Recent approaches in computational modelling for controlling pathogen threats

In this review, we assess the status of computational modelling of pathogens. We focus on three disparate but interlinked research areas that produce models with very different spatial and temporal scope. First, we examine antimicrobial resistance (AMR). Many mechanisms of AMR are not well understood. As a result, it is hard to measure the current incidence of AMR, predict the future incidence, and design strategies to preserve existing antibiotic effectiveness. Next, we look at how to choose the finite number of bacterial strains that can be included in a vaccine. To do this, we need to understand what happens to vaccine and non-vaccine strains after vaccination programmes. Finally, we look at within-host modelling of antibody dynamics. The SARS-CoV-2 pandemic produced huge amounts of antibody data, prompting improvements in this area of modelling. We finish by discussing the challenges that persist in understanding these complex biological systems.

The appropriateness of empirical antibiotic therapy in the management of symptomatic urinary tract infection patients-a cross-sectional study in Nairobi County, Kenya

Background

In low- and middle-income countries, symptomatic urinary tract infection (UTI) patients are often prescribed antibiotics without microbiological confirmation. UTIs caused by antibiotic-resistant bacteria are increasingly common, and this heightens the risk of empirical treatment failure. This study evaluates the appropriateness of empirical antibiotic therapy to UTI patients in Nairobi County, Kenya.

Methods

A hospital-based, cross-sectional study was conducted in Nairobi County, Kenya, amongst symptomatic adult and child patients. UTI was defined as a monoculture growth with colony counts of ≥104 cfu/mL. Antimicrobial susceptibility testing was performed by the Kirby-Bauer disc diffusion method. Empirical therapy was considered appropriate if the pathogen isolated was susceptible to the prescribed antibiotic and inappropriate if the pathogen was resistant to the prescribed antibiotic.

Results

A total of 552 participants were enrolled with a median age of 29 years (interquartile range: 24-36). The majority were female, 398 (72%). Of the 552, 274 (50%) received empirical antibiotic therapy, and 95/274 (35%) were confirmed to have UTI by culture. The antibiotics most frequently prescribed were fluoroquinolones [ciprofloxacin in 80 (30%) and levofloxacin 43 (16%)], amoxicillin-clavulanic acid in 48 (18%) and nitrofurantoin in 32 (12%). Amongst the 95 patients with bacteriological confirmation of UTI, 50 (53%) received appropriate empirical antibiotic therapy, whilst for 38 (40%) participants, the therapy was inappropriate.

Conclusions

The complexity of appropriate empirical treatment for UTIs is compounded by high levels of resistance in UTI pathogens. Antimicrobial resistance surveillance strategies that could help in designing appropriate empirical regimens in resource constrained settings should be adopted for optimal empiric therapy.

Cefiderocol for treating severe aerobic Gram-negative bacterial infections: technology evaluation to inform a novel subscription-style payment model

Background

To limit the use of antimicrobials without disincentivising the development of novel antimicrobials, there is interest in establishing innovative models that fund antimicrobials based on an evaluation of their value as opposed to the volumes used. The aim of this project was to evaluate the population-level health benefit of cefiderocol in the NHS in England, for the treatment of severe aerobic Gram-negative bacterial infections when used within its licensed indications. The results were used to inform the National Institute for Health and Care Excellence guidance in support of commercial discussions regarding contract value between the manufacturer and NHS England.

Methods

The health benefit of cefiderocol was first derived for a series of high-value clinical scenarios. These represented uses that were expected to have a significant impact on patients' mortality risks and health-related quality of life. The clinical effectiveness of cefiderocol relative to its comparators was estimated by synthesising evidence on susceptibility of the pathogens of interest to the antimicrobials in a network meta-analysis. Patient-level costs and health outcomes of cefiderocol under various usage scenarios compared with alternative management strategies were quantified using decision modelling. Results were reported as incremental net health effects expressed in quality-adjusted life-years, which were scaled to 20-year population values using infection number forecasts based on data from Public Health England. The outcomes estimated for the high-value clinical scenarios were extrapolated to other expected uses for cefiderocol.

Results

Among Enterobacterales isolates with the metallo-beta-lactamase resistance mechanism, the base-case network meta-analysis found that cefiderocol was associated with a lower susceptibility relative to colistin (odds ratio 0.32, 95% credible intervals 0.04 to 2.47), but the result was not statistically significant. The other treatments were also associated with lower susceptibility than colistin, but the results were not statistically significant. In the metallo-beta-lactamase Pseudomonas aeruginosa base-case network meta-analysis, cefiderocol was associated with a lower susceptibility relative to colistin (odds ratio 0.44, 95% credible intervals 0.03 to 3.94), but the result was not statistically significant. The other treatments were associated with no susceptibility. In the base case, patient-level benefit of cefiderocol was between 0.02 and 0.15 quality-adjusted life-years, depending on the site of infection, the pathogen and the usage scenario. There was a high degree of uncertainty surrounding the benefits of cefiderocol across all subgroups. There was substantial uncertainty in the number of infections that are suitable for treatment with cefiderocol, so population-level results are presented for a range of scenarios for the current infection numbers, the expected increases in infections over time and rates of emergence of resistance. The population-level benefits varied substantially across the base-case scenarios, from 896 to 3559 quality-adjusted life-years over 20 years.

Conclusion

This work has provided quantitative estimates of the value of cefiderocol within its areas of expected usage within the NHS.

Limitations

Given existing evidence, the estimates of the value of cefiderocol are highly uncertain.

Future work

Future evaluations of antimicrobials would benefit from improvements to NHS data linkages; research to support appropriate synthesis of susceptibility studies; and application of routine data and decision modelling to assess enablement value.

Study registration

No registration of this study was undertaken.

Funding

This award was funded by the National Institute for Health and Care Research (NIHR) Health Technology Assessment Policy Research Programme (NIHR award ref: NIHR135591), conducted through the Policy Research Unit in Economic Methods of Evaluation in Health and Social Care Interventions, PR-PRU-1217-20401, and is published in full in Health Technology Assessment; Vol. 28, No. 28. See the NIHR Funding and Awards website for further award information.

Resistance to first-line antibiotic therapy among patients with uncomplicated acute cystitis in Melbourne, Australia: prevalence, predictors and clinical impact

Background

Australian guidelines recommend trimethoprim or nitrofurantoin as first-line agents for uncomplicated urinary tract infections (UTIs). Laboratory surveillance indicates high rates of trimethoprim resistance among urinary bacterial isolates, but there are scant local clinical data about risk factors and impact of trimethoprim resistance.

Objectives

To determine the prevalence, risk factors, mechanism and impact of resistance to first-line antibiotic therapy for uncomplicated UTIs in the community setting.

Methods

A prospective observational study from October 2019 to November 2021 in four general practices in Melbourne, Australia. Female adult patients prescribed an antibiotic for suspected or confirmed uncomplicated acute cystitis were eligible. Primary outcome was urine isolates with resistance to trimethoprim and/or nitrofurantoin.

Results

We recruited 87 participants across 102 UTI episodes with median (IQR) age of 63 (47-76) years. Escherichia coli was the most common uropathogen cultured (48/62; 77%); 27% (13/48) were resistant to trimethoprim (mediated by a dfrA gene) and none were resistant to nitrofurantoin. Isolates with resistance to a first-line therapy were more common among patients reporting a history of recurrent UTIs [risk ratio (RR): 2.08 (95% CI: 1.24-3.51)] and antibiotic use in the previous 6 months [RR: 1.89 (95% CI: 1.36-2.62)]. Uropathogen resistance to empirical therapy was not associated with worse clinical outcomes.

Conclusions

Resistance to trimethoprim is common in uncomplicated UTIs in Australia but may not impact clinical outcomes. Further research is warranted on the appropriateness of trimethoprim as empirical therapy, particularly for patients with antimicrobial resistance risk factors.

The burden of bacterial antimicrobial resistance in the WHO African region in 2019: a cross-country systematic analysis

BACKGROUND

A critical and persistent challenge to global health and modern health care is the threat of antimicrobial resistance (AMR). Previous studies have reported a disproportionate burden of AMR in low-income and middle-income countries, but there remains an urgent need for more in-depth analyses across Africa. This study presents one of the most comprehensive sets of regional and country-level estimates of bacterial AMR burden in the WHO African region to date.

METHODS

We estimated deaths and disability-adjusted life-years (DALYs) attributable to and associated with AMR for 23 bacterial pathogens and 88 pathogen-drug combinations for countries in the WHO African region in 2019. Our methodological approach consisted of five broad components: the number of deaths in which infection had a role, the proportion of infectious deaths attributable to a given infectious syndrome, the proportion of infectious syndrome deaths attributable to a given pathogen, the percentage of a given pathogen resistant to an antimicrobial drug of interest, and the excess risk of mortality (or duration of an infection) associated with this resistance. These components were then used to estimate the disease burden by using two counterfactual scenarios: deaths attributable to AMR (considering an alternative scenario where infections with resistant pathogens are replaced with susceptible ones) and deaths associated with AMR (considering an alternative scenario where drug-resistant infections would not occur at all). We obtained data from research hospitals, surveillance networks, and infection databases maintained by private laboratories and medical technology companies. We generated 95% uncertainty intervals (UIs) for final estimates as the 25th and 975th ordered values across 1000 posterior draws, and models were cross-validated for out-of-sample predictive validity.

FINDINGS

In the WHO African region in 2019, there were an estimated 1·05 million deaths (95% UI 829 000-1 316 000) associated with bacterial AMR and 250 000 deaths (192 000-325 000) attributable to bacterial AMR. The largest fatal AMR burden was attributed to lower respiratory and thorax infections (119 000 deaths [92 000-151 000], or 48% of all estimated bacterial pathogen AMR deaths), bloodstream infections (56 000 deaths [37 000-82 000], or 22%), intra-abdominal infections (26 000 deaths [17 000-39 000], or 10%), and tuberculosis (18 000 deaths [3850-39 000], or 7%). Seven leading pathogens were collectively responsible for 821 000 deaths (636 000-1 051 000) associated with resistance in this region, with four pathogens exceeding 100 000 deaths each: Streptococcus pneumoniae, Klebsiella pneumoniae, Escherichia coli, and Staphylococcus aureus. Third-generation cephalosporin-resistant K pneumoniae and meticillin-resistant S aureus were shown to be the leading pathogen-drug combinations in 25 and 16 countries, respectively (53% and 34% of the whole region, comprising 47 countries) for deaths attributable to AMR.

INTERPRETATION

This study reveals a high level of AMR burden for several bacterial pathogens and pathogen-drug combinations in the WHO African region. The high mortality rates associated with these pathogens demonstrate an urgent need to address the burden of AMR in Africa. These estimates also show that quality and access to health care and safe water and sanitation are correlated with AMR mortality, with a higher fatal burden found in lower resource settings. Our cross-country analyses within this region can help local governments to leverage domestic and global funding to create stewardship policies that target the leading pathogen-drug combinations.

FUNDING

Bill & Melinda Gates Foundation, Wellcome Trust, and Department of Health and Social Care using UK aid funding managed by the Fleming Fund.

Predominance of multidrug-resistant bacteria causing urinary tract infections among symptomatic patients in East Africa: a call for action

Background

In low- and middle-income countries, antibiotics are often prescribed for patients with symptoms of urinary tract infections (UTIs) without microbiological confirmation. Inappropriate antibiotic use can contribute to antimicrobial resistance (AMR) and the selection of MDR bacteria. Data on antibiotic susceptibility of cultured bacteria are important in drafting empirical treatment guidelines and monitoring resistance trends, which can prevent the spread of AMR. In East Africa, antibiotic susceptibility data are sparse. To fill the gap, this study reports common microorganisms and their susceptibility patterns isolated from patients with UTI-like symptoms in Kenya, Tanzania and Uganda. Within each country, patients were recruited from three sites that were sociodemographically distinct and representative of different populations.

Methods

UTI was defined by the presence of >104 cfu/mL of one or two uropathogens in mid-stream urine samples. Identification of microorganisms was done using biochemical methods. Antimicrobial susceptibility testing was performed by the Kirby-Bauer disc diffusion assay. MDR bacteria were defined as isolates resistant to at least one agent in three or more classes of antimicrobial agents.

Results

Microbiologically confirmed UTI was observed in 2653 (35.0%) of the 7583 patients studied. The predominant bacteria were Escherichia coli (37.0%), Staphylococcus spp. (26.3%), Klebsiella spp. (5.8%) and Enterococcus spp. (5.5%). E. coli contributed 982 of the isolates, with an MDR proportion of 52.2%. Staphylococcus spp. contributed 697 of the isolates, with an MDR rate of 60.3%. The overall proportion of MDR bacteria (n = 1153) was 50.9%.

Conclusions

MDR bacteria are common causes of UTI in patients attending healthcare centres in East African countries, which emphasizes the need for investment in laboratory culture capacity and diagnostic algorithms to improve accuracy of diagnosis that will lead to appropriate antibiotic use to prevent and control AMR.

Clinical Setting Comparative Analysis of Uropathogens and Antibiotic Resistance: A Retrospective Study Spanning the Coronavirus Disease 2019 Pandemic

Background

Antimicrobial resistance (AMR) in uropathogens has been increasing in Australia. Many nations observed heightened AMR during the coronavirus disease 2019 (COVID-19) pandemic, but it is not known how this may vary across clinical settings and in nations with lower infection rates.

Methods

We investigated the uropathogen composition and corresponding antibiotic resistance of 775 559 Australian isolates from the community, hospitals, and aged care facilities before (2016-2019) and during (2020-2022) the COVID-19 pandemic. A mathematical model was developed to predict the likelihood of resistance to currently recommended antibiotics for treating urinary tract infections (UTIs).

Results

Among uropathogens originating from the community, hospitals, and aged care facilities, Escherichia coli accounted for 71.4%, 57.6%, and 65.2%, respectively. During the COVID-19 pandemic period, there was an increase in UTIs caused by E coli across all settings. Uropathogens from aged care and hospitals frequently showed higher resistance to antibiotics compared to those isolated from the community. Interestingly, AMR among uropathogens showed a declining trend during the COVID-19 pandemic. Based on the resistance patterns of the past 3 years, our modeling predicted that 30%, 42.6%, and 38.8% of UTIs in the community, hospitals, and aged care facilities, respectively, would exhibit resistance to trimethoprim treatment as empirical therapy. In contrast, resistance to nitrofurantoin was predicted to be 14.6%, 26%, and 24.1% from these 3 respective settings.

Conclusions

Empirical therapy of UTIs in Australia with trimethoprim requires evaluation due to high rates of resistance observed across clinical settings.

Antimicrobial Susceptibility and Characterization of Extended-Spectrum β-Lactamase-Producing Escherichia coli Isolated from Stools of Primary Healthcare Patients in Ethiopia

Antimicrobial resistance of Escherichia coli is a growing problem in both developed and developing countries. This study aimed to investigate the phenotypic antimicrobial resistance of E. coli isolates (n = 260) isolated from the stool specimen of patients attending public health facilities in Addis Ababa and Hossana. This study also aimed to characterize phenotypically confirmed extended-spectrum beta-lactamase (ESBL)-producing E. coli isolates (n = 22) using whole-genome sequencing. Resistance to 18 different antimicrobials was assessed using the disc diffusion method according to the European Committee on Antimicrobial Susceptibility Testing (EUCAST) guidelines. The highest resistance rate among the E. coli isolates was found for ampicillin (52.7%), followed by trimethoprim-sulfamethoxazole (29.6%). Of all isolates, 50 (19.2%) were multidrug-resistant and 22 (8.5%) were ESBL producers. ESBL genes were detected in 94.7% of the sequenced E. coli isolates, and multiple β-lactamase genes were detected in 57.9% of the isolates. The predominant ESBL gene identified was blaCTX-M-15 (78.9%). The blaTEM-1B gene was detected in combination with other ESBL genes in 57.9% of the isolates, while only one of the sequenced isolates contained the blaTEM-1B gene alone. The blaCTX-M-3 gene was detected in three isolates. The genes blaCTX-M-15 and blaTEM-1B as well as blaCTX-M-15 and blaTEM-169 were confirmed to coexist in 52.6% and 10.5% of the sequenced E. coli isolates, respectively. In addition, blaOXA-1 was identified together with blaCTX-M-15 and blaTEM-1B in one isolate, and in one isolate, blaTEM-169 together with blaCTX-M-15 and blaTEM-1B was found. The results obtained show that measures need to be taken to reduce the spread of drug resistance and ensure the long-term use of available antimicrobials.

Atwill E, Jeamsripong S. Antimicrobial resistance, virulence profile, and genetic analysis of ESBL-producing Escherichia coli isolated from Nile tilapia in fresh markets and supermarkets in Thailand

This study investigated the prevalence and antimicrobial resistance (AMR) of Escherichia coli (E. coli) in Nile tilapia from fresh markets and supermarkets. A total of samples (n = 828) were collected from Nile tilapia including fish flesh (n = 276), liver and kidney (n = 276), and intestine (n = 276). Overall prevalence of fecal coliforms (61.6%) and E. coli (53.0%) were observed. High prevalence of E. coli was found in the intestine (71.4%), followed by the liver and kidney (45.7%). The highest prevalence of resistance was commonly found against tetracycline (78.5%), ampicillin (72.8%), and sulfamethoxazole (45.6%) with resistance to only tetracycline (15.2%) as the most common antibiogram. The prevalence of multidrug resistance (MDR) (54.4%) and Extended-spectrum beta-lactamases (ESBLs) (5.7%) were examined. The predominant virulence genes (n = 158) were st (14.6%), followed by eaeA (0.6%). The blaTEM (73.4%), tetA (65.2%), and qnrS (57.6%). There is statistical significance between Nile tilapia from fresh markets and supermarkets. Based on logistic regression analysis, ampicillin-resistant E. coli was statistically associated with the phenotypic resistance to tetracycline and trimethoprim, and the presence of blaTEM and tetA (p < 0.05). Further investigation of AMR transference and their mechanisms is needed for AMR control.

Interpretable machine learning-based decision support for prediction of antibiotic resistance for complicated urinary tract infections

Urinary tract infections are one of the most common bacterial infections worldwide; however, increasing antimicrobial resistance in bacterial pathogens is making it challenging for clinicians to correctly prescribe patients appropriate antibiotics. In this study, we present four interpretable machine learning-based decision support algorithms for predicting antimicrobial resistance. Using electronic health record data from a large cohort of patients diagnosed with potentially complicated UTIs, we demonstrate high predictability of antibiotic resistance across four antibiotics - nitrofurantoin, co-trimoxazole, ciprofloxacin, and levofloxacin. We additionally demonstrate the generalizability of our methods on a separate cohort of patients with uncomplicated UTIs, demonstrating that machine learning-driven approaches can help alleviate the potential of administering non-susceptible treatments, facilitate rapid effective clinical interventions, and enable personalized treatment suggestions. Additionally, these techniques present the benefit of providing model interpretability, explaining the basis for generated predictions.

Trimethoprim resistance in surface and wastewater is mediated by contrasting variants of the dfrB gene

Trimethoprim (TMP) is a low-cost, widely prescribed antibiotic. Its effectiveness is increasingly challenged by the spread of genes coding for TMP-resistant dihydrofolate reductases: dfrA, and the lesser-known, evolutionarily unrelated dfrB. Despite recent reports of novel variants conferring high level TMP resistance (dfrB10 to dfrB21), the prevalence of dfrB is still unknown due to underreporting, heterogeneity of the analyzed genetic material in terms of isolation sources, and limited bioinformatic processing. In this study, we explored a coherent set of shotgun metagenomic sequences to quantitatively estimate the abundance of dfrB gene variants in aquatic environments. Specifically, we scanned sequences originating from influents and effluents of municipal sewage treatment plants as well as river-borne microbiomes. Our analyses reveal an increased prevalence of dfrB1, dfrB2, dfrB3, dfrB4, dfrB5, and dfrB7 in wastewater microbiomes as compared to freshwater. These gene variants were frequently found in genomic neighborship with other resistance genes, transposable elements, and integrons, indicating their mobility. By contrast, the relative abundances of the more recently discovered variants dfrB9, dfrB10, and dfrB13 were significantly higher in freshwater than in wastewater microbiomes. Moreover, their direct neighborship with other resistance genes or markers of mobile genetic elements was significantly less likely. Our findings suggest that natural freshwater communities form a major reservoir of the recently discovered dfrB gene variants. Their proliferation and mobilization in response to the exposure of freshwater communities to selective TMP concentrations may promote the prevalence of high-level TMP resistance and thus limit the future effectiveness of antimicrobial therapies.

Antimicrobial resistance- and pathogen patterns in the fecal microbiota of sows and their offspring in German commercial pig farms

Reducing antibiotic use is one of the biggest challenges in pig farming, as antibiotics have been used for years to control typical problems such as newborn or post-weaning diarrhea. The pressure a one health approach has created on animal production regarding antimicrobial resistance is an opportunity to find other strategies against enterobacterial pathogens in suckling and weaned piglets. A farm-specific approach could have a good success due to the individual farm structures in Germany and other countries. In this study, non-metric multidimensional scaling, hierarchical clustering, and latent class analysis were used to determine the impact of antibiotic use on antibiotic resistance patterns and pathogen prevalence in 20 German pig farms. This may help to develop individualized health strategies. 802 fresh fecal samples were collected from sows and piglets from 20 piglet production and rearing farms at different production times (sows antepartum and postpartum, suckling piglets, weaned piglets). In addition, the use of antibiotics was recorded. DNA extracts were subjected to quantitative real-time qPCR with primers specific for antibiotic resistance genes (int1, sul1-3, dfrA1, mcr-1, blaCTX-M), and virulence factors of relevant bacteria (C. difficile, C. perfringens, Salmonella, Escherichia/Shigella/Hafnia, E. coli). Linear and logistic regression models were used to analyze the relationship between different antibiotics and the major genes contributing to the clustering of observations for the different animal groups. Clustering revealed different farm clusters for sows, suckling piglets, and weaned piglets, with the most remarkable diversity in antibiotic use among weaned piglets. Amoxicillin, lincomycin, and enrofloxacin were identified as the most probable cause of increased odds of the presence of relevant antibiotic resistance genes (mcr1, dfrA1, blaCTX-M). Still, direct effects of a specific antibiotic on its associated resistance gene were rare. Enrofloxacin and florfenicol favored the occurrence of C. difficile in sows. The E. coli fimbriae genes were less affected by antibiotic use in sows and piglets, but the F4 fimbriae gene could be associated with the integrase 1 gene in piglets. The results confirm that multidrug-resistant enterobacteria are widespread in German pig farms and give awareness of the impact of current antibiotic use while searching for alternative health strategies.

Predicting Antibiotic Resistance in ICUs Patients by Applying Machine Learning in Vietnam

Introduction

Artificial Intelligence (AI) and machine learning (ML) are used extensively in HICs to detect and control antibiotic resistance (AMR) in laboratories and clinical institutions. ML is designed to predict outcome variables using an algorithm to enable "machines" to learn the "rules" from the data. ML is increasingly being applied in intensive care units to identify AMR and to assist empiric antibiotic therapy. This study aimed to evaluate the performance of ML models for predicting AMR bacteria and resistance to antibiotics in two Vietnamese hospitals.

Patients and Methods

A cross-sectional study combined with retrospective was conducted from 1st January 2020 to 30th June 2022. Five models were developed to predict antibiotic resistance of bacterial infections of ICU patients. Two datasets were prepared to predict AMR bacteria and antibiotics with ML models. The performance of the prediction models was evaluated by various indicators (sensitivity, specificity, precision, accuracy, F1-score, PRC, AuROC, and NormMCC) to determine the optimal time point for data selection. Python version 3.8 was used for statistical analyses.

Results

The accuracy, F1-score, AuROC, and normMMC of LightGBM, XGBoost, and Random Forest models were higher than those of other models in both datasets. In both datasets 1 and 2, accuracy, F1-score, AuROC and normMCC of the XGBoost model were the highest among five models (from 0.890 to 1.000). Only Random Forest models had specificity scores higher than 0.850. High scores of sensitivity, accuracy, precision, F1-score, and normMCC indicated that the models were making accurate predictions for datasets 1 and 2.

Conclusion

XGBoost, LightGBM, and Random Forest were the best-performed machine learning models to predict antibiotic resistance of bacterial infections of ICUs patients using the patients' EMRs.

Decline in Antimicrobial Consumption and Stagnation in Reducing Disease Burden due to Antimicrobial Resistance in Japan

INTRODUCTION

Antimicrobial resistance (AMR) is a major global health threat. While antimicrobial consumption (AMC) in Japan substantially decreased after implementation of the AMR National Action Plan, the disease burden due to AMR seems to be unchanged. The main objective of this study is to examine the relationship between AMC and the disease burden due to AMR in Japan.

METHODS

We estimated the annual population-standardized AMC from 2015 to 2021 using defined daily doses (DDDs) per 1000 inhabitants per day (DIDs) and the disease burden due to bloodstream infections caused by nine major antimicrobial-resistant bacteria (AMR-BSIs) from 2015 to 2021 using disability-adjusted life years (DALYs). We then examined the correlation between AMC and DALYs using Spearman's rank correlation coefficient and cross-correlation function. Spearman's [Formula: see text] > 0.7 was considered to indicate a strong correlation.

RESULTS

The sales amounts of third-generation cephalosporins, fluoroquinolones, and macrolides were 3.82 DIDs, 2.71 DIDs, and 4.59 DIDs, respectively, in 2015, but 2.11, 1.48, and 2.72 in 2021. This corresponded to reductions of 44.8%, 45.4%, and 40.7% during the study period. DALYs due to AMR-BSIs were 164.7 per 100,000 population in 2015 but 195.2 per 100,000 in 2021. Spearman's rank correlation coefficients between AMC and DALYs were - 0.37 (total antibiotics), - 0.50 (oral antibiotics), - 0.43 (third-generation cephalosporins), - 0.5 (fluoroquin,olones) and - 0.5 (macrolides). No obvious cross-correlations were found.

CONCLUSIONS

Our results reveal that changes in AMC are not associated with DALYs caused by AMR-BSIs. AMR countermeasures besides efforts to reduce inappropriate AMC might be necessary to mitigate the disease burden due to AMR.

Pivmecillinam, the paradigm of an antibiotic with low resistance rates in Escherichia coli urine isolates despite high consumption

OBJECTIVES

Pivmecillinam, the oral version of mecillinam, represents one of the major recommended and used antibiotics for empiric and targeted treatment of urinary tract infections in primary care in Denmark, Norway and Sweden. Mecillinam resistant mutants in Escherichia coli develop easily in vitro, but their fitness cost has been shown to be high.

METHODS

We revisited the resistance and consumption data from the monitoring programmes in the three countries and compared pivmecillinam with ciprofloxacin from 2010 to 2020.

RESULTS

Mecillinam resistance rates in Escherichia coli remained around 6% in Denmark and Norway relative to a constant consumption in Norway of 1.6-1.8 DID (defined daily doses per 1000 inhabitants per day), and even increasing in Denmark from 1.6 to 2.3 DID. In Sweden resistance was significantly lower at 4% related to the lower consumption of 0.5 DID. For ciprofloxacin, resistance rates fluctuated around 6%-12%, highest in Sweden with the highest consumption (0.8-0.6 DID) and lowest in Denmark (0.55-0.35 DID) and Norway (0.7-0.3 DID), although consumption declined significantly in all three countries.

CONCLUSIONS

Pivmecillinam is an example of an antibiotic, which easily develops resistance in vitro, but apparently can be used broadly in primary care without increase in resistance rates.

Uses of mathematical modeling to estimate the impact of mass drug administration of antibiotics on antimicrobial resistance within and between communities

Background

Antibiotics are a key part of modern healthcare, but their use has downsides, including selecting for antibiotic resistance, both in the individuals treated with antibiotics and in the community at large. When evaluating the benefits and costs of mass administration of azithromycin to reduce childhood mortality, effects of antibiotic use on antibiotic resistance are important but difficult to measure, especially when evaluating resistance that “spills over” from antibiotic-treated individuals to other members of their community. The aim of this scoping review was to identify how the existing literature on antibiotic resistance modeling could be better leveraged to understand the effect of mass drug administration (MDA) on antibiotic resistance.

Main text

Mathematical models of antibiotic use and resistance may be useful for estimating the expected effects of different MDA implementations on different populations, as well as aiding interpretation of existing data and guiding future experimental design. Here, strengths and limitations of models of antibiotic resistance are reviewed, and possible applications of those models in the context of mass drug administration with azithromycin are discussed.

Conclusions

Statistical models of antibiotic use and resistance may provide robust and relevant estimates of the possible effects of MDA on resistance. Mechanistic models of resistance, while able to more precisely estimate the effects of different implementations of MDA on resistance, may require more data from MDA trials to be accurately parameterized.

Graphical Abstract

Epidemiology of Antibiotic Resistant Pathogens in Pediatric Urinary Tract Infections as a Tool to Develop a Prediction Model for Early Detection of Drug-Specific Resistance

Antibiotic resistance is an increasing problem, especially in children with urinary tract infections. Rates of drug-specific resistant pathogens were reported, and an easy prediction model to guide the clinical decision-making process for antibiotic treatment was proposed. Data on microbiological isolation from urinoculture, between January 2007−December 2018 at Istituto Gaslini, Italy, in patients aged <19 years were extracted. Logistic regression-based prediction scores were calculated. Discrimination was determined by the area under the receiver operating characteristic curve; calibration was assessed by the Hosmer and Lemeshow test and the Spiegelhalterz test. A total of 9449 bacterial strains were isolated in 6207 patients; 27.2% were <6 months old at the first episode. Enterobacteriales (Escherichia coli and other Enterobacteriales) accounted for 80.4% of all isolates. Amoxicillin-clavulanate (AMC) and cefixime (CFI) Enterobacteriales resistance was 32.8% and 13.7%, respectively, and remained quite stable among the different age groups. On the contrary, resistance to ciprofloxacin (CIP) (overall 9.6%) and cotrimoxazole (SXT) (overall 28%) increased with age. After multivariable analysis, resistance to AMC/CFI could be predicted by the following: sex; age at sampling; department of admission; previous number of bacterial pathogens isolated. Resistance to CIP/SXT could be predicted by the same factors, excluding sex. The models achieved very good calibration but moderate discrimination performance. Specific antibiotic resistance among Enterobacteriales could be predicted using the proposed scoring system to guide empirical antibiotic choice. Further studies are needed to validate this tool.

Role of locum GPs in antibiotic prescribing and stewardship: a mixed-methods study

Background

Most antibiotics are prescribed in primary care. Locum or sessional GPs (locums) are perceived as contributing to higher prescribing and may face barriers to engaging with antimicrobial stewardship (AMS).

Aim

To identify how locums’ antibiotic prescribing compares with other general practice prescribers, and how they perceive their role in antibiotic prescribing and AMS.

Design and setting

Mixed-methods study in primary care.

Method

Data on antibiotic prescribing, diagnoses, and patient and prescriber characteristics were extracted from The Health Improvement Network database. A mixed-effects logistic model was used to compare locums’ and other prescribers’ antibiotic prescribing for conditions that do not usually benefit from antibiotics. Nineteen semi-structured telephone interviews were conducted with locums in England and analysed thematically.

Results

Locums accounted for 11% of consultations analysed. They prescribed antibiotics more often than other GPs and nurse prescribers for acute cough, sore throat, asthma and chronic obstructive pulmonary disease exacerbations, and acute bronchitis. The number of patients receiving antibiotics for these conditions was 4% higher (on absolute scale) when consulting with locums compared with when they consulted with other GPs. Four themes capture the perceived influences on prescribing antibiotics and AMS: antibiotic prescribing as a complex but individual issue, nature and patterns of locum work, relationships between practices and locums, and professional isolation.

Conclusion

Locums contribute to higher antibiotic prescribing compared with their peers. They experience challenges but also opportunities for contributing to AMS, which should be better addressed. With an increasing proportion of locums in general practice, they have an important role in antibiotic optimisation and AMS.

Beyond Antimicrobial Use: A Framework for Prioritizing Antimicrobial Resistance Interventions

Antimicrobial resistance (AMR) is a threat to animal and human health. Antimicrobial use has been identified as a major driver of AMR, and reductions in use are a focal point of interventions to reduce resistance. Accordingly, stakeholders in human health and livestock production have implemented antimicrobial stewardship programs aimed at reducing use. Thus far, these efforts have yielded variable impacts on AMR. Furthermore, scientific advances are prompting an expansion and more nuanced appreciation of the many nonantibiotic factors that drive AMR, as well as how these factors vary across systems, geographies, and contexts. Given these trends, we propose a framework to prioritize AMR interventions. We use this framework to evaluate the impact of interventions that focus on antimicrobial use. We conclude by suggesting that priorities be expanded to include greater consideration of host-microbial interactions that dictate AMR, as well as anthropogenic and environmental systems that promote dissemination of AMR.

Trends, seasonality and the association between outpatient antibiotic use and antimicrobial resistance among urinary bacteria in the Netherlands

OBJECTIVES

To determine trends, seasonality and the association between community antibiotic use and antimicrobial resistance (AMR) in Escherichia coli and Klebsiella pneumoniae in urinary tract infections.

METHODS

We analysed Dutch national databases from January 2008 to December 2016 regarding antibiotic use and AMR for nitrofurantoin, trimethoprim, fosfomycin and ciprofloxacin. Antibiotic use was expressed as DDD/1000 inhabitant-days (DID) and AMR was expressed as the percentage of resistance from total tested isolates. Temporal trends and seasonality were analysed with autoregressive integrated moving average (ARIMA) models. Each antibiotic use-resistance combination was cross-correlated with a linear regression of the ARIMA residuals.

RESULTS

The trends of DID increased for ciprofloxacin, fosfomycin and nitrofurantoin, but decreased for trimethoprim. Similar trends were found in E. coli and K. pneumoniae resistance to the same antibiotics, except for K. pneumoniae resistance to ciprofloxacin, which decreased. Resistance levels peaked in winter/spring, whereas antibiotic use peaked in summer/autumn. In univariate analysis, the strongest and most significant cross-correlations were approximately 0.20, and had a time delay of 3-6 months between changes in antibiotic use and changes in resistance. In multivariate analysis, significant effects of nitrofurantoin use and ciprofloxacin use on resistance to these antibiotics were found in E. coli and K. pneumoniae, respectively. There was a significant association of nitrofurantoin use with trimethoprim resistance in K. pneumoniae after adjusting for trimethoprim use.

CONCLUSIONS

We found a relatively low use of antibiotics and resistance levels over a 9 year period. Although the correlations were weak, variations in antibiotic use for these four antibiotics were associated with subsequent variations in AMR in urinary pathogens.

Antimicrobial Use in Companion Animals: Assessing Veterinarians' Prescription Patterns through the First National Survey in Chile

Although the relationship between the use of antimicrobials and the development of resistant bacteria is well established, information about the use of antimicrobials in companion animals has been poorly described, which represents a risk to public health. The aim of this study was to describe the antimicrobial prescription patterns of Chilean companion animal veterinarians. A nationally distributed survey targeted at companion animal veterinarians was designed. The survey included questions about the veterinarian's demographics, bacterial diseases treated, prescribed antimicrobials, and the use of laboratory diagnostic tools. Three hundred twenty-three responses were collected, most of the respondents were female (59.4%). The most frequently reported bacterial diseases were pyoderma (17.2%), followed by otitis and abscesses (7.4%). The antimicrobials most used corresponded with critically or highly important drugs for veterinary and human use, including β-lactams (65.3%), quinolones (36.2%) and tetracyclines (23.2%). Only 15% of the veterinarians reported the use of laboratory diagnostic tests, although 67% declared they were aware of the official antimicrobial classification schemes. Our results describe for the first time the usage of antimicrobials by veterinarian practitioners in Chile to treat different diseases in companion animals. The data presented here provide a baseline that could help to promote the implementation of clinical guidelines and regulations in order to improve current treatments.

Bacteriuria resistance patterns and the suitability of urinalysis as an initial diagnostic tool in a post-antibiotic era

AIMS

Urinalysis is used as a first-line investigation throughout healthcare to indicate bacteriuria and guide treatment of potential urinary tract infections. In light of rising bacterial multi-resistance, we aim to analyse its diagnostic accuracy, determine its usefulness in a present-day setting and evaluate current antibiotic resistance patterns across a Trust population.

METHODS

A retrospective case series of 712 paired urinalysis and urine culture results was obtained over a 1-month period. Sensitivity, specificity and diagnostic accuracy were calculated, and resistance profiles of commonly used Trust antibiotics assessed using statistical analysis.

RESULTS

A high false negative rate of nitrites on urinalysis, with sensitivity of 38.4%, was found. Leucocyte sensitivity was 87.6% and specificity 39.7%, with no improvement in diagnostic accuracy seen when combining both. Positive urine culture growth demonstrated a substantial resistance pattern to trimethoprim of 48%, compounded by a statistically significant correlation with gentamicin resistance (p < 0.0001).

CONCLUSION

Our study has highlighted a reduced accuracy of urinalysis compared with previous literature, questioning its usefulness in the real world. We have consolidated growing published trends doubting the efficacy of trimethoprim, revealing co-existing resistance patterns between commonly used antibiotics. This will have implications for future antibiotic-prescribing protocols and requires further research to ensure guidelines are progressive in consciously managing this growing concern in modern-day healthcare.

The role of "spillover" in antibiotic resistance

Antibiotic use is a key driver of antibiotic resistance. Understanding the quantitative association between antibiotic use and resulting resistance is important for predicting future rates of antibiotic resistance and for designing antibiotic stewardship policy. However, the use-resistance association is complicated by "spillover," in which one population's level of antibiotic use affects another population's level of resistance via the transmission of bacteria between those populations. Spillover is known to have effects at the level of families and hospitals, but it is unclear if spillover is relevant at larger scales. We used mathematical modeling and analysis of observational data to address this question. First, we used dynamical models of antibiotic resistance to predict the effects of spillover. Whereas populations completely isolated from one another do not experience any spillover, we found that if even 1% of interactions are between populations, then spillover may have large consequences: The effect of a change in antibiotic use in one population on antibiotic resistance in that population could be reduced by as much as 50%. Then, we quantified spillover in observational antibiotic use and resistance data from US states and European countries for three pathogen-antibiotic combinations, finding that increased interactions between populations were associated with smaller differences in antibiotic resistance between those populations. Thus, spillover may have an important impact at the level of states and countries, which has ramifications for predicting the future of antibiotic resistance, designing antibiotic resistance stewardship policy, and interpreting stewardship interventions.

Macrolide and Nonmacrolide Resistance with Mass Azithromycin Distribution

BACKGROUND

Mass distribution of azithromycin to preschool children twice yearly for 2 years has been shown to reduce childhood mortality in sub-Saharan Africa but at the cost of amplifying macrolide resistance. The effects on the gut resistome, a reservoir of antimicrobial resistance genes in the body, of twice-yearly administration of azithromycin for a longer period are unclear.

METHODS

We investigated the gut resistome of children after they received twice-yearly distributions of azithromycin for 4 years. In the Niger site of the MORDOR trial, we enrolled 30 villages in a concurrent trial in which they were randomly assigned to receive mass distribution of either azithromycin or placebo, offered to all children 1 to 59 months of age every 6 months for 4 years. Rectal swabs were collected at baseline, 36 months, and 48 months for analysis of the participants' gut resistome. The primary outcome was the ratio of macrolide-resistance determinants in the azithromycin group to those in the placebo group at 48 months.

RESULTS

Over the entire 48-month period, the mean (±SD) coverage was 86.6±12% in the villages that received placebo and 83.2±16.4% in the villages that received azithromycin. A total of 3232 samples were collected during the entire trial period; of the samples obtained at the 48-month monitoring visit, 546 samples from 15 villages that received placebo and 504 from 14 villages that received azithromycin were analyzed. Determinants of macrolide resistance were higher in the azithromycin group than in the placebo group: 7.4 times as high (95% confidence interval [CI], 4.0 to 16.7) at 36 months and 7.5 times as high (95% CI, 3.8 to 23.1) at 48 months. Continued mass azithromycin distributions also selected for determinants of nonmacrolide resistance, including resistance to beta-lactam antibiotics, an antibiotic class prescribed frequently in this region of Africa.

CONCLUSIONS

Among villages assigned to receive mass distributions of azithromycin or placebo twice yearly for 4 years, antibiotic resistance was more common in the villages that received azithromycin than in those that received placebo. This trial showed that mass azithromycin distributions may propagate antibiotic resistance. (Funded by the Bill and Melinda Gates Foundation and others; ClinicalTrials.gov number, NCT02047981.).

Improved penicillin susceptibility of Streptococcus pneumoniae and increased penicillin consumption in Japan, 2013-18

OBJECTIVES

To examine the association between penicillin susceptibility of Streptococcus pneumoniae and penicillin consumption in Japan.

METHODS

We used Japan Nosocomial Infection Surveillance data on the susceptibility of S. pneumoniae and sales data obtained from IQVIA Services Japan K.K. for penicillin consumption. We analysed both sets of data by decomposing them into seasonality and chronological trend components. The cross-correlation function was checked using Spearman's rank correlation coefficient to examine the correlation between susceptibility and consumption.

RESULTS

After adjusting for seasonality, the susceptibility of S. pneumoniae to penicillins gradually improved (55.7% in 2013 and 60.6% in 2018, respectively) and penicillin consumption increased during the same period (0.76 defined daily doses per 1,000 inhabitants per day [DID] in 2013, and 0.89 DID in 2018). The results showed positive cross-correlation (coefficient 0.801, p-value < 0.001). In contrast, cephalosporin consumption decreased (3.91 DID in 2013 and 3.19 DID in 2018) and showed negative cross-correlation with susceptibility of S. pneumoniae to penicillins (coefficient -0.981, p-value < 0.001).

CONCLUSIONS

The rates of penicillin-susceptible S. pneumoniae isolates did not negatively correlate with penicillin consumption at the population level. Increased penicillin consumption might not impair the penicillin susceptibility of S. pneumoniae.

Predicting antibiotic resistance in hospitalized patients by applying machine learning to electronic medical records

BACKGROUND

Computerized decision support systems are becoming increasingly prevalent with advances in data collection and machine learning algorithms. However, they are scarcely used for empiric antibiotic therapy. Here we accurately predict the antibiotic resistance profiles of bacterial infections of hospitalized patients using machine learning algorithms applied to patients' electronic medical records (EMR).

METHODS

The data included antibiotic resistance results of bacterial cultures from hospitalized patients, alongside their electronic medical records. Five antibiotics were examined: Ceftazidime (n=2942), Gentamicin (n=4360), Imipenem (n=2235), Ofloxacin (n=3117) and Sulfamethoxazole-Trimethoprim (n=3544). We applied lasso logistic regression, neural networks, gradient boosted trees, and an ensemble combining all three algorithms, to predict antibiotic resistance. Variable influence was gauged by permutation tests and Shapely Additive Explanations analysis.

RESULTS

The ensemble model outperformed the separate models and produced accurate predictions on a test set data. When no knowledge regarding the infecting bacterial species was assumed, the ensemble model yielded area under the receiver-operating-characteristic (auROC) scores of 0.73-0.79, for different antibiotics. Including information regarding the bacterial species improved the auROCs to 0.8-0.88. The effects of different variables on the predictions were assessed and found consistent with previously identified risk factors for antibiotic resistance.

CONCLUSIONS

Our study demonstrates the potential of machine learning models to accurately predict antibiotic resistance of bacterial infections of hospitalized patients. Moreover, we show that rapid information regarding the infecting bacterial species can improve predictions substantially. The implementation of such systems should be seriously considered by clinicians to aid correct empiric therapy and to potentially reduce antibiotic misuse.

Multidrug-resistant Escherichia coli and Salmonella spp. isolated from pigeons

Background and Aim:

Pigeon rearing has been gaining popularity for recent years. They are reared remarkably very close to the house of the owner. This activity, therefore, may pose potential threats for humans as well as other animals as pigeons may carry and spread different pathogens including drug-resistant bacteria. This study was conducted to explore the prevalence of Escherichia coli and Salmonella spp. as well as their antibiogram profile along with an association analysis.

Materials and Methods:

Forty swab samples were collected from 20 pigeons during the study. E. coli and Salmonella spp. were isolated and identified on various types of agars, including MacConkey, Eosin methylene blue, Brilliant green, and Salmonella-Shigella agar. Biochemical tests such as the carbohydrate fermentation test, the triple sugar iron agar slant reaction, the indole test, the methyl red test, the catalase test, as well as the Voges–Proskauer test were also performed. Besides, the presence of E. coli was further confirmed by polymerase chain reaction (PCR). Moreover, antimicrobial susceptibility testing of the isolates was performed against nine antibiotics from seven classes on the Mueller-Hinton agar based on the Kirby–Bauer disk diffusion method.

Results:

The overall prevalence of E. coli and Salmonella spp. was 52.5 and 27.5%, respectively. The prevalence of the pathogenic E. coli was 61.90%. The antibiogram profile of 21 E. coli as well as 11 Salmonella spp. revealed that all isolates, except one, were resistant to one to six antibiotics. Around 61.90%, 71.43%, 23.81%, 61.90%, 23.81%, 19.05%, and 52.38% of E. coli showed resistance against amoxicillin, ampicillin, azithromycin, erythromycin, nalidixic acid, gentamicin, and tetracycline, respectively. Furthermore, E. coli resistance was not observed in case of ciprofloxacin and levofloxacin. Similarly, around 36.36%, 27.27%, 27.27%, 45.45%, 81.82%, 100%, and 18.18% of the Salmonella spp. showed resistance against amoxicillin, ampicillin, azithromycin, erythromycin, nalidixic acid, tetracycline, and levofloxacin, respectively. However, all Salmonella spp. (100%) were found to show sensitivity against ciprofloxacin and gentamicin. Multidrug-resistant (MDR) E. coli (23.80%) and Salmonella spp. (54.54%) were also isolated. Furthermore, both positive (odds ratio [OR] >1) and negative (OR <1) drug resistance associations, with a higher frequency of positive associations, were found in E. coli. A significant positive association was observed between ampicillin and amoxicillin (OR: 81.67, 95% confidence interval: 2.73-2447.57, p=0.01).

Conclusion:

Pigeon carrying MDR E. coli and Salmonella spp. may contribute to the transmission and spread of these microorganisms. Therefore, strict hygienic measures should be taken during the farming of pigeons to decrease the potential transmission of E. coli and Salmonella spp. from pigeon to humans as well as other animals. So far, this is the first report of the PCR-based identification of pathogenic E. coli from pigeons in Bangladesh.

Awareness of Appropriate Antibiotic Use in Primary Care for Influenza-Like Illness: Evidence of Improvement from UK Population-Based Surveys

Influenza-like illnesses (ILI) account for a significant portion of inappropriate antibiotic use. Patient expectations for antibiotics for ILI are likely to play a substantial role in ‘unnecessary’ antibiotic consumption. This study aimed to investigate trends in awareness of appropriate antibiotic use and antimicrobial resistance (AMR). Three sequential online surveys of independent representative samples of adults in the United Kingdom investigated expectations for, and consumption of, antibiotics for ILI (May/June 2015 (n = 2064); Oct/Nov 2016 (n = 4000); Mar 2017 (n = 4000)). Respondents were asked whether they thought antibiotics were effective for ILI and about their antibiotic use. Proportions and 95% confidence intervals (CI) were calculated for each question and interactions with respondent characteristics were tested using logistic regression. Over the three surveys, the proportion of respondents who believed antibiotics would “definitely/probably” help an ILI fell from 37% (95% CI 35–39%) to 28% (95% CI 26–29%). Those who would “definitely/probably” visit a doctor in this situation fell from 48% (95% CI 46–50%) to 36% (95% CI 34–37%), while those who would request antibiotics during a consultation fell from 39% (95% CI 37–41%) to 30% (95% CI 29–32%). The percentage of respondents who found the information we provided about AMR “new/surprising” fell from 34% (95% CI 32–36%) to 28% (95% CI 26–31%). Awareness improved more among black, Asian and minority ethnic (BAME) than white people, with little other evidence of differences in improvements between subgroups. Whilst a degree of selection bias is unavoidable in online survey samples, the results suggest that awareness of AMR and appropriate antibiotic use has recently significantly improved in the United Kingdom, according to a wide range of indicators.

Fluoroquinolone resistance in Escherichia coli isolates after exposure to non-fluoroquinolone antibiotics: a retrospective case-control study

OBJECTIVES

To investigate whether prior exposure to non-fluoroquinolone antibiotics increases the risk of fluoroquinolone resistance in Escherichia coli.

METHODS

This was a secondary analysis of data collected retrospectively in a case-control study linking microbiological test results (isolated bacteria and their susceptibility) of urine samples routinely collected from primary, secondary and tertiary care patients in Belgium with information on prior antibiotic use at the patient level up to 1 year previously.

RESULTS

In urine samples from 6125 patients, 7204 E. coli isolates were retrieved [1949 fluoroquinolone-resistant isolates (cases) and 5255 fluoroquinolone-susceptible isolates (controls)]. After adjusting for potential confounders (including fluoroquinolone use) and correcting for multiple testing there were lower odds of fluoroquinolone resistance in E. coli isolates after exposure to cefazolin (OR = 0.65; 95% CI = 0.52-0.81; P = 0.00014) and higher odds after exposure to trimethoprim/sulfamethoxazole (OR = 1.56; 95% CI = 1.23-1.97; P =0.00020) or nitrofurantoin (OR = 1.50; 95% CI = 1.23-1.84; P =0.000083). A sensitivity analysis excluding samples with antibiotic use during the 6 months prior to the sampling date confirmed the higher odds of fluoroquinolone resistance after exposure to trimethoprim/sulfamethoxazole and nitrofurantoin.

CONCLUSIONS

Assuming no residual confounding or other biases, this study suggests that exposure to non-fluoroquinolone antibiotics, i.e. trimethoprim/sulfamethoxazole and nitrofurantoin, might be causally related to fluoroquinolone resistance in E. coli isolates from urinary samples. Future prospective research is needed to confirm non-fluoroquinolone antibiotics as potential drivers of fluoroquinolone resistance.

Comparison of antimicrobial prescribing for dental and oral infections in England and Scotland with Norway and Sweden and their relative contribution to national consumption 2010-2016

BACKGROUND

Prescribing in dental practice has a relatively small but important contribution to the quantity of antibiotics prescribed in primary care. This study aimed to analyse antibiotic prescribing in dentistry over time (2010-2016) in 4 different Northern European countries and their relative contribution to national outpatients consumption.

METHODS

This retrospective study evaluated the frequency and number of national antibiotic prescriptions written by dentists in England, Scotland, Norway and Sweden. The consumption of such antibiotics was measured using WHO defined daily doses (DDDs), DDDs per 100,000 inhabitants per day (DIDs100,000).

RESULTS

A total of more than 27 million prescriptions (27,026,599) archived between 2010 and 2016 from the four countries were analysed. The national contribution of Norwegian dentists to the total primary care prescription during this period was 8%. The corresponding figures for Sweden, Scotland and England were 7, 6, and 8%. Dental contribution to National antibiotic use in all four countries has decreased over the study time period for commonly prescribed antibiotics in dentistry, i.e., the beta-lactams (Phenoxymethyl penicillin/Amoxicillin) and metronidazole. There were less numbers of prescriptions by dentists in Norway and Sweden compared to England and Scotland. Marked differences in some classes of antibiotics were noted with Phenoxymethyl penicillin dominating in Sweden/Norway compared to Amoxicillin and Metronidazole in England/Scotland. In England and Scotland, dentists were the largest prescribers of metronidazole in primary care. Clindamycin prescriptions was higher in Norway and Sweden.

CONCLUSION

Noticeable differences exist in prescribing patterns for the management of oral infections. High levels of metronidazole use in England and Scotland also require further analysis. All countries over the study period showed a decrease in total numbers of antibiotics prescribed.

Antimicrobial resistance associations with national primary care antibiotic stewardship policy: Primary care-based, multilevel analytic study

Background

Recent UK antibiotic stewardship policies have resulted in significant changes in primary care dispensing, but whether this has impacted antimicrobial resistance is unknown.

Aim

To evaluate associations between changes in primary care dispensing and antimicrobial resistance in community-acquired urinary Escherichia coli infections.

Methods

Multilevel logistic regression modelling investigating relationships between primary care practice level antibiotic dispensing for approximately 1.5 million patients in South West England and resistance in 152,704 community-acquired urinary E. coli between 2013 and 2016. Relationships presented for within and subsequent quarter drug-bug pairs, adjusted for patient age, deprivation, and rurality.

Results

In line with national trends, overall antibiotic dispensing per 1000 registered patients fell 11%. Amoxicillin fell 14%, cefalexin 20%, ciprofloxacin 24%, co-amoxiclav 49% and trimethoprim 8%. Nitrofurantoin increased 7%. Antibiotic reductions were associated with reduced within quarter same-antibiotic resistance to: amoxicillin, ciprofloxacin and trimethoprim. Subsequent quarter reduced resistance was observed for trimethoprim and amoxicillin. Antibiotic dispensing reductions were associated with increased within and subsequent quarter resistance to cefalexin and co-amoxiclav. Increased nitrofurantoin dispensing was associated with reduced within and subsequent quarter trimethoprim resistance without affecting nitrofurantoin resistance.

Conclusions

This evaluation of a national primary care stewardship policy on antimicrobial resistance in the community suggests both hoped-for benefits and unexpected harms. Some increase in resistance to cefalexin and co-amoxiclav could result from residual confounding. Randomised controlled trials are urgently required to investigate causality.

Reducing expectations for antibiotics in primary care: a randomised experiment to test the response to fear-based messages about antimicrobial resistance

BACKGROUND

To reduce inappropriate antibiotic use, public health campaigns often provide fear-based information about antimicrobial resistance (AMR). Meta-analyses have found that fear-based campaigns in other contexts are likely to be ineffective unless respondents feel confident they can carry out the recommended behaviour ('self-efficacy'). This study aimed to test the likely impact of fear-based messages, with and without empowering self-efficacy elements, on patient consultations/antibiotic requests for influenza-like illnesses, using a randomised design.

METHODS

We hypothesised that fear-based messages containing empowering information about self-management without antibiotics would be more effective than fear alone, particularly in a pre-specified subgroup with low AMR awareness. Four thousand respondents from an online panel, representative of UK adults, were randomised to receive three different messages about antibiotic use and AMR, designed to induce fear about AMR to varying degrees. Two messages (one 'strong-fear', one 'mild-fear') also contained empowering information regarding influenza-like symptoms being easily self-managed without antibiotics. The main outcome measures were self-reported effect of information on likelihood of visiting a doctor and requesting antibiotics, for influenza-like illness, analysed separately according to whether or not the AMR information was 'very/somewhat new' to respondents, pre-specified based on a previous (non-randomised) survey.

RESULTS

The 'fear-only' message was 'very/somewhat new' to 285/1000 (28.5%) respondents, 'mild-fear-plus-empowerment' to 336/1500 (22.4%), and 'strong-fear-plus-empowerment' to 388/1500 (25.9%) (p = 0.002). Of those for whom the respective information was 'very/somewhat new', only those given the 'strong-fear-plus-empowerment' message said they would be less likely to request antibiotics if they visited a doctor for an influenza-like illness (p < 0.0001; 182/388 (46.9%) 'much less likely'/'less likely', versus 116/336 (34.5%) with 'mild-fear-plus-empowerment' versus 85/285 (29.8%) with 'fear-alone'). Those for whom the respective information was not 'very/somewhat new' said they would be less likely to request antibiotics for influenza-like illness (p < 0.0001) across all messages (interaction p < 0.0001 versus 'very/somewhat new' subgroup). The three messages had analogous self-reported effects on likelihood of visiting a doctor and in subgroups defined by believing antibiotics would 'definitely/probably' help an influenza-like illness. Results were reproduced in an independent randomised survey (additional 4000 adults).

CONCLUSIONS

Fear could be effective in public campaigns to reduce inappropriate antibiotic use, but should be combined with messages empowering patients to self-manage symptoms effectively without antibiotics.

Quantifying the economic cost of antibiotic resistance and the impact of related interventions: rapid methodological review, conceptual framework and recommendations for future studies

BACKGROUND

Antibiotic resistance (ABR) poses a major threat to health and economic wellbeing worldwide. Reducing ABR will require government interventions to incentivise antibiotic development, prudent antibiotic use, infection control and deployment of partial substitutes such as rapid diagnostics and vaccines. The scale of such interventions needs to be calibrated to accurate and comprehensive estimates of the economic cost of ABR.

METHODS

A conceptual framework for estimating costs attributable to ABR was developed based on previous literature highlighting methodological shortcomings in the field and additional deductive epidemiological and economic reasoning. The framework was supplemented by a rapid methodological review.

RESULTS

The review identified 110 articles quantifying ABR costs. Most were based in high-income countries only (91/110), set in hospitals (95/110), used a healthcare provider or payer perspective (97/110), and used matched cohort approaches to compare costs of patients with antibiotic-resistant infections and antibiotic-susceptible infections (or no infection) (87/110). Better use of methods to correct biases and confounding when making this comparison is needed. Findings also need to be extended beyond their limitations in (1) time (projecting present costs into the future), (2) perspective (from the healthcare sector to entire societies and economies), (3) scope (from individuals to communities and ecosystems), and (4) space (from single sites to countries and the world). Analyses of the impact of interventions need to be extended to examine the impact of the intervention on ABR, rather than considering ABR as an exogeneous factor.

CONCLUSIONS

Quantifying the economic cost of resistance will require greater rigour and innovation in the use of existing methods to design studies that accurately collect relevant outcomes and further research into new techniques for capturing broader economic outcomes.

Cost of inappropriate antimicrobial use for upper respiratory infection in Japan

BACKGROUND

Antibiotics are often prescribed inappropriately to patients with upper respiratory infection (URI) in ambulatory care settings; however, the economic burden of such prescription has not been quantitatively assessed. Here, we aimed to evaluate the additional cost of antimicrobial prescription for URI at the population level in Japan.

METHODS

We conducted a retrospective observational survey using longitudinal claims data between 2013 and 2016 obtained from JMDC Claims Database, which contains data from 5·1 million corporate employees and family members under the age of 65 years. Appropriateness of antibiotic prescription was assessed by a panel of six infectious disease physicians according to ICD-10 code in JMDC Claims Database. Total additional cost of antibiotic prescription for URI at the national level was estimated by weighting of age-structured population data.

RESULTS

The annual additional cost of inappropriate antibiotic prescription for URI was estimated at 423·6 (95% CI: 416·8-430·5) million USD in 2013, 340·9 (95% CI: 335·7-346·2) million USD in 2014, 349·9 (95% CI: 344·5-355·3) million USD in 2015, and 297·1 (95% CI: 292·4-301·9) million USD in 2016. Three classes of broad-spectrum oral antibiotics (third-generation cephalosporins, macrolides, and fluoroquinolones) accounted for > 90% of the total additional cost.

CONCLUSIONS

Although a decreasing trend was observed, annual additional costs of inappropriate antibiotic prescriptions for URI could be a substantial economic burden in Japan. Appropriately prescribing broad-spectrum oral antibiotics might be an important issue to reduce unnecessary medical costs in Japanese ambulatory care.

The relation between prescribing of different antibiotics and rates of mortality with sepsis in US adults

BACKGROUND

Antibiotic use contributes to the rates of sepsis and the associated mortality, particularly through lack of clearance of resistant infections following antibiotic treatment. At the same time, there is limited information on the effects of prescribing of some antibiotics vs. others on subsequent sepsis and sepsis-related mortality.

METHODS

We used a multivariable mixed-effects model to relate state-specific rates of outpatient prescribing overall for oral fluoroquinolones, penicillins, macrolides, and cephalosporins between 2014 and 2015 to state-specific rates of mortality with sepsis (ICD-10 codes A40-41 present as either underlying or contributing causes of death on a death certificate) in different age groups of US adults between 2014 and 2015, adjusting for additional covariates and random effects associated with the ten US Health and Human Services (HHS) regions.

RESULTS

Increase in the rate of prescribing of oral penicillins by 1 annual dose per 1000 state residents was associated with increases in annual rates of mortality with sepsis of 0.95 (95% CI (0.02,1.88)) per 100,000 persons aged 75-84y, and of 2.97 (0.72,5.22) per 100,000 persons aged 85 + y. Additionally, the percent of individuals aged 50-64y lacking health insurance, as well as the percent of individuals aged 65-84y who are African-American were associated with rates of mortality with sepsis in the corresponding age groups.

CONCLUSIONS

Our results suggest that prescribing of penicillins is associated with rates of mortality with sepsis in older US adults. Those results, as well as the related epidemiological data suggest that replacement of certain antibiotics, particularly penicillins in the treatment of different syndromes should be considered with the aim of reducing the rates of severe outcomes, including mortality related to bacterial infections.

Case-based surveillance of antimicrobial resistance with full susceptibility profiles

Surveillance of antimicrobial resistance (AMR) is essential for clinical decision-making and for public health authorities to monitor patterns in resistance and evaluate the effectiveness of interventions and control measures. Existing AMR surveillance is typically based on reports from hospital laboratories and public health laboratories, comprising reports of pathogen frequencies and resistance frequencies among each species detected. Here we propose an improved framework for AMR surveillance, in which the unit of surveillance is patients with specific conditions, rather than biological samples of a particular type. In this 'case-based' surveillance, denominators as well as numerators will be clearly defined with clinical relevance and more comparable at the local, national and international level. In locations with sufficient resources, individual-based data on patient characteristics and full antibiotic susceptibility profiles would provide high-quality evidence for monitoring resistant pathogens of clinical importance, clinical treatment of infections and public health responses to outbreaks of infections with resistant bacteria.

Mathematical modelling for antibiotic resistance control policy: do we know enough?

BACKGROUND

Antibiotics remain the cornerstone of modern medicine. Yet there exists an inherent dilemma in their use: we are able to prevent harm by administering antibiotic treatment as necessary to both humans and animals, but we must be mindful of limiting the spread of resistance and safeguarding the efficacy of antibiotics for current and future generations. Policies that strike the right balance must be informed by a transparent rationale that relies on a robust evidence base.

MAIN TEXT

One way to generate the evidence base needed to inform policies for managing antibiotic resistance is by using mathematical models. These models can distil the key drivers of the dynamics of resistance transmission from complex infection and evolutionary processes, as well as predict likely responses to policy change in silico. Here, we ask whether we know enough about antibiotic resistance for mathematical modelling to robustly and effectively inform policy. We consider in turn the challenges associated with capturing antibiotic resistance evolution using mathematical models, and with translating mathematical modelling evidence into policy.

CONCLUSIONS

We suggest that in spite of promising advances, we lack a complete understanding of key principles. From this we advocate for priority areas of future empirical and theoretical research.

Use of other antimicrobial drugs is associated with trimethoprim resistance in patients with urinary tract infections caused by E. coli

In recent years, high frequencies of trimethoprim resistance in urinary tract infections (UTIs) caused by E. coli are have been reported. Co-resistance to other antimicrobial drugs may play a role in this increase. Therefore, we investigated whether previous use of other antimicrobial drugs was associated with trimethoprim resistance. We conducted a nested case-control study with urinary cultures with E. coli from participants of the Rotterdam Study sent in by general practitioners to the regional laboratory between 1 January 2000 and 1 April 2016. Multivariable logistic regression analysis was performed to study the association between prior prescriptions of several antimicrobial drug groups and trimethoprim resistance using individual participant data. Urinary cultures of 1264 individuals with a UTI caused by E. coli were included. When adjusted for previous other antimicrobial drug use, a history of > 3 prescriptions of extended-spectrum penicillins (OR 1.68; 95% CI 1.10-2.55) was significantly associated with trimethoprim resistance of E. coli as was the use of > 3 prescriptions of sulfonamides and trimethoprim (OR 2.22; 95% CI 1.51-3.26). The use of > 3 prescriptions of nitrofuran derivatives was associated with a lower frequency of trimethoprim resistance (OR 0.60; 95% CI 0.39-0.92), after adjustment for other antimicrobial drug prescriptions. We found that previous use of extended-spectrum penicillins is associated with trimethoprim resistance. On the contrary, previous nitrofurantoin use was associated with a lower frequency of trimethoprim resistance. Especially in individuals with recurrent UTI, co-resistance should be taken into account and susceptibility testing before starting trimethoprim should be considered.

Levels of outpatient prescribing for four major antibiotic classes and rates of septicemia hospitalization in adults in different US states - a statistical analysis

BACKGROUND

Rates of sepsis/septicemia hospitalization in the US have risen significantly during recent years. Antibiotic resistance and use may contribute to those rates through various mechanisms, including lack of clearance of resistant infections following antibiotic treatment, with some of those infections subsequently devolving into sepsis. At the same time, there is limited information on the effect of prescribing of certain antibiotics vs. others on the rates of septicemia and sepsis-related hospitalizations and mortality.

METHODS

We used multivariable linear regression to relate state-specific rates of outpatient prescribing overall for oral fluoroquinolones, penicillins, macrolides, and cephalosporins between 2011 and 2012 to state-specific rates of septicemia hospitalization (ICD-9 codes 038.xx present anywhere on a discharge diagnosis) in each of the following age groups of adults: (18-49y, 50-64y, 65-74y, 75-84y, 85 + y) reported to the Healthcare Cost and Utilization Project (HCUP) between 2011 and 2012, adjusting for additional covariates, and random effects associated with the ten US Health and Human Services (HHS) regions.

RESULTS

Increase in the rate of prescribing of oral penicillins by 1 annual dose per 1000 state residents was associated with increases in annual septicemia hospitalization rates of 0.19 (95% CI (0.02,0.37)) per 10,000 persons aged 50-64y, of 0.48(0.12,0.84) per 10,000 persons aged 65-74y, and of 0.81(0.17,1.40) per 10,000 persons aged 74-84y. Increase by 1 in the percent of African Americans among state residents in a given age group was associated with increases in annual septicemia hospitalization rates of 2.3(0.32,4.2) per 10,000 persons aged 75-84y, and of 5.3(1.1,9.5) per 10,000 persons aged over 85y. Average minimal daily temperature was positively associated with septicemia hospitalization rates in persons aged 18-49y, 50-64y, 75-84y and over 85y.

CONCLUSIONS

Our results suggest positive associations between the rates of prescribing for penicillins and the rates of hospitalization with septicemia in US adults aged 50-84y. Further studies are needed to better understand the potential effect of antibiotic replacement in the treatment of various syndromes, including the potential impact of the recent US FDA guidelines on restriction of fluoroquinolone use, as well as the potential effect of changes in the practices for prescribing of penicillins on the rates of sepsis-related hospitalization and mortality.

Personal clinical history predicts antibiotic resistance of urinary tract infections

Antibiotic resistance is prevalent among the bacterial pathogens causing urinary tract infections. However, antimicrobial treatment is often prescribed “empirically”, in the absence of antibiotic susceptibility testing, risking mismatched and therefore ineffective treatment. Here, linking a 10-year longitudinal dataset of over 700,000 community-acquired UTIs with over 5,000,000 individually-resolved records of antibiotic purchases, we identify strong associations of antibiotic resistance with the demographics, records of past urine cultures and history of drug purchases of the patients. When combined together, these associations allow for machine learning-based personalized drug-specific predictions of antibiotic resistance, thereby enabling drug-prescribing algorithms that match antibiotic treatment recommendation to the expected resistance of each sample. Applying these algorithms retrospectively, over a one-year test period, we find that they much reduce the risk of mismatched treatment compared to the current standard-of-care. The clinical application of such algorithms may help improve the effectiveness of antimicrobial treatments.

Antimicrobial resistance prevalence, rates of hospitalization with septicemia and rates of mortality with sepsis in adults in different US states

OBJECTIVES

Rates of hospitalization with sepsis/septicemia and associated mortality in the US have risen significantly during the last two decades. Antibiotic resistance may contribute to the rates of sepsis-related outcomes through lack of clearance of bacterial infections following antibiotic treatment during different stages of infection. However, there is limited information about the relationship between prevalence of resistance to various antibiotics in different bacteria and rates of sepsis-related outcomes.

METHODS

For different age groups of adults (18-49y, 50-64y, 65-74y, 75-84y, 85+y) and combinations of antibiotics/bacteria, we evaluated associations between state-specific prevalence (percentage) of resistant samples for a given combination of antibiotics/bacteria among catheter-associated urinary tract infections (CAUTIs) in the CDC Antibiotic Resistance Patient Safety Atlas data between 2011-2014, and rates of hospitalization with septicemia (ICD-9 codes 038.xx present on the discharge diagnosis) reported to the Healthcare Cost and Utilization Project (HCUP), as well as rates of mortality with sepsis (ICD-10 codes A40-41.xx present on death certificate).

RESULTS

Among the different combinations of antibiotics/bacteria, prevalence of resistance to fluoroquinolones in Escherichia coli had the strongest association with septicemia hospitalization rates for individuals aged over 50y, and with sepsis mortality rates for individuals aged 18-84y. There were several positive correlations between prevalence of resistance for different combinations of antibiotics/bacteria and septicemia hospitalization/sepsis mortality rates in adults.

CONCLUSIONS

These findings, and those from work on the relationship between antibiotic use and sepsis rates, support the association between use of/resistance to certain antibiotics and rates of sepsis-related outcomes, indicating the potential utility of antibiotic replacement.

Optimising trial designs to identify appropriate antibiotic treatment durations

BACKGROUND

For many infectious conditions, the optimal antibiotic course length remains unclear. The estimation of course length must consider the important trade-off between maximising short- and long-term efficacy and minimising antibiotic resistance and toxicity.

MAIN BODY

Evidence on optimal treatment durations should come from randomised controlled trials. However, most antibiotic randomised controlled trials compare two arbitrarily chosen durations. We argue that alternative trial designs, which allow allocation of patients to multiple different treatment durations, are needed to better identify optimal antibiotic durations. There are important considerations when deciding which design is most useful in identifying optimal treatment durations, including the ability to model the duration-response relationship (or duration-response 'curve'), the risk of allocation concealment bias, statistical efficiency, the possibility to rapidly drop arms that are clearly inferior, and the possibility of modelling the trade-off between multiple competing outcomes.

CONCLUSION

Multi-arm designs modelling duration-response curves with the possibility to drop inferior arms during the trial could provide more information about the optimal duration of antibiotic therapies than traditional head-to-head comparisons of limited numbers of durations, while minimising the probability of assigning trial participants to an ineffective treatment regimen.

Selection and co-selection of antibiotic resistances among Escherichia coli by antibiotic use in primary care: An ecological analysis

Background

The majority of studies that link antibiotic usage and resistance focus on simple associations between the resistance against a specific antibiotic and the use of that specific antibiotic. However, the relationship between antibiotic use and resistance is more complex. Here we evaluate selection and co-selection by assessing which antibiotics, including those mainly prescribed for respiratory tract infections, are associated with increased resistance to various antibiotics among Escherichia coli isolated from urinary samples.

Methods

Monthly primary care prescribing data were obtained from National Health Service (NHS) Digital. Positive E. coli records from urine samples in English primary care (n = 888,207) between April 2014 and January 2016 were obtained from the Second Generation Surveillance System. Elastic net regularization was used to evaluate associations between prescribing of different antibiotic groups and resistance against amoxicillin, cephalexin, ciprofloxacin, co-amoxiclav and nitrofurantoin at the clinical commissioning group (CCG) level. England is divided into 209 CCGs, with each NHS practice prolonging to one CCG.

Results

Amoxicillin prescribing (measured in DDD/ 1000 inhabitants / day) was positively associated with amoxicillin (RR 1.03, 95% CI 1.01–1.04) and ciprofloxacin (RR 1.09, 95% CI 1.04–1.17) resistance. In contrast, nitrofurantoin prescribing was associated with lower levels of resistance to amoxicillin (RR 0.92, 95% CI 0.84–0.97). CCGs with higher levels of trimethoprim prescribing also had higher levels of ciprofloxacin resistance (RR 1.34, 95% CI 1.10–1.59).

Conclusion

Amoxicillin, which is mainly (and often unnecessarily) prescribed for respiratory tract infections is associated with increased resistance against various antibiotics among E. coli causing urinary tract infections. Our findings suggest that when predicting the potential impact of interventions on antibiotic resistances it is important to account for use of other antibiotics, including those typically used for other indications.

Comment on 'The distribution of antibiotic use and its association with antibiotic resistance'

We are writing to comment on the recent study by Olesen et al., 2018 on antibiotic use and antibiotic resistance.

The challenge of antimicrobial resistance: What economics can contribute

As antibiotic consumption grows, bacteria are becoming increasingly resistant to treatment. Antibiotic resistance undermines much of modern health care, which relies on access to effective antibiotics to prevent and treat infections associated with routine medical procedures. The resulting challenges have much in common with those posed by climate change, which economists have responded to with research that has informed and shaped public policy. Drawing on economic concepts such as externalities and the principal–agent relationship, we suggest how economics can help to solve the challenges arising from increasing resistance to antibiotics. We discuss solutions to the key economic issues, from incentivizing the development of effective new antibiotics to improving antibiotic stewardship through financial mechanisms and regulation.

Duration of antibiotic treatment for common infections in English primary care: cross sectional analysis and comparison with guidelines

OBJECTIVE

To evaluate the duration of prescriptions for antibiotic treatment for common infections in English primary care and to compare this with guideline recommendations.

DESIGN

Cross sectional study.

SETTING

General practices contributing to The Health Improvement Network database, 2013-15.

PARTICIPANTS

931 015 consultations that resulted in an antibiotic prescription for one of several indications: acute sinusitis, acute sore throat, acute cough and bronchitis, pneumonia, acute exacerbation of chronic obstructive pulmonary disease (COPD), acute otitis media, acute cystitis, acute prostatitis, pyelonephritis, cellulitis, impetigo, scarlet fever, and gastroenteritis.

MAIN OUTCOME MEASURES

The main outcomes were the percentage of antibiotic prescriptions with a duration exceeding the guideline recommendation and the total number of days beyond the recommended duration for each indication.

RESULTS

The most common reasons for antibiotics being prescribed were acute cough and bronchitis (386 972, 41.6% of the included consultations), acute sore throat (239 231, 25.7%), acute otitis media (83 054, 8.9%), and acute sinusitis (76 683, 8.2%). Antibiotic treatments for upper respiratory tract indications and acute cough and bronchitis accounted for more than two thirds of the total prescriptions considered, and 80% or more of these treatment courses exceeded guideline recommendations. Notable exceptions were acute sinusitis, where only 9.6% (95% confidence interval 9.4% to 9.9%) of prescriptions exceeded seven days and acute sore throat where only 2.1% (2.0% to 2.1%) exceeded 10 days (recent guidance recommends five days). More than half of the antibiotic prescriptions were for longer than guidelines recommend for acute cystitis among females (54.6%, 54.1% to 55.0%). The percentage of antibiotic prescriptions exceeding the recommended duration was lower for most non-respiratory infections. For the 931 015 included consultations resulting in antibiotic prescriptions, about 1.3 million days were beyond the durations recommended by guidelines.

CONCLUSION

For most common infections treated in primary care, a substantial proportion of antibiotic prescriptions have durations exceeding those recommended in guidelines. Substantial reductions in antibiotic exposure can be accomplished by aligning antibiotic prescription durations with guidelines.

The distribution of antibiotic use and its association with antibiotic resistance

Antibiotic use is a primary driver of antibiotic resistance. However, antibiotic use can be distributed in different ways in a population, and the association between the distribution of use and antibiotic resistance has not been explored. Here, we tested the hypothesis that repeated use of antibiotics has a stronger association with population-wide antibiotic resistance than broadly-distributed, low-intensity use. First, we characterized the distribution of outpatient antibiotic use across US states, finding that antibiotic use is uneven and that repeated use of antibiotics makes up a minority of antibiotic use. Second, we compared antibiotic use with resistance for 72 pathogen-antibiotic combinations across states. Finally, having partitioned total use into extensive and intensive margins, we found that intense use had a weaker association with resistance than extensive use. If the use-resistance relationship is causal, these results suggest that reducing total use and selection intensity will require reducing broadly distributed, low-intensity use.