributed to viruses (95% CI 31.1–58.4%), 54.6% (CI 40.4–68.7%) to bacteria, and 0.6% (CI 0–1.7%) to a protozoan (Eimeria spp.). Antimicrobials were more frequently administered on weeks with disease than on weeks without disease (43.3% vs. 17.8%; p

Indiscriminate antimicrobial use (AMU) in animal production is a driver of antimicrobial resistance globally. There is a need to define sustainable interventions to reduce AMU in small-scale production systems, which currently represent the most widespread farming systems in South East Asia and many low- and middle-income countries. We conducted a before-and-after intervention study on a random sample of small-scale chicken farms in the Mekong Delta of Vietnam from 2016 to 2019. The study included a baseline followed by an intervention phase where farmers were provided with regular veterinary advice on flock health and husbandry, as well as antimicrobial replacement products. Of 102 recruited farms (raising >100 chickens per flock cycle), thirty-five (34.2%) entered the intervention phase, whilst the rest stopped raising chickens, mainly due to suboptimal flock performance. Through the implementation of our intervention, chicken flocks reduced levels of AMU by 66% [adjusted hazard ratio (HR) = 0.34; p = 0.002) from a baseline of 343.4 Animal Daily Doses per 1,000 chicken-days and decreased weekly mortality by 40% (adjusted HR = 0.60; p = 0.005) from a baseline mortality of 1.60 per 100 birds. Chicken bodyweight increased by 100 g (p = 0.002) in intervention flocks. Our findings demonstrate that the provision of veterinary advice can achieve substantial reductions in AMU in small-scale production systems without compromising flock health and productivity.

Antimicrobials are included in commercial animal feed rations in many low- and middle-income countries (LMICs). We measured antimicrobial use (AMU) in commercial feed products consumed by 338 small-scale chicken flocks in the Mekong Delta of Vietnam, before a gradual nationwide ban on prophylactic use of antimicrobials (including in commercial feeds) to be introduced in the country over the coming five years. We inspected the labels of commercial feeds and calculated amounts of antimicrobial active ingredients (AAIs) given to flocks. We framed these results in the context of overall AMU in chicken production, and highlighted those products that did not comply with Government regulations. Thirty-five of 99 (35.3%) different antimicrobial-containing feed products included at least one AAI. Eight different AAIs (avilamycin, bacitracin, chlortetracycline, colistin, enramycin, flavomycin, oxytetracycline, virginamycin) belonging to five classes were identified. Brooding feeds contained antimicrobials the most (60.0%), followed by grower (40.9%) and finisher feeds (20.0%). Quantitatively, chlortetracycline was consumed most (42.2 mg/kg SEM ±0.34; 50.0% of total use), followed by enramycin (18.4 mg/kg SEM ±0.03, 21.8%), bacitracin (16.4 mg/kg SEM ±0.20, 19.4%) and colistin (6.40 mg/kg SEM ± 4.21;7.6%). Other antimicrobials consumed were virgianamycin, avilamycin, flavomycin and oxytetracycline (each ≤0.50 mg/kg). Antimicrobials in commercial feeds were more commonly given to flocks in the earlier part of the production cycle. A total of 10 (9.3%) products were not compliant with existing Vietnamese regulation (06/2016/TT-BNNPTNT) either because they included a non-authorised AAI (4), had AAIs over the permitted limits (4), or both (2). A number of commercial feed formulations examined included colistin (polymyxin E), a critically important antimicrobial of highest priority for human medicine. These results illustrate the challenges for effective implementation and enforcement of restrictions of antimicrobials in commercial feeds in LMICs. Results from this study should help encourage discussion about policies on medicated feeds in LMICs.

Chicken is, among farmed species, the target of the highest levels of antimicrobial use (AMU). There are considerable knowledge gaps on how and when antimicrobials are used in commercial small-scale chicken farms. These shortcomings arise from cross-sectional study designs and poor record keeping practiced by many such farmers. Furthermore, there is a large diversity of AMU metrics, and it is not clear how these metrics relate to each other. We performed a longitudinal study on a cohort of small-scale chicken farms (n = 102) in the Mekong Delta (Vietnam), an area regarded as a hotspot of AMU, from October 2016 to May 2018. We collected data on all medicine products administered to 203 flocks with the following aims: (1) to describe types and quantities of antimicrobial active ingredients (AAIs) used; (2) to describe critical time points of AMU; and (3) to compare AMU using three quantitative metrics: (a) weight of AAIs related to bird weight at the time of treatment (mg/kg at treatment); (b) weight of AAIs related to weight of birds sold (mg/kg sold); and (c) “treatment incidence” (TI), or the number of daily doses per kilogram of live chicken [Vietnamese animal daily dose (ADDvetVN)] per 1,000 days. Antimicrobials contained in commercial feed, administered by injection (n = N = 6), or antimicrobials for human medicine (n = N = 16) were excluded. A total of 236 products were identified, containing 42 different AAIs. A total of 76.2% products contained AAIs of “critical importance” according to the World Health Organization (WHO). On average, chickens consumed 791.8 (SEM ±16.7) mg/kg at treatment, 323.4 (SEM ±11.3) mg/kg sold, and the TI was 382.6 (SEM ±5.5) per 1,000 days. AMU was more common early in the production cycle and was highly skewed, with the upper 25% quantile of flocks accounting for 60.7% of total AMU. The observed discrepancies between weight- and dose-based metrics were explained by differences in the strength of AAIs, mortality levels, and the timing of administration. Results suggest that in small-scale chicken production, AMU reduction efforts should preferentially target the early (brooding) period, which is when birds are most likely to be exposed to antimicrobials, whilst restricting access to antimicrobials of critical importance for human medicine.

In the Mekong Delta of Vietnam, farmers use large quantities of antimicrobials to raise small-scale chicken flocks, often including active ingredients regarded of “critical importance’” by the World Health Organization. Due to limitations in laboratory capacity, the choice of antimicrobials normally does not follow any empirical criteria of effectiveness. The aim of this study was to highlight non-critically important antimicrobials against which chicken pathogens are likely to be susceptible as a basis for treatment guidelines. Microtiter broth dilution method was performed to determine the minimal inhibitory concentration (MIC) of 12 commonly used antimicrobials for 58 isolates, including Ornithobacterium rhinotracheale (ORT) (n = 22), Gallibacterium anatis (n = 19), and Avibacterium endocarditidis (n = 17). Unfortunately, internationally accepted breakpoints for resistance in these organisms do not exist. We drew tentative epidemiological cut-offs (TECOFFs) for those antimicrobial-pathogen combinations where MIC distributions suggested the presence of a distinct non-wild-type population. Based on the observed results, doxycycline would be the drug of choice for A.endocarditidis (11.8% presumptive non-wild type) and G. anatis infections (5.3% presumptive non-wild type). A total of 13.6% ORT isolates were non-wild type with regards to oxytetracycline, making it the drug of choice against this pathogen. This study illustrates the challenges in interpreting susceptibility testing results and the need to establish internationally accepted breakpoints for veterinary pathogens.

Cross section data from the Vietnam Household Living Standard Survey 2008 (VHLSS2008) was used to estimate multidimensional poverty in five urban central cities (Ha Noi, Hai Phong, Da Nang, Ho Chi Minh, and Can Tho) in Viet Nam following the methodology developed by Alkire & Santos (2010). Five dimensions of poverty were considered in the study including education, health, standard of living, economic well-being, and employment labor. The findings show that multidimensional poverty is significantly high in central cities, especially in Ho Chi Minh City. The multidimensional poor suffer from the high deprivation intensity of indicators as type of dwelling, underemployment, housing space, and working time. Moreover, five urban central cities present non-depreciable level of deprivation in electricity. Under-employment deprivation significantly increases its contribution as it receives a higher weight in the estimation. The study highlights the potential application of the methodology for national poverty measurement at multidimensional level as well as a tool for state budget allocation.

In the Mekong Delta of Vietnam, small-scale poultry farmers use large amounts of antimicrobials to raise their flocks, and veterinary drug shops owners and their staff are a key source of advice to farmers on antimicrobial use (AMU). We described the network of veterinary drug shops (n = 93) in two districts within Dong Thap province (Mekong Delta). We also interviewed a randomly selected sample of chicken farmers (n = 96) and described their linkages with veterinary drug shops. Antimicrobials represented 15.0% [inter quartile range (IQR) 6.0−25.0] of the shops’ income. Fifty-seven percent shop owners had been/were affiliated to the veterinary authority, 57% provided diagnostic services. The median number of drug shops supplying antimicrobials to each farm during one production cycle was 2 [IQR 1−2]. Visited shops were located within a median distance of 3.96 km [IQR 1.98−5.85] to farms. Drug shops owned by persons affiliated to the veterinary authority that did not provide diagnostic services had a higher fraction of their income consisting of antimicrobial sales (β = 1.913; p < 0.001). These results suggest that interventions targeting veterinary drug shop owners and their staff aiming at improving their knowledge base on livestock/poultry diseases and their diagnosis may contribute to reducing overall levels of AMU in the area.