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Introduction Bacterial bloodstream and urinary tract infections present a huge health burden especially in low-resource settings, which is worsened by the escalating burden of antimicrobial resistance (AMR). However, surveillance data on antimicrobial susceptibility profiles of pathogens remains scarce in Malawi. Therefore, this study aimed at establishing trends and patterns of AMR among common pathogens causing adult bloodstream and urinary tract infections in Malawi. Methods This was a secondary analysis of records from bacterial culture and susceptibility testing results of routinely collected adult blood and urinary tract samples from seven facilities in Malawi between January 2020 and August 2024. Antimicrobial susceptibility testing (AST) was performed using the disk diffusion method and interpreted according to EUCAST guidelines. The outcome of interest was the AST results of the bacterial isolates. Data were analyzed using SPSS version 28. Results Out of the 2787 isolates collected, 80.6% ( n  = 2246) were from urine samples and 19.4% ( n  = 541) were from blood samples. 74.1% ( n  = 2066) of the isolates were Gram-negative organisms. Escherichia coli (37.6%, n  = 1048) and Klebsiella pneumoniae (8.3%, n  = 232) were the most frequent isolates. A total of 16,696 ASTs were performed on the isolates, with 54.3% ( n  = 9,068) showing resistance to the antibiotics tested. Among Gram-positive organisms, there was increasing resistance to co-trimoxazole (71.4-83.3%), vancomycin (20.0-31.0%), with consistently high resistance rates to ciprofloxacin, erythromycin and gentamicin. Gram-negative organisms showed trends of increasing resistance to ceftriaxone (63.0-72.4%), co-trimoxazole (72.7-89.7%), and piperacillin and tazobactam (0.0-35.8%), with a notable significant increase in resistance to ciprofloxacin (66.7-81.0%, p  = 0.001). There was an increasing trend of Enterobacteriaceae resistance to third-generation cephalosporins (58.9-71.5%). Overall, pathogens with the highest resistance include Citrobacter freundii (62.1%, n  = 755/1216), Staphylococcus sp. (62.0%, n  = 163/263) and K. pneumoniae (57.1%, n  = 941/1648). Among the commonly isolated pathogens, E. coli , K. pneumoniae and Enterobacter spp. showed highest resistance to multiple antibiotics. Conclusion The study revealed high resistance levels among pathogens that cause BSIs and UTIs in public hospitals in Malawi. Most pathogens demonstrated high resistance against multiple antibiotic classes. The high AMR trends and patterns pose a significant risk to healthcare provision, calling for enhancing surveillance and upscaling efforts to address the challenge.

Antimicrobial resistance (AMR) has developed as one of the major urgent threats to public health causing serious issues to successful prevention and treatment of persistent diseases. In spite of different actions taken in recent decades to tackle this issue, the trends of global AMR demonstrate no signs of slowing down. Misusing and overusing different antibacterial agents in the health care setting as well as in the agricultural industry are considered the major reasons behind the emergence of antimicrobial resistance. In addition, the spontaneous evolution, mutation of bacteria, and passing the resistant genes through horizontal gene transfer are significant contributors to antimicrobial resistance. Many studies have demonstrated the disastrous financial consequences of AMR including extremely high healthcare costs due to an increase in hospital admissions and drug usage. The literature review, which included articles published after the year 2012, was performed using Scopus, PubMed and Google Scholar with the utilization of keyword searches. Results indicated that the multifactorial threat of antimicrobial resistance has resulted in different complex issues affecting countries across the globe. These impacts found in the sources are categorized into three different levels: patient, healthcare, and economic. Although gaps in knowledge about AMR and areas for improvement are obvious, there is not any clearly understood progress to put an end to the persistent trends of antimicrobial resistance.

Bacterial infections have been traditionally controlled by antibiotics and vaccines, and these approaches have greatly improved health and longevity. However, multiple stakeholders are declaring that the lack of new interventions is putting our ability to prevent and treat bacterial infections at risk. Vaccine and antibiotic approaches still have the potential to address this threat. Innovative vaccine technologies, such as reverse vaccinology, novel adjuvants, and rationally designed bacterial outer membrane vesicles, together with progress in polysaccharide conjugation and antigen design, have the potential to boost the development of vaccines targeting several classes of multidrug-resistant bacteria. Furthermore, new approaches to deliver small-molecule antibacterials into bacteria, such as hijacking active uptake pathways and potentiator approaches, along with a focus on alternative modalities, such as targeting host factors, blocking bacterial virulence factors, monoclonal antibodies, and microbiome interventions, all have potential. Both vaccines and antibacterial approaches are needed to tackle the global challenge of antimicrobial resistance (AMR), and both areas have the underpinning science to address this need. However, a concerted research agenda and rethinking of the value society puts on interventions that save lives, by preventing or treating life-threatening bacterial infections, are needed to bring these ideas to fruition.

Background/Objectives: As part of the European Union’s harmonized monitoring framework, Belgium conducts antimicrobial resistance (AMR) monitoring in commensal bacteria from livestock. The aim of this study was to conduct a cost analysis of the national AMR monitoring in livestock, and to explore sampling size scenarios in relation to their associated costs and statistical performance (power and confidence) of monitoring. Methods: To our knowledge, this is the first published cost evaluation using unit cost aggregation of a national AMR monitoring program in animals. Results: The testing of the different sample size scenarios showed that if the sample size increases, the costs increase linearly. A sample size increase of 10 samples/isolates (e.g., from 170 to 180) can increase the yearly total costs per animal species by 5.2%. Moreover, the testing of the different scenarios showed that if the sample size increases, the power and the confidence level also increase, providing a higher level of trust in the results of the monitoring program. The highest total monitoring costs per animal category were estimated for fattening pigs, broilers and veal calves (over 18% of total costs each, using 2024 data). Among the various monitoring activities, antimicrobial susceptibility testing emerged as the costliest component, representing 50.2% of the total monitoring costs. Conclusions: The approach presented allows it to be used by other countries aiming to estimate the cost of their national AMR monitoring in animals or other similar activities. This economic and scenario testing analysis can be used to suggest informed suggestions to improve AMR monitoring in animals.

The 2021 sales volume in the market of service robots is attractive. Expert reports from the International Federation of Robotics confirm 27 billion USD in total market share. Moreover, the number of new startups with the denomination of service robots nowadays constitutes 29% of the total amount of robotic companies recorded in the United States. Those data, among other similar figures, remark the need for formal development in the service robots area, including knowledge transfer and literature reviews. Furthermore, the COVID-19 spread accelerated business units and some research groups to invest time and effort into the field of service robotics. Therefore, this research work intends to contribute to the formalization of service robots as an area of robotics, presenting a systematic review of scientific literature. First, a definition of service robots according to fundamental ontology is provided, followed by a detailed review covering technological applications; state-of-the-art, commercial technology; and application cases indexed on the consulted databases.

Background: In 2019, a new type of coronavirus emerged and spread to the rest of the world. Numerous drugs were identified as possible treatments. Among the candidates for possible treatment was azithromycin alone or in combination with other drugs. As a result, many clinicians in Brazil have prescribed azithromycin in an attempt to combat or minimize the effects of COVID19. Aim: This study analyzed the sales data of the main antibiotics prescribed in Brazil to verify the change in consumption trends of these drugs during the COVID-19 pandemic. Methods: This is an interrupted time series that analyzed antimicrobial sales data between January 2014 and July 2021, publicly accessible information obtained from the Brazilian government’s website. Monthly means of “defined daily doses of DDDs” (DDDs per 1,000 inhabitants per day) of antibiotics were compared by analysis of variance, followed by the Dunnett Multiple Comparisons Test. Monthly trend changes in antibiotic use were verified using Joinpoint regression. Results: Amoxicillin (31.97%), azithromycin (18.33%), and cefalexin (16.61%) were the most sold antibiotics in Brazil during the evaluation period. Azithromycin consumption rose from 1.40 DDDs in February 2020 to 3.53 DDDs in July 2020. Azithromycin sales showed a significant increase in the pandemic period [Monthly Percent Change (MPC) 5.83%, 95% 1.80; 10.00], whereas there was a fall in amoxicillin sales (MPC −9.00%, 95% CI −14.70; −2.90) and cefalexin [MPC-2.70%, 95% (CI −6.30; −1.10)] in this same period. Conclusion: The COVID-19 pandemic changed the pattern of antibiotic consumption in Brazil, with a decrease in the use of amoxicillin and cefalexin and an increase in the consumption of azithromycin.

Background/Objectives: Antimicrobial resistance (AMR) surveillance is a cornerstone of national AMR strategies but requires sustained, cross-sectoral financing. While the need for such financing is well recognized, its quantification remains scarce in low- and middle-income countries. This study aimed to estimate the full costs of AMR surveillance across the human health, animal health, and food sectors (2021–2030) in selected facilities in Nepal and generate evidence to inform sustainable financing. Methods: A bottom-up micro-costing approach was used to analyze data from five sites. Costs were adjusted for inflation using projected gross domestic product deflators, and probabilistic sensitivity analyses were conducted to assess uncertainty in laboratory sample volumes under four scenarios. Results: The total cost of AMR surveillance in Nepal was$6.7 million: $ 3.4 million for human health (50.3% out of the aggregated costs),$2.7 million for animal health (39.8%), and $ 0.7 million for the food sector (9.9%). Laboratories accounted for >90% of total costs, with consumables and personnel as the main cost drivers. Average cost per sample was$150 (animal), $ 64 (food), and $6 (human). Conclusions: This study offers the first robust, multi-sectoral 10-year cost estimates of AMR surveillance in Nepal. The findings highlight that sustaining AMR surveillance requires predictable domestic financing, particularly to cover recurrent laboratory operations as donor support declines. These results provide cost evidence to support future budgeting and policy planning toward sustainable, nationally financed AMR surveillance in Nepal.

Antimicrobial resistance (AMR) remains of major interest for different types of food stakeholders since it can negatively impact human health on a global scale. Antimicrobial-resistant bacteria and/or antimicrobial resistance genes (transfer in pathogenic bacteria) may contaminate food at any stage, from the field to retail. Research demonstrates that antimicrobial-resistant bacterial infection(s) occur more frequently in low- and middle-income countries (LMICs) than in developed countries. Worldwide, foodborne pathogens are a primary cause of morbidity and mortality. The spread of pathogenic bacteria from food to consumers may occur by direct or indirect routes. Therefore, an array of approaches both at the national and international level to control the spread of foodborne pathogens and promote food safety and security are essential. Zoonotic microbes can spread through the environment, animals, humans, and the food chain. Antimicrobial drugs are used globally to treat infections in humans and animals and prophylactically in production agriculture. Research highlights that foods may become contaminated with AMR bacteria (AMRB) during the continuum from the farm to processing to retail to the consumer. To mitigate the risk of AMRB in humans, it is crucial to control antibiotic use throughout food production, both for animal and crop agriculture. The main inferences of this review are (1) routes by which AMRB enters the food chain during crop and animal production and other modes, (2) prevention and control steps for AMRB, and (3) impact on human health if AMR is not addressed globally. A thorough perspective is presented on the gaps in current systems for surveillance of antimicrobial use in food production and/ or AMR in the food chain.

The emergence of COVID-19 infection led to the indiscriminate use of antimicrobials without knowing their efficacy in treating the disease. The gratuitous use of antibiotics for COVID-19 treatment raises concerns about the emergence of antimicrobial resistance (AMR). In this systematic review, we performed a thorough systematic search using Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines of scientific databases (Scopus, Web of Science, and PubMed) to identify studies where antibiotics were prescribed to treat COVID-19 (December 2019 to December 2021). Of 970 identified studies, 130 were included in our analyses. Almost 78% of COVID-19 patients have been prescribed an antibiotic. Cephalosporins were the most prescribed (30.1% of patients) antibiotics, followed by azithromycin (26% of patients). Antibiotics were prescribed for COVID-19 patients regardless of reported severity; the overall rate of antibiotic use was similar when comparing patients with a severe or critical illness (77.4%) and patients with mild or moderate illness (76.8%). Secondary infections were mentioned in only 11 studies. We conclude that concerns related to COVID-19 and the lack of treatment strategy led to the overuse of antibiotics without proper clinical rationale. Based on our findings, we propose that antimicrobial stewardship should be retained as a priority while treating viral pandemics.

Artificial intelligence (AI) is a branch of science and engineering that focuses on the computational understanding of intelligent behavior. Many human professions, including clinical diagnosis and prognosis, are greatly useful from AI. Antimicrobial resistance (AMR) is among the most critical challenges facing Pakistan and the rest of the world. The rising incidence of AMR has become a significant issue, and authorities must take measures to combat the overuse and incorrect use of antibiotics in order to combat rising resistance rates. The widespread use of antibiotics in clinical practice has not only resulted in drug resistance but has also increased the threat of super-resistant bacteria emergence. As AMR rises, clinicians find it more difficult to treat many bacterial infections in a timely manner, and therapy becomes prohibitively costly for patients. To combat the rise in AMR rates, it is critical to implement an institutional antibiotic stewardship program that monitors correct antibiotic use, controls antibiotics, and generates antibiograms. Furthermore, these types of tools may aid in the treatment of patients in the event of a medical emergency in which a physician is unable to wait for bacterial culture results. AI’s applications in healthcare might be unlimited, reducing the time it takes to discover new antimicrobial drugs, improving diagnostic and treatment accuracy, and lowering expenses at the same time. The majority of suggested AI solutions for AMR are meant to supplement rather than replace a doctor’s prescription or opinion, but rather to serve as a valuable tool for making their work easier. When it comes to infectious diseases, AI has the potential to be a game-changer in the battle against antibiotic resistance. Finally, when selecting antibiotic therapy for infections, data from local antibiotic stewardship programs are critical to ensuring that these bacteria are treated quickly and effectively. Furthermore, organizations such as the World Health Organization (WHO) have underlined the necessity of selecting the appropriate antibiotic and treating for the shortest time feasible to minimize the spread of resistant and invasive resistant bacterial strains.