Whole genome sequencing unravels cryptic circulation of divergent dengue virus lineages in the rainforest region of Nigeria.

Dengue is often misclassified and underreported in Africa due to inaccurate differential diagnoses of nonspecific febrile illnesses such as malaria, sparsity of diagnostic testing and poor clinical and genomic surveillance. There are limited reports on the seroprevalence and genetic diversity of dengue virus (DENV) in humans and vectors in Nigeria. In this study, we investigated the epidemiology and genetic diversity of dengue in the rainforest region of Nigeria. We screened 515 febrile patients who tested negative for malaria and typhoid fever in three hospitals in Oyo and Ekiti States in southern Nigeria with a combination of anti-dengue IgG/IgM/NS1 rapid test kits and metagenomic sequencing. We found that approximately 28% of screened patients had previous DENV exposure, with the highest prevalence in persons over sixty. Approximately 8% of the patients showed evidence of recent or current infection, and 2.7% had acute infection. Following sequencing of sixty samples, we assembled twenty DENV-1 genomes (3 complete and 17 partial). We found that all assembled genomes belonged to DENV-1 genotype III. Our phylogenetic analyses showed evidence of prolonged cryptic circulation of divergent DENV lineages in Oyo state. We were unable to resolve the source of DENV in Nigeria owing to limited sequencing data from the region. However, our sequences clustered closely with sequences in Tanzania and sequences reported in Chinese with travel history to Tanzania in 2019. This may reflect the wider unsampled bidirectional transmission of DENV-1 in Africa, which strongly emphasizes the importance of genomic surveillance in monitoring ongoing DENV transmission in Africa.

Lassa virus in novel hosts: insights into the epidemiology of lassa virus infections in southern Nigeria.

Identification of the diverse animal hosts responsible for spill-over events from animals to humans is crucial for comprehending the transmission patterns of emerging infectious diseases, which pose significant public health risks. To better characterize potential animal hosts of Lassa virus (LASV), we assessed domestic and non-domestic animals from 2021-2022 in four locations in southern Nigeria with reported cases of Lassa fever (LF). Birds, lizards, and domestic mammals (dogs, pigs, cattle and goats) were screened using RT-qPCR, and whole genome sequencing was performed for lineage identification on selected LASV positive samples. Animals were also screened for exposure to LASV by enzyme-linked immunosorbent assay (ELISA). Among these animals, lizards had the highest positivity rate by PCR. Genomic sequencing of samples in most infected animals showed sub-lineage 2 g of LASV. Seropositivity was highest among cattle and lowest in pigs. Though the specific impact these additional hosts may have in the broader virus-host context are still unknown - specifically relating to pathogen diversity, evolution, and transmission - the detection of LASV in non-rodent hosts living in proximity to confirmed human LF cases suggests their involvement during transmission as potential reservoirs. Additional epidemiological data comparing viral genomes from humans and animals, as well as those circulating within the environment will be critical in understanding LASV transmission dynamics and will ultimately guide the development of countermeasures for this zoonotic health threat.

Genomic surveillance reveals dynamic shifts in the connectivity of COVID-19 epidemics.

The maturation of genomic surveillance in the past decade has enabled tracking of the emergence and spread of epidemics at an unprecedented level. During the COVID-19 pandemic, for example, genomic data revealed that local epidemics varied considerably in the frequency of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) lineage importation and persistence, likely due to a combination of COVID-19 restrictions and changing connectivity. Here, we show that local COVID-19 epidemics are driven by regional transmission, including across international boundaries, but can become increasingly connected to distant locations following the relaxation of public health interventions. By integrating genomic, mobility, and epidemiological data, we find abundant transmission occurring between both adjacent and distant locations, supported by dynamic mobility patterns. We find that changing connectivity significantly influences local COVID-19 incidence. Our findings demonstrate a complex meaning of "local" when investigating connected epidemics and emphasize the importance of collaborative interventions for pandemic prevention and mitigation.

The recency and geographical origins of the bat viruses ancestral to SARS-CoV and SARS-CoV-2.

The emergence of SARS-CoV in 2002 and SARS-CoV-2 in 2019 has led to increased sampling of related sarbecoviruses circulating primarily in horseshoe bats. These viruses undergo frequent recombination and exhibit spatial structuring across Asia. Employing recombination-aware phylogenetic inference on bat sarbecoviruses, we find that the closest-inferred bat virus ancestors of SARS-CoV and SARS-CoV-2 existed just ~1-3 years prior to their emergence in humans. Phylogeographic analyses examining the movement of related sarbecoviruses demonstrate that they traveled at similar rates to their horseshoe bat hosts and have been circulating for thousands of years in Asia. The closest-inferred bat virus ancestor of SARS-CoV likely circulated in western China, and that of SARS-CoV-2 likely circulated in a region comprising southwest China and northern Laos, both a substantial distance from where they emerged. This distance and recency indicate that the direct ancestors of SARS-CoV and SARS-CoV-2 could not have reached their respective sites of emergence via the bat reservoir alone. Our recombination-aware dating and phylogeographic analyses reveal a more accurate inference of evolutionary history than performing only whole-genome or single gene analyses. These results can guide future sampling efforts and demonstrate that viral genomic fragments extremely closely related to SARS-CoV and SARS-CoV-2 were circulating in horseshoe bats, confirming their importance as the reservoir species for SARS viruses.

Emergence and spread of two SARS-CoV-2 variants of interest in Nigeria.

Identifying the dissemination patterns and impacts of a virus of economic or health importance during a pandemic is crucial, as it informs the public on policies for containment in order to reduce the spread of the virus. In this study, we integrated genomic and travel data to investigate the emergence and spread of the SARS-CoV-2 B.1.1.318 and B.1.525 (Eta) variants of interest in Nigeria and the wider Africa region. By integrating travel data and phylogeographic reconstructions, we find that these two variants that arose during the second wave in Nigeria emerged from within Africa, with the B.1.525 from Nigeria, and then spread to other parts of the world. Data from this study show how regional connectivity of Nigeria drove the spread of these variants of interest to surrounding countries and those connected by air-traffic. Our findings demonstrate the power of genomic analysis when combined with mobility and epidemiological data to identify the drivers of transmission, as bidirectional transmission within and between African nations are grossly underestimated as seen in our import risk index estimates.

SARS-CoV-2 diagnostic testing rates determine the sensitivity of genomic surveillance programs.

The first step in SARS-CoV-2 genomic surveillance is testing to identify people who are infected. However, global testing rates are falling as we emerge from the acute health emergency and remain low in many low- and middle-income countries (mean = 27 tests per 100,000 people per day). We simulated COVID-19 epidemics in a prototypical low- and middle-income country to investigate how testing rates, sampling strategies and sequencing proportions jointly impact surveillance outcomes, and showed that low testing rates and spatiotemporal biases delay time to detection of new variants by weeks to months and can lead to unreliable estimates of variant prevalence, even when the proportion of samples sequenced is increased. Accordingly, investments in wider access to diagnostics to support testing rates of approximately 100 tests per 100,000 people per day could enable more timely detection of new variants and reliable estimates of variant prevalence. The performance of global SARS-CoV-2 genomic surveillance programs is fundamentally limited by access to diagnostic testing.

Regional connectivity drove bidirectional transmission of SARS-CoV-2 in the Middle East during travel restrictions.

Regional connectivity and land travel have been identified as important drivers of SARS-CoV-2 transmission. However, the generalizability of this finding is understudied outside of well-sampled, highly connected regions. In this study, we investigated the relative contributions of regional and intercontinental connectivity to the source-sink dynamics of SARS-CoV-2 for Jordan and the Middle East. By integrating genomic, epidemiological and travel data we show that the source of introductions into Jordan was dynamic across 2020, shifting from intercontinental seeding in the early pandemic to more regional seeding for the travel restrictions period. We show that land travel, particularly freight transport, drove introduction risk during the travel restrictions period. High regional connectivity and land travel also drove Jordan's export risk. Our findings emphasize regional connectedness and land travel as drivers of transmission in the Middle East.

The molecular epidemiology of multiple zoonotic origins of SARS-CoV-2.

Understanding the circumstances that lead to pandemics is important for their prevention. We analyzed the genomic diversity of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) early in the coronavirus disease 2019 (COVID-19) pandemic. We show that SARS-CoV-2 genomic diversity before February 2020 likely comprised only two distinct viral lineages, denoted "A" and "B." Phylodynamic rooting methods, coupled with epidemic simulations, reveal that these lineages were the result of at least two separate cross-species transmission events into humans. The first zoonotic transmission likely involved lineage B viruses around 18 November 2019 (23 October to 8 December), and the separate introduction of lineage A likely occurred within weeks of this event. These findings indicate that it is unlikely that SARS-CoV-2 circulated widely in humans before November 2019 and define the narrow window between when SARS-CoV-2 first jumped into humans and when the first cases of COVID-19 were reported. As with other coronaviruses, SARS-CoV-2 emergence likely resulted from multiple zoonotic events.

SARS-CoV-2 diagnostic testing rates determine the sensitivity of genomic surveillance programs.

The first step in SARS-CoV-2 genomic surveillance is testing to identify infected people. However, global testing rates are falling as we emerge from the acute health emergency and remain low in many low- and middle-income countries (LMICs) (mean = 27 tests/100,000 people/day). We simulated COVID-19 epidemics in a prototypical LMIC to investigate how testing rates, sampling strategies, and sequencing proportions jointly impact surveillance outcomes and showed that low testing rates and spatiotemporal biases delay time-to-detection of new variants by weeks-to-months and can lead to unreliable estimates of variant prevalence even when the proportion of samples sequenced is increased. Accordingly, investments in wider access to diagnostics to support testing rates of ~100 tests/100,000 people/day could enable more timely detection of new variants and reliable estimates of variant prevalence. The performance of global SARS-CoV-2 genomic surveillance programs is fundamentally limited by access to diagnostic testing.

Introduction and Establishment of SARS-CoV-2 Gamma Variant in New York City in Early 2021.

BACKGROUND: Monitoring the emergence and spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants is an important public health objective. We investigated how the Gamma variant was established in New York City (NYC) in early 2021 in the presence of travel restrictions that aimed to prevent viral spread from Brazil, the country where the variant was first identified. METHODS: We performed phylogeographic analysis on 15 967 Gamma sequences sampled between 10 March and 1 May 2021, to identify geographic sources of Gamma lineages introduced into NYC. We identified locally circulating Gamma transmission clusters and inferred the timing of their establishment in NYC. RESULTS: We identified 16 phylogenetically distinct Gamma clusters established in NYC (cluster sizes ranged 2-108 genomes); most of them were introduced from Florida and Illinois and only 1 directly from Brazil. By the time the first Gamma case was reported by genomic surveillance in NYC on 10 March, the majority (57%) of circulating Gamma lineages had already been established in the city for at least 2 weeks. CONCLUSIONS: Although travel from Brazil to the United States was restricted from May 2020 through the end of the study period, this restriction did not prevent Gamma from becoming established in NYC as most introductions occurred from domestic locations.

Hepatitis C Virus Transmission Among Men Who Have Sex With Men in Amsterdam: External Introductions May Complicate Microelimination Efforts.

BACKGROUND: It is unclear whether unrestricted access and high uptake of direct-acting antivirals (DAAs) is sufficient to eliminate hepatitis C virus (HCV) in high-risk populations such as men who have sex with men (MSM). This study presents historic trends and current dynamics of HCV transmission among MSM in Amsterdam based on sequence data collected between 1994 and 2019. METHODS: Hypervariable region 1 sequences of 232 primary HCV infections and 56 reinfections were obtained from 244 MSM in care in Amsterdam. Maximum-likelihood phylogenies were constructed for HCV genotypes separately, and time-scaled phylogenies were constructed using a Bayesian coalescent approach. Transmission clusters were determined by Phydelity and trends in the proportion of unclustered sequences over time were evaluated using logistic regression. RESULTS: Seventy-six percent (218/288) of sequences were part of 21 transmission clusters and 13 transmission pairs. Transmission cluster sizes ranged from 3 to 44 sequences. Most clusters were introduced between the late 1990s and early 2010s and no new clusters were introduced after 2012. The proportion of unclustered sequences of subtype 1a, the most prevalent subtype in this population, fluctuated between 0% and 20% in 2009-2012, after which an increase occurred from 0% in 2012 to 50% in 2018. CONCLUSIONS: The proportion of external introductions of HCV infections among MSM in Amsterdam has recently increased, coinciding with high DAA uptake. Frequent international transmission events will likely complicate local microelimination efforts. Therefore, international collaboration combined with international scale-up of prevention, testing, and treatment of HCV infections (including reinfections) is warranted, in particular for local microelimination efforts.

Asynchrony between virus diversity and antibody selection limits influenza virus evolution.

Seasonal influenza viruses create a persistent global disease burden by evolving to escape immunity induced by prior infections and vaccinations. New antigenic variants have a substantial selective advantage at the population level, but these variants are rarely selected within-host, even in previously immune individuals. Using a mathematical model, we show that the temporal asynchrony between within-host virus exponential growth and antibody-mediated selection could limit within-host antigenic evolution. If selection for new antigenic variants acts principally at the point of initial virus inoculation, where small virus populations encounter well-matched mucosal antibodies in previously-infected individuals, there can exist protection against reinfection that does not regularly produce observable new antigenic variants within individual infected hosts. Our results provide a theoretical explanation for how virus antigenic evolution can be highly selective at the global level but nearly neutral within-host. They also suggest new avenues for improving influenza control.

Genetic and antigenic characterization of influenza A/H5N1 viruses isolated from patients in Indonesia, 2008-2015.

Since the initial detection in 2003, Indonesia has reported 200 human cases of highly pathogenic avian influenza H5N1 (HPAI H5N1), associated with an exceptionally high case fatality rate (84%) compared to other geographical regions affected by other genetic clades of the virus. However, there is limited information on the genetic diversity of HPAI H5N1 viruses, especially those isolated from humans in Indonesia. In this study, the genetic and antigenic characteristics of 35 HPAI H5N1 viruses isolated from humans were analyzed. Full genome sequences were analyzed for the presence of substitutions in the receptor binding site, and polymerase complex, as markers for virulence or human adaptation, as well as antiviral drug resistance substitutions. Only a few substitutions associated with human adaptation were observed, a remarkably low prevalence of the human adaptive substitution PB2-E627K, which is common during human infection with other H5N1 clades and a known virulence marker for avian influenza viruses during human infections. In addition, the antigenic profile of these Indonesian HPAI H5N1 viruses was determined using serological analysis and antigenic cartography. Antigenic characterization showed two distinct antigenic clusters, as observed previously for avian isolates. These two antigenic clusters were not clearly associated with time of virus isolation. This study provides better insight in genetic diversity of H5N1 viruses during human infection and the presence of human adaptive markers. These findings highlight the importance of evaluating virus genetics for HPAI H5N1 viruses to estimate the risk to human health and the need for increased efforts to monitor the evolution of H5N1 viruses across Indonesia.

Outbreak Severity of Highly Pathogenic Avian Influenza A(H5N8) Viruses Is Inversely Correlated to Polymerase Complex Activity and Interferon Induction.

Highly pathogenic avian influenza A(H5N8) viruses first emerged in China in 2010 and in 2014 spread throughout Asia and to Europe and the United States via migrating birds. Influenza A(H5N8) viruses were first detected in the Netherlands in 2014 and caused five outbreaks in poultry farms but were infrequently detected in wild birds. In 2016, influenza A(H5N8) viruses were reintroduced into the Netherlands, resulting in eight poultry farm outbreaks. This outbreak resulted in numerous dead wild birds with severe pathology. Phylogenetic analysis showed that the polymerase genes of these viruses had undergone extensive reassortment between outbreaks. Here, we investigated the differences in virulence between the 2014-15 and the 2016-17 outbreaks by characterizing the polymerase complex of influenza A(H5N8) viruses from both outbreaks. We found that viruses from the 2014-15 outbreak had significantly higher polymerase complex activity in both human and avian cell lines than did those from the 2016-17 outbreak. No apparent differences in the balance between transcription and replication of the viral genome were observed. Interestingly, the 2014-15 polymerase complexes induced significantly higher levels of interferon beta (IFN-ß) than the polymerase complexes of the 2016-17 outbreak viruses, mediated via retinoic acid-inducible gene I (RIG-I). Inoculation of primary duck cells with recombinant influenza A(H5N8) viruses, including viruses with reassorted polymerase complexes, showed that the polymerase complexes from the 2014-15 outbreak induced higher levels of IFN-ß despite relatively minor differences in replication capacity. Together, these data suggest that despite the lower levels of polymerase activity, the higher 2016-17 influenza A(H5N8) virus virulence may be attributed to the lower level of activation of the innate immune system.IMPORTANCE Compared to the 2014-15 outbreak, the 2016-17 outbreak of influenza A(H5N8) viruses in the Netherlands and Europe was more virulent; the number of dead or diseased wild birds found and the severity of pathological changes were higher during the 2016-17 outbreak. The polymerase complex plays an important role in influenza virus virulence, and the gene segments of influenza A(H5N8) viruses reassorted extensively between the outbreaks. In this study, the 2014-15 polymerase complexes were found to be more active, which is counterintuitive with the observed higher virulence of the 2016-17 outbreak viruses. Interestingly, the 2014-15 polymerase complexes also induced higher levels of IFN-ß. These findings suggest that the higher virulence of influenza A(H5N8) viruses from the 2016-17 outbreak may be related to the lower induction of IFN-ß. An attenuated interferon response could lead to increased dissemination, pathology, and mortality, as observed in (wild) birds infected during the 2016-2017 outbreak.

Incomplete genetic reconstitution of B cell pools contributes to prolonged immunosuppression after measles.

Measles is a disease caused by the highly infectious measles virus (MeV) that results in both viremia and lymphopenia. Lymphocyte counts recover shortly after the disappearance of measles-associated rash, but immunosuppression can persist for months to years after infection, resulting in increased incidence of secondary infections. Animal models and in vitro studies have proposed various immunological factors underlying this prolonged immune impairment, but the precise mechanisms operating in humans are unknown. Using B cell receptor (BCR) sequencing of human peripheral blood lymphocytes before and after MeV infection, we identified two immunological consequences from measles underlying immunosuppression: (i) incomplete reconstitution of the naïve B cell pool leading to immunological immaturity and (ii) compromised immune memory to previously encountered pathogens due to depletion of previously expanded B memory clones. Using a surrogate model of measles in ferrets, we investigated the clinical consequences of morbillivirus infection and demonstrated a depletion of vaccine-acquired immunity to influenza virus, leading to a compromised immune recall response and increased disease severity after secondary influenza virus challenge. Our results show that MeV infection causes changes in naïve and memory B lymphocyte diversity that persist after the resolution of clinical disease and thus contribute to compromised immunity to previous infections or vaccinations. This work highlights the importance of MeV vaccination not only for the control of measles but also for the maintenance of herd immunity to other pathogens, which can be compromised after MeV infection.

Inferring putative transmission clusters with Phydelity.

Current phylogenetic clustering approaches for identifying pathogen transmission clusters are limited by their dependency on arbitrarily defined genetic distance thresholds for within-cluster divergence. Incomplete knowledge of a pathogen's underlying dynamics often reduces the choice of distance threshold to an exploratory, ad hoc exercise that is difficult to standardise across studies. Phydelity is a new tool for the identification of transmission clusters in pathogen phylogenies. It identifies groups of sequences that are more closely related than the ensemble distribution of the phylogeny under a statistically principled and phylogeny-informed framework, without the introduction of arbitrary distance thresholds. Relative to other distance threshold- and model-based methods, Phydelity outputs clusters with higher purity and lower probability of misclassification in simulated phylogenies. Applying Phydelity to empirical datasets of hepatitis B and C virus infections showed that Phydelity identified clusters with better correspondence to individuals that are more likely to be linked by transmission events relative to other widely used non-parametric phylogenetic clustering methods without the need for parameter calibration. Phydelity is generalisable to any pathogen and can be used to identify putative direct transmission events. Phydelity is freely available at https://github.com/alvinxhan/Phydelity.

Phylogenetic Clustering by Linear Integer Programming (PhyCLIP).

Subspecies nomenclature systems of pathogens are increasingly based on sequence data. The use of phylogenetics to identify and differentiate between clusters of genetically similar pathogens is particularly prevalent in virology from the nomenclature of human papillomaviruses to highly pathogenic avian influenza (HPAI) H5Nx viruses. These nomenclature systems rely on absolute genetic distance thresholds to define the maximum genetic divergence tolerated between viruses designated as closely related. However, the phylogenetic clustering methods used in these nomenclature systems are limited by the arbitrariness of setting intra and intercluster diversity thresholds. The lack of a consensus ground truth to define well-delineated, meaningful phylogenetic subpopulations amplifies the difficulties in identifying an informative distance threshold. Consequently, phylogenetic clustering often becomes an exploratory, ad hoc exercise. Phylogenetic Clustering by Linear Integer Programming (PhyCLIP) was developed to provide a statistically principled phylogenetic clustering framework that negates the need for an arbitrarily defined distance threshold. Using the pairwise patristic distance distributions of an input phylogeny, PhyCLIP parameterizes the intra and intercluster divergence limits as statistical bounds in an integer linear programming model which is subsequently optimized to cluster as many sequences as possible. When applied to the hemagglutinin phylogeny of HPAI H5Nx viruses, PhyCLIP was not only able to recapitulate the current WHO/OIE/FAO H5 nomenclature system but also further delineated informative higher resolution clusters that capture geographically distinct subpopulations of viruses. PhyCLIP is pathogen-agnostic and can be generalized to a wide variety of research questions concerning the identification of biologically informative clusters in pathogen phylogenies. PhyCLIP is freely available at http://github.com/alvinxhan/PhyCLIP, last accessed March 15, 2019.

Association between early life antibiotic use and childhood overweight and obesity: a narrative review.

BACKGROUND: Recent research implicates antibiotic use as a potential contributor to child obesity risk. In this narrative review, we examine current observational evidence on the relation between antibiotic use in early childhood and subsequent measures of child body mass. METHODS: We searched PubMed, Web of Science and the Cochrane Library to identify studies that assessed antibiotic exposure before 3 years of age and subsequent measures of body mass or risk of overweight or obesity in childhood. RESULTS: We identified 13 studies published before October 2017, based on a total of 6 81 332 individuals, which examined the relation between early life antibiotic exposure and measures of child body mass. Most studies did not appropriately account for confounding by indication for antibiotic use. Overall, we found no consistent and conclusive evidence of associations between early life antibiotic use and later child body mass [minimum overall adjusted odds ratio (aOR) reported: 1.01, 95% confidence interval (95% CI) 0.98-1.04, N = 2 60 556; maximum overall aOR reported: 2.56, 95% CI 1.36-4.79, N = 616], with no clinically meaningful increases in weight reported (maximum increase: 1.50 kg at 15 years of age). Notable methodological differences between studies, including variable measures of association and inclusion of confounders, limited more comprehensive interpretations. CONCLUSIONS: Evidence to date is insufficient to indicate that antibiotic use is an important risk factor for child obesity, or leads to clinically important differences in weight. Further comparable studies using routine clinical data may help clarify this association.