Temporally structured metapopulation dynamics and persistence of influenza A H3N2 virus in humans

Local patterns of spread of influenza A H3N2 virus in coastal Kenya over a 1-year period revealed through virus sequence data

The patterns of spread of influenza A viruses in local populations in tropical and sub-tropical regions are unclear due to sparsity of representative spatiotemporal sequence data. We sequenced and analyzed 58 influenza A(H3N2) virus genomes sampled between December 2015 and December 2016 from nine health facilities within the Kilifi Health and Demographic Surveillance System (KHDSS), a predominantly rural region, covering approximately 891 km2 along the Kenyan coastline. The genomes were compared with 1571 contemporaneous global sequences from 75 countries. We observed at least five independent introductions of A(H3N2) viruses into the region during the one-year period, with the importations originating from Africa, Europe, and North America. We also inferred 23 virus location transition events between the nine facilities included in the study. International virus imports into the study area were captured at the facilities of Chasimba, Matsangoni, Mtondia, and Mavueni, while all four exports from the region were captured from the Chasimba facility, all occurring to Africa destinations. A strong spatial clustering of virus strains at all locations was observed associated with local evolution. Our study shows that influenza A(H3N2) virus epidemics in local populations appear to be characterized by limited introductions followed by significant local spread and evolution. Knowledge of the viral lineages that circulate within specific populations in understudied tropical and subtropical regions is required to understand the full diversity and global ecology of influenza viruses and to inform vaccination strategies within these populations.

Phylogeography and reassortment patterns of human influenza A viruses in sub-Saharan Africa

The role of sub-Saharan Africa in the global spread of influenza viruses remains unclear due to insufficient spatiotemporal sequence data. Here, we analyzed 222 codon-complete sequences of influenza A viruses (IAVs) sampled between 2011 and 2013 from five countries across sub-Saharan Africa (Kenya, Zambia, Mali, Gambia, and South Africa); these genomes were compared with 1209 contemporaneous global genomes using phylogeographical approaches. The spread of influenza in sub-Saharan Africa was characterized by (i) multiple introductions of IAVs into the region over consecutive influenza seasons, with viral importations originating from multiple global geographical regions, some of which persisted in circulation as intra-subtype reassortants for multiple seasons, (ii) virus transfer between sub-Saharan African countries, and (iii) virus export from sub-Saharan Africa to other geographical regions. Despite sparse data from influenza surveillance in sub-Saharan Africa, our findings support the notion that influenza viruses persist as temporally structured migrating metapopulations in which new virus strains can emerge in any geographical region, including in sub-Saharan Africa; these lineages may have been capable of dissemination to other continents through a globally migrating virus population. Further knowledge of the viral lineages that circulate within understudied sub-Saharan Africa regions is required to inform vaccination strategies in those regions.

Measures of population immunity can predict the dominant clade of influenza A (H3N2) in the 2017-2018 season and reveal age-associated differences in susceptibility and antibody-binding specificity

Background

For antigenically variable pathogens such as influenza, strain fitness is partly determined by the relative availability of hosts susceptible to infection with that strain compared to others. Antibodies to the hemagglutinin (HA) and neuraminidase (NA) confer substantial protection against influenza infection. We asked if a cross-sectionalantibody-derived estimate of population susceptibility to different clades of influenza A (H3N2) could predict the success of clades in the following season.

Methods

We collected sera from 483 healthy individuals aged 1 to 90 years in the summer of 2017 and analyzed neutralizing responses to the HA and NA of representative strains using Focus Reduction Neutralization Tests (FNRT) and Enzyme-Linked Lectin Assays (ELLA). We estimated relative population-average and age-specific susceptibilities to circulating viral clades and compared those estimates to changes in clade frequencies in the following 2017-18 season.

Results

The clade to which neutralizing antibody titers were lowest, indicating greater population susceptibility, dominated the next season. Titers to different HA and NA clades varied dramatically between individuals but showed significant associations with age, suggesting dependence on correlated past exposures.

Conclusions

This study indicates how representative measures of population immunity might improve evolutionary forecasts and inform selective pressures on influenza.

Competition to Explain Stable Prevalence of Seasonal Viral Respiratory Infections in Temperate Climates

The prevalence of seasonal viral respiratory infections in temperate climates is relatively stable, but individual viruses vary. This phenomenon is not explained via the conventional view of influenza seasonality which is still incomplete. The viral-flow theory, an outsider theory about the seasonality of influenza, where insects buffer viruses, is able to explain the stable prevalence of viral respiratory infections. Alternative hypotheses to explain this phenomenon are discussed.

MASCOT-Skyline integrates population and migration dynamics to enhance phylogeographic reconstructions

The spread of infectious diseases is shaped by spatial and temporal aspects, such as host population structure or changes in the transmission rate or number of infected individuals over time. These spatiotemporal dynamics are imprinted in the genome of pathogens and can be recovered from those genomes using phylodynamics methods. However, phylodynamic methods typically quantify either the temporal or spatial transmission dynamics, which leads to unclear biases, as one can potentially not be inferred without the other. Here, we address this challenge by introducing a structured coalescent skyline approach, MASCOT-Skyline that allows us to jointly infer spatial and temporal transmission dynamics of infectious diseases using Markov chain Monte Carlo inference. To do so, we model the effective population size dynamics in different locations using a non-parametric function, allowing us to approximate a range of population size dynamics. We show, using a range of different viral outbreak datasets, potential issues with phylogeographic methods. We then use these viral datasets to motivate simulations of outbreaks that illuminate the nature of biases present in the different phylogeographic methods. We show that spatial and temporal dynamics should be modeled jointly even if one seeks to recover just one of the two. Further, we showcase conditions under which we can expect phylogeographic analyses to be biased, particularly different subsampling approaches, as well as provide recommendations of when we can expect them to perform well. We implemented MASCOT-Skyline as part of the open-source software package MASCOT for the Bayesian phylodynamics platform BEAST2.

Approaches and challenges to inferring the geographical source of infectious disease outbreaks using genomic data

Genomic data hold increasing potential in the elucidation of transmission dynamics and geographical sources of infectious disease outbreaks. Phylogeographic methods that use epidemiological and genomic data obtained from surveillance enable us to infer the history of spatial transmission that is naturally embedded in the topology of phylogenetic trees as a record of the dispersal of infectious agents between geographical locations. In this Review, we provide an overview of phylogeographic approaches widely used for reconstructing the geographical sources of outbreaks of interest. These approaches can be classified into ancestral trait or state reconstruction and structured population models, with structured population models including popular structured coalescent and birth-death models. We also describe the major challenges associated with sequencing technologies, surveillance strategies, data sharing, and analysis frameworks that became apparent during the generation of large-scale genomic data in recent years, extending beyond inference approaches. Finally, we highlight the role of genomic data in geographical source inference and clarify how this enhances understanding and molecular investigations of outbreak sources.

Bidirectional Movement of Emerging H5N8 Avian Influenza Viruses Between Europe and Asia via Migratory Birds Since Early 2020

Migratory birds play a critical role in the rapid spread of highly pathogenic avian influenza (HPAI) H5N8 virus clade 2.3.4.4 across Eurasia. Elucidating the timing and pattern of virus transmission is essential therefore for understanding the spatial dissemination of these viruses. In this study, we surveyed >27,000 wild birds in China, tracked the year-round migration patterns of 20 bird species across China since 2006, and generated new HPAI H5N8 virus genomic data. Using this new data set, we investigated the seasonal transmission dynamics of HPAI H5N8 viruses across Eurasia. We found that introductions of HPAI H5N8 viruses to different Eurasian regions were associated with the seasonal migration of wild birds. Moreover, we report a backflow of HPAI H5N8 virus lineages from Europe to Asia, suggesting that Europe acts as both a source and a sink in the global HPAI virus transmission network.

On the lookout for influenza viruses in Italy during the 2021-2022 season: Along came A(H3N2) viruses with a new phylogenetic makeup of their hemagglutinin

AIMS

To assess influenza viruses (IVs) circulation and to evaluate A(H3N2) molecular evolution during the 2021-2022 season in Italy.

MATERIALS AND METHODS

12,393 respiratory specimens (nasopharyngeal swabs or broncho-alveolar lavages) collected from in/outpatients with influenza illness in the period spanning from January 1, 2022 (week 2022-01) to May 31, 2022 (week 2022-22) were analysed to identify IV genome and were molecularly characterized by 12 laboratories throughout Italy. A(H3N2) evolution was studied by conducting an in-depth phylogenetic analysis of the hemagglutinin (HA) gene sequences. The predicted vaccine efficacy (pVE) of vaccine strain against circulating A(H3N2) viruses was estimated using the sequence-based Pepitope model.

RESULTS

The overall IV-positive rate was 7.2% (894/12,393), all were type A IVs. Almost all influenza A viruses (846/894; 94.6%) were H3N2 that circulated in Italy with a clear epidemic trend, with 10% positivity rate threshold crossed for six consecutive weeks from week 2022-11 to week 2022-16. According to the phylogenetic analysis of a subset of A(H3N2) strains (n=161), the study HA sequences were distributed into five different genetic clusters, all of them belonging to the clade 3C.2a, sub-clade 3C.2a1 and the genetic subgroup 3C.2a1b.2a.2. The selective pressure analysis of A(H3N2) sequences showed evidence of diversifying selection particularly in the amino acid position 156. The comparison between the predicted amino acid sequence of the 2021-2022 vaccine strain (A/Cambodia/e0826360/2020) and the study strains revealed 65 mutations in 59 HA amino acid positions, including the substitution H156S and Y159N in antigenic site B, within major antigenic sites adjacent to the receptor-binding site, suggesting the presence of drifted strains. According to the sequence-based Pepitope model, antigenic site B was the dominant antigenic site and the p(VE) against circulating A(H3N2) viruses was estimated to be -28.9%.

DISCUSSION AND CONCLUSION

After a long period of very low IV activity since public health control measures have been introduced to face COVID-19 pandemic, along came A(H3N2) with a new phylogenetic makeup. Although the delayed 2021-2022 influenza season in Italy was characterized by a significant reduction of the width of the epidemic curve and in the intensity of the influenza activity compared to historical data, a marked genetic diversity of the HA of circulating A(H3N2) strains was observed. The identification of the H156S and Y159N substitutions within the main antigenic sites of most HA sequences also suggested the circulation of drifted variants with respect to the 2021-2022 vaccine strain. Molecular surveillance plays a critical role in the influenza surveillance architecture and it has to be strengthened also at local level to timely assess vaccine effectiveness and detect novel strains with potential impact on public health.

Nonpharmaceutical interventions for COVID-19 disrupt the dynamic balance between influenza A virus and human immunity

During the COVID-19 epidemic, nonpharmaceutical interventions (NPIs) blocked the transmission route of respiratory diseases. This study aimed to investigate the impact of NPIs on the influenza A virus (IAV) outbreak. The present study enrolled all children with respiratory tract infections who came to the Children's Hospital of Zhejiang University between January 2019 and July 2022. A direct immunofluorescence assay kit detected IAV. Virus isolation and Sanger sequencing were performed. From June to July 2022, in Hangzhou, China, the positive rate of IAV infection in children has increased rapidly, reaching 30.41%, and children over 3 years old are the main infected population, accounting for 75% of the total number of infected children. Influenza A (H3N2) viruses are representative strains during this period. In this outbreak, H3N2 was isolated from a cluster of its own and is highly homologous with A/South_Dakota/22/2022 (2021-2022 Northern Hemisphere). Between isolated influenza A (H3N2) viruses and A/South_Dakota/22/2022, the nucleotide homology of the HA gene ranged from 97.3% to 97.5%; the amino acid homology was 97%-97.2%, and the genetic distance of nucleotides ranged from 0.05 to 0.052. Compared with A/South_Dakota/22/2022, the isolated H3N2 showed S156H, N159Y, I160T, D186S, S198P, I48T, S53D, and K171N mutations. There was no variation in 13 key amino acid sites associated with neuraminidase inhibitor resistance in NA protein. Long-term NPIs have significantly affected the evolution and transmission of the influenza virus and human immunity, breaking the dynamic balance between the IAV and human immunity.

Increased genetic variation of A(H3N2) virus from influenza surveillance at the end of the 2016/2017 season for Shanghai port, China

Influenza A(H3N2) virus exhibited complex seasonal patterns to evade pre-existing antibodies, resulting in changes in the antigenicity of the viron surface protein hemagglutinin (HA). To monitor the currently imported influenza viruses as well as to assess the capacity of health emergencies at the Shanghai port, we collected respiratory specimens of passengers from different countries and regions including some of Europe with influenza-like illness at the Shanghai port during 2016/2017, examined amino acid substitutions, and calculated the perfect-match vaccine efficacy using the p epitope model. Phylogenetic analysis of the HA genes revealed that influenza A(H3N2) viruses belonging to eight subclades were detected, and three amino acid substitutions in the subclade 3C.2a.4 were also added. Besides, two epidemic influenza virus strains were found in the 2016/2017 winter and 2016 summer. The results of lower predicted vaccine effectiveness in summer suggest that the imported A(H3N2) strains were not a good match for the A/Hong Kong/4801/2014 vaccine strain since the summer of 2017. Therefore, the Shanghai Port might stop the risk of the international spread of influenza for the first time, and curb the entry of A(H3N2) from overseas at the earliest stage of a probable influenza pandemic.

Genomic Epidemiology of Seasonal Influenza Circulation in China During Prolonged Border Closure from 2020 to 2021

China experienced a resurgence of seasonal influenza activity throughout 2021 despite intermittent control measures and prolonged international border closure. We show genomic evidence for multiple A(H3N2), A(H1N1), and B/Victoria transmission lineages circulating over 3 years, with the 2021 resurgence mainly driven by two B/Victoria clades. Phylodynamic analysis revealed unsampled ancestry prior to widespread outbreaks in December 2020, showing that influenza lineages can circulate cryptically under non-pharmaceutical interventions enacted against COVID-19. Novel haemagglutinin gene mutations and altered age profiles of infected individuals were observed, and Jiangxi province was identified as a major source for nationwide outbreaks. Following major holiday periods, fluctuations in the effective reproduction number were observed, underscoring the importance of influenza vaccination prior to holiday periods or travel. Extensive heterogeneity in seasonal influenza circulation patterns in China determined by historical strain circulation indicates that a better understanding of demographic patterns is needed for improving effective controls.

Molecular Epidemiology and Evolutionary Dynamics of Human Influenza Type-A Viruses in Africa: A Systematic Review

Genomic characterization of circulating influenza type-A viruses (IAVs) directs the selection of appropriate vaccine formulations and early detection of potentially pandemic virus strains. However, longitudinal data on the genomic evolution and transmission of IAVs in Africa are scarce, limiting Africa's benefits from potential influenza control strategies. We searched seven databases: African Journals Online, Embase, Global Health, Google Scholar, PubMed, Scopus, and Web of Science according to the PRISMA guidelines for studies that sequenced and/or genomically characterized Africa IAVs. Our review highlights the emergence and diversification of IAVs in Africa since 1993. Circulating strains continuously acquired new amino acid substitutions at the major antigenic and potential N-linked glycosylation sites in their hemagglutinin proteins, which dramatically affected vaccine protectiveness. Africa IAVs phylogenetically mixed with global strains forming strong temporal and geographical evolution structures. Phylogeographic analyses confirmed that viral migration into Africa from abroad, especially South Asia, Europe, and North America, and extensive local viral mixing sustained the genomic diversity, antigenic drift, and persistence of IAVs in Africa. However, the role of reassortment and zoonosis remains unknown. Interestingly, we observed substitutions and clades and persistent viral lineages unique to Africa. Therefore, Africa's contribution to the global influenza ecology may be understated. Our results were geographically biased, with data from 63% (34/54) of African countries. Thus, there is a need to expand influenza surveillance across Africa and prioritize routine whole-genome sequencing and genomic analysis to detect new strains early for effective viral control.

Human seasonal influenza under COVID-19 and the potential consequences of influenza lineage elimination

Annual epidemics of seasonal influenza cause hundreds of thousands of deaths, high levels of morbidity, and substantial economic loss. Yet, global influenza circulation has been heavily suppressed by public health measures and travel restrictions since the onset of the COVID-19 pandemic. Notably, the influenza B/Yamagata lineage has not been conclusively detected since April 2020, and A(H3N2), A(H1N1), and B/Victoria viruses have since circulated with considerably less genetic diversity. Travel restrictions have largely confined regional outbreaks of A(H3N2) to South and Southeast Asia, B/Victoria to China, and A(H1N1) to West Africa. Seasonal influenza transmission lineages continue to perish globally, except in these select hotspots, which will likely seed future epidemics. Waning population immunity and sporadic case detection will further challenge influenza vaccine strain selection and epidemic control. We offer a perspective on the potential short- and long-term evolutionary dynamics of seasonal influenza and discuss potential consequences and mitigation strategies as global travel gradually returns to pre-pandemic levels.

Subtype H3N2 Influenza A Viruses: An Unmet Challenge in the Western Pacific

Subtype H3N2 influenza A viruses (A(H3N2)) have been the dominant strain in some countries in the Western Pacific region since the 2009 influenza A(H1N1) pandemic. Vaccination is the most effective way to prevent influenza; however, low vaccine effectiveness has been reported in some influenza seasons, especially for A(H3N2). Antigenic mismatch introduced by egg-adaptation during vaccine production between the vaccine and circulating viral stains is one of the reasons for low vaccine effectiveness. Here we review the extent of this phenomenon, the underlying molecular mechanisms and discuss recent strategies to ameliorate this, including new vaccine platforms that may provide better protection and should be considered to reduce the impact of A(H3N2) in the Western Pacific region.

Circulation patterns of human seasonal Influenza A viruses in Chile before H1N1pdm09 pandemic

Understanding the diversity and circulation dynamics of seasonal influenza viruses is key to public health decision-making. The limited genetic information of pre-pandemic seasonal IAVs in Chile has made it difficult to accurately reconstruct the phylogenetic relationships of these viruses within the country. The objective of this study was to determine the genetic diversity of pre-pandemic human seasonal IAVs in Chile. We sequenced the complete genome of 42 historic IAV obtained between 1996 and 2007. The phylogeny was determined using HA sequences and complemented using other segments. Time-scale phylogenetic analyses revealed that the diversity of pre-pandemic human seasonal IAVs in Chile was influenced by continuous introductions of new A/H1N1 and A/H3N2 lineages and constant viral exchange between Chile and other countries every year. These results provide important knowledge about genetic diversity and evolutionary patterns of pre-pandemic human seasonal IAVs in Chile, which can help design optimal surveillance systems and prevention strategies. However, future studies with current sequences should be conducted.

Characterizing the Countrywide Epidemic Spread of Influenza A(H1N1)pdm09 Virus in Kenya between 2009 and 2018

The spatiotemporal patterns of spread of influenza A(H1N1)pdm09 viruses on a countrywide scale are unclear in many tropical/subtropical regions mainly because spatiotemporally representative sequence data are lacking. We isolated, sequenced, and analyzed 383 A(H1N1)pdm09 viral genomes from hospitalized patients between 2009 and 2018 from seven locations across Kenya. Using these genomes and contemporaneously sampled global sequences, we characterized the spread of the virus in Kenya over several seasons using phylodynamic methods. The transmission dynamics of A(H1N1)pdm09 virus in Kenya were characterized by (i) multiple virus introductions into Kenya over the study period, although only a few of those introductions instigated local seasonal epidemics that then established local transmission clusters, (ii) persistence of transmission clusters over several epidemic seasons across the country, (iii) seasonal fluctuations in effective reproduction number (Re) associated with lower number of infections and seasonal fluctuations in relative genetic diversity after an initial rapid increase during the early pandemic phase, which broadly corresponded to epidemic peaks in the northern and southern hemispheres, (iv) high virus genetic diversity with greater frequency of seasonal fluctuations in 2009-2011 and 2018 and low virus genetic diversity with relatively weaker seasonal fluctuations in 2012-2017, and (v) virus spread across Kenya. Considerable influenza virus diversity circulated within Kenya, including persistent viral lineages that were unique to the country, which may have been capable of dissemination to other continents through a globally migrating virus population. Further knowledge of the viral lineages that circulate within understudied low-to-middle-income tropical and subtropical regions is required to understand the full diversity and global ecology of influenza viruses in humans and to inform vaccination strategies within these regions.

Spatiotemporal invasion dynamics of SARS-CoV-2 lineage B.1.1.7 emergence

Understanding the causes and consequences of the emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants of concern is crucial to pandemic control yet difficult to achieve because they arise in the context of variable human behavior and immunity. We investigated the spatial invasion dynamics of lineage B.1.1.7 by jointly analyzing UK human mobility, virus genomes, and community-based polymerase chain reaction data. We identified a multistage spatial invasion process in which early B.1.1.7 growth rates were associated with mobility and asymmetric lineage export from a dominant source location, enhancing the effects of B.1.1.7's increased intrinsic transmissibility. We further explored how B.1.1.7 spread was shaped by nonpharmaceutical interventions and spatial variation in previous attack rates. Our findings show that careful accounting of the behavioral and epidemiological context within which variants of concern emerge is necessary to interpret correctly their observed relative growth rates.

Genetic and evolutionary analysis of SARS-CoV-2 circulating in the region surrounding Islamabad, Pakistan

Genomic epidemiology of Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) has provided global epidemiological insight into the COVID-19 pandemic since it began. Sequencing of the virus has been performed at scale, with many countries depositing data into open access repositories to enable in-depth global phylogenetic analysis. To contribute to these efforts, we established an Oxford Nanopore Technologies (ONT) sequencing capability at the National Institutes of Health (NIH), Pakistan. This study highlights multiple SARS-CoV-2 lineages co-circulating during the peak of a second COVID-19 wave in Pakistan (Nov 2020-Feb 2021), with virus origins traced to the United States of America and Saudi Arabia. Ten SARS-CoV-2 positive samples were used for ONT library preparation. Sequence and phylogenetic analysis determined that the patients were infected with lineage B.1.1.250, originally identified in the United Kingdom and Bangladesh during March and April of 2020, and in circulation until the time of this study in Europe, USA and Australia. Lineage B.1.261 was originally identified in Saudi Arabia with widespread local dissemination in Pakistan. One sample clustered with the parental B.1 lineage and the other with lineage B.6 originally from Singapore. In the future, monitoring the evolutionary dynamics of circulating lineages in Pakistan will enable improved tracing of the viral spread, changing trends of their expansion trajectories, persistence, changes in their demographic dynamics, and provide guidance for better implementation of control measures.

Establishment and lineage dynamics of the SARS-CoV-2 epidemic in the UK

The United Kingdom's COVID-19 epidemic during early 2020 was one of world's largest and was unusually well represented by virus genomic sampling. We determined the fine-scale genetic lineage structure of this epidemic through analysis of 50,887 severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) genomes, including 26,181 from the UK sampled throughout the country's first wave of infection. Using large-scale phylogenetic analyses combined with epidemiological and travel data, we quantified the size, spatiotemporal origins, and persistence of genetically distinct UK transmission lineages. Rapid fluctuations in virus importation rates resulted in >1000 lineages; those introduced prior to national lockdown tended to be larger and more dispersed. Lineage importation and regional lineage diversity declined after lockdown, whereas lineage elimination was size-dependent. We discuss the implications of our genetic perspective on transmission dynamics for COVID-19 epidemiology and control.

Characterising the epidemic spread of influenza A/H3N2 within a city through phylogenetics

Infecting large portions of the global population, seasonal influenza is a major burden on societies around the globe. While the global source sink dynamics of the different seasonal influenza viruses have been studied intensively, its local spread remains less clear. In order to improve our understanding of how influenza is transmitted on a city scale, we collected an extremely densely sampled set of influenza sequences alongside patient metadata. To do so, we sequenced influenza viruses isolated from patients of two different hospitals, as well as private practitioners in Basel, Switzerland during the 2016/2017 influenza season. The genetic sequences reveal that repeated introductions into the city drove the influenza season. We then reconstruct how the effective reproduction number changed over the course of the season. While we did not find that transmission dynamics in Basel correlate with humidity or school closures, we did find some evidence that it may positively correlated with temperature. Alongside the genetic sequence data that allows us to see how individual cases are connected, we gathered patient information, such as the age or household status. Zooming into the local transmission outbreaks suggests that the elderly were to a large extent infected within their own transmission network. In the remaining transmission network, our analyses suggest that school-aged children likely play a more central role than pre-school aged children. These patterns will be valuable to plan interventions combating the spread of respiratory diseases within cities given that similar patterns are observed for other influenza seasons and cities.

Distance metrics for ranked evolutionary trees

Genealogical tree modeling is essential for estimating evolutionary parameters in population genetics and phylogenetics. Recent mathematical results concerning ranked genealogies without leaf labels unlock opportunities in the analysis of evolutionary trees. In particular, comparisons between ranked genealogies facilitate the study of evolutionary processes of different organisms sampled at multiple time periods. We propose metrics on ranked tree shapes and ranked genealogies for lineages isochronously and heterochronously sampled. Our proposed tree metrics make it possible to conduct statistical analyses of ranked tree shapes and timed ranked tree shapes or ranked genealogies. Such analyses allow us to assess differences in tree distributions, quantify estimation uncertainty, and summarize tree distributions. We show the utility of our metrics via simulations and an application in infectious diseases.

Bayesian inference of reassortment networks reveals fitness benefits of reassortment in human influenza viruses

Genetic recombination processes, such as reassortment, make it complex or impossible to use standard phylogenetic and phylodynamic methods. This is due to the fact that the shared evolutionary history of individuals has to be represented by a phylogenetic network instead of a tree. We therefore require novel approaches that allow us to coherently model these processes and that allow us to perform inference in the presence of such processes. Here, we introduce an approach to infer reassortment networks of segmented viruses using a Markov chain Monte Carlo approach. Our approach allows us to study different aspects of the reassortment process and allows us to show fitness benefits of reassortment events in seasonal human influenza viruses.

Reassortment is an important source of genetic diversity in segmented viruses and is the main source of novel pathogenic influenza viruses. Despite this, studying the reassortment process has been constrained by the lack of a coherent, model-based inference framework. Here, we introduce a coalescent-based model that allows us to explicitly model the joint coalescent and reassortment process. In order to perform inference under this model, we present an efficient Markov chain Monte Carlo algorithm to sample rooted networks and the embedding of phylogenetic trees within networks. This algorithm provides the means to jointly infer coalescent and reassortment rates with the reassortment network and the embedding of segments in that network from full-genome sequence data. Studying reassortment patterns of different human influenza datasets, we find large differences in reassortment rates across different human influenza viruses. Additionally, we find that reassortment events predominantly occur on selectively fitter parts of reassortment networks showing that on a population level, reassortment positively contributes to the fitness of human influenza viruses.

The Ecology and Evolution of Influenza Viruses

The patterns and processes of influenza virus evolution are of fundamental importance, underpinning such traits as the propensity to emerge in new host species and the ability to rapidly generate antigenic variation. Herein, we review key aspects of the ecology and evolution of influenza viruses. We begin with an exploration of the origins of influenza viruses within the orthomyxoviruses, showing how our perception of the evolutionary history of these viruses has been transformed with metagenomic sequencing. We then outline the diversity of virus subtypes in different species and the processes by which these viruses have emerged in new hosts, with a particular focus on the role played by segment reassortment. We then turn our attention to documenting the spread and phylodynamics of seasonal influenza A and B viruses in human populations, including the drivers of antigenic evolution, and finish with a discussion of virus diversity and evolution at the scale of individual hosts.

Massive parallelization boosts big Bayesian multidimensional scaling

Big Bayes is the computationally intensive co-application of big data and large, expressive Bayesian models for the analysis of complex phenomena in scientific inference and statistical learning. Standing as an example, Bayesian multidimensional scaling (MDS) can help scientists learn viral trajectories through space-time, but its computational burden prevents its wider use. Crucial MDS model calculations scale quadratically in the number of observations. We partially mitigate this limitation through massive parallelization using multi-core central processing units, instruction-level vectorization and graphics processing units (GPUs). Fitting the MDS model using Hamiltonian Monte Carlo, GPUs can deliver more than 100-fold speedups over serial calculations and thus extend Bayesian MDS to a big data setting. To illustrate, we employ Bayesian MDS to infer the rate at which different seasonal influenza virus subtypes use worldwide air traffic to spread around the globe. We examine 5392 viral sequences and their associated 14 million pairwise distances arising from the number of commercial airline seats per year between viral sampling locations. To adjust for shared evolutionary history of the viruses, we implement a phylogenetic extension to the MDS model and learn that subtype H3N2 spreads most effectively, consistent with its epidemic success relative to other seasonal influenza subtypes. Finally, we provide MassiveMDS, an open-source, stand-alone C++ library and rudimentary R package, and discuss program design and high-level implementation with an emphasis on important aspects of computing architecture that become relevant at scale.

Dynamic interactions of influenza viruses in Hong Kong during 1998-2018

Influenza epidemics cause substantial morbidity and mortality every year worldwide. Currently, two influenza A subtypes, A(H1N1) and A(H3N2), and type B viruses co-circulate in humans and infection with one type/subtype could provide cross-protection against the others. However, it remains unclear how such ecologic competition via cross-immunity and antigenic mutations that allow immune escape impact influenza epidemic dynamics at the population level. Here we develop a comprehensive model-inference system and apply it to study the evolutionary and epidemiological dynamics of the three influenza types/subtypes in Hong Kong, a city of global public health significance for influenza epidemic and pandemic control. Utilizing long-term influenza surveillance data since 1998, we are able to estimate the strength of cross-immunity between each virus-pairs, the timing and frequency of punctuated changes in population immunity in response to antigenic mutations in influenza viruses, and key epidemiological parameters over the last 20 years including the 2009 pandemic. We find evidence of cross-immunity in all types/subtypes, with strongest cross-immunity from A(H1N1) against A(H3N2). Our results also suggest that A(H3N2) may undergo antigenic mutations in both summers and winters and thus monitoring the virus in both seasons may be important for vaccine development. Overall, our study reveals intricate epidemiological interactions and underscores the importance of simultaneous monitoring of population immunity, incidence rates, and viral genetic and antigenic changes.

A brief history of bird flu

In 1918, a strain of influenza A virus caused a human pandemic resulting in the deaths of 50 million people. A century later, with the advent of sequencing technology and corresponding phylogenetic methods, we know much more about the origins, evolution and epidemiology of influenza epidemics. Here we review the history of avian influenza viruses through the lens of their genetic makeup: from their relationship to human pandemic viruses, starting with the 1918 H1N1 strain, through to the highly pathogenic epidemics in birds and zoonoses up to 2018. We describe the genesis of novel influenza A virus strains by reassortment and evolution in wild and domestic bird populations, as well as the role of wild bird migration in their long-range spread. The emergence of highly pathogenic avian influenza viruses, and the zoonotic incursions of avian H5 and H7 viruses into humans over the last couple of decades are also described. The threat of a new avian influenza virus causing a human pandemic is still present today, although control in domestic avian populations can minimize the risk to human health.

This article is part of the theme issue ‘Modelling infectious disease outbreaks in humans, animals and plants: approaches and important themes’. This issue is linked with the subsequent theme issue ‘Modelling infectious disease outbreaks in humans, animals and plants: epidemic forecasting and control’.

Toxigenic Vibrio cholerae evolution and establishment of reservoirs in aquatic ecosystems

The spread of cholera in the midst of an epidemic is largely driven by direct transmission from person to person, although it is well-recognized that Vibrio cholerae is also capable of growth and long-term survival in aquatic ecosystems. While prior studies have shown that aquatic reservoirs are important in the persistence of the disease on the Indian subcontinent, an epidemiological view postulating that locally evolving environmental V. cholerae contributes to outbreaks outside Asia remains debated. The single-source introduction of toxigenic V. cholerae O1 in Haiti, one of the largest outbreaks occurring this century, with 812,586 suspected cases and 9,606 deaths reported through July 2018, provided a unique opportunity to evaluate the role of aquatic reservoirs and assess bacterial transmission dynamics across environmental boundaries. To this end, we investigated the phylogeography of both clinical and aquatic toxigenic V. cholerae O1 isolates and show robust evidence of the establishment of aquatic reservoirs as well as ongoing evolution of V. cholerae isolates from aquatic sites. Novel environmental lineages emerged from sequential population bottlenecks, carrying mutations potentially involved in adaptation to the aquatic ecosystem. Based on such empirical data, we developed a mixed-transmission dynamic model of V. cholerae, where aquatic reservoirs actively contribute to genetic diversification and epidemic emergence, which underscores the complexity of transmission pathways in epidemics and endemic settings and the need for long-term investments in cholera control at both human and environmental levels.

Evolutionary dynamics of influenza B strains detected from paediatric acute respiratory infections in central Vietnam

Influenza virus B belongs to the family Orthomyxoviridae with segmented negative-sense RNA genomes. Since 1970s, influenza B has diverged intoVictoria and Yamagata, which differs in antigenic and evolutionary characteristics. Yet, molecular-epidemiological information of influenza B from developing nations is limited. In central Vietnam, influenza A subtype-specific circulation pattern and clinical characteristics were previously described. However, molecular evolutionary characteristics of influenza B has not been discussed to date. We utilized the influenza B positives obtained from paediatric ARI surveillance during 2007-2013. Influenza B HA and NA genes were amplified, sequenced, and phylogenetic/molecular evolutionary analysis was performed using Maximum Likelihood and Bayesian MCMC. Phylodynamics analysis was performed with Bayesian Skyline Plot (BSP). Furthermore, we performed selection pressure analysis and estimated N-glycosylation sites. In the current study, overall positive rate for influenza B was 3.0%, and Victoria lineage immediately became predominant in post-A/H1N1pdm09 period. The noticeable shift in Victoria lineage WHO Group occurred. With respect to the evolutionary rate (substitutions/site/year), Victoria lineage HA gene was evolving faster than Yamagata lineage (2.43 × 10^-3 vs 2.00 × 10^-3). Furthermore, the evolutionary rate of Victoria Group 5 was greater than Group 1. BSP presented the rapid growth in Effective Population Size (EPS) of Victoria lineage occurred soon after the 1st A/H1N1pdm09 case was detected whereas the EPS of Yamagata lineage was stable for both genes. N-glycosylation pattern between lineages and among WHO Groups were slightly different, and HA gene had a total of 6 amino acid substitutions under positive section pressure (4 for Victoria and 2 for Yamagata). The current results highlight the importance of Victoria lineage in post-A/H1N1pdm09 period. Difference in evolutionary characteristics and phylodynamics may indicate lineage and WHO Group-specific evolutionary dynamics. It is necessary to further continue the molecular-epidemiological surveillance in local setting to gain a better understanding of local evolutionary characteristics of influenza B strains.

Co-circulation of influenza A(H1N1), A(H3N2), B(Yamagata) and B(Victoria) during the 2017-2018 influenza season in Zhejiang Province, China

Influenza is a major human respiratory pathogen. Due to the high levels of influenza-like illness (ILI) in Zhejiang, China, the control and prevention of influenza was challenging during the 2017-2018 season. To identify the clinical spectrum of illness related to influenza and characterise the circulating influenza virus strains during this period, the characteristics of ILI were studied. Viral sequencing and phylogenetic analyses were conducted to investigate the virus types, substitutions at the amino acid level and phylogenetic relationships between sequences. This study has shown that the 2017/18 influenza season was characterised by the co-circulation of influenza A (H1N1) pdm09, A (H3N2) and B viruses (both Yamagata and Victoria lineage). From week 36 of 2017 to week 12 of 2018, ILI cases accounted for 5.58% of the total number of outpatient and emergency patient visits at the surveillance sites. Several amino acid substitutions were detected. Vaccination mismatch may be a potential reason for the high percentage of ILI. Furthermore, it is likely that multiple viral introductions played a role in the endemic co-circulation of influenza in Zhejiang, China. More detailed information regarding the molecular epidemiology of influenza should be included in long-term influenza surveillance.

Divergent evolutionary trajectories of influenza B viruses underlie their contemporaneous epidemic activity

Two influenza B viruses (Victoria and Yamagata) cocirculate in humans and contribute to the estimated 290,000–650,000 annual influenza-attributed deaths. Here, we analysed influenza B genomic data to understand the causes of a recent surge in human influenza B infections. We found that evolution is acting differently on Yamagata and Victoria viruses and that this has led to the cocirculation of a diverse group of influenza B viruses. If this phenomenon continues, we could potentially witness the emergence of 3 or more distinct influenza B viruses that could require their own vaccine component, thereby complicating influenza vaccine formulation and highlighting the urgency of developing universal influenza vaccines.

Influenza B viruses have circulated in humans for over 80 y, causing a significant disease burden. Two antigenically distinct lineages (“B/Victoria/2/87-like” and “B/Yamagata/16/88-like,” termed Victoria and Yamagata) emerged in the 1970s and have cocirculated since 2001. Since 2015 both lineages have shown unusually high levels of epidemic activity, the reasons for which are unclear. By analyzing over 12,000 influenza B virus genomes, we describe the processes enabling the long-term success and recent resurgence of epidemics due to influenza B virus. We show that following prolonged diversification, both lineages underwent selective sweeps across the genome and have subsequently taken alternate evolutionary trajectories to exhibit epidemic dominance, with no reassortment between lineages. Hemagglutinin deletion variants emerged concomitantly in multiple Victoria virus clades and persisted through epistatic mutations and interclade reassortment—a phenomenon previously only observed in the 1970s when Victoria and Yamagata lineages emerged. For Yamagata viruses, antigenic drift of neuraminidase was a major driver of epidemic activity, indicating that neuraminidase-based vaccines and cross-reactivity assays should be employed to monitor and develop robust protection against influenza B morbidity and mortality. Overall, we show that long-term diversification and infrequent selective sweeps, coupled with the reemergence of hemagglutinin deletion variants and antigenic drift of neuraminidase, are factors that contributed to successful circulation of diverse influenza B clades. Further divergence of hemagglutinin variants with poor cross-reactivity could potentially lead to circulation of 3 or more distinct influenza B viruses, further complicating influenza vaccine formulation and highlighting the urgent need for universal influenza vaccines.

Novel Salmonella enterica Serovar Typhimurium Genotype Levels as Herald of Seasonal Salmonellosis Epidemics

We examined the population dynamics of Salmonella enterica serovar Typhimurium during seasonal salmonellosis epidemics in New South Wales, Australia, during 2009–2016. Of 15,626 isolates, 5%–20% consisted of novel genotypes. Seasons with salmonellosis epidemics were associated with a reduction in novel genotypes in the preceding winter and spring.

Metapopulation Model from Pathogen's Perspective: A Versatile Framework to Quantify Pathogen Transfer and Circulation between Environment and Hosts

Metapopulation models have been primarily explored in infectious disease epidemiology to study host subpopulation movements and between-host contact structures. They also have the potential to investigate environmental pathogen transferring. In this study, we demonstrate that metapopulation models serve as an ideal modeling framework to characterize and quantify pathogen transfer between environment and hosts. It therefore unifies host, pathogen, and environment, collectively known as the epidemiological triad, a fundamental concept in epidemiology. We develop a customizable and generalized pathogen-transferring model where pathogens dwell in and transferring (via contact) between environment and hosts. We analyze three specific case studies: pure pathogen transferring without pathogen demography, source-sink dynamics, and pathogen control via external disinfection. We demonstrate how pathogens circulate in the system between environment and hosts, as well as evaluate different controlling efforts for healthcare-associated infections (HAIs). For pure pathogen transferring, system equilibria can be derived analytically to explicitly quantify long-term pathogen distribution in the system. For source-sink dynamics and pathogen control via disinfection, we demonstrate that complete eradication of pathogens can be achieved, but the rates of converging to system equilibria differ based on specific model parameterization. Direct host-host pathogen transferring and within-host dynamics can be future directions of this modeling framework by adding specific modules.

Inferring the global phylodynamics of influenza A/H3N2 viruses in Taiwan

BACKGROUND/PURPOSE

Influenza A/H3N2 viruses are characterized by highly mutated RNA genomes. In this study, we focused on tracing the phylodynamics of Taiwanese strains over the past four decades.

METHODS

All Taiwanese H3N2 HA1 sequences and references were downloaded from public database. A Bayesian skyline plot (BSP) and phylogenetic tree were used to analyze the evolutionary history, and Bayesian phylogeographic analysis was applied to predict the spatiotemporal migrations of influenza outbreaks.

RESULTS

Genetic diversity was found to have peaked near the summer of 2009 in BSP, in addition to the two earlier reported ones in summer of 2005 and 2007. We predicted their spatiotemporal migrations and found the summer epidemic of 2005 from Korea, and 2007 and 2009 from the Western United States. BSP also predicted an elevated genetic diversity in 2015-2017. Quasispecies were found over approximately 20% of the strains included in this time span. In addition, a first-time seen N31S mutation was noted in Taiwan in 2016-2017.

CONCLUSION

We comprehensively investigated the evolutionary history of Taiwanese strains in 1979-2017. An epidemic caution could thus be raised if genetic diversity was found to have peaked. An example showed a newly-discovered cluster in 2016-2017 strains featuring a mutation N31S together with HA-160 quasispecies. Phylogeographic analysis, moreover, provided useful insights in tracing the possible source and migrations of these epidemics around the world. We demonstrated that Asian destinations including Taiwan were the immediate followers, while U.S. continent was predicted the origin of two summer epidemics in 2007 and 2009.

Nonannual seasonality of influenza-like illness in a tropical urban setting

BACKGROUND

In temperate and subtropical climates, respiratory diseases exhibit seasonal peaks in winter. In the tropics, with no winter, peak timings are irregular.

METHODS

To obtain a detailed picture of influenza-like illness (ILI) patterns in the tropics, we established an mHealth study in community clinics in Ho Chi Minh City (HCMC). During 2009-2015, clinics reported daily case numbers via SMS, with a subset performing molecular diagnostics for influenza virus. This real-time epidemiology network absorbs 6000 ILI reports annually, one or two orders of magnitude more than typical surveillance systems. A real-time online ILI indicator was developed to inform clinicians of the daily ILI activity in HCMC.

RESULTS

From August 2009 to December 2015, 63 clinics were enrolled and 36 920 SMS reports were received, covering approximately 1.7M outpatient visits. Approximately 10.6% of outpatients met the ILI case definition. ILI activity in HCMC exhibited strong nonannual dynamics with a dominant periodicity of 206 days. This was confirmed by time series decomposition, stepwise regression, and a forecasting exercise showing that median forecasting errors are 30%-40% lower when using a 206-day cycle. In ILI patients from whom nasopharyngeal swabs were taken, 31.2% were positive for influenza. There was no correlation between the ILI time series and the time series of influenza, influenza A, or influenza B (all P > 0.15).

CONCLUSION

This suggests, for the first time, that a nonannual cycle may be an essential driver of respiratory disease dynamics in the tropics. An immunological interference hypothesis is discussed as a potential underlying mechanism.

Frequent Genetic Mismatch between Vaccine Strains and Circulating Seasonal Influenza Viruses, Hong Kong, China, 1996-2012

The World Health Organization selects influenza vaccine compositions biannually to cater to peaks in temperate regions. In tropical and subtropical regions, where influenza seasonality varies and epidemics can occur year-round, the choice of vaccine remains uncertain. Our 17-year molecular epidemiologic survey showed that most influenza A(H3N2) (9/11) and B (6/7) vaccine strains had circulated in East Asia >1 year before inclusion into vaccines. Northern Hemisphere vaccine strains and circulating strains in East Asia were closely matched in 7 (20.6%) of 34 seasons for H3N2 and 5 (14.7%) of 34 seasons for B. Southern Hemisphere vaccines also had a low probability of matching (H3N2, 14.7%; B, 11.1%). Strain drift among seasons was common (H3N2, 41.2%; B, 35.3%), and biannual vaccination strategy (Northern Hemisphere vaccines in November followed by Southern Hemisphere vaccines in May) did not improve matching. East Asia is an important contributor to influenza surveillance but often has mismatch between vaccine and contemporarily circulating strains.

Estimating Vaccine-Driven Selection in Seasonal Influenza

Vaccination could be an evolutionary pressure on seasonal influenza if vaccines reduce the transmission rates of some ("targeted") strains more than others. In theory, more vaccinated populations should have a lower prevalence of targeted strains compared to less vaccinated populations. We tested for vaccine-induced selection in influenza by comparing strain frequencies between more and less vaccinated human populations. We defined strains in three ways: first as influenza types and subtypes, next as lineages of type B, and finally as clades of influenza A/H3N2. We detected spatial differences partially consistent with vaccine use in the frequencies of subtypes and types and between the lineages of influenza B, suggesting that vaccines do not select strongly among all these phylogenetic groups at regional scales. We did detect a significantly greater frequency of an H3N2 clade with known vaccine escape mutations in more vaccinated countries during the 2014⁻2015 season, which is consistent with vaccine-driven selection within the H3N2 subtype. Overall, we find more support for vaccine-driven selection when large differences in vaccine effectiveness suggest a strong effect size. Variation in surveillance practices across countries could obscure signals of selection, especially when strain-specific differences in vaccine effectiveness are small. Further examination of the influenza vaccine's evolutionary effects would benefit from improvements in epidemiological surveillance and reporting.

Evolutionary study and phylodynamic pattern of human influenza A/H3N2 virus in Indonesia from 2008 to 2010

Influenza viruses are by nature unstable with high levels of mutations. The sequential accumulation of mutations in the surface glycoproteins allows the virus to evade the neutralizing antibodies. The consideration of the tropics as the influenza reservoir where viral genetic and antigenic diversity are continually generated and reintroduced into temperate countries makes the study of influenza virus evolution in Indonesia essential. A total of 100 complete coding sequences (CDS) of Hemagglutinin (HA) and Neuraminidase (NA) genes of H3N2 virus were obtained from archived samples of Influenza-Like Illness (ILI) surveillance collected from 2008 to 2010. Our evolutionary and phylogenetic analyses provide insight into the dynamic changes of Indonesian H3N2 virus from 2008 to 2010. Obvious antigenic drift with typical ‘ladder-like’ phylogeny was observed with multiple lineages found in each year, suggesting co-circulation of H3N2 strains at different time periods. The mutational pattern of the Indonesian H3N2 virus was not geographically related as relatively low levels of mutations with similar pattern of relative genetic diversity were observed in various geographical origins. This study reaffirms that the existence of a particular lineage is most likely the result of adaptation or competitive exclusion among different host populations and combination of stochastic ecological factors, rather than its geographical origin alone.

Centennial review of influenza in Taiwan

The history of influenza in Taiwan can be traced up to the 1918 H1N1 Spanish flu pandemic, followed by several others including the 1957 H2N2, 1968 H3N2, and the 2009 new H1N1. A couple of avian influenza viruses of H5N1 and H7N9 also posed threats to the general public in Taiwan in the two recent decades. Nevertheless, two seasonal influenza A viruses and two lineages of influenza B viruses continue causing annual endemics one after the other, or appearing simultaneously. Their interplay provided interesting evolutionary trajectories for these viruses, allowing us to computationally model their global migrations together with the data collected elsewhere from different geographical locations. An island-wide laboratory-based surveillance network was also established since 2000 for systematically collecting and managing the disease and molecular epidemiology. Experiences learned from this network helped in encountering and managing newly emerging infectious diseases, including the 2003 SARS and 2009 H1N1 outbreaks.

A complex mosaic of enteroviruses shapes community-acquired hand, foot and mouth disease transmission and evolution within a single hospital

Human enteroviruses (EV) pose a major risk to public health. This is especially so in the Asia-Pacific region where increasing numbers of hand, foot and mouth disease (HFMD) cases and large outbreaks of severe neurological disease associated with EV-A71 have occurred. Despite their importance, key aspects of the emergence, epidemiology and evolution of EVs remain unclear, and most studies of EV evolution have focused on a limited number of genes. Here, we describe the genomic-scale evolution of EV-A viruses sampled from pediatric patients with mild disease attending a single hospital in western Sydney, Australia, over an 18-month period. This analysis revealed the presence of eight viral serotypes-Coxsackievirus (CV) A2, A4, A5, A6, A8, A10, A16 and EV-A71-with up to four different serotypes circulating in any 1 month. Despite an absence of large-scale outbreaks, high levels of geographical and temporal mixing of serotypes were identified. Phylogenetic analysis revealed that multiple strains of the same serotype were present in the community, and that this diversity was shaped by multiple introductions into the Sydney population, with only a single lineage of CV-A6 exhibiting in situ transmission over the entire study period. Genomic-scale analyses also revealed the presence of novel and historical EV recombinants. Notably, our analysis revealed no association between viral phylogeny, including serotype, and patient age, sex, nor disease severity (for uncomplicated disease). This study emphasizes the contribution of EV-A viruses other than EV-A71 to mild EV disease including HFMD in Australia and highlights the need for greater surveillance of these viruses to improve strategies for outbreak preparedness and vaccine design.

The effects of random taxa sampling schemes in Bayesian virus phylogeography

Public health researchers are often tasked with accurately and quickly identifying the location and time when an epidemic originated from a representative sample of nucleotide sequences. In this paper, we investigate multiple approaches to subsampling the sequence set when employing a Bayesian phylogeographic generalized linear model. Our results indicate that near-categorical posterior MCC estimates on the root can be obtained with replicate runs using 25-50% of the sequence data, and that including 90% of sequences does not necessarily entail more accurate inferences. We present the first analysis of predictor signal suppression and show how the ability to detect the influence of predictor variables is limited when sample size predictors are included in the models.

Clinical and Molecular Epidemiology of Human Parainfluenza Viruses 1-4 in Children from Viet Nam

HPIVs are serologically and genetically grouped into four species that account for up to 10% of all hospitalizations due to acute respiratory infection in children under the age of five. Genetic and epidemiological data for the four HPIVs derived from two pediatric cohorts in Viet Nam are presented. Respiratory samples were screened for HPIV1-4 by real-time PCR. Demographic and clinical data of patients infected with different HPIV were compared. We used a hemi-nested PCR approach to generate viral genome sequences from HPIV-positive samples and conducted a comprehensive phylogenetic analysis. In total, 170 samples tested positive for HPIV. HPIV3 was most commonly detected in our cohort and 80 co-detections of HPIV with other respiratory viruses were found. Phylogenetic analyses suggest local endemic circulation as well as punctuated introductions of new HPIV lineages. Viral gene flow analysis revealed that Viet Nam is a net importer of viral genetic diversity. Epidemiological analyses imply similar disease severity for all HPIV species. HPIV sequences from Viet Nam formed local clusters and were interspersed with sequences from diverse geographic regions. Combined, this new knowledge will help to investigate global HPIV circulation patterns in more detail and ultimately define more suitable vaccine strains.

The Structured Coalescent and Its Approximations

Phylogeographic methods can help reveal the movement of genes between populations of organisms. This has been widely done to quantify pathogen movement between different host populations, the migration history of humans, and the geographic spread of languages or gene flow between species using the location or state of samples alongside sequence data. Phylogenies therefore offer insights into migration processes not available from classic epidemiological or occurrence data alone. Phylogeographic methods have however several known shortcomings. In particular, one of the most widely used methods treats migration the same as mutation, and therefore does not incorporate information about population demography. This may lead to severe biases in estimated migration rates for data sets where sampling is biased across populations. The structured coalescent on the other hand allows us to coherently model the migration and coalescent process, but current implementations struggle with complex data sets due to the need to infer ancestral migration histories. Thus, approximations to the structured coalescent, which integrate over all ancestral migration histories, have been developed. However, the validity and robustness of these approximations remain unclear. We present an exact numerical solution to the structured coalescent that does not require the inference of migration histories. Although this solution is computationally unfeasible for large data sets, it clarifies the assumptions of previously developed approximate methods and allows us to provide an improved approximation to the structured coalescent. We have implemented these methods in BEAST2, and we show how these methods compare under different scenarios.

Influenza

Influenza is an infectious respiratory disease that, in humans, is caused by influenza A and influenza B viruses. Typically characterized by annual seasonal epidemics, sporadic pandemic outbreaks involve influenza A virus strains of zoonotic origin. The WHO estimates that annual epidemics of influenza result in ~1 billion infections, 3–5 million cases of severe illness and 300,000–500,000 deaths. The severity of pandemic influenza depends on multiple factors, including the virulence of the pandemic virus strain and the level of pre-existing immunity. The most severe influenza pandemic, in 1918, resulted in >40 million deaths worldwide. Influenza vaccines are formulated every year to match the circulating strains, as they evolve antigenically owing to antigenic drift. Nevertheless, vaccine efficacy is not optimal and is dramatically low in the case of an antigenic mismatch between the vaccine and the circulating virus strain. Antiviral agents that target the influenza virus enzyme neuraminidase have been developed for prophylaxis and therapy. However, the use of these antivirals is still limited. Emerging approaches to combat influenza include the development of universal influenza virus vaccines that provide protection against antigenically distant influenza viruses, but these vaccines need to be tested in clinical trials to ascertain their effectiveness.

Explaining the geographical origins of seasonal influenza A (H3N2)

Most antigenically novel and evolutionarily successful strains of seasonal influenza A (H3N2) originate in East, South and Southeast Asia. To understand this pattern, we simulated the ecological and evolutionary dynamics of influenza in a host metapopulation representing the temperate north, tropics and temperate south. Although seasonality and air traffic are frequently used to explain global migratory patterns of influenza, we find that other factors may have a comparable or greater impact. Notably, a region's basic reproductive number (R0) strongly affects the antigenic evolution of its viral population and the probability that its strains will spread and fix globally: a 17-28% higher R0 in one region can explain the observed patterns. Seasonality, in contrast, increases the probability that a tropical (less seasonal) population will export evolutionarily successful strains but alone does not predict that these strains will be antigenically advanced. The relative sizes of different host populations, their birth and death rates, and the region in which H3N2 first appears affect influenza's phylogeography in different but relatively minor ways. These results suggest general principles that dictate the spatial dynamics of antigenically evolving pathogens and offer predictions for how changes in human ecology might affect influenza evolution.

Selection on non-antigenic gene segments of seasonal influenza A virus and its impact on adaptive evolution

Most studies on seasonal influenza A/H3N2 virus adaptation have focused on the main antigenic gene, hemagglutinin. However, there is increasing evidence that the genome-wide genetic background of novel antigenic variants can influence these variants’ emergence probabilities and impact their patterns of dominance in the population. This suggests that non-antigenic genes may be important in shaping the viral evolutionary dynamics. To better understand the role of selection on non-antigenic genes in the adaptive evolution of seasonal influenza viruses, we have developed a simple population genetic model that considers a virus with one antigenic and one non-antigenic gene segment. By simulating this model under different regimes of selection and reassortment, we find that the empirical patterns of lineage turnover for the antigenic and non-antigenic gene segments are best captured when there is both limited viral coinfection and selection operating on both gene segments. In contrast, under a scenario of only neutral evolution in the non-antigenic gene segment, we see persistence of multiple lineages for long periods of time in that segment, which is not compatible with observed molecular evolutionary patterns. Further, we find that reassortment, occurring in coinfected individuals, can increase the speed of viral adaptive evolution by primarily reducing selective interference and genetic linkage effects. Together, these findings suggest that, for influenza, with six internal or non-antigenic gene segments, the evolutionary dynamics of novel antigenic variants are likely to be influenced by the genome-wide genetic background as a result of linked selection among both beneficial and deleterious mutations.

Bayesian phylogeography of influenza A/H3N2 for the 2014-15 season in the United States using three frameworks of ancestral state reconstruction

Ancestral state reconstructions in Bayesian phylogeography of virus pandemics have been improved by utilizing a Bayesian stochastic search variable selection (BSSVS) framework. Recently, this framework has been extended to model the transition rate matrix between discrete states as a generalized linear model (GLM) of genetic, geographic, demographic, and environmental predictors of interest to the virus and incorporating BSSVS to estimate the posterior inclusion probabilities of each predictor. Although the latter appears to enhance the biological validity of ancestral state reconstruction, there has yet to be a comparison of phylogenies created by the two methods. In this paper, we compare these two methods, while also using a primitive method without BSSVS, and highlight the differences in phylogenies created by each. We test six coalescent priors and six random sequence samples of H3N2 influenza during the 2014–15 flu season in the U.S. We show that the GLMs yield significantly greater root state posterior probabilities than the two alternative methods under five of the six priors, and significantly greater Kullback-Leibler divergence values than the two alternative methods under all priors. Furthermore, the GLMs strongly implicate temperature and precipitation as driving forces of this flu season and nearly unanimously identified a single root state, which exhibits the most tropical climate during a typical flu season in the U.S. The GLM, however, appears to be highly susceptible to sampling bias compared with the other methods, which casts doubt on whether its reconstructions should be favored over those created by alternate methods. We report that a BSSVS approach with a Poisson prior demonstrates less bias toward sample size under certain conditions than the GLMs or primitive models, and believe that the connection between reconstruction method and sampling bias warrants further investigation.

For the better part of the last decade, epidemiological researchers have employed a Bayesian framework to reconstruct phylogenetic trees and determine the spatiotemporal relationships between clades of viruses. Recently, an extension of this framework has enabled direct assessment of how various demographic, geographic, genetic, and environmental variables play a role in these relationships, but there has yet to be a comparison between the former and the latter. Here, we aim to assess the differences between the two reconstruction techniques, as well as an additional primitive method, using the 2014–15 influenza season in the U.S. as a case study under a variety of population growth scenarios. We highlight how the new method demonstrates significant increases in commonly-reported trends in phylogenies and that the method identifies climate predictors that appear to be consistent with known trends in seasonal trends in influenza. However, we found that this method appears to be the most heavily influenced by the locations at which the viruses were obtained. Our work offers valuable insight for researchers wishing to study the evolutionary history of viruses and also may prove useful in determining the correct method to choose for a given application of virus phylogeography.

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.

Emerging Concepts of Data Integration in Pathogen Phylodynamics

Phylodynamics has become an increasingly popular statistical framework to extract evolutionary and epidemiological information from pathogen genomes. By harnessing such information, epidemiologists aim to shed light on the spatio-temporal patterns of spread and to test hypotheses about the underlying interaction of evolutionary and ecological dynamics in pathogen populations. Although the field has witnessed a rich development of statistical inference tools with increasing levels of sophistication, these tools initially focused on sequences as their sole primary data source. Integrating various sources of information, however, promises to deliver more precise insights in infectious diseases and to increase opportunities for statistical hypothesis testing. Here, we review how the emerging concept of data integration is stimulating new advances in Bayesian evolutionary inference methodology which formalize a marriage of statistical thinking and evolutionary biology. These approaches include connecting sequence to trait evolution, such as for host, phenotypic and geographic sampling information, but also the incorporation of covariates of evolutionary and epidemic processes in the reconstruction procedures. We highlight how a full Bayesian approach to covariate modeling and testing can generate further insights into sequence evolution, trait evolution, and population dynamics in pathogen populations. Specific examples demonstrate how such approaches can be used to test the impact of host on rabies and HIV evolutionary rates, to identify the drivers of influenza dispersal as well as the determinants of rabies cross-species transmissions, and to quantify the evolutionary dynamics of influenza antigenicity. Finally, we briefly discuss how data integration is now also permeating through the inference of transmission dynamics, leading to novel insights into tree-generative processes and detailed reconstructions of transmission trees. [Bayesian inference; birth–death models; coalescent models; continuous trait evolution; covariates; data integration; discrete trait evolution; pathogen phylodynamics.