Monitoring the fitness of antiviral-resistant influenza strains during an epidemic: a mathematical modelling study

Extraction methods, structural diversity and potential biological activities of Artemisia L. polysaccharides (APs): A review

The extraction and structural characterization of polysaccharides are challenging in plants with overlapping distributions such as Artemisia, the plant genus producing antimalarial drug artemisinin discovered by the Nobel Prize 2015 winning Professor Tu You-you. The diversity in Artemisia polysaccharides (APs) is due to difference in extraction methods leading to different bioactivities. In spite of that, APs utilization is decelerated due to lack of a review portraying current advancements. This review delivers data on extraction, structural characterization and bioactivities of APs with emphasis on mechanisms of action and structure-function relationships. Outcomes indicated that various polysaccharides in 16 Artemisia species were reported and comprehensively described. The common methods for preparing APs were hot water and microwave assisted extractions with maximum yield. Maximum plant parts used to extract APs include leaves, aerial part, whole plant and seeds. The APs presented varying molecular weight, monosaccharide composition, carbohydrates, proteins, uronic acids and phenolic content with around 20 bioactivities. Data on structure-function relationships indicated that the bioactivities of APs are highly correlated with the differences in Mw and monosaccharide's type. While Artemisia species discussed here are the most studied species for their polysaccharides, other Artemisia species may offer unique polysaccharides with distinct biological properties; hence, the future research could focus on expanding the scope of species studied. Broader investigations are also needed specifically on the structure-function relationships of APs with the elucidation of impact of unknown factors on their efficacy.

Epidemic graph diagrams as analytics for epidemic control in the data-rich era

COVID-19 highlighted modeling as a cornerstone of pandemic response. But it also revealed that current models may not fully exploit the high-resolution data on disease progression, epidemic surveillance and host behavior, now available. Take the epidemic threshold, which quantifies the spreading risk throughout epidemic emergence, mitigation, and control. Its use requires oversimplifying either disease or host contact dynamics. We introduce the epidemic graph diagrams to overcome this by computing the epidemic threshold directly from arbitrarily complex data on contacts, disease and interventions. A grammar of diagram operations allows to decompose, compare, simplify models with computational efficiency, extracting theoretical understanding. We use the diagrams to explain the emergence of resistant influenza variants in the 2007-2008 season, and demonstrate that neglecting non-infectious prodromic stages of sexually transmitted infections biases the predicted epidemic risk, compromising control. The diagrams are general, and improve our capacity to respond to present and future public health challenges.

The mechanism shaping the logistic growth of mutation proportion in epidemics at population scale

Virus evolution is a common process of pathogen adaption to host population and environment. Frequently, a small but important fraction of virus mutations are reported to contribute to higher risks of host infection, which is one of the major determinants of infectious diseases outbreaks at population scale. The key mutations contributing to transmission advantage of a genetic variant often grow and reach fixation rapidly. Based on classic epidemiology theories of disease transmission, we proposed a mechanistic explanation of the process that between-host transmission advantage may shape the observed logistic curve of the mutation proportion in population. The logistic growth of mutation is further generalized by incorporating time-varying selective pressure to account for impacts of external factors on pathogen adaptiveness. The proposed model is implemented in real-world data of COVID-19 to capture the emerging trends and changing dynamics of the B.1.1.7 strains of SARS-CoV-2 in England. The model characterizes and establishes the underlying theoretical mechanism that shapes the logistic growth of mutation in population.

Predicting the Trajectory of Replacements of SARS-CoV-2 Variants Using Relative Reproduction Numbers

New variants of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) with high effective reproduction numbers are continuously being selected by natural selection. To establish effective control measures for new variants, it is crucial to know their transmissibility and replacement trajectory in advance. In this paper, we conduct retrospective prediction tests for the variant replacement from Alpha to Delta in England, using the relative reproduction numbers of Delta with respect to Alpha estimated from partial observations. We found that once Delta's relative frequency reached 0.15, the date when the relative frequency of Delta would reach 0.90 was predicted with maximum absolute prediction errors of three days. This means that the time course of the variant replacement could be accurately predicted from early observations. Together with the estimated relative reproduction number of a new variant with respect to old variants, the predicted replacement timing will be crucial information for planning control strategies against the new variant.

Estimating relative generation times and reproduction numbers of Omicron BA.1 and BA.2 with respect to Delta variant in Denmark

The Omicron variant spreads fastest as ever among the severe acute respiratory syndrome coronaviruses 2 (SARS-CoV-2) we had so far. The BA.1 and BA.2 sublineages of Omicron are circulating worldwide and it is urgent to evaluate the transmission advantages of these sublineages. Using a mathematical model describing trajectories of variant frequencies that assumes a constant ratio in mean generation times and a constant ratio in effective reproduction numbers among variants, trajectories of variant frequencies in Denmark from November 22, 2021 to February 26, 2022 were analyzed. We found that the mean generation time of Omicron BA.1 is 0.44-0.46 times that of Delta and the effective reproduction number of Omicron BA.1 is 1.88-2.19 times larger than Delta under the epidemiological conditions at the time. We also found that the mean generation time of Omicron BA.2 is 0.76-0.80 times that of BA.1 and the effective reproduction number of Omicron BA.2 is 1.25-1.27 times larger than Omicron BA.1. These estimates on the ratio of mean generation times and the ratio of effective reproduction numbers have epidemiologically important implications. The contact tracing for Omicron BA.2 infections must be done more quickly than that for BA.1 to stop further infections by quarantine. In the Danish population, the control measures against Omicron BA.2 need to reduce 20-21% of additional contacts compared to that against BA.1.

The importance of the generation interval in investigating dynamics and control of new SARS-CoV-2 variants

Inferring the relative strength (i.e. the ratio of reproduction numbers) and relative speed (i.e. the difference between growth rates) of new SARS-CoV-2 variants is critical to predicting and controlling the course of the current pandemic. Analyses of new variants have primarily focused on characterizing changes in the proportion of new variants, implicitly or explicitly assuming that the relative speed remains fixed over the course of an invasion. We use a generation-interval-based framework to challenge this assumption and illustrate how relative strength and speed change over time under two idealized interventions: a constant-strength intervention like idealized vaccination or social distancing, which reduces transmission rates by a constant proportion, and a constant-speed intervention like idealized contact tracing, which isolates infected individuals at a constant rate. In general, constant-strength interventions change the relative speed of a new variant, while constant-speed interventions change its relative strength. Differences in the generation-interval distributions between variants can exaggerate these changes and modify the effectiveness of interventions. Finally, neglecting differences in generation-interval distributions can bias estimates of relative strength.

The non-pharmaceutical interventions may affect the advantage in transmission of mutated variants during epidemics: A conceptual model for COVID-19

As the COVID-19 pandemic continues, genetic mutations in SARS-CoV-2 emerge, and some of them are found more contagious than the previously identified strains, acting as the major mechanism for many large-scale epidemics. The transmission advantage of mutated variants is widely believed as an innate biological feature that is difficult to be altered by artificial factors. In this study, we explore how non-pharmaceutical interventions (NPI) may affect transmission advantage. A two-strain compartmental epidemic model is proposed and simulated to investigate the biological mechanism of the relationships among different NPIs, the changes in transmissibility of each strain and transmission advantage. Although the NPIs are effective in flattening the epidemic curve, we demonstrate that NPIs probably lead to a decline in transmission advantage, which is likely to occur if the NPIs become intensive. Our findings uncover the mechanistic relationship between NPIs and transmission advantage dynamically, and highlight the important role of NPIs not only in controlling the intensity of epidemics but also in slowing or even containing the growth of the proportion of variants.

Genomic epidemiology of SARS-CoV-2 under an elimination strategy in Hong Kong

Hong Kong employed a strategy of intermittent public health and social measures alongside increasingly stringent travel regulations to eliminate domestic SARS-CoV-2 transmission. By analyzing 1899 genome sequences (>18% of confirmed cases) from 23-January-2020 to 26-January-2021, we reveal the effects of fluctuating control measures on the evolution and epidemiology of SARS-CoV-2 lineages in Hong Kong. Despite numerous importations, only three introductions were responsible for 90% of locally-acquired cases. Community outbreaks were caused by novel introductions rather than a resurgence of circulating strains. Thus, local outbreak prevention requires strong border control and community surveillance, especially during periods of less stringent social restriction. Non-adherence to prolonged preventative measures may explain sustained local transmission observed during wave four in late 2020 and early 2021. We also found that, due to a tight transmission bottleneck, transmission of low-frequency single nucleotide variants between hosts is rare.

The co-circulating transmission dynamics of SARS-CoV-2 Alpha and Eta variants in Nigeria: A retrospective modeling study of COVID-19

BACKGROUND

The COVID-19 pandemic poses serious threats to public health globally, and the emerging mutations in SARS-CoV-2 genomes has become one of the major challenges of disease control. In the second epidemic wave in Nigeria, the roles of co-circulating SARS-CoV-2 Alpha (ie, B.1.1.7) and Eta (ie, B.1.525) variants in contributing to the epidemiological outcomes were of public health concerns for investigation.

METHODS

We developed a mathematical model to capture the transmission dynamics of different types of strains in Nigeria. By fitting to the national-wide COVID-19 surveillance data, the transmission advantages of SARS-CoV-2 variants were estimated by likelihood-based inference framework.

RESULTS

The reproduction numbers were estimated to decrease steadily from 1.5 to 0.8 in the second epidemic wave. In December 2020, when both Alpha and Eta variants were at low prevalent levels, their transmission advantages (against the wild type) were estimated at 1.51 (95% credible intervals (CrI) = 1.48, 1.54), and 1.56 (95% CrI = 1.54, 1.59), respectively. In January 2021, when the original variants almost vanished, we estimated a weak but significant transmission advantage of Eta against Alpha variants with 1.14 (95% CrI = 1.11, 1.16).

CONCLUSIONS

Our findings suggested evidence of the transmission advantages for both Alpha and Eta variants, of which Eta appeared slightly more infectious than Alpha. We highlighted the critical importance of COVID-19 control measures in mitigating the outbreak size and relaxing the burdens to health care systems in Nigeria.

Estimating the transmission advantage of the D614G mutant strain of SARS-CoV-2, December 2019 to June 2020

IntroductionThe SARS-CoV-2 lineages carrying the amino acid change D614G have become the dominant variants in the global COVID-19 pandemic. By June 2021, all the emerging variants of concern carried the D614G mutation. The rapid spread of the G614 mutant suggests that it may have a transmission advantage over the D614 wildtype.AimOur objective was to estimate the transmission advantage of D614G by integrating phylogenetic and epidemiological analysis.MethodsWe assume that the mutation D614G was the only site of interest which characterised the two cocirculating virus strains by June 2020, but their differential transmissibility might be attributable to a combination of D614G and other mutations. We define the fitness of G614 as the ratio of the basic reproduction number of the strain with G614 to the strain with D614 and applied an epidemiological framework for fitness inference to analyse SARS-CoV-2 surveillance and sequence data.ResultsUsing this framework, we estimated that the G614 mutant is 31% (95% credible interval: 28-34) more transmissible than the D614 wildtype. Therefore, interventions that were previously effective in containing or mitigating the D614 wildtype (e.g. in China, Vietnam and Thailand) may be less effective against the G614 mutant.ConclusionOur framework can be readily integrated into current SARS-CoV-2 surveillance to monitor the emergence and fitness of mutant strains such that pandemic surveillance, disease control and development of treatment and vaccines can be adjusted dynamically.

Real-time quantification of the transmission advantage associated with a single mutation in pathogen genomes: a case study on the D614G substitution of SARS-CoV-2

BACKGROUND

The COVID-19 pandemic poses serious threats to global health, and the emerging mutation in SARS-CoV-2 genomes, e.g., the D614G substitution, is one of the major challenges of disease control. Characterizing the role of the mutation activities is of importance to understand how the evolution of pathogen shapes the epidemiological outcomes at population scale.

METHODS

We developed a statistical framework to reconstruct variant-specific reproduction numbers and estimate transmission advantage associated with the mutation activities marked by single substitution empirically. Using likelihood-based approach, the model is exemplified with the COVID-19 surveillance data from January 1 to June 30, 2020 in California, USA. We explore the potential of this framework to generate early warning signals for detecting transmission advantage on a real-time basis.

RESULTS

The modelling framework in this study links together the mutation activity at molecular scale and COVID-19 transmissibility at population scale. We find a significant transmission advantage of COVID-19 associated with the D614G substitution, which increases the infectivity by 54% (95%CI: 36, 72). For the early alarming potentials, the analytical framework is demonstrated to detect this transmission advantage, before the mutation reaches dominance, on a real-time basis.

CONCLUSIONS

We reported an evidence of transmission advantage associated with D614G substitution, and highlighted the real-time estimating potentials of modelling framework.

Exploring the Interaction between E484K and N501Y Substitutions of SARS-CoV-2 in Shaping the Transmission Advantage of COVID-19 in Brazil: A Modeling Study

The COVID-19 pandemic poses serious threats to global health, and the emerging mutation in SARS-CoV-2 genomes is one of the major challenges of disease control. Considering the growth of epidemic curve and the circulating SARS-CoV-2 variants in Brazil, the role of locally prevalent E484K and N501Y substitutions in contributing to the epidemiological outcomes is of public health interest for investigation. We developed a likelihood-based statistical framework to reconstruct reproduction numbers, estimate transmission advantage associated with different SARS-CoV-2 variants regarding the marking (identifying) 484K and 501Y substitutions (including Alpha, Zeta, and Gamma variants) in Brazil, and explored the interactive effects of genetic activities on transmission advantage marked by these two mutations. We found a significant transmission advantage associated with the 484K/501Y variants (including P.1 or Gamma variants), which increased the infectivity significantly by 23%. In contrast and by comparison to Gamma variants, E484K or N501Y (including Alpha or Zeta variants) substitution alone appeared less likely to secure a concrete transmission advantage in Brazil. Our finding indicates that the combined impact of genetic activities on transmission advantage marked by 484K/501Y outperforms their independent contributions in Brazil, which implies an interactive effect in shaping the increase in the infectivity of COVID-19. Future studies are needed to investigate the mechanisms of how E484K and N501Y mutations and the complex genetic mutation activities marked by them in SARS-CoV-2 affect the transmissibility of COVID-19.

SARS-CoV-2 under an elimination strategy in Hong Kong

Hong Kong utilized an elimination strategy with intermittent use of public health and social measures and increasingly stringent travel regulations to control SARS-CoV-2 transmission. By analyzing >1700 genome sequences representing 17% of confirmed cases from 23-January-2020 to 26-January-2021, we reveal the effects of fluctuating control measures on the evolution and epidemiology of SARS-CoV-2 lineages in Hong Kong. Despite numerous importations, only three introductions were responsible for 90% of locally-acquired cases, two of which circulated cryptically for weeks while less stringent measures were in place. We found that SARS-CoV-2 within-host diversity was most similar among transmission pairs and epidemiological clusters due to a strong transmission bottleneck through which similar genetic background generates similar within-host diversity.

ONE SENTENCE SUMMARY

Out of the 170 detected introductions of SARS-CoV-2 in Hong Kong during 2020, three introductions caused 90% of community cases.

Early transmissibility assessment of the N501Y mutant strains of SARS-CoV-2 in the United Kingdom, October to November 2020

Two new SARS-CoV-2 lineages with the N501Y mutation in the receptor-binding domain of the spike protein spread rapidly in the United Kingdom. We estimated that the earlier 501Y lineage without amino acid deletion Δ69/Δ70, circulating mainly between early September and mid-November, was 10% (6-13%) more transmissible than the 501N lineage, and the 501Y lineage with amino acid deletion Δ69/Δ70, circulating since late September, was 75% (70-80%) more transmissible than the 501N lineage.

CD137 costimulation enhances the antiviral activity of Vγ9Vδ2-T cells against influenza virus

Influenza epidemics and pandemics are constant threats to global public health. Although strategies including vaccines and antiviral drugs have achieved great advances in controlling influenza virus infection, the efficacy of these strategies is limited by the highly frequent mutations in the viral genome and the emergence of drug-resistant strains. Our previous study indicated that boosting the immunity of human Vγ9Vδ2-T cells with the phosphoantigen pamidronate could be a therapeutic strategy to treat seasonal and avian influenza virus infections. However, one notable drawback of γδ-T cell-based immunotherapy is the rapid exhaustion of proliferation and effector responses due to repeated treatments with phosphoantigens. Here, we found that the expression of CD137 was inducible in Vγ9Vδ2-T cells following antigenic stimulation. CD137⁺ Vγ9Vδ2-T cells displayed more potent antiviral activity against influenza virus than their CD137⁻ counterparts in vitro and in Rag2^-/- γc^-/- mice. We further demonstrated that CD137 costimulation was essential for Vγ9Vδ2-T cell activation, proliferation, survival and effector functions. In humanized mice reconstituted with human peripheral blood mononuclear cells, CD137 costimulation with a recombinant human CD137L protein boosted the therapeutic effects of pamidronate against influenza virus. Our study provides a novel strategy of targeting CD137 to improve the efficacy of Vγ9Vδ2-T cell-based immunotherapy.

Neuraminidase inhibitor resistance in influenza: a clinical perspective

PURPOSE OF REVIEW

Neuraminidase inhibitors (NAIs), including oseltamivir, zanamivir, and peramivir, is the main class of antiviral available for clinical use. As such, development of resistance toward these agents is of great clinical and public health concern.

RECENT FINDINGS

At present, NAI resistance remains uncommon among the circulating viruses (oseltamivir <3.5%, zanamivir <1%). Resistance risk is slightly higher in A(H1N1) than A(H3N2) and B viruses. Resistance may emerge during drug exposure, particularly among young children (<5 years), the immunocompromised, and individuals receiving prophylactic regimens. H275Y A(H1N1) variant, showing high-level oseltamivir resistance, is capable of causing outbreaks. R294K A(H7N9) variant shows reduced inhibition across NAIs. Multi-NAI resistance has been reported in the immunocompromised.

SUMMARY

These findings highlight the importance of continuous surveillance, and assessment of viral fitness and transmissibility of resistant virus strains. Detection can be challenging, especially in a mix of resistant and wild-type viruses. Recent advances in molecular techniques (e.g. targeted mutation PCR, iART, ddPCR, pyrosequencing, next-generation sequencing) have improved detection and our understanding of viral dynamics. Treatment options available for oseltamivir-resistant viruses are limited, and susceptibility testing of other NAIs may be required, but non-NAI antivirals (e.g. polymerase inhibitors) that are active against these resistant viruses are in late-stage clinical development.

Aloe Polysaccharides Inhibit Influenza A Virus Infection-A Promising Natural Anti-flu Drug

Influenza A virus causes periodic outbreaks and seriously threatens human health. The drug-resistant mutants have shown an epidemic trend because of the abuse of chemical drugs. Aloe polysaccharides (APS) extracted from Aloe vera leaves have evident effects on the therapy of virus infection. However, the activity of APS in anti-influenza virus has yet to be investigated. Here, we refined polysaccharides from A. vera leaf. In vitro test revealed that APS could inhibit the replication of a H1N1 subtype influenza virus, and the most obvious inhibitory effect was observed in the viral adsorption period. Transmission electron microscopy indicated that APS directly interacted with influenza virus particles. Experiments on PR8 (H1N1) virus infection in mice demonstrated that APS considerably ameliorated the clinical symptoms and the lung damage of the infected mice, and significantly reduced the virus loads and mortality. Our findings provided a theoretical basis for the development of novel natural anti-influenza agents.

Zoonotic Potential of Influenza A Viruses: A Comprehensive Overview

Influenza A viruses (IAVs) possess a great zoonotic potential as they are able to infect different avian and mammalian animal hosts, from which they can be transmitted to humans. This is based on the ability of IAV to gradually change their genome by mutation or even reassemble their genome segments during co-infection of the host cell with different IAV strains, resulting in a high genetic diversity. Variants of circulating or newly emerging IAVs continue to trigger global health threats annually for both humans and animals. Here, we provide an introduction on IAVs, highlighting the mechanisms of viral evolution, the host spectrum, and the animal/human interface. Pathogenicity determinants of IAVs in mammals, with special emphasis on newly emerging IAVs with pandemic potential, are discussed. Finally, an overview is provided on various approaches for the prevention of human IAV infections.

Triple combination of FDA-approved drugs including flufenamic acid, clarithromycin and zanamivir improves survival of severe influenza in mice

Seasonal influenza virus remains a common cause of mortality despite the use of neuraminidase inhibitors. This study evaluated the efficacy of a triple combination of zanamivir, clarithromycin and flufenamic acid (FFA) in the treatment of influenza virus A(H1N1) infection. An in vitro cell protection assay and a multiple-cycle growth assay showed that the antiviral activity of zanamivir was enhanced when combined with clarithromycin or FFA. A mouse challenge model was used here for the evaluation of the in vivo efficacy of the triple combination treatment. We found that mice receiving the triple combination of FFA, zanamivir, and clarithromycin had a significantly better survival rate than those receiving the double combination of zanamivir and clarithromycin (88% versus 44%, P = 0.0083) or zanamivir monotherapy (88% versus 26%, P = 0.0002). Mice in the FFA-zanamivir-clarithromycin triple combination group also exhibited significantly less body weight loss than those in the zanamivir-clarithromycin double combination group. There was no significant difference in the lung viral titers among the different groups from day 2 to day 6 postinfection. However, the levels of IL-1β, TNF-α and RANTES in the FFA-zanamivir-clarithromycin triple combination group were significantly lower than those in the zanamivir-clarithromycin double combination group, zanamivir monotherapy group, or solvent group on day 2 postinfection. Our findings showed that the FFA-zanamivir-clarithromycin triple combination improved the inflammatory markers and survival of severe influenza A(H1N1) infection in mice.