The global spread of drug-resistant influenza

Time-varying sensitivity analysis of an influenza model with interventions

We formulate an influenza model with treatment and vaccination. Both time invariant and time-dependent uncertainty analyses and sensitivity analysis of the model parameter values are carried out to understand the dependence of the reproduction numbers and model state variables on their components. Results show that the relationship between treatment and epidemic size is nonlinear and that there exists a critical threshold treatment rate under which treatment is beneficial. Sensitivity analysis suggests that the most significant parameters are those related to infection transmission, infectiousness, duration of infectiousness and waning immunity. Further, there are important instances when the relationship between some parameters and model outputs changes behavior from negatively to positively correlated or vice versa because all sensitivity indices, except [Formula: see text] are functions of other parameters and thus will change with the change in parameter values. For example, treatment helps to lower the epidemic size, but may then become a “source” of infection likely due to resistance de novo. This knowledge is critical for proper public health planning and guidance of control strategies.

Influenza polymerase inhibitor resistance: Assessment of the current state of the art - A report of the isirv Antiviral group

It is more than 20 years since the neuraminidase inhibitors, oseltamivir and zanamivir were approved for the treatment and prevention of influenza. Guidelines for global surveillance and methods for evaluating resistance were established initially by the Neuraminidase Inhibitor Susceptibility Network (NISN), which merged 10 years ago with the International Society for influenza and other Respiratory Virus Diseases (isirv) to become the isirv-Antiviral Group (isirv-AVG). With the ongoing development of new influenza polymerase inhibitors and recent approval of baloxavir marboxil, the isirv-AVG held a closed meeting in August 2019 to discuss the impact of resistance to these inhibitors. Following this meeting and review of the current literature, this article is intended to summarize current knowledge regarding the clinical impact of resistance to polymerase inhibitors and approaches for surveillance and methods for laboratory evaluation of resistance, both in vitro and in animal models. We highlight limitations and gaps in current knowledge and suggest some strategies for addressing these gaps, including the need for additional clinical studies of influenza antiviral drug combinations. Lessons learned from influenza resistance monitoring may also be helpful for establishing future drug susceptibility surveillance and testing for SARS-CoV-2.

COVID-19 mortality analysis from soft-data multivariate curve regression and machine learning

A multiple objective space-time forecasting approach is presented involving cyclical curve log-regression, and multivariate time series spatial residual correlation analysis. Specifically, the mean quadratic loss function is minimized in the framework of trigonometric regression. While, in our subsequent spatial residual correlation analysis, maximization of the likelihood allows us to compute the posterior mode in a Bayesian multivariate time series soft-data framework. The presented approach is applied to the analysis of COVID-19 mortality in the first wave affecting the Spanish Communities, since March 8, 2020 until May 13, 2020. An empirical comparative study with Machine Learning (ML) regression, based on random k-fold cross-validation, and bootstrapping confidence interval and probability density estimation, is carried out. This empirical analysis also investigates the performance of ML regression models in a hard- and soft-data frameworks. The results could be extrapolated to other counts, countries, and posterior COVID-19 waves.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s00477-021-02021-0.

The multifarious roles of heterogeneous ribonucleoprotein A1 in viral infections

Viruses are obligate parasites known to interact with a wide variety of host proteins at different stages of infection. Current antiviral treatments target viral proteins and may be compromised due to the emergence of drug resistant viral strains. Targeting viral-host interactions is now gaining recognition as an alternative approach against viral infections. Recent research has revealed that heterogeneous ribonucleoprotein A1, an RNA-binding protein, plays an essential functional and regulatory role in the life cycle of many viruses. In this review, we summarize the interactions between heterogeneous ribonucleoprotein A1 (hnRNPA1) and multiple viral proteins during the life cycle of RNA and DNA viruses. hnRNPA1 protein levels are modulated differently, in different viruses, which further dictates its stability, function, and intracellular localization. Multiple reports have emphasized that in Sindbis virus, enteroviruses, porcine endemic diarrhea virus, and rhinovirus infection, hnRNPA1 enhances viral replication and survival. However, in others like hepatitis C virus and human T-cell lymphotropic virus, it exerts a protective response. The involvement of hnRNPA1 in viral infections highlights its importance as a central regulator of host and viral gene expression. Understanding the nature of these interactions will increase our understanding of specific viral infections and pathogenesis and eventually aid in the development of novel and robust antiviral intervention strategies.

Population-level mathematical modeling of antimicrobial resistance: a systematic review

BACKGROUND

Mathematical transmission models are increasingly used to guide public health interventions for infectious diseases, particularly in the context of emerging pathogens; however, the contribution of modeling to the growing issue of antimicrobial resistance (AMR) remains unclear. Here, we systematically evaluate publications on population-level transmission models of AMR over a recent period (2006-2016) to gauge the state of research and identify gaps warranting further work.

METHODS

We performed a systematic literature search of relevant databases to identify transmission studies of AMR in viral, bacterial, and parasitic disease systems. We analyzed the temporal, geographic, and subject matter trends, described the predominant medical and behavioral interventions studied, and identified central findings relating to key pathogens.

RESULTS

We identified 273 modeling studies; the majority of which (> 70%) focused on 5 infectious diseases (human immunodeficiency virus (HIV), influenza virus, Plasmodium falciparum (malaria), Mycobacterium tuberculosis (TB), and methicillin-resistant Staphylococcus aureus (MRSA)). AMR studies of influenza and nosocomial pathogens were mainly set in industrialized nations, while HIV, TB, and malaria studies were heavily skewed towards developing countries. The majority of articles focused on AMR exclusively in humans (89%), either in community (58%) or healthcare (27%) settings. Model systems were largely compartmental (76%) and deterministic (66%). Only 43% of models were calibrated against epidemiological data, and few were validated against out-of-sample datasets (14%). The interventions considered were primarily the impact of different drug regimens, hygiene and infection control measures, screening, and diagnostics, while few studies addressed de novo resistance, vaccination strategies, economic, or behavioral changes to reduce antibiotic use in humans and animals.

CONCLUSIONS

The AMR modeling literature concentrates on disease systems where resistance has been long-established, while few studies pro-actively address recent rise in resistance in new pathogens or explore upstream strategies to reduce overall antibiotic consumption. Notable gaps include research on emerging resistance in Enterobacteriaceae and Neisseria gonorrhoeae; AMR transmission at the animal-human interface, particularly in agricultural and veterinary settings; transmission between hospitals and the community; the role of environmental factors in AMR transmission; and the potential of vaccines to combat AMR.

Influenza Virus Neuraminidase Structure and Functions

With the constant threat of emergence of a novel influenza virus pandemic, there must be continued evaluation of the molecular mechanisms that contribute to virulence. Although the influenza A virus surface glycoprotein neuraminidase (NA) has been studied mainly in the context of its role in viral release from cells, accumulating evidence suggests it plays an important, multifunctional role in virus infection and fitness. This review investigates the various structural features of NA, linking these with functional outcomes in viral replication. The contribution of evolving NA activity to viral attachment, entry and release of virions from infected cells, and maintenance of functional balance with the viral hemagglutinin are also discussed. Greater insight into the role of this important antiviral drug target is warranted.

Metabolic conversion of CI-1040 turns a cellular MEK-inhibitor into an antibacterial compound

Influenza virus (IV) infections cause severe respiratory illnesses that can be complicated by bacterial super-infections. Previously, we identified the cellular Raf-MEK-ERK cascade as a promising antiviral target. Inhibitors of MEK, such as CI-1040, showed potent antiviral activity. However, it remained unclear if this inhibitor and its active form, ATR-002, might sensitize host cells to either IV or secondary bacterial infections. To address these questions, we studied the anti-pathogen activity of ATR-002 in comparison to CI-1040, particularly, its impact on Staphylococcus aureus (S. aureus), which is a major cause of IV super-infections. We analysed IV and S. aureus titres in vitro during super-infection in the presence and absence of the drugs and characterized the direct impact of ATR-002 on bacterial growth and phenotypic changes. Importantly, neither CI-1040 nor ATR-002 treatment led to increased bacterial titres during super-infection, indicating that the drug does not sensitize cells for bacterial infection. In contrast, we rather observed reduced bacterial titres in presence of ATR-002. Surprisingly, ATR-002 also led to reduced bacterial growth in suspension cultures, reduced stress- and antibiotic tolerance without resistance induction. Our data identified for the first time that a particular MEK-inhibitor metabolite exhibits direct antibacterial activity, which is likely due to interference with the bacterial PknB kinase/Stp phosphatase signalling system.

Temporally Varying Relative Risks for Infectious Diseases: Implications for Infectious Disease Control

Risks for disease in some population groups relative to others (relative risks) are usually considered to be consistent over time, although they are often modified by other, nontemporal factors. For infectious diseases, in which overall incidence often varies substantially over time, the patterns of temporal changes in relative risks can inform our understanding of basic epidemiologic questions. For example, recent studies suggest that temporal changes in relative risks of infection over the course of an epidemic cycle can both be used to identify population groups that drive infectious disease outbreaks, and help elucidate differences in the effect of vaccination against infection (that is relevant to transmission control) compared with its effect against disease episodes (that reflects individual protection). Patterns of change in the age groups affected over the course of seasonal outbreaks can provide clues to the types of pathogens that could be responsible for diseases for which an infectious cause is suspected. Changing apparent efficacy of vaccines during trials may provide clues to the vaccine's mode of action and/or indicate risk heterogeneity in the trial population. Declining importance of unusual behavioral risk factors may be a signal of increased local transmission of an infection. We review these developments and the related public health implications.

Modelling the emergence of influenza drug resistance: The roles of surface proteins, the immune response and antiviral mechanisms

The emergence of influenza drug resistance has become of particular interest as current planning for an influenza pandemic involves using massive amounts of antiviral drugs. We use semi-stochastic simulations to examine the emergence of drug resistant mutants during the course of a single infection within a patient in the presence and absence of antiviral therapy. We specifically examine three factors and their effect on the emergence of drug-resistant mutants: antiviral mechanism, the immune response, and surface proteins. We find that adamantanes, because they act at the start of the replication cycle to prevent infection, are less likely to produce drug-resistant mutants than NAIs, which act at the end of the replication cycle. A mismatch between surface proteins and internal RNA results in drug-resistant mutants being less likely to emerge, and emerging later in the infection because the mismatch gives antivirals a second chance to prevent propagation of the mutation. The immune response subdues slow growing infections, further reducing the probability that a drug resistant mutant will emerge and yield a drug-resistant infection. These findings improve our understanding of the factors that contribute to the emergence of drug resistance during the course of a single influenza infection.

Virus evolution and transmission in an ever more connected world

The frequency and global impact of infectious disease outbreaks, particularly those caused by emerging viruses, demonstrate the need for a better understanding of how spatial ecology and pathogen evolution jointly shape epidemic dynamics. Advances in computational techniques and the increasing availability of genetic and geospatial data are helping to address this problem, particularly when both information sources are combined. Here, we review research at the intersection of evolutionary biology, human geography and epidemiology that is working towards an integrated view of spatial incidence, host mobility and viral genetic diversity. We first discuss how empirical studies have combined viral spatial and genetic data, focusing particularly on the contribution of evolutionary analyses to epidemiology and disease control. Second, we explore the interplay between virus evolution and global dispersal in more depth for two pathogens: human influenza A virus and chikungunya virus. We discuss the opportunities for future research arising from new analyses of human transportation and trade networks, as well as the associated challenges in accessing and sharing relevant spatial and genetic data.

Antiviral Resistance in Influenza Viruses: Clinical and Epidemiological Aspects

There are three classes of antiviral drugs approved for the treatment of influenza: the M2 ion channel inhibitors (amantadine, rimantadine), neuraminidase (NA) inhibitors (laninamivir, oseltamivir, peramivir, zanamivir), and the protease inhibitor (favipiravir); some of the agents are only available in selected countries [1, 2]. These agents are effective at treating the signs and symptoms of influenza in patients infected with susceptible viruses. Clinical failure has been demonstrated in patients infected with viruses with primary resistance, i.e., antivirals can be present in the virus initially infecting the patient, or resistance may emerge during the course of therapy [3–5]. NA inhibitors are active against all nine NA subtypes recognized in nature [6], including highly pathogenic avian influenza A/H5N1 and recent low-pathogenic avian influenza A/H7N9 viruses [7]. Since seasonal influenza is usually an acute, self-limited illness in which viral clearance usually occurs rapidly due to innate and adaptive host immune responses, the emergence of drug-resistant variants would be anticipated to have limited effect on clinical recovery in otherwise healthy patients, as has been demonstrated clinically [3, 8, 9]. Unfortunately, immunocompromised or immunologically naïve hosts, such as young children and infants or those exposed to novel strains, are more likely to have mutations that confer resistance emergence during therapy; such resistant variants may also result in clinically significant adverse outcomes [10–13].

Monitoring the fitness of antiviral-resistant influenza strains during an epidemic: a mathematical modelling study

BACKGROUND

Antivirals (eg, oseltamivir) are important for mitigating influenza epidemics. In 2007, an oseltamivir-resistant influenza seasonal A H1N1 strain emerged and spread to global fixation within 1 year. This event showed that antiviral-resistant (AVR) strains can be intrinsically more transmissible than their contemporaneous antiviral-sensitive (AVS) counterpart. Surveillance of AVR fitness is therefore essential. Our objective was to develop a simple method for estimating AVR fitness from surveillance data.

METHODS

We defined the fitness of AVR strains as their reproductive number relative to their co-circulating AVS counterparts. We developed a simple method for real-time estimation of AVR fitness from surveillance data. This method requires only information on generation time without other specific details regarding transmission dynamics. We first used simulations to validate this method by showing that it yields unbiased and robust fitness estimates in most epidemic scenarios. We then applied this method to two retrospective case studies and one hypothetical case study.

FINDINGS

We estimated that the oseltamivir-resistant A H1N1 strain that emerged in 2007 was 4% (95% credible interval [CrI] 3-5) more transmissible than its oseltamivir-sensitive predecessor and the oseltamivir-resistant pandemic A H1N1 strain that emerged and circulated in Japan during 2013-14 was 24% (95% CrI 17-30) less transmissible than its oseltamivir-sensitive counterpart. We show that in the event of large-scale antiviral interventions during a pandemic with co-circulation of AVS and AVR strains, our method can be used to inform optimal use of antivirals by monitoring intrinsic AVR fitness and drug pressure on the AVS strain.

INTERPRETATION

We developed a simple method that can be easily integrated into contemporary influenza surveillance systems to provide reliable estimates of AVR fitness in real time.

FUNDING

Research Fund for the Control of Infectious Disease (09080792) and a commissioned grant from the Health and Medical Research Fund from the Government of the Hong Kong Special Administrative Region, Harvard Center for Communicable Disease Dynamics from the National Institute of General Medical Sciences (grant number U54 GM088558), Area of Excellence Scheme of the Hong Kong University Grants Committee (grant number AoE/M-12/06).

Emergence and spread of drug resistant influenza: A two-population game theoretical model

Background

The potential for emergence of antiviral drug resistance during influenza pandemics has raised great concern for public health. Widespread use of antiviral drugs is a significant factor in producing resistant strains. Recent studies show that some influenza viruses may gain antiviral drug resistance without a fitness penalty. This creates the possibility of strategic interaction between populations considering antiviral drug use strategies.

Methods

To explain why, we develop and analyze a classical 2-player game theoretical model where each player chooses from a range of possible rates of antiviral drug use, and payoffs are derived as a function of final size of epidemic with the regular and mutant strain. Final sizes are derived from a stochastic compartmental epidemic model that captures transmission within each population and between populations, and the stochastic emergence of antiviral drug resistance. High treatment levels not only increase the spread of the resistant strain in the subject population but also affect the other population by increasing the density of the resistant strain infectious individuals due to travel between populations.

Results

We found two Nash equilibria where both populations treat at a high rate, or both treat at a low rate. Hence the game theoretical analysis predicts that populations will not choose different treatment strategies than other populations, under these assumptions. The populations may choose to cooperate by maintaining a low treatment rate that does not increase the incidence of mutant strain infections or cause case importations to the other population. Alternatively, if one population is treating at a high rate, this will generate a large number of mutant infections that spread to the other population, in turn incentivizing that population to also treat at a high rate. The prediction of two separate Nash equilibria is robust to the mutation rate and the effectiveness of the drug in preventing transmission, but it is sensitive to the volume of travel between the two populations.

Conclusions

Model-based evaluations of antiviral influenza drug use during a pandemic usually consider populations in isolation from one another, but our results show that strategic interactions could strongly influence a population's choice of antiviral drug use policy. Furthermore, the high treatment rate Nash equilibrium has the potential to become socially suboptimal (i.e. non-Pareto optimal) under model assumptions that might apply under other conditions. Because of the need for players to coordinate their actions, we conclude that communication and coordination between jurisdictions during influenza pandemics is a priority, especially for influenza strains that do not evolve a fitness penalty under antiviral drug resistance.

Transmission in the guinea pig model

The ability of an influenza virus to transmit efficiently from human-to-human is a major factor in determining the epidemiological impact of that strain. The use of a relevant animal model to identify viral determinants of transmission, as well as host and environmental factors affecting transmission efficiency, is therefore critical for public health. The characterization of newly emerging influenza viruses in terms of their potential to transmit in a mammalian host is furthermore an important part of pandemic risk assessment. For these reasons, a guinea pig model of influenza virus transmission was developed in 2006. The guinea pig provides an important alternative to preexisting models for influenza. Most influenza viruses do not readily transmit among mice. Ferrets, while highly relevant, are expensive and can be difficult to obtain in high numbers. Moreover, it is generally accepted that efforts to accurately model human disease are strengthened by the use of multiple animal species. Herein, we provide an overview of influenza virus infectivity, growth, and transmission in the guinea pig and highlight knowledge gained on the topic of influenza virus transmission using the guinea pig model.

Preclinical activity of VX-787, a first-in-class, orally bioavailable inhibitor of the influenza virus polymerase PB2 subunit

VX-787 is a novel inhibitor of influenza virus replication that blocks the PB2 cap-snatching activity of the influenza viral polymerase complex. Viral genetics and X-ray crystallography studies provide support for the idea that VX-787 occupies the 7-methyl GTP (m(7)GTP) cap-binding site of PB2. VX-787 binds the cap-binding domain of the PB2 subunit with a KD (dissociation constant) of 24 nM as determined by isothermal titration calorimetry (ITC). The cell-based EC50 (the concentration of compound that ensures 50% cell viability of an uninfected control) for VX-787 is 1.6 nM in a cytopathic effect (CPE) assay, with a similar EC50 in a viral RNA replication assay. VX-787 is active against a diverse panel of influenza A virus strains, including H1N1pdm09 and H5N1 strains, as well as strains with reduced susceptibility to neuraminidase inhibitors (NAIs). VX-787 was highly efficacious in both prophylaxis and treatment models of mouse influenza and was superior to the neuraminidase inhibitor, oseltamivir, including in delayed-start-to-treat experiments, with 100% survival at up to 96 h postinfection and partial survival in groups where the initiation of therapy was delayed up to 120 h postinfection. At different doses, VX-787 showed a 1-log to >5-log reduction in viral load (relative to vehicle controls) in mouse lungs. Overall, these favorable findings validate the PB2 subunit of the viral polymerase as a drug target for influenza therapy and support the continued development of VX-787 as a novel antiviral agent for the treatment of influenza infection.

Andrographolide as an anti-H1N1 drug and the mechanism related to retinoic acid-inducible gene-I-like receptors signaling pathway

OBJECTIVE

To observe the anti-virus effects of andrographolide (AD) on the retinoic acid-inducible gene-I (RIG-I)-like receptors (RLRs) signaling pathway when immunological cells were infected with H1N1.

METHODS

Leukomonocyte was obtained from umbilical cord blood by Ficoll density gradient centrifugation, and immunological cells were harvested after cytokines stimulation. Virus infected cell model was established by H1N1 co-cultured with normal human bronchial epithelial cell line (16HBE). The optimal concentration of AD was defined by methyl-thiazolyl-tetrazolium (MTT) assay. After the virus infected cell model was established, AD was added into the medium as a treatment intervention. After 24-h co-culture, cell supernatant was collected for interferon gamma (IFN-γ) and interleukin-4 (IL-4) enzyme-linked immunosorbent assay (ELISA) detection while immunological cells for real-time polymerase chain reaction (RT-PCR).

RESULTS

The optimal concentration of AD for anti-virus effect was 250 μg/mL. IL-4 and IFN-γ in the supernatant and mRNA levels in RLRs pathway increased when cells was infected by virus, RIG-I, IFN-β promoter stimulator-1 (IPS-1), interferon regulatory factor (IRF)-7, IRF-3 and nuclear transcription factor κB (NF-κB) mRNA levels increased significantly (P<0.05). When AD was added into co-culture medium, the levels of IL-4 and IFN-γ were lower than those in the non-interference groups and the mRNA expression levels decreased, RIG-I, IPS-1, IRF-7, IRF-3 and NF-κB decreased significantly in each group with significant statistic differences (P<0.05).

CONCLUSIONS

The RLRs mediated viral recognition provided a potential molecular target for acute viral infections and andrographolide could ameliorate H1N1 virus-induced cell mortality. And the antiviral effects might be related to its inhibition of viral-induced activation of the RLRs signaling pathway.

Chimerization and characterization of a monoclonal antibody with potent neutralizing activity across multiple influenza A H5N1 clades

The persistent evolution and circulation of highly pathogenic avian influenza H5N1 viruses pose a serious threat to global heath and hamper pandemic preparedness through conventional vaccine strategies. Combination passive immunotherapy using non-competing neutralizing antibodies has been proposed as a viable alternative to provide broad protection against drift variants. This necessitates the pre-pandemic production and characterization of potently neutralizing monoclonal antibodies (MAbs). One such antibody, MAb 9F4 was shown to provide heterologous protection against multiple H5N1 clade viruses, including one of the recently designated subclades, namely 2.3.4, through binding to a novel epitope, warranting its further development and characterization as a therapeutic candidate. In this study, the conversion of MAb 9F4 from mouse IgG2b to mouse-human chimeric (xi) IgG1 and IgA1 was achieved. These chimeric MAb versions were found to retain high degrees of binding and neutralizing activity against H5N1. The demonstration that xi-IgA1-9F4 retains a fairly high level of neutralizing activity, which is ∼10-fold lower than the corresponding xi-IgG1 isotype, suggests that this MAb could be further developed and engineered for intranasal administration.

Ethical alternatives to experiments with novel potential pandemic pathogens

Please see later in the article for the Editors' Summary

Animal models for influenza virus pathogenesis, transmission, and immunology

In humans, infection with an influenza A or B virus manifests typically as an acute and self-limited upper respiratory tract illness characterized by fever, cough, sore throat, and malaise. However, influenza can present along a broad spectrum of disease, ranging from sub-clinical or even asymptomatic infection to a severe primary viral pneumonia requiring advanced medical supportive care. Disease severity depends upon the virulence of the influenza virus strain and the immune competence and previous influenza exposures of the patient. Animal models are used in influenza research not only to elucidate the viral and host factors that affect influenza disease outcomes in and spread among susceptible hosts, but also to evaluate interventions designed to prevent or reduce influenza morbidity and mortality in man. This review will focus on the three animal models currently used most frequently in influenza virus research - mice, ferrets, and guinea pigs - and discuss the advantages and disadvantages of each.

Targeting imperfect vaccines against drug-resistance determinants: a strategy for countering the rise of drug resistance

The growing prevalence of antimicrobial resistance in major pathogens is outpacing discovery of new antimicrobial classes. Vaccines mitigate the effect of antimicrobial resistance by reducing the need for treatment, but vaccines for many drug-resistant pathogens remain undiscovered or have limited efficacy, in part because some vaccines selectively favor pathogen strains that escape vaccine-induced immunity. A strain with even a modest advantage in vaccinated hosts can have high fitness in a population with high vaccine coverage, which can offset a strong selection pressure such as antimicrobial use that occurs in a small fraction of hosts. We propose a strategy to target vaccines against drug-resistant pathogens, by using resistance-conferring proteins as antigens in multicomponent vaccines. Resistance determinants may be weakly immunogenic, offering only modest specific protection against resistant strains. Therefore, we assess here how varying the specific efficacy of the vaccine against resistant strains would affect the proportion of drug-resistant vs. -sensitive strains population-wide for three pathogens--Streptococcus pneumoniae, Staphylococcus aureus, and influenza virus--in which drug resistance is a problem. Notably, if such vaccines confer even slightly higher protection (additional efficacy between 1% and 8%) against resistant variants than sensitive ones, they may be an effective tool in controlling the rise of resistant strains, given current levels of use for many antimicrobial agents. We show that the population-wide impact of such vaccines depends on the additional effect on resistant strains and on the overall effect (against all strains). Resistance-conferring accessory gene products or resistant alleles of essential genes could be valuable as components of vaccines even if their specific protective effect is weak.

Modeling the global transmission of antiviral-resistant influenza viruses

BACKGROUND

The mutations that confer resistance to antiviral agents are thought to be detrimental, or at best neutral, to influenza virus fitness. The fact that resistant influenza strains can circulate and sometimes replace sensitive strains is of great public health concern.

OBJECTIVES

We used mathematical modeling to test various hypotheses about the transmission of antiviral-resistant influenza viruses by comparing the model's output with the observed rise in antiviral resistance of seasonal A(H1N1) influenza viruses between 2006 and 2009.

METHODS

We developed a mathematical model of the transmission of influenza among 321 cities around the globe. In the model, influenza strains resistant to antiviral agents competed with sensitive strains.

RESULTS AND CONCLUSIONS

We found that a resistant strain of influenza could not displace the sensitive strain as rapidly as has been observed unless it was more transmissible than the sensitive strain in the general population. We believe that an antiviral-resistant strain displaced the antiviral-sensitive seasonal A(H1N1) virus by hitchhiking on an escape mutation. Because of the complex global patterns of influenza circulation, tracking the emergence and spread of antiviral resistance must be a coordinated global effort.

Viral phylodynamics

Viral phylodynamics is defined as the study of how epidemiological, immunological, and evolutionary processes act and potentially interact to shape viralphylogenies. Since the coining of the term in 2004, research on viral phylodynamics has focused on transmission dynamics in an effort to shed light on how these dynamics impact viral genetic variation. Transmission dynamics can be considered at the level of cells within an infected host, individual hosts within a population, or entire populations of hosts. Many viruses, especially RNA viruses, rapidly accumulate genetic variation because of short generation times and high mutation rates. Patterns of viral genetic variation are therefore heavily influenced by how quickly transmission occurs and by which entities transmit to one another. Patterns of viral genetic variation will also be affected by selection acting on viral phenotypes. Although viruses can differ with respect to many phenotypes, phylodynamic studies have to date tended to focus on a limited number of viral phenotypes. These include virulence phenotypes, phenotypes associated with viral transmissibility, cell or tissue tropism phenotypes, and antigenic phenotypes that can facilitate escape from host immunity. Due to the impact that transmission dynamics and selection can have on viral genetic variation, viral phylogenies can therefore be used to investigate important epidemiological, immunological, and evolutionary processes, such as epidemic spread[2], spatio-temporal dynamics including metapopulation dynamics[3], zoonotic transmission, tissue tropism[4], and antigenic drift[5]. The quantitative investigation of these processes through the consideration of viral phylogenies is the central aim of viral phylodynamics.

Influenza virus resistance to antiviral therapy

Antiviral drugs for influenza therapy and prophylaxis are either of the adamantane or neuraminidase inhibitor (NAI) class. However, the NAIs are mainly prescribed nowadays, because of widespread adamantane resistance among influenza A viruses and ineffectiveness of adamantanes against influenza B. Emergence and spread of NAI resistance would further limit our therapeutic options. Taking into account the previous spread of oseltamivir-resistant viruses during the 2007/2008 season preceding the last pandemic, emergence of yet another naturally NAI-resistant influenza virus may not be an unlikely event. This previous incident also underlines the importance of resistance surveillance and asks for a better understanding of the mechanisms underlying primary resistance development. We provide an overview of the major influenza antiviral resistance mechanisms and future therapies for influenza. Here, we call for a better understanding of the effect of virus mutations upon antiviral treatment and for a tailored antiviral approach to severe influenza virus infections.

Drivers and consequences of influenza antiviral resistant-strain emergence in a capacity-constrained pandemic response

Antiviral agents remain a key component of most pandemic influenza preparedness plans, but there is considerable uncertainty regarding their optimal use. In particular, concerns exist regarding the likelihood of wide-scale distribution to select for drug-resistant variants. We used a model that considers the influence of logistical constraints on diagnosis and drug delivery to consider achievable 'reach' of alternative antiviral intervention strategies targeted at cases of varying severity, with or without pre-exposure prophylaxis of contacts. To identify key drivers of epidemic mitigation and resistance emergence, we used Latin hypercube sampling to explore plausible ranges of parameters describing characteristics of wild type and resistant viruses, along with intervention efficacy, target coverage and distribution capacity. Within our model framework, 'real world' constraints substantially reduced achievable drug coverage below stated targets as the epidemic progressed. In consequence, predictions of both intervention impact and selection for resistance were more modest than earlier work that did not consider such limitations. Definitive containment of transmission was unlikely but, where observed, achieved through early liberal post-exposure prophylaxis of known contacts of treated cases. Predictors of resistant strain dominance were high intrinsic fitness relative to the wild type virus, and early emergence in the course of the epidemic into a largely susceptible population, even when drug use was restricted to severe case treatment. Our work demonstrates the importance of consideration of 'real world' constraints in scenario analysis modeling, and highlights the utility of models to guide surveillance activities in preparedness and response.

Enhanced mammalian transmissibility of seasonal influenza A/H1N1 viruses encoding an oseltamivir-resistant neuraminidase

Between 2007 and 2009, oseltamivir resistance developed among seasonal influenza A/H1N1 (sH1N1) virus isolates at an exponential rate, without a corresponding increase in oseltamivir usage. We hypothesized that the oseltamivir-resistant neuraminidase (NA), in addition to being relatively insusceptible to the antiviral effect of oseltamivir, might confer an additional fitness advantage on these viruses by enhancing their transmission efficiency among humans. Here we demonstrate that an oseltamivir-resistant clinical isolate, an A/Brisbane/59/2007(H1N1)-like virus isolated in New York State in 2008, transmits more efficiently among guinea pigs than does a highly similar, contemporaneous oseltamivir-sensitive isolate. With reverse genetics reassortants and point mutants of the two clinical isolates, we further show that expression of the oseltamivir-resistant NA in the context of viral proteins from the oseltamivir-sensitive virus (a 7:1 reassortant) is sufficient to enhance transmissibility. In the guinea pig model, the NA is the critical determinant of transmission efficiency between oseltamivir-sensitive and -resistant Brisbane/59-like sH1N1 viruses, independent of concurrent drift mutations that occurred in other gene products. Our data suggest that the oseltamivir-resistant NA (specifically, one or both of the companion mutations, H275Y and D354G) may have allowed resistant Brisbane/59-like viruses to outtransmit sensitive isolates. These data provide in vivo evidence of an evolutionary mechanism that would explain the rapidity with which oseltamivir resistance achieved fixation among sH1N1 isolates in the human reservoir.

Efficient transmission of pandemic H1N1 influenza viruses with high-level oseltamivir resistance

The limited availability of approved influenza virus antivirals highlights the importance of studying the fitness and transmissibility of drug-resistant viruses. S247N is a novel, naturally occurring N1 neuraminidase mutation that reduces oseltamivir sensitivity and greatly potentiates oseltamivir resistance in the context of the H275Y mutation. Here we show that highly oseltamivir-resistant viruses containing both the S247N and H275Y mutations transmit efficiently in the guinea pig transmission model.