Spatiotemporal genotype replacement of H5N8 avian influenza viruses contributed to H5N1 emergence in 2021/2022 panzootic.

Since 2020, clade 2.3.4.4b highly pathogenic avian influenza H5N8 and H5N1 viruses have swept through continents, posing serious threats to the world. Through comprehensive analyses of epidemiological, genetic, and bird migration data, we found that the dominant genotype replacement of the H5N8 viruses in 2020 contributed to the H5N1 outbreak in the 2021/2022 wave. The 2020 outbreak of the H5N8 G1 genotype instead of the G0 genotype produced reassortment opportunities and led to the emergence of a new H5N1 virus with G1's HA and MP genes. Despite extensive reassortments in the 2021/2022 wave, the H5N1 virus retained the HA and MP genes, causing a significant outbreak in Europe and North America. Furtherly, through the wild bird migration flyways investigation, we found that the temporal-spatial coincidence between the outbreak of the H5N8 G1 virus and the bird autumn migration may have expanded the H5 viral spread, which may be one of the main drivers of the emergence of the 2020-2022 H5 panzootic.IMPORTANCESince 2020, highly pathogenic avian influenza (HPAI) H5 subtype variants of clade 2.3.4.4b have spread across continents, posing unprecedented threats globally. However, the factors promoting the genesis and spread of H5 HPAI viruses remain unclear. Here, we found that the spatiotemporal genotype replacement of H5N8 HPAI viruses contributed to the emergence of the H5N1 variant that caused the 2021/2022 panzootic, and the viral evolution in poultry of Egypt and surrounding area and autumn bird migration from the Russia-Kazakhstan region to Europe are important drivers of the emergence of the 2020-2022 H5 panzootic. These findings provide important targets for early warning and could help control the current and future HPAI epidemics.

Genesis and spread of multiple reassortants during the 2016/2017 H5 avian influenza epidemic in Eurasia.

Highly pathogenic avian influenza (HPAI) viruses of the H5 A/goose/Guangdong/1/96 lineage can cause severe disease in poultry and wild birds, and occasionally in humans. In recent years, H5 HPAI viruses of this lineage infecting poultry in Asia have spilled over into wild birds and spread via bird migration to countries in Europe, Africa, and North America. In 2016/2017, this spillover resulted in the largest HPAI epidemic on record in Europe and was associated with an unusually high frequency of reassortments between H5 HPAI viruses and cocirculating low-pathogenic avian influenza viruses. Here, we show that the seven main H5 reassortant viruses had various combinations of gene segments 1, 2, 3, 5, and 6. Using detailed time-resolved phylogenetic analysis, most of these gene segments likely originated from wild birds and at dates and locations that corresponded to their hosts' migratory cycles. However, some gene segments in two reassortant viruses likely originated from domestic anseriforms, either in spring 2016 in east China or in autumn 2016 in central Europe. Our results demonstrate that, in addition to domestic anseriforms in Asia, both migratory wild birds and domestic anseriforms in Europe are relevant sources of gene segments for recent reassortant H5 HPAI viruses. The ease with which these H5 HPAI viruses reassort, in combination with repeated spillovers of H5 HPAI viruses into wild birds, increases the risk of emergence of a reassortant virus that persists in wild bird populations yet remains highly pathogenic for poultry.

Contribution of Segment 3 to the Acquisition of Virulence in Contemporary H9N2 Avian Influenza Viruses.

H9N2 avian influenza viruses (AIVs) circulate in poultry throughout much of Asia, the Middle East, and Africa. These viruses cause huge economic damage to poultry production systems and pose a zoonotic threat both in their own right and in the generation of novel zoonotic viruses, for example, H7N9. In recent years, it has been observed that H9N2 viruses have further adapted to gallinaceous poultry, becoming more highly transmissible and causing higher morbidity and mortality. Here, we investigate the molecular basis for this increased virulence, comparing a virus from the 1990s and a contemporary field strain. The modern virus replicated to higher titers in various systems, and this difference mapped to a single amino acid polymorphism at position 26 of the endonuclease domain shared by the PA and PA-X proteins. This change was responsible for increased replication and higher morbidity and mortality rates along with extended tissue tropism seen in chickens. Although the PA K26E change correlated with increased host cell shutoff activity of the PA-X protein in vitro, it could not be overridden by frameshift site mutations that block PA-X expression and therefore increased PA-X activity could not explain the differences in replication phenotype. Instead, this indicates that these differences are due to subtle effects on PA function. This work gives insight into the ongoing evolution and poultry adaptation of H9N2 and other avian influenza viruses and helps us understand the striking morbidity and mortality rates in the field, as well as the rapidly expanding geographical range seen in these viruses.IMPORTANCE Avian influenza viruses, such as H9N2, cause huge economic damage to poultry production worldwide and are additionally considered potential pandemic threats. Understanding how these viruses evolve in their natural hosts is key to effective control strategies. In the Middle East and South Asia, an older H9N2 virus strain has been replaced by a new reassortant strain with greater fitness. Here, we take representative viruses and investigate the genetic basis for this "fitness." A single mutation in the virus was responsible for greater fitness, enabling high growth of the contemporary H9N2 virus in cells, as well as in chickens. The genetic mutation that modulates this change is within the viral PA protein, a part of the virus polymerase gene that contributes to viral replication as well as to virus accessory functions-however, we find that the fitness effect is specifically due to changes in the protein polymerase activity.

The genesis and source of the H7N9 influenza viruses causing human infections in China.

A novel H7N9 influenza A virus first detected in March 2013 has since caused more than 130 human infections in China, resulting in 40 deaths. Preliminary analyses suggest that the virus is a reassortant of H7, N9 and H9N2 avian influenza viruses, and carries some amino acids associated with mammalian receptor binding, raising concerns of a new pandemic. However, neither the source populations of the H7N9 outbreak lineage nor the conditions for its genesis are fully known. Using a combination of active surveillance, screening of virus archives, and evolutionary analyses, here we show that H7 viruses probably transferred from domestic duck to chicken populations in China on at least two independent occasions. We show that the H7 viruses subsequently reassorted with enzootic H9N2 viruses to generate the H7N9 outbreak lineage, and a related previously unrecognized H7N7 lineage. The H7N9 outbreak lineage has spread over a large geographic region and is prevalent in chickens at live poultry markets, which are thought to be the immediate source of human infections. Whether the H7N9 outbreak lineage has, or will, become enzootic in China and neighbouring regions requires further investigation. The discovery here of a related H7N7 influenza virus in chickens that has the ability to infect mammals experimentally, suggests that H7 viruses may pose threats beyond the current outbreak. The continuing prevalence of H7 viruses in poultry could lead to the generation of highly pathogenic variants and further sporadic human infections, with a continued risk of the virus acquiring human-to-human transmissibility.

Quantifying predictors for the spatial diffusion of avian influenza virus in China.

BACKGROUND: Avian influenza virus (AIV) causes both severe outbreaks and endemic disease among poultry and has caused sporadic human infections in Asia, furthermore the routes of transmission in avian species between geographic regions can be numerous and complex. Using nucleotide sequences from the internal protein coding segments of AIV, we performed a Bayesian phylogeographic study to uncover regional routes of transmission and factors predictive of the rate of viral diffusion within China. RESULTS: We found that the Central area and Pan-Pearl River Delta were the two main sources of AIV diffusion, while the East Coast areas especially the Yangtze River delta, were the major targets of viral invasion. Next we investigated the extent to which economic, agricultural, environmental and climatic regional data was predictive of viral diffusion by fitting phylogeographic discrete trait models using generalised linear models. CONCLUSIONS: Our results highlighted that the economic-agricultural predictors, especially the poultry population density and the number of farm product markets, are the key determinants of spatial diffusion of AIV in China; high human density and freight transportation are also important predictors of high rates of viral transmission; Climate features (e.g. temperature) were correlated to the viral invasion in the destination to some degree; while little or no impacts were found from natural environment factors (such as surface water coverage). This study uncovers the risk factors and enhances our understanding of the spatial dynamics of AIV in bird populations.

Using whole genome sequencing to investigate transmission in a multi-host system: bovine tuberculosis in New Zealand.

BACKGROUND: Bovine tuberculosis (bTB), caused by Mycobacterium bovis, is an important livestock disease raising public health and economic concerns around the world. In New Zealand, a number of wildlife species are implicated in the spread and persistence of bTB in cattle populations, most notably the brushtail possum (Trichosurus vulpecula). Whole Genome Sequenced (WGS) M. bovis isolates sourced from infected cattle and wildlife across New Zealand were analysed. Bayesian phylogenetic analyses were conducted to estimate the substitution rate of the sampled population and investigate the role of wildlife. In addition, the utility of WGS was examined with a view to these methods being incorporated into routine bTB surveillance. RESULTS: A high rate of exchange was evident between the sampled wildlife and cattle populations but directional estimates of inter-species transmission were sensitive to the sampling strategy employed. A relatively high substitution rate was estimated, this, in combination with a strong spatial signature and a good agreement to previous typing methods, acts to endorse WGS as a typing tool. CONCLUSIONS: In agreement with the current knowledge of bTB in New Zealand, transmission of M. bovis between cattle and wildlife was evident. Without direction, these estimates are less informative but taken in conjunction with the low prevalence of bTB in New Zealand's cattle population it is likely that, currently, wildlife populations are acting as the main bTB reservoir. Wildlife should therefore continue to be targeted if bTB is to be eradicated from New Zealand. WGS will be a considerable aid to bTB eradication by greatly improving the discriminatory power of molecular typing data. The substitution rates estimated here will be an important part of epidemiological investigations using WGS data.

Role of the B Allele of Influenza A Virus Segment 8 in Setting Mammalian Host Range and Pathogenicity.

UNLABELLED: Two alleles of segment 8 (NS) circulate in nonchiropteran influenza A viruses. The A allele is found in avian and mammalian viruses, but the B allele is viewed as being almost exclusively found in avian viruses. This might reflect the fact that one or both of its encoded proteins (NS1 and NEP) are maladapted for replication in mammalian hosts. To test this, a number of clade A and B avian virus-derived NS segments were introduced into human H1N1 and H3N2 viruses. In no case was the peak virus titer substantially reduced following infection of various mammalian cell types. Exemplar reassortant viruses also replicated to similar titers in mice, although mice infected with viruses with the avian virus-derived segment 8s had reduced weight loss compared to that achieved in mice infected with the A/Puerto Rico/8/1934 (H1N1) parent. In vitro, the viruses coped similarly with type I interferons. Temporal proteomics analysis of cellular responses to infection showed that the avian virus-derived NS segments provoked lower levels of expression of interferon-stimulated genes in cells than wild type-derived NS segments. Thus, neither the A nor the B allele of avian virus-derived NS segments necessarily attenuates virus replication in a mammalian host, although the alleles can attenuate disease. Phylogenetic analyses identified 32 independent incursions of an avian virus-derived A allele into mammals, whereas 6 introductions of a B allele were identified. However, A-allele isolates from birds outnumbered B-allele isolates, and the relative rates of Aves-to-Mammalia transmission were not significantly different. We conclude that while the introduction of an avian virus segment 8 into mammals is a relatively rare event, the dogma of the B allele being especially restricted is misleading, with implications in the assessment of the pandemic potential of avian influenza viruses. IMPORTANCE: Influenza A virus (IAV) can adapt to poultry and mammalian species, inflicting a great socioeconomic burden on farming and health care sectors. Host adaptation likely involves multiple viral factors. Here, we investigated the role of IAV segment 8. Segment 8 has evolved into two distinct clades: the A and B alleles. The B-allele genes have previously been suggested to be restricted to avian virus species. We introduced a selection of avian virus A- and B-allele segment 8s into human H1N1 and H3N2 virus backgrounds and found that these reassortant viruses were fully competent in mammalian host systems. We also analyzed the currently available public data on the segment 8 gene distribution and found surprisingly little evidence for specific avian host restriction of the B-clade segment. We conclude that B-allele segment 8 genes are, in fact, capable of supporting infection in mammals and that they should be considered during the assessment of the pandemic risk of zoonotic influenza A viruses.

Transmission of Non-B HIV Subtypes in the United Kingdom Is Increasingly Driven by Large Non-Heterosexual Transmission Clusters.

BACKGROUND: The United Kingdom human immunodeficiency virus (HIV) epidemic was historically dominated by HIV subtype B transmission among men who have sex with men (MSM). Now 50% of diagnoses and prevalent infections are among heterosexual individuals and mainly involve non-B subtypes. Between 2002 and 2010, the prevalence of non-B diagnoses among MSM increased from 5.4% to 17%, and this study focused on the drivers of this change. METHODS: Growth between 2007 and 2009 in transmission clusters among 14 000 subtype A1, C, D, and G sequences from the United Kingdom HIV Drug Resistance Database was analysed by risk group. RESULTS: Of 1148 clusters containing at least 2 sequences in 2007, >75% were pairs and >90% were heterosexual. Most clusters (71.4%) did not grow during the study period. Growth was significantly lower for small clusters and higher for clusters of ≥7 sequences, with the highest growth observed for clusters comprising sequences from MSM and people who inject drugs (PWID). Risk group (P< .0001), cluster size (P< .0001), and subtype (P< .01) were predictive of growth in a generalized linear model. DISCUSSION: Despite the increase in non-B subtypes associated with heterosexual transmission, MSM and PWID are at risk for non-B infections. Crossover of subtype C from heterosexuals to MSM has led to the expansion of this subtype within the United Kingdom.

Broadwick: a framework for computational epidemiology.

BACKGROUND: Modelling disease outbreaks often involves integrating the wealth of data that are gathered during modern outbreaks into complex mathematical or computational models of transmission. Incorporating these data into simple compartmental epidemiological models is often challenging, requiring the use of more complex but also more efficient computational models. In this paper we introduce a new framework that allows for a more systematic and user-friendly way of building and running epidemiological models that efficiently handles disease data and reduces much of the boilerplate code that usually associated to these models. We introduce the framework by developing an SIR model on a simple network as an example. RESULTS: We develop Broadwick, a modular, object-oriented epidemiological framework that efficiently handles large epidemiological datasets and provides packages for stochastic simulations, parameter inference using Approximate Bayesian Computation (ABC) and Markov Chain Monte Carlo (MCMC) methods. Each algorithm used is fully customisable with sensible defaults that are easily overridden by custom algorithms as required. CONCLUSION: Broadwick is an epidemiological modelling framework developed to increase the productivity of researchers by providing a common framework with which to develop and share complex models. It will appeal to research team leaders as it allows for models to be created prior to a disease outbreak and has the ability to handle large datasets commonly found in epidemiological modelling.

Origins and evolutionary genomics of the 2009 swine-origin H1N1 influenza A epidemic.

In March and early April 2009, a new swine-origin influenza A (H1N1) virus (S-OIV) emerged in Mexico and the United States. During the first few weeks of surveillance, the virus spread worldwide to 30 countries (as of May 11) by human-to-human transmission, causing the World Health Organization to raise its pandemic alert to level 5 of 6. This virus has the potential to develop into the first influenza pandemic of the twenty-first century. Here we use evolutionary analysis to estimate the timescale of the origins and the early development of the S-OIV epidemic. We show that it was derived from several viruses circulating in swine, and that the initial transmission to humans occurred several months before recognition of the outbreak. A phylogenetic estimate of the gaps in genetic surveillance indicates a long period of unsampled ancestry before the S-OIV outbreak, suggesting that the reassortment of swine lineages may have occurred years before emergence in humans, and that the multiple genetic ancestry of S-OIV is not indicative of an artificial origin. Furthermore, the unsampled history of the epidemic means that the nature and location of the genetically closest swine viruses reveal little about the immediate origin of the epidemic, despite the fact that we included a panel of closely related and previously unpublished swine influenza isolates. Our results highlight the need for systematic surveillance of influenza in swine, and provide evidence that the mixing of new genetic elements in swine can result in the emergence of viruses with pandemic potential in humans.

Reassortment patterns of avian influenza virus internal segments among different subtypes.

BACKGROUND: The segmented RNA genome of avian Influenza viruses (AIV) allows genetic reassortment between co-infecting viruses, providing an evolutionary pathway to generate genetic innovation. The genetic diversity (16 haemagglutinin and 9 neuraminidase subtypes) of AIV indicates an extensive reservoir of influenza viruses exists in bird populations, but how frequently subtypes reassort with each other is still unknown. Here we quantify the reassortment patterns among subtypes in the Eurasian avian viral pool by reconstructing the ancestral states of the subtypes as discrete states on time-scaled phylogenies with respect to the internal protein coding segments. We further analyzed how host species, the inferred evolutionary rates and the dN/dS ratio varied among segments and between discrete subtypes, and whether these factors may be associated with inter-subtype reassortment rate. RESULTS: The general patterns of reassortment are similar among five internal segments with the exception of segment 8, encoding the Non-Structural genes, which has a more divergent phylogeny. However, significant variation in rates between subtypes was observed. In particular, hemagglutinin-encoding segments of subtypes H5 to H9 reassort at a lower rate compared to those of H1 to H4, and Neuraminidase-encoding segments of subtypes N1 and N2 reassort less frequently than N3 to N9. Both host species and dN/dS ratio were significantly associated with reassortment rate, while evolutionary rate was not associated. The dN/dS ratio was negatively correlated with reassortment rate, as was the number of negatively selected sites for all segments. CONCLUSIONS: These results indicate that overall selective constraint and host species are both associated with reassortment rate. These results together identify the wild bird population as the major source of new reassortants, rather than domestic poultry. The lower reassortment rates observed for H5N1 and H9N2 may be explained by the large proportion of strains derived from domestic poultry populations. In contrast, the higher rates observed in the H1N1, H3N8 and H4N6 subtypes could be due to their primary origin as infections of wild birds with multiple low pathogenicity strains in the large avian reservoir.

Investigation of influenza virus polymerase activity in pig cells.

Reassortant influenza viruses with combinations of avian, human, and/or swine genomic segments have been detected frequently in pigs. As a consequence, pigs have been accused of being a "mixing vessel" for influenza viruses. This implies that pig cells support transcription and replication of avian influenza viruses, in contrast to human cells, in which most avian influenza virus polymerases display limited activity. Although influenza virus polymerase activity has been studied in human and avian cells for many years by use of a minigenome assay, similar investigations in pig cells have not been reported. We developed the first minigenome assay for pig cells and compared the activities of polymerases of avian or human influenza virus origin in pig, human, and avian cells. We also investigated in pig cells the consequences of some known mammalian host range determinants that enhance influenza virus polymerase activity in human cells, such as PB2 mutations E627K, D701N, G590S/Q591R, and T271A. The two typical avian influenza virus polymerases used in this study were poorly active in pig cells, similar to what is seen in human cells, and mutations that adapt the avian influenza virus polymerase for human cells also increased activity in pig cells. In contrast, a different pattern was observed in avian cells. Finally, highly pathogenic avian influenza virus H5N1 polymerase activity was tested because this subtype has been reported to replicate only poorly in pigs. H5N1 polymerase was active in swine cells, suggesting that other barriers restrict these viruses from becoming endemic in pigs.

Estimating the rate of intersubtype recombination in early HIV-1 group M strains.

West Central Africa has been implicated as the epicenter of the HIV-1 epidemic, and almost all group M subtypes can be found there. Previous analysis of early HIV-1 group M sequences from Kinshasa in the Democratic Republic of Congo, formerly Zaire, revealed that isolates from a number of individuals fall in different positions in phylogenetic trees constructed from sequences from opposite ends of the genome as a result of recombination between viruses of different subtypes. Here, we use discrete ancestral trait mapping to develop a procedure for quantifying HIV-1 group M intersubtype recombination across phylogenies, using individuals' gag (p17) and env (gp41) subtypes. The method was applied to previously described HIV-1 group M sequences from samples obtained in Kinshasa early in the global radiation of HIV. Nine different p17 and gp41 intersubtype recombinant combinations were present in the data set. The mean number of excess ancestral subtype transitions (NEST) required to map individuals' p17 subtypes onto the gp14 phylogeny samples, compared to the number required to map them onto the p17 phylogenies, and vice versa, indicated that excess subtype transitions occurred at a rate of approximately 7 × 10(-3) to 8 × 10(-3) per lineage per year as a result of intersubtype recombination. Our results imply that intersubtype recombination may have occurred in approximately 20% of lineages evolving over a period of 30 years and confirm intersubtype recombination as a substantial force in generating HIV-1 group M diversity.

Evolutionary interactions between haemagglutinin and neuraminidase in avian influenza.

BACKGROUND: Reassortment between the RNA segments encoding haemagglutinin (HA) and neuraminidase (NA), the major antigenic influenza proteins, produces viruses with novel HA and NA subtype combinations and has preceded the emergence of pandemic strains. It has been suggested that productive viral infection requires a balance in the level of functional activity of HA and NA, arising from their closely interacting roles in the viral life cycle, and that this functional balance could be mediated by genetic changes in the HA and NA. Here, we investigate how the selective pressure varies for H7 avian influenza HA on different NA subtype backgrounds. RESULTS: By extending Bayesian stochastic mutational mapping methods to calculate the ratio of the rate of non-synonymous change to the rate of synonymous change (d(N)/d(S)), we found the average d(N)/d(S) across the avian influenza H7 HA1 region to be significantly greater on an N2 NA subtype background than on an N1, N3 or N7 background. Observed differences in evolutionary rates of H7 HA on different NA subtype backgrounds could not be attributed to underlying differences between avian host species or virus pathogenicity. Examination of d(N)/d(S) values for each subtype on a site-by-site basis indicated that the elevated d(N)/d(S) on the N2 NA background was a result of increased selection, rather than a relaxation of selective constraint. CONCLUSIONS: Our results are consistent with the hypothesis that reassortment exposes influenza HA to significant changes in selective pressure through genetic interactions with NA. Such epistatic effects might be explicitly accounted for in future models of influenza evolution.

Unraveling the epidemiology of Mycobacterium bovis using whole-genome sequencing combined with environmental and demographic data.

When studying the dynamics of a pathogen in a host population, one crucial question is whether it transitioned from an epidemic (i.e., the pathogen population and the number of infected hosts are increasing) to an endemic stable state (i.e., the pathogen population reached an equilibrium). For slow-growing and slow-evolving clonal pathogens such as Mycobacterium bovis, the causative agent of bovine (or animal) and zoonotic tuberculosis, it can be challenging to discriminate between these two states. This is a result of the combination of suboptimal detection tests so that the actual extent of the pathogen prevalence is often unknown, as well as of the low genetic diversity, which can hide the temporal signal provided by the accumulation of mutations in the bacterial DNA. In recent years, the increased availability, efficiency, and reliability of genomic reading techniques, such as whole-genome sequencing (WGS), have significantly increased the amount of information we can use to study infectious diseases, and therefore, it has improved the precision of epidemiological inferences for pathogens such as M. bovis. In this study, we use WGS to gain insights into the epidemiology of M. bovis in Cameroon, a developing country where the pathogen has been reported for decades. A total of 91 high-quality sequences were obtained from tissue samples collected in four abattoirs, 64 of which were with complete metadata. We combined these with environmental, demographic, ecological, and cattle movement data to generate inferences using phylodynamic models. Our findings suggest M. bovis in Cameroon is slowly expanding its epidemiological range over time; therefore, endemic stability is unlikely. This suggests that animal movement plays an important role in transmission. The simultaneous prevalence of M. bovis in co-located cattle and humans highlights the risk of such transmission being zoonotic. Therefore, using genomic tools as part of surveillance would vastly improve our understanding of disease ecology and control strategies.

Transmission network parameters estimated from HIV sequences for a nationwide epidemic.

BACKGROUND: Many studies of sexual behavior have shown that individuals vary greatly in their number of sexual partners over time, but it has proved difficult to obtain parameter estimates relating to the dynamics of human immunodeficiency virus (HIV) transmission except in small-scale contact tracing studies. Recent developments in molecular phylodynamics have provided new routes to obtain these parameter estimates, and current clinical practice provides suitable data for entire infected populations. METHODS: A phylodynamic analysis was performed on partial pol gene sequences obtained for routine clinical care from 14,560 individuals, representing approximately 60% of the HIV-positive men who have sex with men (MSM) under care in the United Kingdom. RESULTS: Among individuals linked to others in the data set, 29% are linked to only 1 individual, 41% are linked to 2-10 individuals, and 29% are linked to ≥10 individuals. The right-skewed degree distribution can be approximated by a power law, but the data are best fitted by a Waring distribution for all time depths. For time depths of 5-7 years, the distribution parameter ρ lies within the range that indicates infinite variance. CONCLUSIONS: The transmission network among UK MSM is characterized by preferential association such that a randomly distributed intervention would not be expected to stop the epidemic.

Molecular phylodynamics of the heterosexual HIV epidemic in the United Kingdom.

The heterosexual risk group has become the largest HIV infected group in the United Kingdom during the last 10 years, but little is known of the network structure and dynamics of viral transmission in this group. The overwhelming majority of UK heterosexual infections are of non-B HIV subtypes, indicating viruses originating among immigrants from sub-Saharan Africa. The high rate of HIV evolution, combined with the availability of a very high density sample of viral sequences from routine clinical care has allowed the phylodynamics of the epidemic to be investigated for the first time. Sequences of the viral protease and partial reverse transcriptase coding regions from 11,071 patients infected with HIV of non-B subtypes were studied. Of these, 2774 were closely linked to at least one other sequence by nucleotide distance. Including the closest sequences from the global HIV database identified 296 individuals that were in UK-based groups of 3 or more individuals. There were a total of 8 UK-based clusters of 10 or more, comprising 143/2774 (5%) individuals, much lower than the figure of 25% obtained earlier for men who have sex with men (MSM). Sample dates were incorporated into relaxed clock phylogenetic analyses to estimate the dates of internal nodes. From the resulting time-resolved phylogenies, the internode lengths, used as estimates of maximum transmission intervals, had a median of 27 months overall, over twice as long as obtained for MSM (14 months), with only 2% of transmissions occurring in the first 6 months after infection. This phylodynamic analysis of non-B subtype HIV sequences representing over 40% of the estimated UK HIV-infected heterosexual population has revealed heterosexual HIV transmission in the UK is clustered, but on average in smaller groups and is transmitted with slower dynamics than among MSM. More effective intervention to restrict the epidemic may therefore be feasible, given effective diagnosis programmes.

Identifying likely transmissions in Mycobacterium bovis infected populations of cattle and badgers using the Kolmogorov Forward Equations.

Established methods for whole-genome-sequencing (WGS) technology allow for the detection of single-nucleotide polymorphisms (SNPs) in the pathogen genomes sourced from host samples. The information obtained can be used to track the pathogen's evolution in time and potentially identify 'who-infected-whom' with unprecedented accuracy. Successful methods include 'phylodynamic approaches' that integrate evolutionary and epidemiological data. However, they are typically computationally intensive, require extensive data, and are best applied when there is a strong molecular clock signal and substantial pathogen diversity. To determine how much transmission information can be inferred when pathogen genetic diversity is low and metadata limited, we propose an analytical approach that combines pathogen WGS data and sampling times from infected hosts. It accounts for 'between-scale' processes, in particular within-host pathogen evolution and between-host transmission. We applied this to a well-characterised population with an endemic Mycobacterium bovis (the causative agent of bovine/zoonotic tuberculosis, bTB) infection. Our results show that, even with such limited data and low diversity, the computation of the transmission probability between host pairs can help discriminate between likely and unlikely infection pathways and therefore help to identify potential transmission networks. However, the method can be sensitive to assumptions about within-host evolution.

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'.

A guide to machine learning for bacterial host attribution using genome sequence data.

With the ever-expanding number of available sequences from bacterial genomes, and the expectation that this data type will be the primary one generated from both diagnostic and research laboratories for the foreseeable future, then there is both an opportunity and a need to evaluate how effectively computational approaches can be used within bacterial genomics to predict and understand complex phenotypes, such as pathogenic potential and host source. This article applied various quantitative methods such as diversity indexes, pangenome-wide association studies (GWAS) and dimensionality reduction techniques to better understand the data and then compared how well unsupervised and supervised machine learning (ML) methods could predict the source host of the isolates. The study uses the example of the pangenomes of 1203 Salmonella enterica serovar Typhimurium isolates in order to predict 'host of isolation' using these different methods. The article is aimed as a review of recent applications of ML in infection biology, but also, by working through this specific dataset, it allows discussion of the advantages and drawbacks of the different techniques. As with all such sub-population studies, the biological relevance will be dependent on the quality and diversity of the input data. Given this major caveat, we show that supervised ML has the potential to add real value to interpretation of bacterial genomic data, as it can provide probabilistic outcomes for important phenotypes, something that is very difficult to achieve with the other methods.