Emergence of drug resistance: implications for antiviral control of pandemic influenza

Given the danger of an unprecedented spread of the highly pathogenic avian influenza strain H5N1 in humans, and great challenges to the development of an effective influenza vaccine, antiviral drugs will probably play a pivotal role in combating a novel pandemic strain. A critical limitation to the use of these drugs is the evolution of highly transmissible drug-resistant viral mutants. Here, we develop a mathematical model to evaluate the potential impact of an antiviral treatment strategy on the emergence of drug resistance and containment of a pandemic. The results show that elimination of the wild-type strain depends crucially on both the early onset of treatment in indexed cases and population-level treatment. Given the probable delay of 0.5-1 day in seeking healthcare and therefore initiating therapy, the findings indicate that a single strategy of antiviral treatment will be unsuccessful at controlling the spread of disease if the reproduction number of the wild-type strain (R0s) exceeds 1.4. We demonstrate the possible occurrence of a self-sustaining epidemic of resistant strain, in terms of its transmission fitness relative to the wild-type, and the reproduction number R0s. Considering reproduction numbers estimated for the past three pandemics, the findings suggest that an uncontrollable pandemic is likely to occur if resistant viruses with relative transmission fitness above 0.4 emerge. While an antiviral strategy is crucial for containing a pandemic, its effectiveness depends critically on timely and strategic use of drugs.     

Prophylaxis or treatment? Optimal use of an antiviral stockpile during an influenza pandemic

We introduce a novel mathematical model that effectively incorporates contact tracing in a realistic distribution mechanism for antiviral drugs in an influenza pandemic scenario. A strategy focused on targeted provision of post-exposure prophylaxis, rather than treatment, will provide the greatest chance of minimising the impact of an influenza pandemic. Targeted post-exposure prophylaxis delays the onset of the pandemic and for a wide range of parameter values, a delay of the order of 6-18 months may be achievable. This may provide enough time to develop and distribute a vaccine. In contrast, a treatment based strategy typically does not delay the onset of a pandemic by an appreciable amount and, in general, is not capable of significantly reducing the attack rate from baseline.     

Using a Dynamic Model to Consider Optimal Antiviral Stockpile Size in the Face of Pandemic Influenza Uncertainty

Background

The Canadian National Antiviral Stockpile (NAS) contains treatment for 17.5% of Canadians. This assumes no concurrent intervention strategies and no wastage due to non-influenza respiratory infections. A dynamic model can provide a mechanism to consider complex scenarios to support decisions regarding the optimal NAS size under uncertainty.

Methods

We developed a dynamic model for pandemic influenza in Canada that is structured by age and risk to calculate the demand for antivirals to treat persons with pandemic influenza under a wide-range of scenarios that incorporated transmission dynamics, disease severity, and intervention strategies. The anticipated per capita number of acute respiratory infections due to viruses other than influenza was estimated for the full pandemic period from surveys based on criteria to identify potential respiratory infections.

Results

Our results demonstrate that up to two thirds of the population could develop respiratory symptoms as a result of infection with a pandemic strain. In the case of perfect antiviral allocation, up to 39.8% of the population could request antiviral treatment. As transmission dynamics, severity and timing of the emergence of a novel influenza strain are unknown, the sensitivity analysis produced considerable variation in potential demand (median: 11%, IQR: 2–21%). If the next pandemic strain emerges in late spring or summer and a vaccine is available before the anticipated fall wave, the median prediction was reduced to 6% and IQR to 0.7–14%. Under the strategy of offering empirical treatment to all patients with influenza like symptoms who present for care, demand could increase to between 65 and 144%.

Conclusions

The demand for antivirals during a pandemic is uncertain. Unless an accurate, timely and cost-effective test is available to identify influenza cases, demand for antivirals from persons infected with other respiratory viruses will be substantial and have a significant impact on the NAS.     

Optimizing tactics for use of the U.S. antiviral strategic national stockpile for pandemic influenza

In 2009, public health agencies across the globe worked to mitigate the impact of the swine-origin influenza A (pH1N1) virus. These efforts included intensified surveillance, social distancing, hygiene measures, and the targeted use of antiviral medications to prevent infection (prophylaxis). In addition, aggressive antiviral treatment was recommended for certain patient subgroups to reduce the severity and duration of symptoms. To assist States and other localities meet these needs, the U.S. Government distributed a quarter of the antiviral medications in the Strategic National Stockpile within weeks of the pandemic's start. However, there are no quantitative models guiding the geo-temporal distribution of the remainder of the Stockpile in relation to pandemic spread or severity. We present a tactical optimization model for distributing this stockpile for treatment of infected cases during the early stages of a pandemic like 2009 pH1N1, prior to the wide availability of a strain-specific vaccine. Our optimization method efficiently searches large sets of intervention strategies applied to a stochastic network model of pandemic influenza transmission within and among U.S. cities. The resulting optimized strategies depend on the transmissability of the virus and postulated rates of antiviral uptake and wastage (through misallocation or loss). Our results suggest that an aggressive community-based antiviral treatment strategy involving early, widespread, pro-rata distribution of antivirals to States can contribute to slowing the transmission of mildly transmissible strains, like pH1N1. For more highly transmissible strains, outcomes of antiviral use are more heavily impacted by choice of distribution intervals, quantities per shipment, and timing of shipments in relation to pandemic spread. This study supports previous modeling results suggesting that appropriate antiviral treatment may be an effective mitigation strategy during the early stages of future influenza pandemics, increasing the need for systematic efforts to optimize distribution strategies and provide tactical guidance for public health policy-makers.     

Antiviral resistance and the control of pandemic influenza: the roles of stochasticity, evolution and model details

Antiviral drugs, most notably the neuraminidase inhibitors, are an important component of control strategies aimed to prevent or limit any future influenza pandemic. The potential large-scale use of antiviral drugs brings with it the danger of drug resistance evolution. A number of recent studies have shown that the emergence of drug-resistant influenza could undermine the usefulness of antiviral drugs for the control of an epidemic or pandemic outbreak. While these studies have provided important insights, the inherently stochastic nature of resistance generation and spread, as well as the potential for ongoing evolution of the resistant strain have not been fully addressed. Here, we study a stochastic model of drug resistance emergence and consecutive evolution of the resistant strain in response to antiviral control during an influenza pandemic. We find that taking into consideration the ongoing evolution of the resistant strain does not increase the probability of resistance emergence; however, it increases the total number of infecteds if a resistant outbreak occurs. Our study further shows that taking stochasticity into account leads to results that can differ from deterministic models. Specifically, we find that rapid and strong control cannot only contain a drug sensitive outbreak, it can also prevent a resistant outbreak from occurring. We find that the best control strategy is early intervention heavily based on prophylaxis at a level that leads to outbreak containment. If containment is not possible, mitigation works best at intermediate levels of antiviral control. Finally, we show that the results are not very sensitive to the way resistance generation is modeled.     

Can Antiviral Drugs Contain Pandemic Influenza Transmission?

Antiviral drugs dispensed during the 2009 influenza pandemic generally failed to contain transmission. This poses the question of whether preparedness for a future pandemic should include plans to use antiviral drugs to mitigate transmission.Simulations using a standard transmission model that allows for infected arrivals and delayed vaccination show that attempts to contain transmission require relatively few antiviral doses. In contrast, persistent use of antiviral drugs when the reproduction number remains above 1 use very many doses and are unlikely to reduce the eventual attack rate appreciably unless the stockpile is very large. A second model, in which the community has a household structure, shows that the effectiveness of a strategy of dispensing antiviral drugs to infected households decreases rapidly with time delays in dispensing the antivirals. Using characteristics of past pandemics it is estimated that at least 80% of primary household cases must present upon show of symptoms to have a chance of containing transmission by dispensing antiviral drugs to households. To determine data needs, household outbreaks were simulated with 50% receiving antiviral drugs early and 50% receiving antiviral drugs late. A test to compare the size of household outbreaks indicates that at least 100-200 household outbreaks need to be monitored to find evidence that antiviral drugs can mitigate transmission of the newly emerged virus.Use of antiviral drugs in an early attempt to contain transmission should be part of preparedness plans for a future influenza pandemic. Data on the incidence of the first 350 cases and the eventual attack rates of the first 200 hundred household outbreaks should be used to estimate the initial reproduction number R and the effectiveness of antiviral drugs to mitigate transmission. Use of antiviral drugs to mitigate general transmission should cease if these estimates indicate that containment of transmission is unlikely.     

Optimal control for pandemic influenza: The role of limited antiviral treatment and isolation

The implementation of optimal control strategies involving antiviral treatment and/or isolation measures can reduce significantly the number of clinical cases of influenza. Pandemic-level control measures must be carefully assessed specially in resource-limited situations. A model for the transmission dynamics of influenza is used to evaluate the impact of isolation and/or antiviral drug delivery measures during an influenza pandemic. Five pre-selected control strategies involving antiviral treatment and isolation are tested under the “unlimited” resource assumption followed by an exploration of the impact of these “optimal” policies when resources are limited in the context of a 1918-type influenza pandemic scenario. The implementation of antiviral treatment at the start of a pandemic tends to reduce the magnitude of epidemic peaks, spreading the maximal impact of an outbreak over an extended window in time. Hence, the controls’ timing and intensity can reduce the pressures placed on the health care infrastructure by a pandemic reducing the stress put on the system during epidemic peaks. The role of isolation strategies is highlighted in this study particularly when access to antiviral resources is limited.     

Correlates of severe disease in patients with 2009 pandemic influenza (H1N1) virus infection

Background

In the context of 2009 pandemic influenza (H1N1) virus infection (pandemic H1N1 influenza), identifying correlates of the severity of disease is critical to guiding the implementation of antiviral strategies, prioritization of vaccination efforts and planning of health infrastructure. The objective of this study was to identify factors correlated with severity of disease in confirmed cases of pandemic H1N1 influenza.

Methods

This cumulative case–control study included all laboratory-confirmed cases of pandemic H1N1 influenza among residents of the province of Manitoba, Canada, for whom the final location of treatment was known. Severe cases were defined by admission to a provincial intensive care unit (ICU). Factors associated with severe disease necessitating admission to the ICU were determined by comparing ICU cases with two control groups: patients who were admitted to hospital but not to an ICU and those who remained in the community.

Results

As of Sept. 5, 2009, there had been 795 confirmed cases of pandemic H1N1 influenza in Manitoba for which the final treatment location could be determined. The mean age of individuals with laboratory-confirmed infection was 25.3 (standard deviation 18.8) years. More than half of the patients (417 or 52%) were female, and 215 (37%) of 588 confirmed infections for which ethnicity was known occurred in First Nations residents. The proportion of First Nations residents increased with increasing severity of disease (116 [28%] of 410 community cases, 74 [54%] of 136 admitted to hospital and 25 [60%] of 42 admitted to an ICU; p < 0.001), as did the presence of an underlying comorbidity (201 [35%] of 569 community cases, 103 [57%] of 181 admitted to hospital and 34 [76%] of 45 admitted to an ICU; p < 0.001). The median interval from onset of symptoms to initiation of antiviral therapy was 2 days (interquartile range, IQR 1–3) for community cases, 4 days (IQR 2–6) for patients admitted to hospital and 6 days (IQR 4–9) for those admitted to an ICU (p < 0.001). In a multivariable logistic model, the interval from onset of symptoms to initiation of antiviral therapy (odds ratio [OR] 8.24, 95% confidence interval [CI] 2.82–24.1), First Nations ethnicity (OR 6.52, 95% CI 2.04–20.8) and presence of an underlying comorbidity (OR 3.19, 95% CI 1.07–9.52) were associated with increased odds of admission to the ICU (i.e., severe disease) relative to community cases. In an analysis of ICU cases compared with patients admitted to hospital, First Nations ethnicity (OR 3.23, 95% CI 1.04–10.1) was associated with increased severity of disease.

Interpretation

Severe pandemic H1N1 influenza necessitating admission to the ICU was associated with a longer interval from onset of symptoms to treatment with antiviral therapy and with the presence of an underlying comorbidity. First Nations ethnicity appeared to be an independent determinant of severe infection. Despite these associations, the cause and outcomes of pandemic HINI influenza may involve many complex and interrelated factors, all of which require further research and analysis.In April 2009, Canada’s first wave of pandemic influenza (H1N1) virus infections (pandemic H1N1 influenza) began. The highest burden of severe illness in Canada occurred in the province of Manitoba, where 45 Manitobans and 9 out-of-province patients were admitted to an intensive care unit (ICU). In this first wave, ICU staff and equipment were mobilized to expand bed capacity and ventilator capabilities to accommodate clinical need.Although many individuals presented with mild, self-limited symptoms and no sign of pulmonary involvement, some people required admission to an ICU and received maximal life support measures.^1–3 Predicting disease and mitigating hazard in at-risk populations is an important aim of public heath epidemiology, and in preparation for future waves of pandemic H1N1 influenza, determining correlates of the severity of disease may be very important. Initial reports have suggested that, in addition to many of the previously known risk factors for complications of seasonal influenza, obesity⁴ and other underlying comorbidities^3,5 may be risk factors for severe disease. The interval from onset of symptoms to initiation of antiviral therapy or other treatment and supportive care was also associated with adverse outcome in a recent case series.⁶ In a Canadian study of severe pandemic H1N1 influenza, First Nations people were proportionally overrepresented among patients in the ICU.² However, it is unclear if this association was independent of potential confounding factors. The ability to determine correlates of severe pandemic H1N1 disease and subsequent need for ICU resources in at-risk populations would provide opportunities for public and population health analysis and action, public education, strategic prioritization of vaccination efforts, efficient and equitable allocation and use of antiviral drugs, and development of infrastructure within the health system.The objectives of this study were to identify factors that were correlated with severity of disease in confirmed cases of pandemic H1N1 influenza. Our hypothesis, which was based on existing literature, was that obesity, First Nations ethnicity and longer interval from onset of symptoms to treatment would be important determinants of the severity of disease.     

A comparative evaluation of modelling strategies for the effect of treatment and host interactions on the spread of drug resistance

The evolutionary responses of infectious pathogens often have ruinous consequences for the control of disease spread in the population. Drug resistance is a well-documented instance that is generally driven by the selective pressure of drugs on both the replication of the pathogen within hosts and its transmission between hosts. Management of drug resistance therefore requires the development of treatment strategies that can impede the emergence and spread of resistance in the population. This study evaluates various treatment strategies for influenza infection as a case study by comparing the long-term epidemiological outcomes predicted by deterministic and stochastic versions of a homogeneously mixing (mean-field) model and those predicted by a heterogeneous model that incorporates spatial pair-wise correlation. We discuss the importance of three major parameters in our evaluation: the basic reproduction number, the population level of treatment, and the degree of clustering as a key parameter determining the structure of heterogeneous interactions. The results show that, as a common feature in all models, high treatment levels during the early stages of disease outset can result in large resistant outbreaks, with the possibility of a second wave of infection appearing in the pair-approximation model. Our simulations demonstrate that, if the basic reproduction number exceeds a threshold value, the population-wide spread of the resistant pathogen emerges more rapidly in the pair-approximation model with significantly lower treatment levels than in the homogeneous models. We tested an antiviral strategy that delays the onset of aggressive treatment for a certain amount of time after the onset of the outbreak. The findings indicate that the overall disease incidence is reduced as the degree of clustering increases, and a longer delay should be considered for implementing the large-scale treatment.     

An analysis of 332 fatalities infected with pandemic 2009 influenza A (H1N1) in Argentina

Background

The apparent high number of deaths in Argentina during the 2009 pandemic led to concern that the influenza A H1N1pdm disease was different there. We report the characteristics and risk factors for influenza A H1N1pdm fatalities.

Methods

We identified laboratory-confirmed influenza A H1N1pdm fatalities occurring during June-July 2009. Physicians abstracted data on age, sex, time of onset of illness, medical history, clinical presentation at admission, laboratory, treatment, and outcomes using standardize questionnaires. We explored the characteristics of fatalities according to their age and risk group.

Results

Of 332 influenza A H1N1pdm fatalities, 226 (68%) were among persons aged <50 years. Acute respiratory failure was the leading cause of death. Of all cases, 249 (75%) had at least one comorbidity as defined by Advisory Committee on Immunization Practices. Obesity was reported in 32% with data and chronic pulmonary disease in 28%. Among the 40 deaths in children aged <5 years, chronic pulmonary disease (42%) and neonatal pathologies (35%) were the most common co-morbidities. Twenty (6%) fatalities were among pregnant or postpartum women of which only 47% had diagnosed co-morbidities. Only 13% of patients received antiviral treatment within 48 hours of symptom onset. None of children aged <5 years or the pregnant women received antivirals within 48 h of symptom onset. As the pandemic progressed, the time from symptom-onset to medical care and to antiviral treatment decreased significantly among case-patients who subsequently died (p<0.001).

Conclusion

Persons with co-morbidities, pregnant and who received antivirals late were over-represented among influenza A H1N1pdm deaths in Argentina, though timeliness of antiviral treatment improved during the pandemic.     

Influenza pandemic waves under various mitigation strategies with 2009 H1N1 as a case study

A significant feature of influenza pandemics is multiple waves of morbidity and mortality over a few months or years. The size of these successive waves depends on intervention strategies including antivirals and vaccination, as well as the effects of immunity gained from previous infection. However, the global vaccine manufacturing capacity is limited. Also, antiviral stockpiles are costly and thus, are limited to very few countries. The combined effect of antivirals and vaccination in successive waves of a pandemic has not been quantified. The effect of acquired immunity from vaccination and previous infection has also not been characterized. In times of a pandemic threat countries must consider the effects of a limited vaccine, limited antiviral use and the effects of prior immunity so as to adopt a pandemic strategy that will best aid the population. We developed a mathematical model describing the first and second waves of an influenza pandemic including drug therapy, vaccination and acquired immunity. The first wave model includes the use of antiviral drugs under different treatment profiles. In the second wave model the effects of antivirals, vaccination and immunity gained from the first wave are considered. The models are used to characterize the severity of infection in a population under different drug therapy and vaccination strategies, as well as school closure, so that public health policies regarding future influenza pandemics are better informed.     

Population-wide emergence of antiviral resistance during pandemic influenza

Background

The emergence of neuraminidase inhibitor resistance has raised concerns about the prudent use of antiviral drugs in response to the next influenza pandemic. While resistant strains may initially emerge with compromised viral fitness, mutations that largely compensate for this impaired fitness can arise. Understanding the extent to which these mutations affect the spread of disease in the population can have important implications for developing pandemic plans.

Methodology/Principal Findings

By employing a deterministic mathematical model, we investigate possible scenarios for the emergence of population-wide resistance in the presence of antiviral drugs. The results show that if the treatment level (the fraction of clinical infections which receives treatment) is maintained constant during the course of the outbreak, there is an optimal level that minimizes the final size of the pandemic. However, aggressive treatment above the optimal level can substantially promote the spread of highly transmissible resistant mutants and increase the total number of infections. We demonstrate that resistant outbreaks can occur more readily when the spread of disease is further delayed by applying other curtailing measures, even if treatment levels are kept modest. However, by changing treatment levels over the course of the pandemic, it is possible to reduce the final size of the pandemic below the minimum achieved at the optimal constant level. This reduction can occur with low treatment levels during the early stages of the pandemic, followed by a sharp increase in drug-use before the virus becomes widely spread.

Conclusions/Significance

Our findings suggest that an adaptive antiviral strategy with conservative initial treatment levels, followed by a timely increase in the scale of drug-use, can minimize the final size of a pandemic while preventing large outbreaks of resistant infections.     

Oseltamivir Treatment for Children with Influenza-Like Illness in China: A Cost-Effectiveness Analysis

BackgroundInfluenza is a common viral respiratory infection that causes epidemics and pandemics in the human population. Oseltamivir is a neuraminidase inhibitor—a new class of antiviral therapy for influenza. Although its efficacy and safety have been established, there is uncertainty regarding whether influenza-like illness (ILI) in children is best managed by oseltamivir at the onset of illness, and its cost-effectiveness in children has not been studied in China.ObjectiveTo evaluate the cost-effectiveness of post rapid influenza diagnostic test (RIDT) treatment with oseltamivir and empiric treatment with oseltamivir comparing with no antiviral therapy against influenza for children with ILI.MethodsWe developed a decision-analytic model based on previously published evidence to simulate and evaluate 1-year potential clinical and economic outcomes associated with three managing strategies for children presenting with symptoms of influenza. Model inputs were derived from literature and expert opinion of clinical practice and research in China. Outcome measures included costs and quality-adjusted life year (QALY). All the interventions were compared with incremental cost-effectiveness ratios (ICER).ResultsIn base case analysis, empiric treatment with oseltamivir consistently produced the greatest gains in QALY. When compared with no antiviral therapy, the empiric treatment with oseltamivir strategy is very cost effective with an ICER of RMB 4,438. When compared with the post RIDT treatment with oseltamivir, the empiric treatment with oseltamivir strategy is dominant. Probabilistic sensitivity analysis projected that there is a 100% probability that empiric oseltamivir treatment would be considered as a very cost-effective strategy compared to the no antiviral therapy, according to the WHO recommendations for cost-effectiveness thresholds. The same was concluded with 99% probability for empiric oseltamivir treatment being a very cost-effective strategy compared to the post RIDT treatment with oseltamivir.ConclusionIn the Chinese setting of current health system, our modelling based simulation analysis suggests that empiric treatment with oseltamivir to be a cost-saving and very cost-effective strategy in managing children with ILI.     

A hospital-based strategy for setting priorities for antiviral prophylaxis during an influenza pandemic

An influenza pandemic would place an unprecedented strain on the nation's healthcare system-a compelling reason to carefully plan how priorities would be set for distributing antiviral medications. While antiviral medications have been added to the Strategic National Stockpile (SNS), these supplies are not designated as frontline resources and remain far from sufficient to provide mass prophylaxis for the entire population of the country. In the healthcare setting, providing general chemoprophylaxis may not be feasible because of high costs or inadequate supply. We propose a hospital-based strategy for setting priorities for antiviral prophylaxis that may offer a rational starting point for discussion and guide allocation decisions in the event of a shortage during a pandemic influenza outbreak.     

Optimal Control and Sensitivity Analysis of an Influenza Model with Treatment and Vaccination

We formulate and analyze the dynamics of an influenza pandemic model with vaccination and treatment using two preventive scenarios: increase and decrease in vaccine uptake. Due to the seasonality of the influenza pandemic, the dynamics is studied in a finite time interval. We focus primarily on controlling the disease with a possible minimal cost and side effects using control theory which is therefore applied via the Pontryagin’s maximum principle, and it is observed that full treatment effort should be given while increasing vaccination at the onset of the outbreak. Next, sensitivity analysis and simulations (using the fourth order Runge-Kutta scheme) are carried out in order to determine the relative importance of different factors responsible for disease transmission and prevalence. The most sensitive parameter of the various reproductive numbers apart from the death rate is the inflow rate, while the proportion of new recruits and the vaccine efficacy are the most sensitive parameters for the endemic equilibrium point.     

Biological and epidemiological aspects of influenza virus H5N1 in context of India

Since 1997, highly pathogenic avian influenza (HPAI) H5N1 virus crossed the species barriers from birds to humans and caused fatal disease, leading to great speculation about a possible influenza pandemic. This subtype is characterized by its pathogenicity in a large number of animal species and resistance to older class of antiviral drugs. At present, two out of three general conditions for the onset of pandemic have been met, emergence of new virus; and its ability to replicate in humans causing serious illness. Next influenza pandemic might be due to human to human transmission. This review addresses the biological and epidemiological aspects of influenza in context of India.     

Preclinical and clinical developments for combination treatment of influenza

Antiviral drugs are an important measure of control for influenza in the population, particularly for those that are severely ill or hospitalised. The neuraminidase inhibitor (NAI) class of drugs, including oseltamivir, have been the standard of care (SOC) for severe influenza illness for many years. The approval of drugs with novel mechanisms of action, such as baloxavir marboxil, is important and broadens potential treatment options for combination therapy. The use of antiviral treatments in combination for influenza is of interest; one potential benefit of this treatment strategy is that the combination of drugs with different mechanisms of action may lower the selection of resistance due to treatment. In addition, combination therapy may become an important treatment option to improve patient outcomes in those with severe illness due to influenza or those that are immunocompromised. Clinical trials increasingly evaluate drug combinations in a range of patient cohorts. Here, we summarise preclinical and clinical advances in combination therapy for the treatment of influenza with reference to immunocompromised animal models and clinical data in hospitalised patient cohorts where available. There is a wide array of drug categories in development that have also been tested in combination. Therefore, in this review, we have included polymerase inhibitors, monoclonal antibodies (mAbs), host-targeted therapies, and adjunctive therapies. Combination treatment regimens should be carefully evaluated to determine whether they provide an added benefit relative to effectiveness of monotherapy and in a variety of patient cohorts, particularly, if there is a greater chance of an adverse outcome. Safe and effective treatment of influenza is important not only for seasonal influenza infection, but also if a pandemic strain was to emerge.     

Higher level of replication efficiency of 2009 (H1N1) pandemic influenza virus than those of seasonal and avian strains: kinetics from epithelial cell culture and computational modeling

The pathogenicity and transmission of influenza A viruses are likely determined in part by replication efficiency in human cells, which is the net effect of complex virus-host interactions. H5N1 avian, H1N1 seasonal, and H1N1 2009 pandemic influenza virus strains were compared by infecting human differentiated bronchial epithelial cells in air-liquid interface cultures at relatively low virus particle/cell ratios. Differential equation and computational models were used to characterize the in vitro kinetic behaviors of the three strains. The models were calibrated by fitting experimental data in order to estimate difficult-to-measure parameters. Both models found marked differences in the relative values of p, the virion production rate per cell, and R(0), an index of the spread of infection through the monolayer, with the values for the strains in the following rank order (from greatest to least): pandemic strain, followed by seasonal strain, followed by avian strain, as expected. In the differential equation model, which treats virus and cell populations as well mixed, R(0) and p varied proportionately for all 3 strains, consistent with a primary role for productivity. In the spatially explicit computational model, R(0) and p also varied proportionately except that R(0) derived for the pandemic strain was reduced, consistent with constrained viral spread imposed by multiple host defenses, including mucus and paracrine antiviral effects. This synergistic experimental-computational strategy provides relevant parameters for identifying and phenotyping potential pandemic strains.     

Influenza A virus infection in zebrafish recapitulates mammalian infection and sensitivity to anti-influenza drug treatment

Seasonal influenza virus infections cause annual epidemics and sporadic pandemics. These present a global health concern, resulting in substantial morbidity, mortality and economic burdens. Prevention and treatment of influenza illness is difficult due to the high mutation rate of the virus, the emergence of new virus strains and increasing antiviral resistance. Animal models of influenza infection are crucial to our gaining a better understanding of the pathogenesis of and host response to influenza infection, and for screening antiviral compounds. However, the current animal models used for influenza research are not amenable to visualization of host-pathogen interactions or high-throughput drug screening. The zebrafish is widely recognized as a valuable model system for infectious disease research and therapeutic drug testing. Here, we describe a zebrafish model for human influenza A virus (IAV) infection and show that zebrafish embryos are susceptible to challenge with both influenza A strains APR8 and X-31 (Aichi). Influenza-infected zebrafish show an increase in viral burden and mortality over time. The expression of innate antiviral genes, the gross pathology and the histopathology in infected zebrafish recapitulate clinical symptoms of influenza infections in humans. This is the first time that zebrafish embryos have been infected with a fluorescent IAV in order to visualize infection in a live vertebrate host, revealing a pattern of vascular endothelial infection. Treatment of infected zebrafish with a known anti-influenza compound, Zanamivir, reduced mortality and the expression of a fluorescent viral gene product, demonstrating the validity of this model to screen for potential antiviral drugs. The zebrafish model system has provided invaluable insights into host-pathogen interactions for a range of infectious diseases. Here, we demonstrate a novel use of this species for IAV research. This model has great potential to advance our understanding of influenza infection and the associated host innate immune response.KEY WORDS: Influenza, Zebrafish, Virus, Innate immunity     

The role of health care workers and antiviral drugs in the control of pandemic influenza

Until a vaccine against the new strain becomes available, the response to newly emerged pandemic influenza will consist of the use of antiviral drugs and measures that limit exposure to infectious individuals. These first-line defence measures include isolating cases upon diagnosis, reducing close contacts, the use of personal protective equipment and hygiene, and using antiviral drugs for treatment and prophylaxis. There are significant 'costs' associated with control measures, so to justify such interventions it is important to assess their potential to reduce transmission. In this paper, we determine the effect that a number of different antiviral interventions have on the reproduction number of infectives and the probability that an imported infection fades out, and determine parameter scenarios for which these interventions are able to eliminate an emerging pandemic of influenza. We also assess the role that health care workers play in transmission and the extent to which providing them with antiviral prophylaxis and personal protective equipment modifies this role. Our results indicate that this class requires protection to avoid a greatly disproportionate contribution to early infective numbers, and for the maintenance of a stable health care system. Further, we show that the role children play in increasing transmission is moderate, in spite of closer mixing with other children.