Mapping influenza transmission in the ferret model to transmission in humans

Machine learning approaches for influenza A virus risk assessment identifies predictive correlates using ferret model in vivo data

In vivo assessments of influenza A virus (IAV) pathogenicity and transmissibility in ferrets represent a crucial component of many pandemic risk assessment rubrics, but few systematic efforts to identify which data from in vivo experimentation are most useful for predicting pathogenesis and transmission outcomes have been conducted. To this aim, we aggregated viral and molecular data from 125 contemporary IAV (H1, H2, H3, H5, H7, and H9 subtypes) evaluated in ferrets under a consistent protocol. Three overarching predictive classification outcomes (lethality, morbidity, transmissibility) were constructed using machine learning (ML) techniques, employing datasets emphasizing virological and clinical parameters from inoculated ferrets, limited to viral sequence-based information, or combining both data types. Among 11 different ML algorithms tested and assessed, gradient boosting machines and random forest algorithms yielded the highest performance, with models for lethality and transmission consistently better performing than models predicting morbidity. Comparisons of feature selection among models was performed, and highest performing models were validated with results from external risk assessment studies. Our findings show that ML algorithms can be used to summarize complex in vivo experimental work into succinct summaries that inform and enhance risk assessment criteria for pandemic preparedness that take in vivo data into account.

Comparative Pathology of Animal Models for Influenza A Virus Infection

Animal models are essential for studying disease pathogenesis and to test the efficacy and safety of new vaccines and therapeutics. For most diseases, there is no single model that can recapitulate all features of the human condition, so it is vital to understand the advantages and disadvantages of each. The purpose of this review is to describe popular comparative animal models, including mice, ferrets, hamsters, and non-human primates (NHPs), that are being used to study clinical and pathological changes caused by influenza A virus infection with the aim to aid in appropriate model selection for disease modeling.

Block the Spread: Barriers to Transmission of Influenza Viruses

Respiratory viruses, such as influenza viruses, cause significant morbidity and mortality worldwide through seasonal epidemics and sporadic pandemics. Influenza viruses transmit through multiple modes including contact (either direct or through a contaminated surface) and inhalation of expelled aerosols. Successful human to human transmission requires an infected donor who expels virus into the environment, a susceptible recipient, and persistence of the expelled virus within the environment. The relative efficiency of each mode can be altered by viral features, environmental parameters, donor and recipient host characteristics, and viral persistence. Interventions to mitigate transmission of influenza viruses can target any of these factors. In this review, we discuss many aspects of influenza virus transmission, including the systems to study it, as well as the impact of natural barriers and various nonpharmaceutical and pharmaceutical interventions.

Utility of Human In Vitro Data in Risk Assessments of Influenza A Virus Using the Ferret Model

As influenza A viruses (IAV) continue to cross species barriers and cause human infection, the establishment of risk assessment rubrics has improved pandemic preparedness efforts. In vivo pathogenicity and transmissibility evaluations in the ferret model represent a critical component of this work. As the relative contribution of in vitro experimentation to these rubrics has not been closely examined, we sought to evaluate to what extent viral titer measurements over the course of in vitro infections are predictive or correlates of nasal wash and tissue measurements for IAV infections in vivo. We compiled data from ferrets inoculated with an extensive panel of over 50 human and zoonotic IAV (inclusive of swine-origin and high- and low-pathogenicity avian influenza viruses associated with human infection) under a consistent protocol, with all viruses concurrently tested in a human bronchial epithelial cell line (Calu-3). Viral titers in ferret nasal wash specimens and nasal turbinate tissue correlated positively with peak titer in Calu-3 cells, whereas additional phenotypic and molecular determinants of influenza virus virulence and transmissibility in ferrets varied in their association with in vitro viral titer measurements. Mathematical modeling was used to estimate more generalizable key replication kinetic parameters from raw in vitro viral titers, revealing commonalities between viral infection progression in vivo and in vitro. Meta-analyses inclusive of IAV that display a diverse range of phenotypes in ferrets, interpreted with mathematical modeling of viral kinetic parameters, can provide critical information supporting a more rigorous and appropriate contextualization of in vitro experiments toward pandemic preparedness. IMPORTANCE Both in vitro and in vivo models are employed for assessing the pandemic potential of novel and emerging influenza A viruses in laboratory settings, but systematic examinations of how well viral titer measurements obtained in vitro align with results from in vivo experimentation are not frequently performed. We show that certain viral titer measurements following infection of a human bronchial epithelial cell line are positively correlated with viral titers in specimens collected from virus-inoculated ferrets and employ mathematical modeling to identify commonalities between viral infection progression between both models. These analyses provide a necessary first step in enhanced interpretation and incorporation of in vitro-derived data in risk assessment activities and highlight the utility of employing mathematical modeling approaches to more closely examine features of virus replication not identifiable by experimental studies alone.

Avian H7N9 influenza viruses are evolutionarily constrained by stochastic processes during replication and transmission in mammals

H7N9 avian influenza viruses (AIVs) have caused over 1,500 documented human infections since emerging in 2013. Although wild-type H7N9 AIVs can be transmitted by respiratory droplets in ferrets, they have not yet caused widespread outbreaks in humans. Previous studies have revealed molecular determinants of H7N9 AIV host switching, but little is known about potential evolutionary constraints on this process. Here, we compare patterns of sequence evolution for H7N9 AIV and mammalian H1N1 viruses during replication and transmission in ferrets. We show that three main factors-purifying selection, stochasticity, and very narrow transmission bottlenecks-combine to severely constrain the ability of H7N9 AIV to effectively adapt to mammalian hosts in isolated, acute spillover events. We find rare evidence of natural selection favoring new, potentially mammal-adapting mutations within ferrets but no evidence of natural selection acting during transmission. We conclude that human-adapted H7N9 viruses are unlikely to emerge during typical spillover infections. Our findings are instead consistent with a model in which the emergence of a human-transmissible virus would be a rare and unpredictable, though highly consequential, 'jackpot' event. Strategies to control the total number of spillover infections will limit opportunities for the virus to win this evolutionary lottery.

Sequential Transmission of Influenza Viruses in Ferrets Does Not Enhance Infectivity and Does Not Predict Transmissibility in Humans

Airborne transmission in ferrets is a key component of pandemic risk assessment. However, some emerging avian influenza viruses transmit between ferrets but do not spread in humans. Therefore, we evaluated sequential rounds of airborne transmission as an approach to enhance the predictive accuracy of the ferret model. We reasoned that infection of ferrets via the respiratory route and onward transmission would more closely model transmission in humans. We hypothesized that pandemic and seasonal viruses would transmit efficiently over two rounds of transmission, while emerging avian viruses would fail to transmit in a second round. The 2009 pandemic H1N1 (pdm09) and seasonal H3N2 viruses were compared to avian-origin H7N9 and H3N8 viruses. Depending on the virus strain, transmission efficiency varied from 50 to 100% during the first round of transmission; the efficiency for each virus did not change during the second round, and viral replication kinetics in both rounds of transmission were similar. Both the H1N1pdm09 and H7N9 viruses acquired specific mutations during sequential transmission, while the H3N2 and H3N8 viruses did not; however, a global analysis of host-adaptive mutations revealed that minimal changes were associated with transmission of H1N1 and H3N2 viruses, while a greater number of changes occurred in the avian H3N8 and H7N9 viruses. Thus, influenza viruses that transmit in ferrets maintain their transmission efficiency through serial rounds of transmission. This answers the question of whether ferrets can propagate viruses through more than one round of airborne transmission and emphasizes that transmission in ferrets is necessary but not sufficient to infer transmissibility in humans. IMPORTANCE Airborne transmission in ferrets is used to gauge the pandemic potential of emerging influenza viruses; however, some emerging influenza viruses that transmit between ferrets do not spread between humans. Therefore, we evaluated sequential rounds of airborne transmission in ferrets as a strategy to enhance the predictive accuracy of the ferret model. Human influenza viruses transmitted efficiently (>83%) over two rounds of airborne transmission, demonstrating that, like humans, ferrets infected by the respiratory route can propagate the infection onward through the air. However, emerging avian influenza viruses with associated host-adaptive mutations also transmitted through sequential transmission. Thus, airborne transmission in ferrets is necessary but not sufficient to infer transmissibility in humans, and sequential transmission did not enhance pandemic risk assessment.

Robustness of the Ferret Model for Influenza Risk Assessment Studies: a Cross-Laboratory Exercise

Past pandemic influenza viruses with sustained human-to-human transmissibility have emerged from animal influenza viruses. Employment of experimental models to assess the pandemic risk of emerging zoonotic influenza viruses provides critical information supporting public health efforts. Ferret transmission experiments have been utilized to predict the human-to-human transmission potential of novel influenza viruses. However, small sample sizes and a lack of standardized protocols can introduce interlaboratory variability, complicating interpretation of transmission experimental data. To assess the range of variation in ferret transmission experiments, a global exercise was conducted by 11 laboratories using two common stock H1N1 influenza viruses with different transmission characteristics in ferrets. Parameters known to affect transmission were standardized, including the inoculation route, dose, and volume, as well as a strict 1:1 donor/contact ratio for respiratory droplet transmission. Additional host and environmental parameters likely to affect influenza transmission kinetics were monitored and analyzed. The overall transmission outcomes for both viruses across 11 laboratories were concordant, suggesting the robustness of the ferret model for zoonotic influenza risk assessment. Among environmental parameters that varied across laboratories, donor-to-contact airflow directionality was associated with increased transmissibility. To attain high confidence in identifying viruses with moderate to high transmissibility or low transmissibility under a smaller number of participating laboratories, our analyses support the notion that as few as three but as many as five laboratories, respectively, would need to independently perform viral transmission experiments with concordant results. This exercise facilitates the development of a more homogenous protocol for ferret transmission experiments that are employed for the purposes of risk assessment.

Inherent heterogeneity of influenza A virus stability following aerosolization

Efficient human-to-human transmission represents a necessary adaptation for a zoonotic influenza A virus (IAV) to cause a pandemic. As such, many emerging IAVs are characterized for transmissibility phenotypes in mammalian models, with an emphasis on elucidating viral determinants of transmission and the role host immune responses contribute to mammalian adaptation. Investigations of virus infectivity and stability in aerosols concurrent with transmission assessments have increased in recent years, enhancing our understanding of this dynamic process. Here, we employ a diverse panel of 17 human and zoonotic IAVs, inclusive of seasonally circulating H1N1 and H3N2 viruses, and avian and swine viruses associated with human infection, to evaluate differences in spray factor (a value that assesses efficiency of the aerosolization process), stability, and infectivity following aerosolization. While most seasonal influenza viruses did not exhibit substantial variability within these parameters, there was more heterogeneity among zoonotic influenza viruses, which possess a diverse range of transmission phenotypes. Aging of aerosols at different relative humidities identified strain-specific levels of stability with different profiles identified between zoonotic H3, H5, and H7 subtype viruses associated with human infection. As studies continue to elucidate the complex components governing virus transmissibility, notably aerosol matrices and environmental parameters, considering the relative role of subtype- and strain-specific factors to modulate these parameters will improve our understanding of the pandemic potential of zoonotic influenza A viruses. Importance Transmission of respiratory pathogens through the air can facilitate the rapid and expansive spread of infection and disease through a susceptible population. While seasonal influenza viruses are quite capable of airborne spread, there is a lack of knowledge regarding how well influenza viruses remain viable after aerosolization, and if influenza viruses capable of jumping species barriers to cause human infection differ in this property from seasonal strains. We evaluated a diverse panel of influenza viruses associated with human infection (originating from human, avian, and swine reservoirs) for their ability to remain viable after aerosolization in the laboratory under a range of conditions. We found greater diversity among avian and swine-origin viruses compared with seasonal influenza viruses; strain-specific stability was also noted. Although influenza virus stability in aerosols is an underreported property, if molecular markers associated with enhanced stability are identified, we will be able to quickly recognize emerging strains of influenza that present the greatest pandemic threat.

Non-respiratory particles emitted by guinea pigs in airborne disease transmission experiments

Animal models are often used to assess the airborne transmissibility of various pathogens, which are typically assumed to be carried by expiratory droplets emitted directly from the respiratory tract of the infected animal. We recently established that influenza virus is also transmissible via "aerosolized fomites," micron-scale dust particulates released from virus-contaminated surfaces (Asadi et al. in Nat Commun 11(1):4062, 2020). Here we expand on this observation, by counting and characterizing the particles emitted from guinea pig cages using an Aerodynamic Particle Sizer (APS) and an Interferometric Mie Imaging (IMI) system. Of over 9000 airborne particles emitted from guinea pig cages and directly imaged with IMI, none had an interference pattern indicative of a liquid droplet. Separate measurements of the particle count using the APS indicate that particle concentrations spike upwards immediately following animal motion, then decay exponentially with a time constant commensurate with the air exchange rate in the cage. Taken together, the results presented here raise the possibility that a non-negligible fraction of airborne influenza transmission events between guinea pigs occurs via aerosolized fomites rather than respiratory droplets, though the relative frequencies of these two routes have yet to be definitively determined.

Transmission and Protection against Reinfection in the Ferret Model with the SARS-CoV-2 USA-WA1/2020 Reference Isolate

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has initiated a global pandemic, and several vaccines have now received emergency use authorization. Using the reference strain SARS-CoV-2 USA-WA1/2020, we evaluated modes of transmission and the ability of prior infection or vaccine-induced immunity to protect against infection in ferrets. Ferrets were semipermissive to infection with the USA-WA1/2020 isolate. When transmission was assessed via the detection of viral RNA (vRNA) at multiple time points, direct contact transmission was efficient to 3/3 and 3/4 contact animals in 2 respective studies, while respiratory droplet transmission was poor to only 1/4 contact animals. To determine if previously infected ferrets were protected against reinfection, ferrets were rechallenged 28 or 56 days postinfection. Following viral challenge, no infectious virus was recovered in nasal wash samples. In addition, levels of vRNA in the nasal wash were several orders of magnitude lower than during primary infection, and vRNA was rapidly cleared. To determine if intramuscular vaccination protected ferrets, ferrets were vaccinated using a prime-boost strategy with the S protein receptor-binding domain formulated with an oil-in-water adjuvant. Upon viral challenge, none of the mock or vaccinated animals were protected against infection, and there were no significant differences in vRNA or infectious virus titers in the nasal wash. Combined, these studies demonstrate direct contact is the predominant mode of transmission of the USA-WA1/2020 isolate in ferrets and that immunity to SARS-CoV-2 is maintained for at least 56 days. Our studies also indicate protection of the upper respiratory tract against SARS-CoV-2 will require vaccine strategies that mimic natural infection or induce site-specific immunity. IMPORTANCE The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) USA-WA1/2020 strain is a CDC reference strain used by multiple research laboratories. Here, we show that the predominant mode of transmission of this isolate in ferrets is by direct contact. We further demonstrate ferrets are protected against reinfection for at least 56 days even when levels of neutralizing antibodies are low or undetectable. Last, we show that when ferrets were vaccinated by the intramuscular route to induce antibodies against SARS-CoV-2, ferrets remain susceptible to infection of the upper respiratory tract. Collectively, these studies suggest that protection of the upper respiratory tract will require vaccine approaches that mimic natural infection.

Prophylactic intranasal administration of a TLR2/6 agonist reduces upper respiratory tract viral shedding in a SARS-CoV-2 challenge ferret model

BACKGROUND

The novel human coronavirus SARS-CoV-2 is a major ongoing global threat with huge economic burden. Like all respiratory viruses, SARS-CoV-2 initiates infection in the upper respiratory tract (URT). Infected individuals are often asymptomatic, yet highly infectious and readily transmit virus. A therapy that restricts initial replication in the URT has the potential to prevent progression of severe lower respiratory tract disease as well as limiting person-to-person transmission.

METHODS

SARS-CoV-2 Victoria/01/2020 was passaged in Vero/hSLAM cells and virus titre determined by plaque assay. Challenge virus was delivered by intranasal instillation to female ferrets at 5.0 × 106 pfu/ml. Treatment groups received intranasal INNA-051, developed by Ena Respiratory. SARS-CoV-2 RNA was detected using the 2019-nCoV CDC RUO Kit and QuantStudio™ 7 Flex Real-Time PCR System. Histopathological analysis was performed using cut tissues stained with haematoxylin and eosin (H&E).

FINDINGS

We show that prophylactic intra-nasal administration of the TLR2/6 agonist INNA-051 in a SARS-CoV-2 ferret infection model effectively reduces levels of viral RNA in the nose and throat. After 5 days post-exposure to SARS-CoV-2, INNA-051 significantly reduced virus in throat swabs (p=<0.0001) by up to a 24 fold (96% reduction) and in nasal wash (p=0.0107) up to a 15 fold (93% reduction) in comparison to untreated animals.

INTERPRETATION

The results of our study support clinical development of a therapy based on prophylactic TLR2/6 innate immune activation in the URT, to reduce SARS-CoV-2 transmission and provide protection against COVID-19.

FUNDING

This work was funded by Ena Respiratory, Melbourne, Australia.

Beyond clinical trials: Evolutionary and epidemiological considerations for development of a universal influenza vaccine

The prospect of universal influenza vaccines is generating much interest and research at the intersection of immunology, epidemiology, and viral evolution. While the current focus is on developing a vaccine that elicits a broadly cross-reactive immune response in clinical trials, there are important downstream questions about global deployment of a universal influenza vaccine that should be explored to minimize unintended consequences and maximize benefits. Here, we review and synthesize the questions most relevant to predicting the population benefits of universal influenza vaccines and discuss how existing information could be mined to begin to address these questions. We review three research topics where computational modeling could bring valuable evidence: immune imprinting, viral evolution, and transmission. We address the positive and negative consequences of imprinting, in which early childhood exposure to influenza shapes and limits immune responses to future infections via memory of conserved influenza antigens. However, the mechanisms at play, their effectiveness, breadth of protection, and the ability to "reprogram" already imprinted individuals, remains heavily debated. We describe instances of rapid influenza evolution that illustrate the plasticity of the influenza virus in the face of drug pressure and discuss how novel vaccines could introduce new selective pressures on the evolution of the virus. We examine the possible unintended consequences of broadly protective (but infection-permissive) vaccines on the dynamics of epidemic and pandemic influenza, compared to conventional vaccines that have been shown to provide herd immunity benefits. In conclusion, computational modeling offers a valuable tool to anticipate the benefits of ambitious universal influenza vaccine programs, while balancing the risks from endemic influenza strains and unpredictable pandemic viruses. Moving forward, it will be important to mine the vast amount of data generated in clinical studies of universal influenza vaccines to ensure that the benefits and consequences of these vaccine programs have been carefully modeled and explored.

Ferreting Out Influenza Virus Pathogenicity and Transmissibility: Past and Future Risk Assessments in the Ferret Model

As influenza A viruses continue to jump species barriers, data generated in the ferret model to assess influenza virus pathogenicity, transmissibility, and tropism of these novel strains continues to inform an increasing scope of public health-based applications. This review presents the suitability of ferrets as a small mammalian model for influenza viruses and describes the breadth of pathogenicity and transmissibility profiles possible in this species following inoculation with a diverse range of viruses. Adaptation of aerobiology-based techniques and analyses have furthered our understanding of data obtained from this model and provide insight into the capacity of novel and emerging influenza viruses to cause human infection and disease.

Predicting the Next Influenza Pandemics

Worldwide outbreaks of influenza (pandemics) are caused by influenza A viruses to which persons lack protective immune responses. Currently, we are unable to predict which influenza virus strains may cause a pandemic. In this article, we summarize some of the information that will be needed to better assess the pandemic potential of influenza viruses, and we discuss our current gaps in knowledge.

Improving immunological insights into the ferret model of human viral infectious disease

Ferrets are a well-established model for studying both the pathogenesis and transmission of human respiratory viruses and evaluation of antiviral vaccines. Advanced immunological studies would add substantial value to the ferret models of disease but are hindered by the low number of ferret-reactive reagents available for flow cytometry and immunohistochemistry. Nevertheless, progress has been made to understand immune responses in the ferret model with a limited set of ferret-specific reagents and assays. This review examines current immunological insights gained from the ferret model across relevant human respiratory diseases, with a focus on influenza viruses. We highlight key knowledge gaps that need to be bridged to advance the utility of ferrets for immunological studies.

Fogarty International Center collaborative networks in infectious disease modeling: Lessons learnt in research and capacity building

Due to a combination of ecological, political, and demographic factors, the emergence of novel pathogens has been increasingly observed in animals and humans in recent decades. Enhancing global capacity to study and interpret infectious disease surveillance data, and to develop data-driven computational models to guide policy, represents one of the most cost-effective, and yet overlooked, ways to prepare for the next pandemic. Epidemiological and behavioral data from recent pandemics and historic scourges have provided rich opportunities for validation of computational models, while new sequencing technologies and the 'big data' revolution present new tools for studying the epidemiology of outbreaks in real time. For the past two decades, the Division of International Epidemiology and Population Studies (DIEPS) of the NIH Fogarty International Center has spearheaded two synergistic programs to better understand and devise control strategies for global infectious disease threats. The Multinational Influenza Seasonal Mortality Study (MISMS) has strengthened global capacity to study the epidemiology and evolutionary dynamics of influenza viruses in 80 countries by organizing international research activities and training workshops. The Research and Policy in Infectious Disease Dynamics (RAPIDD) program and its precursor activities has established a network of global experts in infectious disease modeling operating at the research-policy interface, with collaborators in 78 countries. These activities have provided evidence-based recommendations for disease control, including during large-scale outbreaks of pandemic influenza, Ebola and Zika virus. Together, these programs have coordinated international collaborative networks to advance the study of emerging disease threats and the field of computational epidemic modeling. A global community of researchers and policy-makers have used the tools and trainings developed by these programs to interpret infectious disease patterns in their countries, understand modeling concepts, and inform control policies. Here we reflect on the scientific achievements and lessons learnt from these programs (h-index = 106 for RAPIDD and 79 for MISMS), including the identification of outstanding researchers and fellows; funding flexibility for timely research workshops and working groups (particularly relative to more traditional investigator-based grant programs); emphasis on group activities such as large-scale modeling reviews, model comparisons, forecasting challenges and special journal issues; strong quality control with a light touch on outputs; and prominence of training, data-sharing, and joint publications.

Sowing the Seeds of a Pandemic? Mammalian Pathogenicity and Transmissibility of H1 Variant Influenza Viruses from the Swine Reservoir

Emergence of genetically and antigenically diverse strains of influenza to which the human population has no or limited immunity necessitates continuous risk assessments to determine the likelihood of these viruses acquiring adaptations that facilitate sustained human-to-human transmission. As the North American swine H1 virus population has diversified over the last century by means of both antigenic drift and shift, in vivo assessments to study multifactorial traits like mammalian pathogenicity and transmissibility of these emerging influenza viruses are critical. In this review, we examine genetic, molecular, and pathogenicity and transmissibility data from a panel of contemporary North American H1 subtype swine-origin viruses isolated from humans, as compared to H1N1 seasonal and pandemic viruses, including the reconstructed 1918 virus. We present side-by-side analyses of experiments performed in the mouse and ferret models using consistent experimental protocols to facilitate enhanced interpretation of in vivo data. Contextualizing these analyses in a broader context permits a greater appreciation of the role that in vivo risk assessment experiments play in pandemic preparedness. Collectively, we find that despite strain-specific heterogeneity among swine-origin H1 viruses, contemporary swine viruses isolated from humans possess many attributes shared by prior pandemic strains, warranting heightened surveillance and evaluation of these zoonotic viruses.

Mechanistic insights into the effect of humidity on airborne influenza virus survival, transmission and incidence

Influenza incidence and seasonality, along with virus survival and transmission, appear to depend at least partly on humidity, and recent studies have suggested that absolute humidity (AH) is more important than relative humidity (RH) in modulating observed patterns. In this perspective article, we re-evaluate studies of influenza virus survival in aerosols, transmission in animal models and influenza incidence to show that the combination of temperature and RH is equally valid as AH as a predictor. Collinearity must be considered, as higher levels of AH are only possible at higher temperatures, where it is well established that virus decay is more rapid. In studies of incidence that employ meteorological data, outdoor AH may be serving as a proxy for indoor RH in temperate regions during the wintertime heating season. Finally, we present a mechanistic explanation based on droplet evaporation and its impact on droplet physics and chemistry for why RH is more likely than AH to modulate virus survival and transmission.

Mechanistic insights into the effect of humidity on airborne influenza virus survival, transmission and incidence

Influenza incidence and seasonality, along with virus survival and transmission, appear to depend at least partly on humidity, and recent studies have suggested that absolute humidity (AH) is more important than relative humidity (RH) in modulating observed patterns. In this perspective article, we re-evaluate studies of influenza virus survival in aerosols, transmission in animal models and influenza incidence to show that the combination of temperature and RH is equally valid as AH as a predictor. Collinearity must be considered, as higher levels of AH are only possible at higher temperatures, where it is well established that virus decay is more rapid. In studies of incidence that employ meteorological data, outdoor AH may be serving as a proxy for indoor RH in temperate regions during the wintertime heating season. Finally, we present a mechanistic explanation based on droplet evaporation and its impact on droplet physics and chemistry for why RH is more likely than AH to modulate virus survival and transmission.

A novel framework for inferring parameters of transmission from viral sequence data

Transmission between hosts is a critical part of the viral lifecycle. Recent studies of viral transmission have used genome sequence data to evaluate the number of particles transmitted between hosts, and the role of selection as it operates during the transmission process. However, the interpretation of sequence data describing transmission events is a challenging task. We here present a novel and comprehensive framework for using short-read sequence data to understand viral transmission events, designed for influenza virus, but adaptable to other viral species. Our approach solves multiple shortcomings of previous methods for this purpose; for example, we consider transmission as an event involving whole viruses, rather than sets of independent alleles. We demonstrate how selection during transmission and noisy sequence data may each affect naive inferences of the population bottleneck, accounting for these in our framework so as to achieve a correct inference. We identify circumstances in which selection for increased viral transmission may or may not be identified from data. Applying our method to experimental data in which transmission occurs in the presence of strong selection, we show that our framework grants a more quantitative insight into transmission events than previous approaches, inferring the bottleneck in a manner that accounts for selection, both for within-host virulence, and for inherent viral transmissibility. Our work provides new opportunities for studying transmission processes in influenza, and by extension, in other infectious diseases.

The Pandemic Threat of Emerging H5 and H7 Avian Influenza Viruses

The 1918 H1N1 Spanish Influenza pandemic was the most severe pandemic in modern history. Unlike more recent pandemics, most of the 1918 H1N1 virus' genome was derived directly from an avian influenza virus. Recent avian-origin H5 A/goose/Guangdong/1/1996 (GsGd) and Asian H7N9 viruses have caused several hundred human infections with high mortality rates. While these viruses have not spread beyond infected individuals, if they evolve the ability to transmit efficiently from person-to-person, specifically via the airborne route, they will initiate a pandemic. Therefore, this review examines H5 GsGd and Asian H7N9 viruses that have caused recent zoonotic infections with a focus on viral properties that support airborne transmission. Several GsGd H5 and Asian H7N9 viruses display molecular changes that potentiate transmission and/or exhibit ability for limited transmission between ferrets. However, the hemagglutinin of these viruses is unstable; this likely represents the most significant obstacle to the emergence of a virus capable of efficient airborne transmission. Given the global disease burden of an influenza pandemic, continued surveillance and pandemic preparedness efforts against H5 GsGd and Asian lineage H7N9 viruses are warranted.

Defining the sizes of airborne particles that mediate influenza transmission in ferrets

Emerging respiratory pathogens pose significant public health threats as a result of their potential for rapid global spread via multiple non-mutually exclusive modes of transmission. The relative significance of contact, droplet, and airborne transmission for many respiratory pathogens remains a knowledge gap, and better understanding is essential for developing evidence-based measures for effective infection control. Here, we describe and evaluate a transmission chamber that separates virus-laden particles in air by size to study airborne particles that mediate influenza transmission in ferrets. Our results provide direct experimental evidence of influenza transmission via droplets and fine droplet nuclei, albeit at different efficiency. This transmission device can also be applied to elucidate the mode of transmission of other respiratory pathogens.

Epidemics and pandemics of influenza are characterized by rapid global spread mediated by non-mutually exclusive transmission modes. The relative significance between contact, droplet, and airborne transmission is yet to be defined, a knowledge gap for implementing evidence-based infection control measures. We devised a transmission chamber that separates virus-laden particles by size and determined the particle sizes mediating transmission of influenza among ferrets through the air. Ferret-to-ferret transmission was mediated by airborne particles larger than 1.5 µm, consistent with the quantity and size of virus-laden particles released by the donors. Onward transmission by donors was most efficient before fever onset and may continue for 5 days after inoculation. Multiple virus gene segments enhanced the transmissibility of a swine influenza virus among ferrets by increasing the release of virus-laden particles into the air. We provide direct experimental evidence of influenza transmission via droplets and fine droplet nuclei, albeit at different efficiency.

Why Do Exceptionally Dangerous Gain-of-Function Experiments in Influenza?

This chapter makes the case against performing exceptionally dangerous gain-of-function experiments that are designed to create potentially pandemic and novel strains of influenza, for example, by enhancing the airborne transmissibility in mammals of highly virulent avian influenza strains. This is a question of intense debate over the last 5 years, though the history of such experiments goes back at least to the synthesis of viable influenza A H1N1 (1918) based on material preserved from the 1918 pandemic. This chapter makes the case that experiments to create potential pandemic pathogens (PPPs) are nearly unique in that they present biosafety risks that extend well beyond the experimenter or laboratory performing them; an accidental release could, as the name suggests, lead to global spread of a virulent virus, a biosafety incident on a scale never before seen. In such cases, biosafety considerations should be uppermost in the consideration of alternative approaches to experimental objectives and design, rather than being settled after the fact, as is appropriately done for most research involving pathogens. The extensive recent discussion of the magnitude of risks from such experiments is briefly reviewed. The chapter argues that, while there are indisputably certain questions that can be answered only by gain-of-function experiments in highly pathogenic strains, these questions are narrow and unlikely to meaningfully advance public health goals such as vaccine production and pandemic prediction. Alternative approaches to experimental influenza virology and characterization of existing strains are in general completely safe, higher throughput, more generalizable, and less costly than creation of PPP in the laboratory and can thereby better inform public health. Indeed, virtually every finding of recent PPP experiments that has been cited for its public health value was predated by similar findings using safe methodologies. The chapter concludes that the unique scientific and public health value of PPP experiments is inadequate to justify the unique risks they entail and that researchers would be well-advised to turn their talents to other methodologies that will be safe and more rewarding scientifically.

Transmission Bottleneck Size Estimation from Pathogen Deep-Sequencing Data, with an Application to Human Influenza A Virus

The bottleneck governing infectious disease transmission describes the size of the pathogen population transferred from the donor to the recipient host. Accurate quantification of the bottleneck size is particularly important for rapidly evolving pathogens such as influenza virus, as narrow bottlenecks reduce the amount of transferred viral genetic diversity and, thus, may decrease the rate of viral adaptation. Previous studies have estimated bottleneck sizes governing viral transmission by using statistical analyses of variants identified in pathogen sequencing data. These analyses, however, did not account for variant calling thresholds and stochastic viral replication dynamics within recipient hosts. Because these factors can skew bottleneck size estimates, we introduce a new method for inferring bottleneck sizes that accounts for these factors. Through the use of a simulated data set, we first show that our method, based on beta-binomial sampling, accurately recovers transmission bottleneck sizes, whereas other methods fail to do so. We then apply our method to a data set of influenza A virus (IAV) infections for which viral deep-sequencing data from transmission pairs are available. We find that the IAV transmission bottleneck size estimates in this study are highly variable across transmission pairs, while the mean bottleneck size of 196 virions is consistent with a previous estimate for this data set. Furthermore, regression analysis shows a positive association between estimated bottleneck size and donor infection severity, as measured by temperature. These results support findings from experimental transmission studies showing that bottleneck sizes across transmission events can be variable and influenced in part by epidemiological factors.IMPORTANCE The transmission bottleneck size describes the size of the pathogen population transferred from the donor to the recipient host and may affect the rate of pathogen adaptation within host populations. Recent advances in sequencing technology have enabled bottleneck size estimation from pathogen genetic data, although there is not yet a consistency in the statistical methods used. Here, we introduce a new approach to infer the bottleneck size that accounts for variant identification protocols and noise during pathogen replication. We show that failing to account for these factors leads to an underestimation of bottleneck sizes. We apply this method to an existing data set of human influenza virus infections, showing that transmission is governed by a loose, but highly variable, transmission bottleneck whose size is positively associated with the severity of infection of the donor. Beyond advancing our understanding of influenza virus transmission, we hope that this work will provide a standardized statistical approach for bottleneck size estimation for viral pathogens.

Evidence for history-dependence of influenza pandemic emergence

Influenza A viruses have caused a number of global pandemics, with considerable mortality in humans. Here, we analyse the time periods between influenza pandemics since 1700 under different assumptions to determine whether the emergence of new pandemic strains is a memoryless or history-dependent process. Bayesian model selection between exponential and gamma distributions for these time periods gives support to the hypothesis of history-dependence under eight out of nine sets of modelling assumptions. Using the fitted parameters to make predictions shows a high level of variability in the modelled number of pandemics from 2010–2110. The approach we take here relies on limited data, so is uncertain, but it provides cheap, safe and direct evidence relating to pandemic emergence, a field where indirect measurements are often made at great risk and cost.

The effective rate of influenza reassortment is limited during human infection

We characterise the evolutionary dynamics of influenza infection described by viral sequence data collected from two challenge studies conducted in human hosts. Viral sequence data were collected at regular intervals from infected hosts. Changes in the sequence data observed across time show that the within-host evolution of the virus was driven by the reversion of variants acquired during previous passaging of the virus. Treatment of some patients with oseltamivir on the first day of infection did not lead to the emergence of drug resistance variants in patients. Using an evolutionary model, we inferred the effective rate of reassortment between viral segments, measuring the extent to which randomly chosen viruses within the host exchange genetic material. We find strong evidence that the rate of effective reassortment is low, such that genetic associations between polymorphic loci in different segments are preserved during the course of an infection in a manner not compatible with epistasis. Combining our evidence with that of previous studies we suggest that spatial heterogeneity in the viral population may reduce the extent to which reassortment is observed. Our results do not contradict previous findings of high rates of viral reassortment in vitro and in small animal studies, but indicate that in human hosts the effective rate of reassortment may be substantially more limited.

The influenza virus is an important cause of disease in the human population. During the course of an infection the virus can evolve rapidly. An important mechanism of viral evolution is reassortment, whereby different segments of the influenza genome are shuffled with other segments, producing new viral combinations. Here we study natural selection and reassortment during the course of infections occurring in human hosts. Examining viral genome sequence data from these infections, we note that genetic variants that were acquired during the growth of viruses in culture are selected against in the human host. In addition, we find evidence that the effective rate of reassortment is low. We suggest that the spatial separation between viruses in different parts of the host airway may limit the extent to which genetically distinct segments reassort with one another. Within the global population of influenza viruses, reassortment remains an important factor. However, reassortment is not so rapid as to exclude the possibility of interactions between genome segments affecting the course of influenza evolution during a single infection.

Viral factors in influenza pandemic risk assessment

The threat of an influenza A virus pandemic stems from continual virus spillovers from reservoir species, a tiny fraction of which spark sustained transmission in humans. To date, no pandemic emergence of a new influenza strain has been preceded by detection of a closely related precursor in an animal or human. Nonetheless, influenza surveillance efforts are expanding, prompting a need for tools to assess the pandemic risk posed by a detected virus. The goal would be to use genetic sequence and/or biological assays of viral traits to identify those non-human influenza viruses with the greatest risk of evolving into pandemic threats, and/or to understand drivers of such evolution, to prioritize pandemic prevention or response measures. We describe such efforts, identify progress and ongoing challenges, and discuss three specific traits of influenza viruses (hemagglutinin receptor binding specificity, hemagglutinin pH of activation, and polymerase complex efficiency) that contribute to pandemic risk.

Genomic Analysis of the Emergence, Evolution, and Spread of Human Respiratory RNA Viruses

The emergence and reemergence of rapidly evolving RNA viruses-particularly those responsible for respiratory diseases, such as influenza viruses and coronaviruses-pose a significant threat to global health, including the potential of major pandemics. Importantly, recent advances in high-throughput genome sequencing enable researchers to reveal the genomic diversity of these viral pathogens at much lower cost and with much greater precision than they could before. In particular, the genome sequence data generated allow inferences to be made on the molecular basis of viral emergence, evolution, and spread in human populations in real time. In this review, we introduce recent computational methods that analyze viral genomic data, particularly in combination with metadata such as sampling time, geographic location, and virulence. We then outline the insights these analyses have provided into the fundamental patterns and processes of evolution and emergence in human respiratory RNA viruses, as well as the major challenges in such genomic analyses.

What can imaging tell us about influenza virus transmission and protection?

The emergence of zoonotic influenza infections is a constant threat to public health. One of the major determinants of pandemic potential is the ability to transmit from animal to human and/or human to human via respiratory droplets. Understanding viral tropism and spread is crucial for predicting which viruses represent the most threatening to human health. Recently, a replication-competent influenza reporter virus was described that permitted in vivo imaging and visualization of infection in ferrets for the first time. This review will focus on the applications of luminescent reporter viruses toward understanding transmission of influenza viruses and development of therapeutic interventions.

Contact transmission of influenza virus between ferrets imposes a looser bottleneck than respiratory droplet transmission allowing propagation of antiviral resistance

Influenza viruses cause annual seasonal epidemics and occasional pandemics. It is important to elucidate the stringency of bottlenecks during transmission to shed light on mechanisms that underlie the evolution and propagation of antigenic drift, host range switching or drug resistance. The virus spreads between people by different routes, including through the air in droplets and aerosols, and by direct contact. By housing ferrets under different conditions, it is possible to mimic various routes of transmission. Here, we inoculated donor animals with a mixture of two viruses whose genomes differed by one or two reverse engineered synonymous mutations, and measured the transmission of the mixture to exposed sentinel animals. Transmission through the air imposed a tight bottleneck since most recipient animals became infected by only one virus. In contrast, a direct contact transmission chain propagated a mixture of viruses suggesting the dose transferred by this route was higher. From animals with a mixed infection of viruses that were resistant and sensitive to the antiviral drug oseltamivir, resistance was propagated through contact transmission but not by air. These data imply that transmission events with a looser bottleneck can propagate minority variants and may be an important route for influenza evolution.

Complexities in Ferret Influenza Virus Pathogenesis and Transmission Models

Ferrets are widely employed to study the pathogenicity, transmissibility, and tropism of influenza viruses. However, inherent variations in inoculation methods, sampling schemes, and experimental designs are often overlooked when contextualizing or aggregating data between laboratories, leading to potential confusion or misinterpretation of results. Here, we provide a comprehensive overview of parameters to consider when planning an experiment using ferrets, collecting data from the experiment, and placing results in context with previously performed studies. This review offers information that is of particular importance for researchers in the field who rely on ferret data but do not perform the experiments themselves. Furthermore, this review highlights the breadth of experimental designs and techniques currently available to study influenza viruses in this model, underscoring the wide heterogeneity of protocols currently used for ferret studies while demonstrating the wealth of information which can benefit risk assessments of emerging influenza viruses.

Using the Ferret as an Animal Model for Investigating Influenza Antiviral Effectiveness

The concern of the emergence of a pandemic influenza virus has sparked an increased effort toward the development and testing of novel influenza antivirals. Central to this is the animal model of influenza infection, which has played an important role in understanding treatment effectiveness and the effect of antivirals on host immune responses. Among the different animal models of influenza, ferrets can be considered the most suitable for antiviral studies as they display most of the human-like symptoms following influenza infections, they can be infected with human influenza virus without prior viral adaptation and have the ability to transmit influenza virus efficiently between one another. However, an accurate assessment of the effectiveness of an antiviral treatment in ferrets is dependent on three major experimental considerations encompassing firstly, the volume and titer of virus, and the route of viral inoculation. Secondly, the route and dose of drug administration, and lastly, the different methods used to assess clinical symptoms, viral shedding kinetics and host immune responses in the ferrets. A good understanding of these areas is necessary to achieve data that can accurately inform the human use of influenza antivirals. In this review, we discuss the current progress and the challenges faced in these three major areas when using the ferret model to measure influenza antiviral effectiveness.