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.

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.

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.

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 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.

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.

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.

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.

Reduction in Antimicrobial Use and Resistance to Salmonella, Campylobacter, and Escherichia coli in Broiler Chickens, Canada, 2013-2019.

Antimicrobial use contributes to the global rise of antimicrobial resistance (AMR). In 2014, the poultry industry in Canada initiated its Antimicrobial Use Reduction Strategy to mitigate AMR in the poultry sector. We monitored trends in antimicrobial use and AMR of foodborne bacteria (Salmonella, Escherichia coli, and Campylobacter) in broiler chickens during 2013 and 2019. We quantified the effect of antimicrobial use and management factors on AMR by using LASSO regression and generalized mixed-effect models. AMR in broiler chickens declined by 6%-38% after the decrease in prophylactic antimicrobial use. However, the withdrawal of individual compounds, such as cephalosporins and fluoroquinolones, prompted an increase in use of and resistance levels for other drug classes, such as aminoglycosides. Canada's experience with antimicrobial use reduction illustrates the potential for progressive transitions from conventional antimicrobial-dependent broiler production to more sustainable production with respect to antimicrobial use.

Global increase and geographic convergence in antibiotic consumption between 2000 and 2015.

Tracking antibiotic consumption patterns over time and across countries could inform policies to optimize antibiotic prescribing and minimize antibiotic resistance, such as setting and enforcing per capita consumption targets or aiding investments in alternatives to antibiotics. In this study, we analyzed the trends and drivers of antibiotic consumption from 2000 to 2015 in 76 countries and projected total global antibiotic consumption through 2030. Between 2000 and 2015, antibiotic consumption, expressed in defined daily doses (DDD), increased 65% (21.1-34.8 billion DDDs), and the antibiotic consumption rate increased 39% (11.3-15.7 DDDs per 1,000 inhabitants per day). The increase was driven by low- and middle-income countries (LMICs), where rising consumption was correlated with gross domestic product per capita (GDPPC) growth (P = 0.004). In high-income countries (HICs), although overall consumption increased modestly, DDDs per 1,000 inhabitants per day fell 4%, and there was no correlation with GDPPC. Of particular concern was the rapid increase in the use of last-resort compounds, both in HICs and LMICs, such as glycylcyclines, oxazolidinones, carbapenems, and polymyxins. Projections of global antibiotic consumption in 2030, assuming no policy changes, were up to 200% higher than the 42 billion DDDs estimated in 2015. Although antibiotic consumption rates in most LMICs remain lower than in HICs despite higher bacterial disease burden, consumption in LMICs is rapidly converging to rates similar to HICs. Reducing global consumption is critical for reducing the threat of antibiotic resistance, but reduction efforts must balance access limitations in LMICs and take account of local and global resistance patterns.

Global trends in antimicrobial use in food animals.

Demand for animal protein for human consumption is rising globally at an unprecedented rate. Modern animal production practices are associated with regular use of antimicrobials, potentially increasing selection pressure on bacteria to become resistant. Despite the significant potential consequences for antimicrobial resistance, there has been no quantitative measurement of global antimicrobial consumption by livestock. We address this gap by using Bayesian statistical models combining maps of livestock densities, economic projections of demand for meat products, and current estimates of antimicrobial consumption in high-income countries to map antimicrobial use in food animals for 2010 and 2030. We estimate that the global average annual consumption of antimicrobials per kilogram of animal produced was 45 mg⋅kg(-1), 148 mg⋅kg(-1), and 172 mg⋅kg(-1) for cattle, chicken, and pigs, respectively. Starting from this baseline, we estimate that between 2010 and 2030, the global consumption of antimicrobials will increase by 67%, from 63,151 ± 1,560 tons to 105,596 ± 3,605 tons. Up to a third of the increase in consumption in livestock between 2010 and 2030 is imputable to shifting production practices in middle-income countries where extensive farming systems will be replaced by large-scale intensive farming operations that routinely use antimicrobials in subtherapeutic doses. For Brazil, Russia, India, China, and South Africa, the increase in antimicrobial consumption will be 99%, up to seven times the projected population growth in this group of countries. Better understanding of the consequences of the uninhibited growth in veterinary antimicrobial consumption is needed to assess its potential effects on animal and human health.

Avian influenza H5N1 viral and bird migration networks in Asia.

The spatial spread of the highly pathogenic avian influenza virus H5N1 and its long-term persistence in Asia have resulted in avian influenza panzootics and enormous economic losses in the poultry sector. However, an understanding of the regional long-distance transmission and seasonal patterns of the virus is still lacking. In this study, we present a phylogeographic approach to reconstruct the viral migration network. We show that within each wild fowl migratory flyway, the timing of H5N1 outbreaks and viral migrations are closely associated, but little viral transmission was observed between the flyways. The bird migration network is shown to better reflect the observed viral gene sequence data than other networks and contributes to seasonal H5N1 epidemics in local regions and its large-scale transmission along flyways. These findings have potentially far-reaching consequences, improving our understanding of how bird migration drives the periodic reemergence of H5N1 in Asia.

Hand, Foot, and Mouth Disease in China: Modeling Epidemic Dynamics of Enterovirus Serotypes and Implications for Vaccination.

BACKGROUND: Hand, foot, and mouth disease (HFMD) is a common childhood illness caused by serotypes of the Enterovirus A species in the genus Enterovirus of the Picornaviridae family. The disease has had a substantial burden throughout East and Southeast Asia over the past 15 y. China reported 9 million cases of HFMD between 2008 and 2013, with the two serotypes Enterovirus A71 (EV-A71) and Coxsackievirus A16 (CV-A16) being responsible for the majority of these cases. Three recent phase 3 clinical trials showed that inactivated monovalent EV-A71 vaccines manufactured in China were highly efficacious against HFMD associated with EV-A71, but offered no protection against HFMD caused by CV-A16. To better inform vaccination policy, we used mathematical models to evaluate the effect of prospective vaccination against EV-A71-associated HFMD and the potential risk of serotype replacement by CV-A16. We also extended the model to address the co-circulation, and implications for vaccination, of additional non-EV-A71, non-CV-A16 serotypes of enterovirus. METHODS AND FINDINGS: Weekly reports of HFMD incidence from 31 provinces in Mainland China from 1 January 2009 to 31 December 2013 were used to fit multi-serotype time series susceptible-infected-recovered (TSIR) epidemic models. We obtained good model fit for the two-serotype TSIR with cross-protection, capturing the seasonality and geographic heterogeneity of province-level transmission, with strong correlation between the observed and simulated epidemic series. The national estimate of the basic reproduction number, R0, weighted by provincial population size, was 26.63 for EV-A71 (interquartile range [IQR]: 23.14, 30.40) and 27.13 for CV-A16 (IQR: 23.15, 31.34), with considerable variation between provinces (however, predictions about the overall impact of vaccination were robust to this variation). EV-A71 incidence was projected to decrease monotonically with higher coverage rates of EV-A71 vaccination. Across provinces, CV-A16 incidence in the post-EV-A71-vaccination period remained either comparable to or only slightly increased from levels prior to vaccination. The duration and strength of cross-protection following infection with EV-A71 or CV-A16 was estimated to be 9.95 wk (95% confidence interval [CI]: 3.31, 23.40) in 68% of the population (95% CI: 37%, 96%). Our predictions are limited by the necessarily short and under-sampled time series and the possible circulation of unidentified serotypes, but, nonetheless, sensitivity analyses indicate that our results are robust in predicting that the vaccine should drastically reduce incidence of EV-A71 without a substantial competitive release of CV-A16. CONCLUSIONS: The ability of our models to capture the observed epidemic cycles suggests that herd immunity is driving the epidemic dynamics caused by the multiple serotypes of enterovirus. Our results predict that the EV-A71 and CV-A16 serotypes provide a temporary immunizing effect against each other. Achieving high coverage rates of EV-A71 vaccination would be necessary to eliminate the ongoing transmission of EV-A71, but serotype replacement by CV-A16 following EV-A71 vaccination is likely to be transient and minor compared to the corresponding reduction in the burden of EV-A71-associated HFMD. Therefore, a mass EV-A71 vaccination program of infants and young children should provide significant benefits in terms of a reduction in overall HFMD burden.

Air temperature suitability for Plasmodium falciparum malaria transmission in Africa 2000-2012: a high-resolution spatiotemporal prediction.

BACKGROUND: Temperature suitability for malaria transmission is a useful predictor variable for spatial models of malaria infection prevalence. Existing continental or global models, however, are synoptic in nature and so do not characterize inter-annual variability in seasonal patterns of temperature suitability, reducing their utility for predicting malaria risk. METHODS: A malaria Temperature Suitability Index (TSI) was created by first modeling minimum and maximum air temperature with an eight-day temporal resolution from gap-filled MODerate Resolution Imaging Spectroradiometer (MODIS) daytime and night-time Land Surface Temperature (LST) datasets. An improved version of an existing biological model for malaria temperature suitability was then applied to the resulting temperature information for a 13-year data series. The mechanism underlying this biological model is simulation of emergent mosquito cohorts on a two-hour time-step and tracking of each cohort throughout its life to quantify the impact air temperature has on both mosquito survival and sporozoite development. RESULTS: The results of this research consist of 154 monthly raster surfaces that characterize spatiotemporal patterns in TSI across Africa from April 2000 through December 2012 at a 1 km spatial resolution. Generalized TSI patterns were as expected, with consistently high values in equatorial rain forests, seasonally variable values in tropical savannas (wet and dry) and montane areas, and low values in arid, subtropical regions. Comparisons with synoptic approaches demonstrated the additional information available within the dynamic TSI dataset that is lost in equivalent synoptic products derived from long-term monthly averages. CONCLUSIONS: The dynamic TSI dataset presented here provides a new product with far richer spatial and temporal information than any other presently available for Africa. As spatiotemporal malaria modeling endeavors evolve, dynamic predictor variables such as the malaria temperature suitability data developed here will be essential for the rational assessment of changing patterns of malaria risk.

Geographical variation in Plasmodium vivax relapse.

BACKGROUND: Plasmodium vivax has the widest geographic distribution of the human malaria parasites and nearly 2.5 billion people live at risk of infection. The control of P. vivax in individuals and populations is complicated by its ability to relapse weeks to months after initial infection. Strains of P. vivax from different geographical areas are thought to exhibit varied relapse timings. In tropical regions strains relapse quickly (three to six weeks), whereas those in temperate regions do so more slowly (six to twelve months), but no comprehensive assessment of evidence has been conducted. Here observed patterns of relapse periodicity are used to generate predictions of relapse incidence within geographic regions representative of varying parasite transmission. METHODS: A global review of reports of P. vivax relapse in patients not treated with a radical cure was conducted. Records of time to first P. vivax relapse were positioned by geographic origin relative to expert opinion regions of relapse behaviour and epidemiological zones. Mixed-effects meta-analysis was conducted to determine which geographic classification best described the data, such that a description of the pattern of relapse periodicity within each region could be described. Model outputs of incidence and mean time to relapse were mapped to illustrate the global variation in relapse. RESULTS: Differences in relapse periodicity were best described by a historical geographic classification system used to describe malaria transmission zones based on areas sharing zoological and ecological features. Maps of incidence and time to relapse showed high relapse frequency to be predominant in tropical regions and prolonged relapse in temperate areas. CONCLUSIONS: The results indicate that relapse periodicity varies systematically by geographic region and are categorized by nine global regions characterized by similar malaria transmission dynamics. This indicates that relapse may be an adaptation evolved to exploit seasonal changes in vector survival and therefore optimize transmission. Geographic patterns in P. vivax relapse are important to clinicians treating individual infections, epidemiologists trying to infer P. vivax burden, and public health officials trying to control and eliminate the disease in human populations.

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.

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.

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.

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.