Within-Host Viral Diversity: A Window into Viral Evolution

2020 ◽  
Vol 7 (1) ◽  
pp. 63-81 ◽  
Author(s):  
Adam S. Lauring
Keyword(s):  
Large Scale ◽  
Evolutionary Dynamics ◽  
Viral Evolution ◽  
Experimental Studies ◽  
Disease Spread ◽  
Viral Diversity ◽  
Host Diversity ◽  
Models Of Disease ◽  
Host Evolution ◽  
Viral Sequencing

The evolutionary dynamics of a virus can differ within hosts and across populations. Studies of within-host evolution provide an important link between experimental studies of virus evolution and large-scale phylodynamic analyses. They can determine the extent to which global processes are recapitulated on local scales and how accurately experimental infections model natural ones. They may also inform epidemiologic models of disease spread and reveal how host-level dynamics contribute to a virus's evolution at a larger scale. Over the last decade, advances in viral sequencing have enabled detailed studies of viral genetic diversity within hosts. I review how within-host diversity is sampled, measured, and expressed, and how comparative studies of viral diversity can be leveraged to elucidate a virus's evolutionary dynamics. These concepts are illustrated with detailed reviews of recent research on the within-host evolution of influenza virus, dengue virus, and cytomegalovirus.

scholarly journals Lineage replacement and evolution captured by the United Kingdom Covid Infection Survey

2022 ◽  
Author(s):  
Katrina A Lythgoe ◽  
Tanya Golubchik ◽  
Matthew Hall ◽  
Thomas House ◽  
George MacIntyre-Cockett ◽  
...  
Keyword(s):  
United Kingdom ◽  
Large Scale ◽  
Evolutionary Dynamics ◽  
Surveillance Studies ◽  
National Statistics ◽  
Major Lineage ◽  
The United Kingdom ◽  
Rates Of Evolution ◽  
Large Household ◽  
Viral Sequencing

The Office for National Statistics COVID-19 Infection Survey is a large household-based surveillance study based in the United Kingdom. Here, we report on the epidemiological and evolutionary dynamics of SARS-CoV-2 determined by analysing sequenced samples collected up until 13th November 2021. We observed four distinct sweeps or partial-sweeps, by lineages B.1.177, B.1.1.7/Alpha, B.1.617.2/Delta, and finally AY.4.2, a sublineage of B.1.617.2, with each sweeping lineage having a distinct growth advantage compared to their predecessors. Evolution was characterised by steady rates of evolution and increasing diversity within lineages, but with step increases in divergence associated with each sweeping major lineage, leading to a faster overall rate of evolution and fluctuating levels of diversity. These observations highlight the value of viral sequencing integrated into community surveillance studies to monitor the viral epidemiology and evolution of SARS-CoV-2, and potentially other pathogens, particularly as routine PCR testing is phased out or in settings where large-scale sequencing is not feasible.

scholarly journals Exploiting the “survival of the likeliest” to enable evolution-guided drug design

2019 ◽  
Author(s):  
Chuan Liu ◽  
Scott M. Leighow ◽  
Haider Inam ◽  
Boyang Zhao ◽  
Justin R. Pritchard
Keyword(s):  
Drug Resistance ◽  
Drug Design ◽  
Large Scale ◽  
Evolutionary Dynamics ◽  
Stochastic Dynamics ◽  
Genetic Resistance ◽  
Experimental Studies ◽  
New Paradigm ◽  
Resistant Species ◽  
Codon Substitution

SummaryTheoretical treatments of evolutionary dynamics tend to model the probability that a single “resistant” species will arise in a population. However, experimental studies have identified a diversity of mutations that can lead to genetic resistance. By quantitatively predicting mutations that occur across an entire drug target during treatment, we identify and bridge a fundamental gap in drug resistance theory: that nucleotide/codon substitution biases can dictate which resistant variants arise in the clinic. We find that the likeliest mutation can beat the most resistant mutation. This creates a new paradigm in drug resistance that we term“survival of the likeliest”. We use epidemiological evidence in leukemia, isogenic experiments, stochastic dynamics, and large-scale simulations to support this theory. In addition, this work has strong implications for drug design because not all resistance liabilities are created equal. In pathogenic populations that exhibit survival of the likeliest, exploiting the least likely evolutionary path can minimize resistance across a population during widespread drug use, even when a vulnerability-free molecule or combination cannot be made.Data and Code Availabilityhttps://github.com/pritchardlabatpsu/SurvivalOfTheLikeliest/

scholarly journals Large-Scale Measurement of Aggregate Human Colocation Patterns for Epidemiological Modeling

2020 ◽  
Author(s):  
Shankar Iyer ◽  
Brian Karrer ◽  
Daniel Citron ◽  
Farshad Kooti ◽  
Paige Maas ◽  
...  
Keyword(s):  
Large Scale ◽  
Physical Space ◽  
Disease Spread ◽  
Good Program ◽  
Epidemiological Modeling ◽  
Public Health Emergencies ◽  
Large Scale Analysis ◽  
Global Pandemic ◽  
Models Of Disease ◽  
Further Development

AbstractTo understand and model public health emergencies, epidemiologists need data that describes how humans are moving and interacting across physical space. Such data has traditionally been difficult for researchers to obtain with the temporal resolution and geographic breadth that is needed to study, for example, a global pandemic. This paper describes Colocation Maps, which are spatial network datasets that have been developed within Facebook’s Data For Good program. These Maps estimate how often people from different regions are colocated: in particular, for a pair of geographic regions x and y, these Maps estimate the probability that a randomly chosen person from x and a randomly chosen person from y are simultaneously located in the same place during a randomly chosen minute in a given week. These datasets are well suited to parametrize metapopulation models of disease spread or to measure temporal changes in interactions between people from different regions; indeed, they have already been used for both of these purposes during the COVID-19 pandemic. In this paper, we show how Colocation Maps differ from existing data sources, describe how the datasets are built, provide examples of their use in compartmental modeling, and summarize ideas for further development of these and related datasets. We also conduct the first large-scale analysis of human colocation patterns across the world. Among the findings of this study, we observe that a pair of regions can exhibit high colocation despite few people moving between them. We also find that although few pairs of people are colocated for many days over the course of a week, these pairs can contribute significant fractions of the total colocation time within a region or between pairs of regions.

scholarly journals Leisure Time Sports Activities and Life Satisfaction: Deeper Insights Based on a Representative Survey from Germany

2020 ◽  
Author(s):  
Michael Mutz ◽  
Anne K. Reimers ◽  
Yolanda Demetriou
Keyword(s):  
Life Satisfaction ◽  
Large Scale ◽  
Leisure Time ◽  
Organizational Context ◽  
Experimental Studies ◽  
Well Being ◽  
Activity Level ◽  
Leisure Satisfaction ◽  
General Life Satisfaction ◽  
Sports Activities

Abstract Observational and experimental studies show that leisure time sporting activity (LTSA) is associated with higher well-being. However, scholars often seem to assume that 1) LTSA fosters “general” life satisfaction, thereby ignoring effects on domain satisfaction; 2) the effect of LTSA on well-being is linear and independent of a person’s general activity level; 3) the amount of LTSA is more important than the repertoire of LTSA, i.e. the number of different activities; 4) all kinds of LTSA are equal in their effects, irrespective of spatial and organisational context conditions. Using data from the German SALLSA-Study (“Sport, Active Lifestyle and Life Satisfaction”), a large-scale CAWI-Survey (N = 1008) representing the population ≥ 14 years, the paper takes a closer look on these assumptions. Findings demonstrate that LTSA is associated with general life satisfaction and domain-specific satisfaction (concerning relationships, appearance, leisure, work and health), but that the relationship is most pronounced for leisure satisfaction. Associations of sport with life satisfaction, leisure satisfaction and subjective health are non-linear, approaching an injection point from which on additional LTSA is no longer beneficial. Moreover, findings lend support to the notion that diversity in LTSA matters, as individuals with higher variation in sports activities are more satisfied. Finally, results with regard to spatial and organizational context suggest that outdoor sports and club-organized sports have additional benefits.

scholarly journals Why does the spread of COVID-19 vary greatly in different countries? Revealing the efficacy of face masks in epidemic prevention

2021 ◽  
Vol 149 ◽  
Author(s):  
Jincheng Wei ◽  
Shurui Guo ◽  
Enshen Long ◽  
Li Zhang ◽  
Bizhen Shu ◽  
...  
Keyword(s):  
Social Isolation ◽  
Large Scale ◽  
Experimental Studies ◽  
Weighted Average ◽  
Filtration Efficiency ◽  
Volume Distribution ◽  
Particle Sizes ◽  
Economic Activities ◽  
Protection Measure ◽  
Source Of Infection

Abstract The severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) is highly contagious, and the coronavirus disease 2019 (COVID-19) pandemic caused by it has forced many countries to adopt ‘lockdown’ measures to prevent the spread of the epidemic through social isolation of citizens. Some countries proposed universal mask wearing as a protection measure of public health to strengthen national prevention efforts and to limit the wider spread of the epidemic. In order to reveal the epidemic prevention efficacy of masks, this paper systematically evaluates the experimental studies of various masks and filter materials, summarises the general characteristics of the filtration efficiency of isolation masks with particle size, and reveals the actual efficacy of masks by combining the volume distribution characteristics of human exhaled droplets with different particle sizes and the SARS-CoV-2 virus load of nasopharynx and throat swabs from patients. The existing measured data show that the filtration efficiency of all kinds of masks for large particles and extra-large droplets is close to 100%. From the perspective of filtering the total number of pathogens discharged in the environment and protecting vulnerable individuals from breathing live viruses, the mask has a higher protective effect. If considering the weighted average filtration efficiency with different particle sizes, the filtration efficiencies of the N95 mask and the ordinary mask are 99.4% and 98.5%, respectively. The mask can avoid releasing active viruses to the environment from the source of infection, thus maximising the protection of vulnerable individuals by reducing the probability of inhaling a virus. Therefore, if the whole society strictly implements the policy of publicly wearing masks, the risk of large-scale spread of the epidemic can be greatly reduced. Compared with the overall cost of social isolation, limited personal freedoms and forced suspension of economic activities, the inconvenience for citizens caused by wearing masks is perfectly acceptable.

scholarly journals The Role of Risk Preferences in Responses to Messaging About COVID-19 Vaccine Take-Up

2021 ◽  
pp. 194855062199962
Author(s):  
Jennifer S. Trueblood ◽  
Abigail B. Sussman ◽  
Daniel O’Leary
Keyword(s):  
Large Scale ◽  
Risk Preferences ◽  
Herd Immunity ◽  
Disease Spread ◽  
Short Term ◽  
Policy Makers ◽  
Health Crisis ◽  
Flu Vaccine ◽  
Nationally Representative

Development of an effective COVID-19 vaccine is widely considered as one of the best paths to ending the current health crisis. While the ability to distribute a vaccine in the short-term remains uncertain, the availability of a vaccine alone will not be sufficient to stop disease spread. Instead, policy makers will need to overcome the additional hurdle of rapid widespread adoption. In a large-scale nationally representative survey ( N = 34,200), the current work identifies monetary risk preferences as a correlate of take-up of an anticipated COVID-19 vaccine. A complementary experiment ( N = 1,003) leverages this insight to create effective messaging encouraging vaccine take-up. Individual differences in risk preferences moderate responses to messaging that provides benchmarks for vaccine efficacy (by comparing it to the flu vaccine), while messaging that describes pro-social benefits of vaccination (specifically herd immunity) speeds vaccine take-up irrespective of risk preferences. Findings suggest that policy makers should consider risk preferences when targeting vaccine-related communications.

scholarly journals Interventions to optimize medication use in nursing homes: a narrative review

2021 ◽  
Author(s):  
Anne Spinewine ◽  
Perrine Evrard ◽  
Carmel Hughes
Keyword(s):  
Nursing Homes ◽  
Large Scale ◽  
Adverse Drug Events ◽  
Experimental Studies ◽  
Medication Use ◽  
Nursing Home Residents ◽  
Qualitative Studies ◽  
Patient Centered ◽  
Barriers And Enablers ◽  
Specific Medication

Abstract Purpose Polypharmacy, medication errors and adverse drug events are frequent among nursing home residents. Errors can occur at any step of the medication use process. We aimed to review interventions aiming at optimization of any step of medication use in nursing homes. Methods We narratively reviewed quantitative as well as qualitative studies, observational and experimental studies that described interventions, their effects as well as barriers and enablers to implementation. We prioritized recent studies with relevant findings for the European setting. Results Many interventions led to improvements in medication use. However, because of outcome heterogeneity, comparison between interventions was difficult. Prescribing was the most studied aspect of medication use. At the micro-level, medication review, multidisciplinary work, and more recently, patient-centered care components dominated. At the macro-level, guidelines and legislation, mainly for specific medication classes (e.g., antipsychotics) were employed. Utilization of technology also helped improve medication administration. Several barriers and enablers were reported, at individual, organizational, and system levels. Conclusion Overall, existing interventions are effective in optimizing medication use. However there is a need for further European well-designed and large-scale evaluations of under-researched intervention components (e.g., health information technology, patient-centered approaches), specific medication classes (e.g., antithrombotic agents), and interventions targeting medication use aspects other than prescribing (e.g., monitoring). Further development and uptake of core outcome sets is required. Finally, qualitative studies on barriers and enablers for intervention implementation would enable theory-driven intervention design.

scholarly journals Different Within-Host Viral Evolution Dynamics in Severely Immunosuppressed Cases with Persistent SARS-CoV-2

Biomedicines ◽  
2021 ◽  
Vol 9 (7) ◽  
pp. 808
Author(s):  
Laura Pérez-Lago ◽  
Teresa Aldámiz-Echevarría ◽  
Rita García-Martínez ◽  
Leire Pérez-Latorre ◽  
Marta Herranz ◽  
...  
Keyword(s):  
Single Nucleotide Polymorphisms ◽  
Evolutionary Dynamics ◽  
Viral Evolution ◽  
Special Focus ◽  
Nucleotide Polymorphisms ◽  
Single Nucleotide ◽  
New Variant ◽  
History Of ◽  
Evolution Dynamics ◽  
The Uk

A successful Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) variant, B.1.1.7, has recently been reported in the UK, causing global alarm. Most likely, the new variant emerged in a persistently infected patient, justifying a special focus on these cases. Our aim in this study was to explore certain clinical profiles involving severe immunosuppression that may help explain the prolonged persistence of viable viruses. We present three severely immunosuppressed cases (A, B, and C) with a history of lymphoma and prolonged SARS-CoV-2 shedding (2, 4, and 6 months), two of whom finally died. Whole-genome sequencing of 9 and 10 specimens from Cases A and B revealed extensive within-patient acquisition of diversity, 12 and 28 new single nucleotide polymorphisms, respectively, which suggests ongoing SARS-CoV-2 replication. This diversity was not observed for Case C after analysing 5 sequential nasopharyngeal specimens and one plasma specimen, and was only observed in one bronchoaspirate specimen, although viral viability was still considered based on constant low Ct values throughout the disease and recovery of the virus in cell cultures. The acquired viral diversity in Cases A and B followed different dynamics. For Case A, new single nucleotide polymorphisms were quickly fixed (13–15 days) after emerging as minority variants, while for Case B, higher diversity was observed at a slower emergence: fixation pace (1–2 months). Slower SARS-CoV-2 evolutionary pace was observed for Case A following the administration of hyperimmune plasma. This work adds knowledge on SARS-CoV-2 prolonged shedding in severely immunocompromised patients and demonstrates viral viability, noteworthy acquired intra-patient diversity, and different SARS-CoV-2 evolutionary dynamics in persistent cases.

scholarly journals Opportunistic Large Array Propagation Models: A Comprehensive Survey

Sensors ◽  
2021 ◽  
Vol 21 (12) ◽  
pp. 4206
Author(s):  
Farhan Nawaz ◽  
Hemant Kumar ◽  
Syed Ali Hassan ◽  
Haejoon Jung
Keyword(s):  
Energy Efficient ◽  
Large Scale ◽  
Performance Metrics ◽  
Experimental Studies ◽  
Cooperative Transmission ◽  
Analytical Models ◽  
Future Research ◽  
Large Array ◽  
Propagation Models ◽  
Comprehensive Survey

Enabled by the fifth-generation (5G) and beyond 5G communications, large-scale deployments of Internet-of-Things (IoT) networks are expected in various application fields to handle massive machine-type communication (mMTC) services. Device-to-device (D2D) communications can be an effective solution in massive IoT networks to overcome the inherent hardware limitations of small devices. In such D2D scenarios, given that a receiver can benefit from the signal-to-noise-ratio (SNR) advantage through diversity and array gains, cooperative transmission (CT) can be employed, so that multiple IoT nodes can create a virtual antenna array. In particular, Opportunistic Large Array (OLA), which is one type of CT technique, is known to provide fast, energy-efficient, and reliable broadcasting and unicasting without prior coordination, which can be exploited in future mMTC applications. However, OLA-based protocol design and operation are subject to network models to characterize the propagation behavior and evaluate the performance. Further, it has been shown through some experimental studies that the most widely-used model in prior studies on OLA is not accurate for networks with networks with low node density. Therefore, stochastic models using quasi-stationary Markov chain are introduced, which are more complex but more exact to estimate the key performance metrics of the OLA transmissions in practice. Considering the fact that such propagation models should be selected carefully depending on system parameters such as network topology and channel environments, we provide a comprehensive survey on the analytical models and framework of the OLA propagation in the literature, which is not available in the existing survey papers on OLA protocols. In addition, we introduce energy-efficient OLA techniques, which are of paramount importance in energy-limited IoT networks. Furthermore, we discuss future research directions to combine OLA with emerging technologies.

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