A model-guided analysis and perspective on the evolution and epidemiology of antibiotic resistance and its future

Cost-effectiveness of screening, decolonisation and isolation strategies for carbapenem-resistant Enterobacterales and methicillin-resistant Staphylococcus aureus infections in hospitals: a sex-stratified mathematical modelling study

Background

Methicillin-resistant Staphylococcus aureus (MRSA) and carbapenem-resistant Enterobacterales (CRE) impose the greatest burden among critical bacterial pathogens. Evidence for sex differences among antibiotic resistant bacterial infections is increasing but a focus on policy implications is needed. We assessed impact of CRE/MRSA on excess length of hospital stay, intensive care unit admission, and mortality by sex from a retrospective cohort study (n = 873) of patients in three Chilean hospitals, 2018-2021.

Methods

We used inverse-probability weighting combined with descriptive, logistic, and competing-risks analyses. We developed a sex-stratified deterministic compartmental model to analyse hospital transmission dynamics and the cost-effectiveness of nine interventions. We compared interventions based on the incremental cost-effectiveness ratio (ICER) per quality-adjusted life year (QALY) gained and estimated net benefits.

Findings

The adjusted odds of women acquiring CRE and MRSA were 0.44 (0.28-0.70; p = 0.0013) and 0.73 (95% CI = 0.48-1.01; p = 0.050), respectively. Competing-risk models indicated higher mortality rates among women, compared to men. Mathematical model projections showed that pre-emptive isolation across all newly admitted high-risk men was the most cost-effective intervention (ICER = $1366/QALY and $1083/QALY for CRE and MRSA, respectively). Chromogenic agar coupled with MRSA decolonisation was the second most cost-effective intervention ($2099/QALY), followed by screening plus isolation or pre-emptive isolation strategies (ICER ranged between $2411/QALY and $4216/QALY across CRE and MRSA models). Probabilistic sensitivity analysis showed that strategies were ICER < willingness-to-pay in 80% of simulations, except for testing plus digestive decolonisation for CRE. At a 20% national hospital coverage at least $12.2 million could be saved.

Interpretation

Our model suggests that targeted infection control strategies would effectively address rising CRE and MRSA infections. Maximising health-economic gains may be achieved by focusing on control measures for men as primary drivers for transmission, thereby reducing the disproportionate disease burden borne by women.

Funding

Agencia Nacional de Investigación y Desarrollo ANID, Chile.

A cyclic behavioral modeling aspect to understand the effects of vaccination and treatment on epidemic transmission dynamics

Evolutionary epidemiological models have played an active part in analyzing various contagious diseases and intervention policies in the biological sciences. The design in this effort is the addition of compartments for treatment and vaccination, so the system is designated as susceptible, vaccinated, infected, treated, and recovered (SVITR) epidemic dynamic. The contact of a susceptible individual with a vaccinated or an infected individual makes the individual either immunized or infected. Inventively, the assumption that infected individuals enter the treatment and recover state at different rates after a time interval is also deliberated through the presence of behavioral aspects. The rate of change from susceptible to vaccinated and infected to treatment is studied in a comprehensive evolutionary game theory with a cyclic epidemic model. We theoretically investigate the cyclic SVITR epidemic model framework for disease-free and endemic equilibrium to show stable conditions. Then, the embedded vaccination and treatment strategies are present using extensive evolutionary game theory aspects among the individuals in society through a ridiculous phase diagram. Extensive numerical simulation suggests that effective vaccination and treatment may implicitly reduce the community risk of infection when reliable and cheap. The results exhibited the dilemma and benefitted situation, in which the interplay between vaccination and treatment evolution and coexistence are investigated by the indicators of social efficiency deficit and socially benefited individuals.

Transmission of gram-negative antibiotic-resistant bacteria following differing exposure to antibiotic-resistance reservoirs in a rural community: a modelling study for bloodstream infections

Exposure to community reservoirs of gram-negative antibiotic-resistant bacteria (GN-ARB) genes poses substantial health risks to individuals, complicating potential infections. Transmission networks and population dynamics remain unclear, particularly in resource-poor communities. We use a dynamic compartment model to assess GN-ARB transmission quantitatively, including the susceptible, colonised, infected, and removed populations at the community-hospital interface. We used two side streams to distinguish between individuals at high- and low-risk exposure to community ARB reservoirs. The model was calibrated using data from a cross-sectional cohort study (N = 357) in Chile and supplemented by existing literature. Most individuals acquired ARB from the community reservoirs (98%) rather than the hospital. High exposure to GN-ARB reservoirs was associated with 17% and 16% greater prevalence for GN-ARB carriage in the hospital and community settings, respectively. The higher exposure has led to 16% more infections and attributed mortality. Our results highlight the need for early-stage identification and testing capability of bloodstream infections caused by GN-ARB through a faster response at the community level, where most GN-ARB are likely to be acquired. Increasing treatment rates for individuals colonised or infected by GN-ARB and controlling the exposure to antibiotic consumption and GN-ARB reservoirs, is crucial to curve GN-ABR transmission.

Disparity in socio-economic status explains the pattern of self-medication of antibiotics in India: understanding from game-theoretic perspective

The emergence of antimicrobial resistance has raised great concern for public health in many lower-income countries including India. Socio-economic determinants like poverty, health expenditure and awareness accelerate this emergence by influencing individuals' attitudes and healthcare practices such as self-medication. This self-medication practice is highly prevalent in many countries, where antibiotics are available without prescriptions. Thus, complex dynamics of drug- resistance driven by economy, human behaviour, and disease epidemiology poses a serious threat to the community, which has been less emphasized in prior studies. Here, we formulate a game-theoretic model of human choices in self-medication integrating economic growth and disease transmission processes. We show that this adaptive behaviour emerges spontaneously in the population through a self-reinforcing process and continual feedback from the economy, resulting in the emergence of resistance as externalities of human choice under resource constraints situations. We identify that the disparity between social-optimum and individual interest in self-medication is primarily driven by the effectiveness of treatment, health awareness and public health interventions. Frequent multiple-peaks of resistant strains are also observed when individuals imitate others more readily and self-medication is more likely. Our model exemplifies that timely public health intervention for financial risk protection, and antibiotic stewardship policies can improve the epidemiological situation and prevent economic collapse.

Mathematical Models of Plasmid Population Dynamics

With plasmid-mediated antibiotic resistance thriving and threatening to become a serious public health problem, it is paramount to increase our understanding of the forces that enable the spread and maintenance of drug resistance genes encoded in mobile genetic elements. The relevance of plasmids as vehicles for the dissemination of antibiotic resistance genes, in addition to the extensive use of plasmid-derived vectors for biotechnological and industrial purposes, has promoted the in-depth study of the molecular mechanisms controlling multiple aspects of a plasmids' life cycle. This body of experimental work has been paralleled by the development of a wealth of mathematical models aimed at understanding the interplay between transmission, replication, and segregation, as well as their consequences in the ecological and evolutionary dynamics of plasmid-bearing bacterial populations. In this review, we discuss theoretical models of plasmid dynamics that span from the molecular mechanisms of plasmid partition and copy-number control occurring at a cellular level, to their consequences in the population dynamics of complex microbial communities. We conclude by discussing future directions for this exciting research topic.

A Review on Occurrence and Spread of Antibiotic Resistance in Wastewaters and in Wastewater Treatment Plants: Mechanisms and Perspectives

This paper reviews current knowledge on sources, spread and removal mechanisms of antibiotic resistance genes (ARGs) in microbial communities of wastewaters, treatment plants and downstream recipients. Antibiotic is the most important tool to cure bacterial infections in humans and animals. The over- and misuse of antibiotics have played a major role in the development, spread, and prevalence of antibiotic resistance (AR) in the microbiomes of humans and animals, and microbial ecosystems worldwide. AR can be transferred and spread amongst bacteria via intra- and interspecies horizontal gene transfer (HGT). Wastewater treatment plants (WWTPs) receive wastewater containing an enormous variety of pollutants, including antibiotics, and chemicals from different sources. They contain large and diverse communities of microorganisms and provide a favorable environment for the spread and reproduction of AR. Existing WWTPs are not designed to remove micropollutants, antibiotic resistant bacteria (ARB) and ARGs, which therefore remain present in the effluent. Studies have shown that raw and treated wastewaters carry a higher amount of ARB in comparison to surface water, and such reports have led to further studies on more advanced treatment processes. This review summarizes what is known about AR removal efficiencies of different wastewater treatment methods, and it shows the variations among different methods. Results vary, but the trend is that conventional activated sludge treatment, with aerobic and/or anaerobic reactors alone or in series, followed by advanced post treatment methods like UV, ozonation, and oxidation removes considerably more ARGs and ARB than activated sludge treatment alone. In addition to AR levels in treated wastewater, it examines AR levels in biosolids, settled by-product from wastewater treatment, and discusses AR removal efficiency of different biosolids treatment procedures. Finally, it puts forward key-points and suggestions for dealing with and preventing further increase of AR in WWTPs and other aquatic environments, together with a discussion on the use of mathematical models to quantify and simulate the spread of ARGs in WWTPs. Mathematical models already play a role in the analysis and development of WWTPs, but they do not consider AR and challenges remain before models can be used to reliably study the dynamics and reduction of AR in such systems.

Detailed characterization, antibiotic resistance and seasonal variation of hospital wastewater

This study investigates the presence of the different classes of micro-pollutants such as pharmaceutical active compounds (PhACs) (20 antibiotics, 8 analgesics and anti-inflammatories, 5 cytostatic agents, 7 β-blockers, 4 lipid regulators, 13 psychiatrics, 1 antidiabetic, 1 receptor antagonist, 1 local anaesthetic, 1 antihypertensive and their 5 metabolites), hormones (8 compounds), X-ray contrast agents (6 compounds), benzotriazoles (3 compounds) and pesticides (6 compounds), and antibiotic resistance in hospital wastewater (HWW) of a medical faculty in Istanbul, Turkey. In addition, the seasonal variations of the selected PhACs and X-ray contrast agents and antibiotic resistance were evaluated for 2 years in a total of eight samples. In the PhACs, sulfamethoxazole and its metabolite (4 N-acethyl-sulfamethoxazole) in the antibiotic group and paracetamol in the analgesic and anti-inflammatory group were found at 100% of frequency and the highest concentrations as 35, 43 and 210 μg/L, respectively. The mean concentrations of psychiatric compounds were found less than 0.25 μg/L except carbamazepine (1.36 μg/L). Bisphenol A in hormone group had the highest concentration up to 14 μg/L. In the hormone group compounds, 17-α-Ethinylestradiol and 17-β-Estradiol were detected at lower mean concentrations of 0.2 and 0.05 μg/L, respectively. 1H-benzotriazole had the highest concentration with the mean concentration of 24.8 μg/L in benzotriazole group compounds. The compounds in X-ray contrast agents group were noted as compounds detected at the highest concentration in HWW up to 3000 μg/L. Antibiotic resistance against azithromycin, clindamycin and trimethoprim-sulfamethoxazole antibiotics was observed around 50% in the winter period. The seasonal variation was detected for the most of the investigated PhACs, especially in antibiotic group which was in line with those significant differences in antibiotic resistance rates in the studied antibiotics between winter and summer seasons.

A survey of within-host and between-hosts modelling for antibiotic resistance

Antibiotic resistance is a global public health problem which has the attention of many stakeholders including clinicians, the pharmaceutical industry, researchers and policy makers. Despite the existence of many studies, control of resistance transmission has become a rather daunting task as the mechanisms underlying resistance evolution and development are not fully known. Here, we discuss the mechanisms underlying antibiotic resistance development, explore some treatment strategies used in the fight against antibiotic resistance and consider recent findings on collateral susceptibilities amongst antibiotic classes. Mathematical models have proved valuable for unravelling complex mechanisms in biology and such models have been used in the quest of understanding the development and spread of antibiotic resistance. While assessing the importance of such mathematical models, previous systematic reviews were interested in investigating whether these models follow good modelling practice. We focus on theoretical approaches used for resistance modelling considering both within and between host models as well as some pharmacodynamic and pharmakokinetic approaches and further examine the interaction between drugs and host immune response during treatment with antibiotics. Finally, we provide an outlook for future research aimed at modelling approaches for combating antibiotic resistance.

Head and neck surgical antibiotic prophylaxis in resource-constrained settings

PURPOSE OF REVIEW

Antimicrobial resistance represents a global threat and causes almost 700 000 deaths per year. The rapid dissemination of resistant bacteria is occurring globally, turning this into the primary threat to public health in the 21st century and forcing organizations around the globe to take urgent action.

RECENT FINDINGS

About risks related to surgical site infection (SSI) in head and neck surgery, surgical limitations in resource-constrained settings, comorbidities and the risk of SSI, evidence about surgical prophylaxis from low and middle-income countries, SSI gap between the developed and developing worlds and how to reduce resistance.

SUMMARY

Antibiotic protocols can be adjusted to local and regional bacterial resistance profiles, taking into account the availability of antibiotics and cost limitations on each country in order to decrease the SSI risk.

Antimicrobial stewardship programs; a two-part narrative review of step-wise design and issues of controversy. Part II: Ten questions reflecting knowledge gaps and issues of controversy in the field of antimicrobial stewardship

Regardless of one's opinion on antimicrobial stewardship programs (ASPs), it is hardly possible to work in hospital care and not be exposed to the term or its practical effects. Despite the term being relatively new, the number of publications in the field is vast, including several excellent reviews of general and specific aspects. Work in antimicrobial stewardship is complex, and include aspects not only of infectious disease and microbiology, but also of epidemiology, genetics, behavioural psychology, systems science, economics and ethics, to name but a few. This review aims to take several of these aspects and the scientific evidence from antimicrobial stewardship studies and merge them into two questions: How should we design ASPs based on what we know today? and Which are the most essential unanswered questions regarding antimicrobial stewardship on a broader scale? This narrative review is written in two separate parts aiming to provide answers to the two questions. The first part, published separately, is written as a step-wise approach to designing a stewardship intervention based on the pillars of unmet need, feasibility, scientific evidence and necessary core elements. It is written mainly as a guide to someone new to the field. It is sorted into five distinct steps; (a) focusing on designing aims; (b) assessing performance and local barriers to rational antimicrobial use; (c) deciding on intervention technique; (d) practical, tailored design including core element inclusion; and (e) evaluation and sustainability. This second part formulates 10 critical questions on controversies in the field of antimicrobial stewardship. It is aimed at clinicians and researchers with stewardship experience and strives to promote discussion, not to provide answers.

Lying in Wait: Modeling the Control of Bacterial Infections via Antibiotic-Induced Proviruses

Antibiotic resistance is a growing concern for management of common bacterial infections. Here, we show that antibiotics can be effective at subinhibitory levels when bacteria carry latent phage. Our findings suggest that specific treatment strategies based on the identification of latent viruses in individual bacterial strains may be an effective personalized medicine approach to antibiotic stewardship.

Most bacteria and archaea are infected by latent viruses that change their physiology and responses to environmental stress. We use a population model of the bacterium-phage relationship to examine the role that latent phage play in the bacterial population over time in response to antibiotic treatment. We demonstrate that the stress induced by antibiotic administration, even if bacteria are resistant to killing by antibiotics, is sufficient to control the infection under certain conditions. This work expands the breadth of understanding of phage-antibiotic synergy to include both temperate and chronic viruses persisting in their latent form in bacterial populations.

IMPORTANCE Antibiotic resistance is a growing concern for management of common bacterial infections. Here, we show that antibiotics can be effective at subinhibitory levels when bacteria carry latent phage. Our findings suggest that specific treatment strategies based on the identification of latent viruses in individual bacterial strains may be an effective personalized medicine approach to antibiotic stewardship.

Defining and combating antibiotic resistance from One Health and Global Health perspectives

Several interconnected human, animal and environmental habitats can contribute to the emergence, evolution and spread of antibiotic resistance, and the health of these contiguous habitats (the focus of the One Health approach) may represent a risk to human health. Additionally, the expansion of resistant clones and antibiotic resistance determinants among human-associated, animal-associated and environmental microbiomes have the potential to alter bacterial population genetics at local and global levels, thereby modifying the structure, and eventually the productivity, of microbiomes where antibiotic-resistant bacteria can expand. Conversely, any change in these habitats (including pollution by antibiotics or by antibiotic-resistant organisms) may influence the structures of their associated bacterial populations, which might affect the spread of antibiotic resistance to, and among, the above-mentioned microbiomes. Besides local transmission among connected habitats-the focus of studies under the One Health concept-the transmission of resistant microorganisms might occur on a broader (even worldwide) scale, requiring coordinated Global Health actions. This Review provides updated information on the elements involved in the evolution and spread of antibiotic resistance at local and global levels, and proposes studies to be performed and strategies to be followed that may help reduce the burden of antibiotic resistance as well as its impact on human and planetary health.

Antibiotic drug-resistance as a complex system driven by socio-economic growth and antibiotic misuse

Overwhelming antibiotic use poses a serious challenge today to the public-health policymakers worldwide. Many empirical studies pointed out this ever-increasing antibiotic consumption as primary driver of the community-acquired antibiotic drug-resistance, especially in the middle- and lower-income countries. The association is well documented across spatio-temporal gradients in many parts of the world, but there is rarely any study that emphasizes the mechanism of the association, which is important for combating drug-resistance. Formulating a mathematical model of emergence and transmission of drug-resistance, we in this paper, present how amalgamating three components: socio-economic growth, population ecology of infectious disease, and antibiotic misuse can instinctively incite proliferation of resistance in the society. We show that combined impact of economy, infections, and self-medication yield synergistic interactions through feedbacks on each other, presenting the emergence of drug-resistance as a self-reinforcing cycle in the population. Analysis of our model not only determines the threshold of antibiotic use beyond which the emergence of resistance may occur, but also characterizes how fast it develops depending on economic growth, and lack of education and awareness of the population. Our model illustrates that proper and timely government aid in population health can break the self-reinforcing process and reduce the burden of drug-resistance in the community.

Collateral sensitivity constrains resistance evolution of the CTX-M-15 β-lactamase

Antibiotic resistance is a major challenge to global public health. Discovery of new antibiotics is slow and to ensure proper treatment of bacterial infections new strategies are needed. One way to curb the development of antibiotic resistance is to design drug combinations where the development of resistance against one drug leads to collateral sensitivity to the other drug. Here we study collateral sensitivity patterns of the globally distributed extended-spectrum β-lactamase CTX-M-15, and find three non-synonymous mutations with increased resistance against mecillinam or piperacillin-tazobactam that simultaneously confer full susceptibility to several cephalosporin drugs. We show in vitro and in mice that a combination of mecillinam and cefotaxime eliminates both wild-type and resistant CTX-M-15. Our results indicate that mecillinam and cefotaxime in combination constrain resistance evolution of CTX-M-15, and illustrate how drug combinations can be rationally designed to limit the resistance evolution of horizontally transferred genes by exploiting collateral sensitivity patterns.

Application of dynamic modelling techniques to the problem of antibacterial use and resistance: a scoping review

Selective pressure exerted by the widespread use of antibacterial drugs is accelerating the development of resistant bacterial populations. The purpose of this scoping review was to summarise the range of studies that use dynamic models to analyse the problem of bacterial resistance in relation to antibacterial use in human and animal populations. A comprehensive search of the peer-reviewed literature was performed and non-duplicate articles (n = 1486) were screened in several stages. Charting questions were used to extract information from the articles included in the final subset (n = 81). Most studies (86%) represent the system of interest with an aggregate model; individual-based models are constructed in only seven articles. There are few examples of inter-host models outside of human healthcare (41%) and community settings (38%). Resistance is modelled for a non-specific bacterial organism and/or antibiotic in 40% and 74% of the included articles, respectively. Interventions with implications for antibacterial use were investigated in 67 articles and included changes to total antibiotic consumption, strategies for drug management and shifts in category/class use. The quality of documentation related to model assumptions and uncertainty varies considerably across this subset of articles. There is substantial room to improve the transparency of reporting in the antibacterial resistance modelling literature as is recommended by best practice guidelines.

Send more data: a systematic review of mathematical models of antimicrobial resistance

Background

Antimicrobial resistance is a global health problem that demands all possible means to control it. Mathematical modelling is a valuable tool for understanding the mechanisms of AMR development and spread, and can help us to investigate and propose novel control strategies. However, it is of vital importance that mathematical models have a broad utility, which can be assured if good modelling practice is followed.

Objective

The objective of this study was to provide a comprehensive systematic review of published models of AMR development and spread. Furthermore, the study aimed to identify gaps in the knowledge required to develop useful models.

Methods

The review comprised a comprehensive literature search with 38 selected studies. Information was extracted from the selected papers using an adaptation of previously published frameworks, and was evaluated using the TRACE good modelling practice guidelines.

Results

None of the selected papers fulfilled the TRACE guidelines. We recommend that future mathematical models should: a) model the biological processes mechanistically, b) incorporate uncertainty and variability in the system using stochastic modelling, c) include a sensitivity analysis and model external and internal validation.

Conclusion

Many mathematical models of AMR development and spread exist. There is still a lack of knowledge about antimicrobial resistance, which restricts the development of useful mathematical models.

Critical knowledge gaps and research needs related to the environmental dimensions of antibiotic resistance

There is growing understanding that the environment plays an important role both in the transmission of antibiotic resistant pathogens and in their evolution. Accordingly, researchers and stakeholders world-wide seek to further explore the mechanisms and drivers involved, quantify risks and identify suitable interventions. There is a clear value in establishing research needs and coordinating efforts within and across nations in order to best tackle this global challenge. At an international workshop in late September 2017, scientists from 14 countries with expertise on the environmental dimensions of antibiotic resistance gathered to define critical knowledge gaps. Four key areas were identified where research is urgently needed: 1) the relative contributions of different sources of antibiotics and antibiotic resistant bacteria into the environment; 2) the role of the environment, and particularly anthropogenic inputs, in the evolution of resistance; 3) the overall human and animal health impacts caused by exposure to environmental resistant bacteria; and 4) the efficacy and feasibility of different technological, social, economic and behavioral interventions to mitigate environmental antibiotic resistance.1.

Artificial Gene Amplification in Escherichia coli Reveals Numerous Determinants for Resistance to Metal Toxicity

When organisms are subjected to environmental challenges, including growth inhibitors and toxins, evolution often selects for the duplication of endogenous genes, whose overexpression can provide a selective advantage. Such events occur both in natural environments and in clinical settings. Microbial cells-with their large populations and short generation times-frequently evolve resistance to a range of antimicrobials. While microbial resistance to antibiotic drugs is well documented, less attention has been given to the genetic elements responsible for resistance to metal toxicity. To assess which overexpressed genes can endow gram-negative bacteria with resistance to metal toxicity, we transformed a collection of plasmids overexpressing all E. coli open reading frames (ORFs) into naive cells, and selected for survival in toxic concentrations of six transition metals: Cd, Co, Cu, Ni, Ag, Zn. These selections identified 48 hits. In each of these hits, the overexpression of an endogenous E. coli gene provided a selective advantage in the presence of at least one of the toxic metals. Surprisingly, the majority of these cases (28/48) were not previously known to function in metal resistance or homeostasis. These findings highlight the diverse mechanisms that biological systems can deploy to adapt to environments containing toxic concentrations of metals.

Environmental factors influencing the development and spread of antibiotic resistance

Antibiotic resistance and its wider implications present us with a growing healthcare crisis. Recent research points to the environment as an important component for the transmission of resistant bacteria and in the emergence of resistant pathogens. However, a deeper understanding of the evolutionary and ecological processes that lead to clinical appearance of resistance genes is still lacking, as is knowledge of environmental dispersal barriers. This calls for better models of how resistance genes evolve, are mobilized, transferred and disseminated in the environment. Here, we attempt to define the ecological and evolutionary environmental factors that contribute to resistance development and transmission. Although mobilization of resistance genes likely occurs continuously, the great majority of such genetic events do not lead to the establishment of novel resistance factors in bacterial populations, unless there is a selection pressure for maintaining them or their fitness costs are negligible. To enable preventative measures it is therefore critical to investigate under what conditions and to what extent environmental selection for resistance takes place. In addition, understanding dispersal barriers is not only key to evaluate risks, but also to prevent resistant pathogens, as well as novel resistance genes, from reaching humans.

Reversing resistance: different routes and common themes across pathogens

Resistance spreads rapidly in pathogen or pest populations exposed to biocides, such as fungicides and antibiotics, and in many cases new biocides are in short supply. How can resistance be reversed in order to prolong the effectiveness of available treatments? Some key parameters affecting reversion of resistance are well known, such as the fitness cost of resistance. However, the population biological processes that actually cause resistance to persist or decline remain poorly characterized, and consequently our ability to manage reversion of resistance is limited. Where do susceptible genotypes that replace resistant lineages come from? What is the epidemiological scale of reversion? What information do we need to predict the mechanisms or likelihood of reversion? Here, we define some of the population biological processes that can drive reversion, using examples from a wide range of taxa and biocides. These processes differ primarily in the origin of revertant genotypes, but also in their sensitivity to factors such as coselection and compensatory evolution that can alter the rate of reversion, and the likelihood that resistance will re-emerge upon re-exposure to biocides. We therefore argue that discriminating among different types of reversion allows for better prediction of where resistance is most likely to persist.

Basic Sciences Fertilizing Clinical Microbiology and Infection Management

Basic sciences constitute the most abundant sources of creativity and innovation, as they are based on the passion of knowing. Basic knowledge, in close and fertile contact with medical and public health needs, produces distinct advancements in applied sciences. Basic sciences play the role of stem cells, providing material and semantics to construct differentiated tissues and organisms and enabling specialized functions and applications. However, eventually processes of "practice deconstruction" might reveal basic questions, as in de-differentiation of tissue cells. Basic sciences, microbiology, infectious diseases, and public health constitute an epistemological gradient that should also be an investigational continuum. The coexistence of all these interests and their cross-fertilization should be favored by interdisciplinary, integrative research organizations working simultaneously in the analytical and synthetic dimensions of scientific knowledge.

Dueling biological and social contagions

Numerous models explore how a wide variety of biological and social phenomena spread in social networks. However, these models implicitly assume that the spread of one phenomenon is not affected by the spread of another. Here, we develop a model of “dueling contagions”, with a particular illustration of a situation where one is biological (influenza) and the other is social (flu vaccination). We apply the model to unique time series data collected during the 2009 H1N1 epidemic that includes information about vaccination, flu, and face-to-face social networks. The results show that well-connected individuals are more likely to get vaccinated, as are people who are exposed to friends who get vaccinated or are exposed to friends who get the flu. Our dueling contagion model suggests that other epidemiological models may be dramatically underestimating the R₀ of contagions. It also suggests that the rate of vaccination contagion may be even more important than the biological contagion in determining the course of the disease. These results suggest that real world and online platforms that make it easier to see when friends have been vaccinated (personalized vaccination campaigns) and when they get the flu (personalized flu warnings) could have a large impact on reducing the severity of epidemics. They also suggest possible benefits from understanding the coevolution of many kinds of dueling contagions.

Using antibiotics responsibly: are we there yet?

Problems of antibiotic access and excess coexist in the world today and are compounded by rising rates of antibiotic resistance. We introduce two dimensions of responsibility to this context: responsible individual practices and a broad societal obligation centered on sustainability. Acting on these responsibilities requires recognizing the potential tensions between an individual optimum for antibiotic use and the societal optimum. We relate the tragedy of the commons metaphor to this situation to illustrate the complexity involved, and we draw on real-world experiences in Uganda, India, China and France. We conclude that we must form a global stewardship of antibiotics that can link access, innovation and conservation efforts across countries to ensure sustainable access to effective antibiotics for all who need them.

Mathematical modelling of antimicrobial resistance in agricultural waste highlights importance of gene transfer rate

Antimicrobial resistance is of global concern. Most antimicrobial use is in agriculture; manures and slurry are especially important because they contain a mix of bacteria, including potential pathogens, antimicrobial resistance genes and antimicrobials. In many countries, manures and slurry are stored, especially over winter, before spreading onto fields as organic fertilizer. Thus, these are a potential location for gene exchange and selection for resistance. We develop and analyse a mathematical model to quantify the spread of antimicrobial resistance in stored agricultural waste. We use parameters from a slurry tank on a UK dairy farm as an exemplar. We show that the spread of resistance depends in a subtle way on the rates of gene transfer and antibiotic inflow. If the gene transfer rate is high, then its reduction controls resistance, while cutting antibiotic inflow has little impact. If the gene transfer rate is low, then reducing antibiotic inflow controls resistance. Reducing length of storage can also control spread of resistance. Bacterial growth rate, fitness costs of carrying antimicrobial resistance and proportion of resistant bacteria in animal faeces have little impact on spread of resistance. Therefore, effective treatment strategies depend critically on knowledge of gene transfer rates.

The evolutionary dynamics of integrons in changing environments

Integrons are genetic elements that are common in bacteria and are hotspots for genome evolution. They facilitate the acquisition and reassembly of gene cassettes encoding a variety of functions, including drug resistance. Despite their importance in clinical settings, the selective forces responsible for the evolution and maintenance of integrons are poorly understood. We present a mathematical model of integron evolution within bacterial populations subject to fluctuating antibiotic exposures. Bacteria carrying a functional integrase that mediates reshuffling of cassette genes and thereby modulates gene expression patterns compete with bacteria without a functional integrase. Our results indicate that for a wide range of parameters, the functional integrase can be stably maintained in the population despite substantial fitness costs. This selective advantage arises because gene-cassette shuffling generates genetic diversity, thus enabling the population to respond rapidly to changing selective pressures. We also show that horizontal gene transfer promotes stable maintenance of the integrase and can also lead to de novo assembly of integrons. Our model generates testable predictions for integron evolution, including loss of functional integrases in stable environments and selection for intermediate gene-shuffling rates in changing environments. Our results highlight the need for experimental studies of integron population biology.