The scope of the antimicrobial resistance challenge.

Each year, an estimated 7·7 million deaths are attributed to bacterial infections, of which 4.95 million are associated with drug-resistant pathogens, and 1·27 million are caused by bacterial pathogens resistant to the antibiotics available. Access to effective antibiotics when indicated prolongs life, reduces disability, reduces health-care expenses, and enables access to other life-saving medical innovations. Antimicrobial resistance undoes these benefits and is a major barrier to attainment of the Sustainable Development Goals, including targets for newborn survival, progress on healthy ageing, and alleviation of poverty. Adverse consequences from antimicrobial resistance are seen across the human life course in both health-care-associated and community-associated infections, as well as in animals and the food chain. The small set of effective antibiotics has narrowed, especially in resource-poor settings, and people who are very young, very old, and severely ill are particularly susceptible to resistant infections. This paper, the first in a Series on the challenge of antimicrobial resistance, considers the global scope of the problem and how it should be measured. Robust and actionable data are needed to drive changes and inform effective interventions to contain resistance. Surveillance must cover all geographical regions, minimise biases towards hospital-derived data, and include non-human niches.

Global surveillance of antimicrobial resistance in food animals using priority drugs maps.

Antimicrobial resistance (AMR) in food animals is a growing threat to animal health and potentially to human health. In resource-limited settings, allocating resources to address AMR can be guided with maps. Here, we mapped AMR prevalence in 7 antimicrobials in Escherichia coli and nontyphoidal Salmonella species across low- and middle-income countries (LIMCs), using 1088 point-prevalence surveys in combination with a geospatial model. Hotspots of AMR were predicted in China, India, Brazil, Chile, and part of central Asia and southeastern Africa. The highest resistance prevalence was for tetracycline (59% for E. coli and 54% for nontyphoidal Salmonella, average across LMICs) and lowest for cefotaxime (33% and 19%). We also identified the antimicrobial with the highest probability of resistance exceeding critical levels (50%) in the future (1.7-12.4 years) for each 10 × 10 km pixel on the map. In Africa and South America, 78% locations were associated with penicillins or tetracyclines crossing 50% resistance in the future. In contrast, in Asia, 77% locations were associated with penicillins or sulphonamides. Our maps highlight diverging geographic trends of AMR prevalence across antimicrobial classes, and can be used to target AMR surveillance in AMR hotspots for priority antimicrobial classes.

Health system assessment for access to care after injury in low- or middle-income countries: A mixed methods study from Northern Malawi.

BACKGROUND: Injuries represent a vast and relatively neglected burden of disease affecting low- and middle-income countries (LMICs). While many health systems underperform in treating injured patients, most assessments have not considered the whole system. We integrated findings from 9 methods using a 3 delays approach (delays in seeking, reaching, or receiving care) to prioritise important trauma care health system barriers in Karonga, Northern Malawi, and exemplify a holistic health system assessment approach applicable in comparable settings. METHODS AND FINDINGS: To provide multiple perspectives on each conceptual delay and include data from community-based and facility-based sources, we used 9 methods to examine the injury care health system. The methods were (1) household survey; (2) verbal autopsy analysis; (3) community focus group discussions (FGDs); (4) community photovoice; (5) facility care-pathway process mapping and elucidation of barriers following injury; (6) facility healthcare worker survey; (7) facility assessment survey; (8) clinical vignettes for care process quality assessment of facility-based healthcare workers; and (9) geographic information system (GIS) analysis. Empirical data collection took place in Karonga, Northern Malawi, between July 2019 and February 2020. We used a convergent parallel study design concurrently conducting all data collection before subsequently integrating results for interpretation. For each delay, a matrix was created to juxtapose method-specific data relevant to each barrier identified as driving delays to injury care. Using a consensus approach, we graded the evidence from each method as to whether an identified barrier was important within the health system. We identified 26 barriers to access timely quality injury care evidenced by at least 3 of the 9 study methods. There were 10 barriers at delay 1, 6 at delay 2, and 10 at delay 3. We found that the barriers "cost," "transport," and "physical resources" had the most methods providing strong evidence they were important health system barriers within delays 1 (seeking care), 2 (reaching care), and 3 (receiving care), respectively. Facility process mapping provided evidence for the greatest number of barriers-25 of 26 within the integrated analysis. There were some barriers with notable divergent findings between the community- and facility-based methods, as well as among different community- and facility-based methods, which are discussed. The main limitation of our study is that the framework for grading evidence strength for important health system barriers across the 9 studies was done by author-derived consensus; other researchers might have created a different framework. CONCLUSIONS: By integrating 9 different methods, including qualitative, quantitative, community-, patient-, and healthcare worker-derived data sources, we gained a rich insight into the functioning of this health system's ability to provide injury care. This approach allowed more holistic appraisal of this health system's issues by establishing convergence of evidence across the diverse methods used that the barriers of cost, transport, and physical resources were the most important health system barriers driving delays to seeking, reaching, and receiving injury care, respectively. This offers direction and confidence, over and above that derived from single methodology studies, for prioritising barriers to address through health service development and policy.

A case for ongoing structural support to maximise infectious disease modelling efficiency for future public health emergencies: A modelling perspective.

This short communication reflects upon the challenges and recommendations of multiple COVID-19 modelling and data analytic groups that provided quantitative evidence to support health policy discussions in Switzerland and Germany during the SARS-CoV-2 pandemic. Capacity strengthening outside infectious disease emergencies will be required to enable an environment for a timely, efficient, and data-driven response to support decisions during any future infectious disease emergency. This will require 1) a critical mass of trained experts who continuously advance state-of-the-art methodological tools, 2) the establishment of structural liaisons amongst scientists and decision-makers, and 3) the foundation and management of data-sharing frameworks.

Predictive Mapping of Antimicrobial Resistance for Escherichia coli, Salmonella, and Campylobacter in Food-Producing Animals, Europe, 2000-2021.

In Europe, systematic national surveillance of antimicrobial resistance (AMR) in food-producing animals has been conducted for decades; however, geographic distribution within countries remains unknown. To determine distribution within Europe, we combined 33,802 country-level AMR prevalence estimates with 2,849 local AMR prevalence estimates from 209 point prevalence surveys across 31 countries. We produced geospatial models of AMR prevalence in Escherichia coli, nontyphoidal Salmonella, and Campylobacter for cattle, pigs, and poultry. We summarized AMR trends by using the proportion of tested antimicrobial compounds with resistance >50% and generated predictive maps at 10 × 10 km resolution that disaggregated AMR prevalence. For E. coli, predicted prevalence rates were highest in southern Romania and southern/eastern Italy; for Salmonella, southern Hungary and central Poland; and for Campylobacter, throughout Spain. Our findings suggest that AMR distribution is heterogeneous within countries and that surveillance data from below the country level could help with prioritizing resources to reduce AMR.

Taxation of veterinary antibiotics to reduce antimicrobial resistance.

Routine usage of antibiotics for animal health is a key driver of antimicrobial resistance (AMR) in food-producing animals. Taxation is a possible approach to incentivise appropriate antibiotic usage in food-producing animals. Taxation can be applied flatly across all antibiotic classes, targeted to single antibiotic classes, or scaled based on resistance in each class, so called "differential" taxation. However, quantifying the potential impact of taxation is challenging, due to the nonlinear and unintuitive response of AMR dynamics to interventions and changes in antibiotic usage caused by alterations in price. We combine epidemiological models with price elasticities of demand for veterinary antibiotics, to compare the potential benefits of taxation schemes with currently implemented bans on antibiotic usage. Taxation strategies had effects comparable to bans on antibiotic usage in food-producing animals to reduce average resistance prevalence and prevent increases in overall infection. Taxation could also maximise the average number of antibiotics with a resistance prevalence of under 25% and potentially generate annual global revenues of ∼1 billion US$ under a 50% taxation to current prices of food-producing animal antibiotics. Differential taxation was also able to maintain a high availability of antibiotics over time compared to single and flat taxation strategies, while also having the lowest rates of intervention failure and highest potential revenue across all taxation strategies. These findings suggest that taxation should be further explored as a tool to combat the ongoing AMR crisis.

Dispersal history and bidirectional human-fish host switching of invasive, hypervirulent Streptococcus agalactiae sequence type 283.

Human group B Streptococcus (GBS) infections attributable to an invasive, hypervirulent sequence type (ST) 283 have been associated with freshwater fish consumption in Asia. The origin, geographic dispersion pathways and host transitions of GBS ST283 remain unresolved. We gather 328 ST283 isolate whole-genome sequences collected from humans and fish between 1998 and 2021, representing eleven countries across four continents. We apply Bayesian phylogeographic analyses to reconstruct the dispersal history of ST283 and combine ST283 phylogenies with genetic markers and host association to investigate host switching and the gain and loss of antimicrobial resistance and virulence factor genes. Initial dispersal within Asia followed ST283 emergence in the early 1980s, with Singapore, Thailand and Hong Kong observed as early transmission hubs. Subsequent intercontinental dispersal originating from Vietnam began in the decade commencing 2001, demonstrating ST283 holds potential to expand geographically. Furthermore, we observe bidirectional host switching, with the detection of more frequent human-to-fish than fish-to-human transitions, suggesting that sound wastewater management, hygiene and sanitation may help to interrupt chains of transmission between hosts. We also show that antimicrobial resistance and virulence factor genes were lost more frequently than gained across the evolutionary history of ST283. Our findings highlight the need for enhanced surveillance, clinical awareness, and targeted risk mitigation to limit transmission and reduce the impact of an emerging pathogen associated with a high-growth aquaculture industry.

Global incidence in hospital-associated infections resistant to antibiotics: An analysis of point prevalence surveys from 99 countries.

BACKGROUND: Hospital-associated infections (HAIs) are an important cause of morbidity and mortality around the world. Many HAIs are caused by drug-resistant bacterial pathogens, but there are major gaps in our understanding of the number of hospital-associated drug-resistant infections (HARIs) worldwide. As such, we estimated trends in prevalence of HARIs caused by high priority pathogens (Escherichia coli, Acinetobacter spp., Klebsiella spp., Staphylococcus aureus, Enterobacter spp., and Pseudomonas spp.) in 195 countries. METHODS AND FINDINGS: Resistance prevalence estimates were extracted from 474-point prevalence surveys (PPS) from 99 countries published between 2010 and 2020 coupled with country-level estimates of hospitalization rates and length of stay. Prevalence estimates were transformed in yearly incidence of HARIs per year by country and income group. We estimate the global number of HARIs per year to be 136 million (95% credible interval (CI) 26 to 246 million) per year, with the highest burden in China (52 million, 95% CI 10 to 95 million), Pakistan (10 million, 95% CI 2 to 18 million), and India (9 million, 95% CI 3 to 15 million). Among income groups, middle-income countries bore the highest burden of HARIs per year (119 million, 95% CI 23 to 215 million). Our analysis was constrained by the limited number of PPS for HARIs, lack of community-associated data on antibiotic-resistant infections, and our population level analysis. CONCLUSIONS: In this study, we observe, in the absence of systematic surveillance systems for HARIs, a baseline overview of their rates. Our yearly estimates highlight the global threat of HARIs and may help define strategies to tackle resistance in hospital settings.

Global antimicrobial-resistance drivers: an ecological country-level study at the human-animal interface.

BACKGROUND: Antimicrobial resistance (AMR) is a pressing, holistic, and multisectoral challenge facing contemporary global health. In this study we assessed the associations between socioeconomic, anthropogenic, and environmental indicators and country-level rates of AMR in humans and food-producing animals. METHODS: In this modelling study, we obtained data on Carbapenem-resistant Acinetobacter baumanii and Pseudomonas aeruginosa, third generation cephalosporins-resistant Escherichia coli and Klebsiella pneumoniae, oxacillin-resistant Staphylococcus aureus and vancomycin-resistant Enterococcus faecium AMR in humans and food-producing animals from publicly available sources, including WHO, World Bank, and Center for Disease Dynamics Economics and Policy. AMR in food-producing animals presented a combined prevalence of AMR exposure in cattle, pigs, and chickens. We used multivariable ß regression models to determine the adjusted association between human and food-producing animal AMR rates and an array of ecological country-level indicators. Human AMR rates were classified according to the WHO priority pathogens list and antibiotic-bacterium pairs. FINDINGS: Significant associations were identified between animal antimicrobial consumption and AMR in food-producing animals (OR 1·05 [95% CI 1·01-1·10]; p=0·013), and between human antimicrobial consumption and AMR specifically in WHO critical priority (1·06 [1·00-1·12]; p=0·035) and high priority (1·22 [1·09-1·37]; p<0·0001) pathogens. Bidirectional associations were also found: animal antibiotic consumption was positively linked with resistance in critical priority human pathogens (1·07 [1·01-1·13]; p=0·020) and human antibiotic consumption was positively linked with animal AMR (1·05 [1·01-1·09]; p=0·010). Carbapenem-resistant Acinetobacter baumanii, third generation cephalosporins-resistant Escherichia coli, and oxacillin-resistant Staphylococcus aureus all had significant associations with animal antibiotic consumption. Analyses also suggested significant roles of socioeconomics, including governance on AMR rates in humans and animals. INTERPRETATION: Reduced rates of antibiotic consumption alone will not be sufficient to combat the rising worldwide prevalence of AMR. Control methods should focus on poverty reduction and aim to prevent AMR transmission across different One Health domains while accounting for domain-specific risk factors. The levelling up of livestock surveillance systems to better match those reporting on human AMR, and, strengthening all surveillance efforts, particularly in low-income and middle-income countries, are pressing priorities. FUNDING: None.

Exploring the epidemiology of mcr genes, genetic context and plasmids in Enterobacteriaceae originating from pigs and humans on farms in Thailand.

OBJECTIVES: In veterinary medicine, colistin has been widely used as therapeutic and prophylactic agent, and for growth promotion. However, colistin has been re-introduced into treatment of human MDR bacterial infections. We assessed the characteristics and spread of plasmid-borne colistin resistance among healthy pigs, workers with animal-contact and their household members in Thailand. METHODS: WGS and MIC data of 146 mcr-positive isolates from a cross-sectional One Health study were analysed. Long-read sequencing and conjugation were performed for selected isolates. RESULTS: mcr-carrying isolates were detected in 38% of pooled-pig samples and 16% of human faecal samples. Of 143 Escherichia coli and three Escherichia fergusonii, mcr-1, mcr-3, and mcr-9 variants were identified in 96 (65.8%), 61 (41.8%) and one (0.7%) isolate, respectively. Twelve E. coli co-harboured two mcr variants (mcr-1 and mcr-3). Clonal transmission was detected in five out of 164 farms. mcr-1 was mostly harboured by epidemic IncX4 and IncHI1 plasmids (89.9%). Conversely, mcr-3 was harboured by a range of different plasmids. Comparative plasmid studies suggested IncP and IncFII plasmids as possible endemic mcr-3 plasmids in Asian countries. Moreover, mcr-3 was associated with different mobile genetic elements including TnAs2, ISKpn40 and IS26/15DI. Detected genetic signatures (DRs) indicated recent mcr-3 transpositions, underlining the mobilizable nature of the mcr-3 cassette. CONCLUSIONS: The epidemiology of mcr and the possible evolution of successful plasmids and transposition modules should be carefully monitored. Of special concern is the growing number of different horizontal gene transferring pathways encompassing various transposable modules the mcr genes can be shared between bacteria.

Global trends in antimicrobial use in food-producing animals: 2020 to 2030.

Use of antimicrobials in farming has enabled the growth of intensive animal production and helped in meeting the global increase in demand for animal protein. However, the widespread use of veterinary antimicrobials drives antimicrobial resistance, with important consequences for animal health, and potentially human health. Global monitoring of antimicrobial use is essential: first, to track progress in reducing the reliance of farming on antimicrobials. Second, to identify countries where antimicrobial-stewardship efforts should be targeted to curb antimicrobial resistance. Data on usage of antimicrobials in food animals were collected from 42 countries. Multivariate regression models were used in combination with projections of animal counts for cattle, sheep, chicken, and pigs from the Food and Agriculture Organization to estimate global antimicrobial usage of veterinary antimicrobials in 2020 and 2030. Maps of animal densities were used to identify geographic hotspots of antimicrobial use. In each country, estimates of antimicrobial use (tonnes) were calibrated to match continental-level reports of antimicrobial use intensity (milligrams per kilogram of animal) from the World Organization for Animal Health, as well as country-level reports of antimicrobial use from countries that made this information publicly available. Globally, antimicrobial usage was estimated at 99,502 tonnes (95% CI 68,535-198,052) in 2020 and is projected, based on current trends, to increase by 8.0% to 107,472 tonnes (95% CI: 75,927-202,661) by 2030. Hotspots of antimicrobial use were overwhelmingly in Asia (67%), while <1% were in Africa. Findings indicate higher global antimicrobial usage in 2030 compared to prior projections that used data from 2017; this is likely associated with an upward revision of antimicrobial use in Asia/Oceania (~6,000 tonnes) and the Americas (~4,000 tonnes). National-level reporting of antimicrobial use should be encouraged to better evaluate the impact of national policies on antimicrobial use levels.

Mapping Global Bushmeat Activities to Improve Zoonotic Spillover Surveillance by Using Geospatial Modeling.

Human populations that hunt, butcher, and sell bushmeat (bushmeat activities) are at increased risk for zoonotic pathogen spillover. Despite associations with global epidemics of severe illnesses, such as Ebola and mpox, quantitative assessments of bushmeat activities are lacking. However, such assessments could help prioritize pandemic prevention and preparedness efforts. We used geospatial models that combined published data on bushmeat activities and ecologic and demographic drivers to map the distribution of bushmeat activities in rural regions globally. The resulting map had high predictive capacity for bushmeat activities (true skill statistic = 0.94). The model showed that mammal species richness and deforestation were principal drivers of the geographic distribution of bushmeat activities and that countries in West and Central Africa had the highest proportion of land area associated with bushmeat activities. These findings could help prioritize future surveillance of bushmeat activities and forecast emerging zoonoses at a global scale.

Global biogeography and projection of soil antibiotic resistance genes.

Although edaphic antibiotic resistance genes (ARGs) pose serious threats to human well-being, their spatially explicit patterns and responses to environmental constraints at the global scale are not well understood. This knowledge gap is hindering the global action plan on antibiotic resistance launched by the World Health Organization. Here, a global analysis of 1088 soil metagenomic samples detected 558 ARGs in soils, where ARG abundance in agricultural habitats was higher than that in nonagricultural habitats. Soil ARGs were mostly carried by clinical pathogens and gut microbes that mediated the control of climatic and anthropogenic factors to ARGs. We generated a global map of soil ARG abundance, where the identified microbial hosts, agricultural activities, and anthropogenic factors explained ARG hot spots in India, East Asia, Western Europe, and the United States. Our results highlight health threats from soil clinical pathogens carrying ARGs and determine regions prioritized to control soil antibiotic resistance worldwide.

Genome-associations of extended-spectrum ß-lactamase producing (ESBL) or AmpC producing E. coli in small and medium pig farms from Khon Kaen province, Thailand.

Thailand is undergoing rapid intensification of livestock production where small subsistence farms and medium sized commercial farms coexist. In medium farms, antimicrobials are prescribed by a veterinarian, whereas in small farms antimicrobial use remains largely unsupervised. The impact of these differences as well as other farming practices on the emergence and composition of antimicrobial resistance genes (ARGs) remains largely unknown. We analyzed 363 genomes of extended-spectrum ß-lactamase producing (ESBL) and/or AmpC producing Escherichia coli recovered from humans and pigs at small and medium farms from the Khon Kaen province, Thailand. We tested for genome-wide associations to identify links between ARGs, host, and farm size. Pig isolates from small farms were associated with mcr and qnr genes conferring resistance to colistin and fluoroquinolones, respectively. In contrast, pig isolates from medium farms were associated with ARGs conferring resistance to drugs commonly used on medium farms (i.e., streptomycin). ESBL plasmids from small farms co-carried ARGs conferring resistance to critically important antimicrobials more frequently compared to plasmid from medium farms. Frequent ARG combinations included blaCTX-M-55 + qnrS1 (29.8% vs 17.5% in small and medium farms, respectively), blaCTX-M-55 + qnrS1 + mcr-3.19 (5% vs 0%), blaCTX-M-14 + qnrS1 (9.3% vs 6.2%), and blaCTX-M-14 + qnrS1 + mcr-1.1 (3.1% vs 0%). The co-location on plasmids of ARGs conferring resistance to critically important antimicrobials as defined by the World Health Organization is concerning, and actions to curb their spread are urgently needed. Legislation on limiting antimicrobial sales and initiatives to better inform farmers and veterinarians on appropriate antimicrobial usage and farm biosecurity could help reduce antimicrobial use on farms.

A hybrid Neural Network-SEIR model for forecasting intensive care occupancy in Switzerland during COVID-19 epidemics.

Anticipating intensive care unit (ICU) occupancy is critical in supporting decision makers to impose (or relax) measures that mitigate COVID-19 transmission. Mechanistic approaches such as Susceptible-Infected-Recovered (SIR) models have traditionally been used to achieve this objective. However, formulating such models is challenged by the necessity to formulate equations for plausible causal mechanisms between the intensity of COVID-19 transmission and external epidemic drivers such as temperature, and the stringency of non-pharmaceutical interventions. Here, we combined a neural network model (NN) with a Susceptible-Exposed-Infected-Recovered model (SEIR) in a hybrid model and attempted to increase the prediction accuracy of existing models used to forecast ICU occupancy. Between 1st of October, 2020 - 1st of July, 2021, the hybrid model improved performances of the SEIR model at different geographical levels. At a national level, the hybrid model improved, prediction accuracy (i.e., mean absolute error) by 74%. At the cantonal and hospital levels, the reduction on the forecast's mean absolute error were 46% and 50%, respectively. Our findings illustrate those predictions from hybrid model can be used to anticipate occupancy in ICU, and support the decision-making for lifesaving actions such as the transfer of patients and dispatching of medical personnel and ventilators.

Access to care following injury in Northern Malawi, a comparison of travel time estimates between Geographic Information System and community household reports.

INTRODUCTION: Injuries disproportionately impact low- and middle-income countries like Malawi. The Lancet Commission on Global Surgery's indicators include the population proportion accessing laparotomy and open fracture care, key trauma interventions, within two hours. The "Golden Hour" for receiving facility-based resuscitation also guides injury care system strengthening. Firstly, we estimated the proportion of the local population able to reach primary, secondary and tertiary facility care within two and one hours using Geographic Information System (GIS) analysis. Secondly, we compared community household-reported with GIS-estimated travel time. METHODS: Using information from a Health and Demographic Surveillance Site (Karonga, Malawi) on road network, facility location, and local staff-estimated travel speeds, we used a GIS-generated friction surface to calculate the shortest travel time from all households to each facility serving the population. We surveyed community households who reported travel time to their preferred, closest, government secondary and tertiary facilities. For recently injured community members, time to reach facility care was recorded. To assess the relationship between community household-reported travel time and GIS-estimated travel time, we used linear regression to generate a proportionality constant. To assess associations and agreement between injured patient-reported and GIS-estimated travel time, we used Kendall rank and Cohen's kappa tests. RESULTS: Using GIS, we estimated 79.1% of households could reach any secondary facility, 20.5% the government secondary facility, and 0% the government tertiary facility, within two hours. Only 28.2% could reach any secondary facility within one hour, 0% for the government secondary facility. Community household-reported travel time exceeded GIS-estimated travel time. The proportionality constant was 1.25 (95%CI 1.21-1.30) for the closest facility, 1.28 (95%CI 1.23-1.34) for the preferred facility, 1.45 (95%CI 1.33-1.58) for the government secondary facility, and 2.12 (95%CI 1.84-2.41) for tertiary care. Comparing injured patient-reported with GIS-estimated travel time, the correlation coefficient was 0.25 (SE 0.047) and Cohen's kappa was 0.15 (95%CI 0.078-0.23), suggesting poor agreement. DISCUSSION: Most households couldn't reach government secondary care within recognised thresholds indicating poor temporal access. Since GIS-estimated travel time was shorter than community-reported travel time, the true proportion may be lower still. GIS derived estimates of population emergency care access in similar contexts should be interpreted accordingly.

Increase in antimicrobial resistance in Escherichia coli in food animals between 1980 and 2018 assessed using genomes from public databases.

BACKGROUND: Next-generation sequencing has considerably increased the number of genomes available in the public domain. However, efforts to use these genomes for surveillance of antimicrobial resistance have thus far been limited and geographically heterogeneous. We inferred global resistance trends in Escherichia coli in food animals using genomes from public databases. METHODS: We retrieved 7632 E. coli genomes from public databases (NCBI, PATRIC and EnteroBase) and screened for antimicrobial resistance genes (ARGs) using ResFinder. Selection bias towards resistance, virulence or specific strains was accounted for by screening BioProject descriptions. Temporal trends for MDR, resistance to antimicrobial classes and ARG prevalence were inferred using generalized linear models for all genomes, including those not subjected to selection bias. RESULTS: MDR increased by 1.6 times between 1980 and 2018, as genomes carried, on average, ARGs conferring resistance to 2.65 antimicrobials in swine, 2.22 in poultry and 1.58 in bovines. Highest resistance levels were observed for tetracyclines (42.2%-69.1%), penicillins (19.4%-47.5%) and streptomycin (28.6%-56.6%). Resistance trends were consistent after accounting for selection bias, although lower mean absolute resistance estimates were associated with genomes not subjected to selection bias (difference of 3.16%±3.58% across years, hosts and antimicrobial classes). We observed an increase in extended-spectrum cephalosporin ARG blaCMY-2 and a progressive substitution of tetB by tetA. Estimates of resistance prevalence inferred from genomes in the public domain were in good agreement with reports from systematic phenotypic surveillance. CONCLUSIONS: Our analysis illustrates the potential of using the growing volume of genomes in public databases to track AMR trends globally.

Multidrug Resistance Dynamics in Salmonella in Food Animals in the United States: An Analysis of Genomes from Public Databases.

The number of bacterial genomes deposited each year in public databases is growing exponentially. However, efforts to use these genomes to track trends in antimicrobial resistance (AMR) have been limited thus far. We used 22,102 genomes from public databases to track AMR trends in nontyphoidal Salmonella in food animals in the United States. In 2018, genomes deposited in public databases carried genes conferring resistance, on average, to 2.08 antimicrobial classes in poultry, 1.74 in bovines, and 1.28 in swine. This represents a decline in AMR of over 70% compared to the levels in 2000 in bovines and swine, and an increase of 13% for poultry. Trends in resistance inferred from genomic data showed good agreement with U.S. phenotypic surveillance data (weighted mean absolute difference ± standard deviation, 5.86% ± 8.11%). In 2018, resistance to 3rd-generation cephalosporins in bovines, swine, and poultry decreased to 9.97% on average, whereas in quinolones and 4th-generation cephalosporins, resistance increased to 12.53% and 3.87%, respectively. This was concomitant with a decrease of blaCMY-2 but an increase in blaCTX-M-65 and gyrA D87Y (encoding a change of D to Y at position 87). Core genome single-nucleotide polymorphism (SNP) phylogenies show that resistance to these antimicrobial classes was predominantly associated with Salmonella enterica serovar Infantis and, to a lesser extent, S. enterica serovar Typhimurium and its monophasic variant I 4,[5],12:i:-, whereas quinolone resistance was also associated with S. enterica serovar Dublin. Between 2000 and 2018, trends in serovar prevalence showed a composition shift where S. Typhimurium decreased while S. Infantis increased. Our findings illustrate the growing potential of using genomes in public databases to track AMR in regions where sequencing capacities are currently expanding. IMPORTANCE Next-generation sequencing has led to an exponential increase in the number of genomes deposited in public repositories. This growing volume of information presents opportunities to track the prevalence of genes conferring antimicrobial resistance (AMR), a growing threat to the health of humans and animals. Using 22,102 public genomes, we estimated that the prevalence of multidrug resistance (MDR) in the United States decreased in nontyphoidal Salmonella isolates recovered from bovines and swine between 2000 and 2018, whereas it increased in poultry. These trends are consistent with those detected by national surveillance systems that monitor resistance using phenotypic testing. However, using genomes, we identified that genes conferring resistance to critically important antimicrobials were associated with specific MDR serovars that could be the focus for future interventions. Our analysis illustrates the growing potential of public repositories to monitor AMR trends and shows that similar efforts could soon be carried out in other regions where genomic surveillance is increasing.

Twenty-year trends in antimicrobial resistance from aquaculture and fisheries in Asia.

Antimicrobial resistance (AMR) is a growing threat to human and animal health. However, in aquatic animals-the fastest growing food animal sector globally-AMR trends are seldom documented, particularly in Asia, which contributes two-thirds of global food fish production. Here, we present a systematic review and meta-analysis of 749 point prevalence surveys reporting antibiotic-resistant bacteria from aquatic food animals in Asia, extracted from 343 articles published in 2000-2019. We find concerning levels of resistance to medically important antimicrobials in foodborne pathogens. In aquaculture, the percentage of antimicrobial compounds per survey with resistance exceeding 50% (P50) plateaued at 33% [95% confidence interval (CI) 28 to 37%] between 2000 and 2018. In fisheries, P50 decreased from 52% [95% CI 39 to 65%] to 22% [95% CI 14 to 30%]. We map AMR at 10-kilometer resolution, finding resistance hotspots along Asia's major river systems and coastal waters of China and India. Regions benefitting most from future surveillance efforts are eastern China and India. Scaling up surveillance to strengthen epidemiological evidence on AMR and inform aquaculture and fisheries interventions is needed to mitigate the impact of AMR globally.