Spread of a SARS-CoV-2 variant through Europe in the summer of 2020

SARS-CoV-2 epidemiology, kinetics, and evolution: A narrative review

Since winter 2019, SARS-CoV-2 has emerged, spread, and evolved all around the globe. We explore 4 y of evolutionary epidemiology of this virus, ranging from the applied public health challenges to the more conceptual evolutionary biology perspectives. Through this review, we first present the spread and lethality of the infections it causes, starting from its emergence in Wuhan (China) from the initial epidemics all around the world, compare the virus to other betacoronaviruses, focus on its airborne transmission, compare containment strategies ("zero-COVID" vs. "herd immunity"), explain its phylogeographical tracking, underline the importance of natural selection on the epidemics, mention its within-host population dynamics. Finally, we discuss how the pandemic has transformed (or should transform) the surveillance and prevention of viral respiratory infections and identify perspectives for the research on epidemiology of COVID-19.

Large-Scale Genomic Analysis of SARS-CoV-2 Omicron BA.5 Emergence, United States

The COVID-19 pandemic has been marked by continuous emergence of novel SARS-CoV-2 variants. Questions remain about the mechanisms with which those variants establish themselves in new geographic areas. We performed a discrete phylogeographic analysis on 18,529 sequences of the SARS-CoV-2 Omicron BA.5 sublineage sampled during February-June 2022 to elucidate emergence of that sublineage in different regions of the United States. The earliest BA.5 sublineage introductions came from Africa, the putative variant origin, but most were from Europe, matching a high volume of air travelers. In addition, we discovered extensive domestic transmission between different US regions, driven by population size and cross-country transmission between key hotspots. We found most BA.5 virus transmission within the United States occurred between 3 regions in the southwestern, southeastern, and northeastern parts of the country. Our results form a framework for analyzing emergence of novel SARS-CoV-2 variants and other pathogens in the United States.

Long-Term Persistent Headache After SARS-CoV-2 Infection: A Follow-Up Population-Based Study

BACKGROUND

Headache is a symptom of the long-COVID syndrome. The incidence and characteristics of de novo post-COVID headaches remain unclear. Our aim was to characterize new-onset headaches in a population-based prospective cohort of COVID-19 patients from the first pandemic wave.

METHODS

This study followed a prospective cohort of 732 COVID-19 patients consecutively diagnosed between March and June 2020. Neurological follow-up was performed face-to-face or by phone at 3, 12, and 24 months. A structured clinical questionnaire was used to characterize headaches before infection and 24 months postinfection.

RESULTS

Overall, 448 patients completed the 24-month follow-up, with a mean age of 51.6 years at SARS-CoV-2 infection; 272 (60.7%) were women. A prior history of headaches was reported by 115 (25.7%). Patients with either pre-existing or de novo persistent headaches were younger, more often women, and exhibited hyposmia, hypogeusia, and headache during the acute phase of infection. De novo persistent headaches occurred in 54 of 333 (16.2%) headache-naïve patients. Of these, 35 (64.8%) fulfilled migraine-like headache (MLH) criteria (mean age of 49.1 years at 24-month follow-up), with a cumulative incidence of 42/1000/year.

CONCLUSIONS

De novo persistent headaches are common 2 years after COVID-19, with MLH being the most frequent type. MLH incidence after COVID-19 is elevated and de novo "migraineurs-like" tend to be older compared to the general population. This is an important finding with potential implications for healthcare and quality of life, considering the high number of COVID-19 cases and the global burden of migraine.

A Genomic Surveillance Circuit for Emerging Viral Pathogens

Genomic surveillance has been crucial in monitoring the evolution and spread of SARS-CoV-2. In Andalusia (Spain), a coordinated genomic surveillance circuit was established to systematically sequence and analyze viral genomes across the region. This initiative organizes sample collection through 27 hospitals, which act as regional hubs within their respective health districts. Sequencing is performed at three reference laboratories, with downstream data analysis and reporting centralized at a bioinformatics platform. From 2021 to 2025, over 42,500 SARS-CoV-2 genomes were sequenced, enabling the identification of major variants and their evolutionary dynamics. The circuit tracked the transition from Alpha and Delta to successive Omicron waves, including both recombinant and non-recombinant clades. The integration of genomic and epidemiological data facilitated rapid variant detection, outbreak investigation, and public health decision making. This surveillance framework at a regional granularity demonstrates the feasibility of large-scale sequencing within a decentralized healthcare system and has expanded to monitor other pathogens, reinforcing its value for epidemic preparedness. Continued investment in genomic surveillance is critical for tracking viral evolution, guiding interventions, and mitigating future public health threats.

Analysis of six consecutive waves of ICU-admitted COVID-19 patients: key findings and insights from a Portuguese population

Identifying high-risk patients, particularly in intensive care units (ICUs), enhances treatment and reduces severe outcomes. Since the pandemic, numerous studies have examined COVID-19 patient profiles and factors linked to increased mortality. Despite six pandemic waves, to the best of our knowledge, there is no extensive comparative analysis of patients' characteristics across these waves in Portugal. Thus, we aimed to analyze the demographic and clinical features of 1041 COVID-19 patients admitted to an ICU and their relationship with the different SARS-Cov-2 variants in Portugal. Additionally, we conducted an in-depth examination of factors contributing to early and late mortality by analyzing clinical data and laboratory results from the first 72 h of ICU admission. Our findings revealed a notable decline in ICU admissions due to COVID-19, with the highest mortality rates observed during the second and third waves. Furthermore, immunization could have significantly contributed to the reduction in the median age of ICU-admitted patients and the severity of their conditions. The factors contributing to early and late mortality differed. Age, wave number, D-dimers, and procalcitonin were independently associated with the risk of early death. As a measure of discriminative power for the derived multivariable model, an AUC of 0.825 (p < 0.001; 95% CI, 0.719-0.931) was obtained. For late mortality, a model incorporating age, wave number, hematologic cancer, C-reactive protein, lactate dehydrogenase, and platelet counts resulted in an AUC of 0.795 (p < 0.001; 95% CI, 0.759-0.831). These findings underscore the importance of conducting comprehensive analyses across pandemic waves to better understand the dynamics of COVID-19.

Diversity, Complexity, and Challenges of Viral Infectious Disease Data in the Big Data Era: A Comprehensive Review

Viral infectious diseases, characterized by their intricate nature and wide-ranging diversity, pose substantial challenges in the domain of data management. The vast volume of data generated by these diseases, spanning from the molecular mechanisms within cells to large-scale epidemiological patterns, has surpassed the capabilities of traditional analytical methods. In the era of artificial intelligence (AI) and big data, there is an urgent necessity for the optimization of these analytical methods to more effectively handle and utilize the information. Despite the rapid accumulation of data associated with viral infections, the lack of a comprehensive framework for integrating, selecting, and analyzing these datasets has left numerous researchers uncertain about which data to select, how to access it, and how to utilize it most effectively in their research.This review endeavors to fill these gaps by exploring the multifaceted nature of viral infectious diseases and summarizing relevant data across multiple levels, from the molecular details of pathogens to broad epidemiological trends. The scope extends from the micro-scale to the macro-scale, encompassing pathogens, hosts, and vectors. In addition to data summarization, this review thoroughly investigates various dataset sources. It also traces the historical evolution of data collection in the field of viral infectious diseases, highlighting the progress achieved over time. Simultaneously, it evaluates the current limitations that impede data utilization.Furthermore, we propose strategies to surmount these challenges, focusing on the development and application of advanced computational techniques, AI-driven models, and enhanced data integration practices. By providing a comprehensive synthesis of existing knowledge, this review is designed to guide future research and contribute to more informed approaches in the surveillance, prevention, and control of viral infectious diseases, particularly within the context of the expanding big-data landscape.

Age- and disease severity-associated changes in the nasopharyngeal microbiota of COVID-19 patients

Although many studies have associated changes in the nasopharyngeal microbiota to patient's susceptibility to COVID-19, their results are highly variable and contradictory. Addressing the limitations in previous research responsible for that variability, this study uses 16S rRNA gene sequencing to analyze the nasopharyngeal microbiota of 395 subjects, 117 controls, and 278 COVID-19 patients, of different age groups that cover the entire lifespan and across varying disease severities. This revealed that bacterial alpha diversity decreases progressively throughout life but only in severely ill COVID-19 patients, in whose nasopharynx, moreover, several opportunistic pathogen bacterial genera are overrepresented. Notably, Scardovia wiggsiae appears only in severe COVID-19 patients over 60 years of age, suggesting its potential utility as a COVID-19 severity biomarker in the elderly, who are the most susceptible individuals to suffer from serious forms of the disease. Thus, our results provide valuable insights into age-associated dynamics within nasopharyngeal microbiota during severe COVID-19.

Early suPAR levels as a predictor of COVID-19 severity: A new tool for efficient patient triage

BACKGROUND

Following several waves of the COVID-19 pandemic, we are now facing a lower but persistent rate of SARS-CoV-2 infections, with seasonal resurgences often coinciding with other respiratory tract infections.

OBJECTIVE

We aimed to identify early clinico-biological variables predictive of an unfavorable outcome in patients with primary SARS-CoV-2 infection. We also evaluated the role of suPAR, an innovative biomarker, in predicting disease severity.

METHODS

We included 255 patients with PCR-confirmed primary SARS-CoV-2 infection and with a 30-day follow-up minimum. Blood samples were collected within the first 24 h of hospitalization to measure suPAR levels. Comprehensive data from medical records were analyzed to assess their predictive value in stratifying patients into seven severity groups, with groups 1 to 3 representing severe COVID-19 (death, intubation, ECMO, or non-invasive ventilation).

RESULTS

Early plasma suPAR levels were significantly associated with severe disease progression, as evidenced by ANOVA and logistic regression models, highlighting suPAR as a persistent predictive factor for unfavorable outcomes.

CONCLUSION

Our findings suggest that a single suPAR measurement, performed early after a positive PCR test for SARS-CoV-2, holds strong predictive value for patient outcomes. This biomarker, alongside pulse oximetry and CT scan results, could be instrumental in early patient triage during seasonal COVID-19 resurgences.

Intersecting SARS-CoV-2 spike mutations and global vaccine efficacy against COVID-19

In line with encountering the world with the emergence of vaccine-resistance variants of SARS-CoV-2, 15,669,529 samples that received COVID-19 vaccines until April 2023 were investigated as two doses in the first phase and booster vaccinations in the second phase. The analysis shows that D614G and P681 mutations occurred in both phases. The E484 and Y655 mutations significantly emerged during the second phase. The 762-889 and 254-381 regions are revealed as conserved parts and could be considered in vaccine design. The Kruskal-Wallis test revealed a significant reduction in single mutations between populations with 20%-50% and those with 70%-100% vaccination coverage (p=0.017). The Mann-Whitney U test proposes a link between vaccination and suppression of viral mutation rates. Dynamic modeling suggests that key mutations have facilitated the virus' evolution and immune escape. The study's findings are crucial for understanding virus genome mutations, especially E614 and P681 in Delta and E484 and H655 in Omicron. This highlights the need to adjust strategies and strengthen global efforts in combating the pandemic.

Quasi-species prevalence and clinical impact of evolving SARS-CoV-2 lineages in European COVID-19 cohorts, January 2020 to February 2022

BackgroundEvolution of SARS-CoV-2 is continuous.AimBetween 01/2020 and 02/2022, we studied SARS-CoV-2 variant epidemiology, evolution and association with COVID-19 severity.MethodsIn nasopharyngeal swabs of COVID-19 patients (n = 1,762) from France, Italy, Spain, and the Netherlands, SARS-CoV-2 was investigated by reverse transcription-quantitative PCR and whole-genome sequencing, and the virus variant/lineage (NextStrain/Pangolin) was determined. Patients' demographic and clinical details were recorded. Associations between mild/moderate or severe COVID-19 and SARS-CoV-2 variants and patient characteristics were assessed by logistic regression. Rates and genomic locations of mutations, as well as quasi-species distribution (≥ 2 heterogeneous positions, ≥ 50× coverage) were estimated based on 1,332 high-quality sequences.ResultsOverall, 11 SARS-CoV-2 clades infected 1,762 study patients of median age 59 years (interquartile range (IQR): 45-73), with 52.5% (n = 925) being male. In total, 101 non-synonymous substitutions/insertions correlated with disease prognosis (severe, n = 27; mild-to-moderate, n = 74). Several hotspots (mutation rates ≥ 85%) occurred in Alpha, Delta, and Omicron variants of concern (VOCs) but none in pre-Alpha strains. Four hotspots were retained across all study variants, including spike:D614G. Average number of mutations per open-reading-frame (ORF) increased in the spike gene (average < 5 per genome in January 2020 to > 15 in 2022), but remained stable in ORF1ab, membrane, and nucleocapsid genes. Quasi-species were most prevalent in 20A/EU2 (48.9%), 20E/EU1 (48.6%), 20A (38.8%), and 21K/Omicron (36.1%) infections. Immunocompromised status and age (≥ 60 years), while associated with severe COVID-19 or death irrespective of variant (odds ratio (OR): 1.60-2.25; p ≤ 0.014), did not affect quasi-species' prevalence (p > 0.05).ConclusionSpecific mutations correlate with COVID-19 severity. Quasi-species potentially shaping VOCs' emergence are relevant to consider.

Secondary structure of the SARS-CoV-2 genome is predictive of nucleotide substitution frequency

Accurate estimation of the effects of mutations on SARS-CoV-2 viral fitness can inform public-health responses such as vaccine development and predicting the impact of a new variant; it can also illuminate biological mechanisms including those underlying the emergence of variants of concern. Recently, Lan et al. reported a model of SARS-CoV-2 secondary structure and its underlying dimethyl sulfate reactivity data (Lan et al., 2022). I investigated whether base reactivities and secondary structure models derived from them can explain some variability in the frequency of observing different nucleotide substitutions across millions of patient sequences in the SARS-CoV-2 phylogenetic tree. Nucleotide basepairing was compared to the estimated 'mutational fitness' of substitutions, a measurement of the difference between a substitution's observed and expected frequency that is correlated with other estimates of viral fitness (Bloom and Neher, 2023). This comparison revealed that secondary structure is often predictive of substitution frequency, with significant decreases in substitution frequencies at basepaired positions. Focusing on the mutational fitness of C→U, the most common type of substitution, I describe C→U substitutions at basepaired positions that characterize major SARS-CoV-2 variants; such mutations may have a greater impact on fitness than appreciated when considering substitution frequency alone.

Selective Control by Pistacia vera L. and Its Carotenoid Zeaxanthin on SARS-CoV-2 Virus

Since the onset of the COVID-19 (COronaVIrus Disease 19) pandemic, SARS-CoV-2 has exhibited a high transmission rate, further enhanced by new variants able to better adapt to humans. Addressing this issue has been challenging due to viral resistance and side effects associated with antiviral drugs and vaccines. As a result, there has been a growing interest in plant-derived compounds with antiviral properties. Our study revealed that pistachio extracts significantly inhibited SARS-CoV-2 viral entry. Employing pseudotyped particles bearing the S protein of SARS-CoV-2, we demonstrated that treatment with pistachio extracts inhibited binding of alpha (α) and omicron (ο) SARS-CoV-2 variants. Furthermore, our study revealed that the pistachio carotenoid zeaxanthin exhibited a different inhibitory activity against two SARS-CoV-2 variants. In silico analyses demonstrated a strong interaction between zeaxanthin and the receptor-binding domain (RBD) domain of the omicron spike (S) protein, thus reducing pseudovirus entry. However, zeaxanthin's weaker interaction with the alpha variant's RBD was insufficient to inhibit entry. Additionally, zeaxanthin suppressed the expression of the host protease TMPRSS2 at the protein level, thereby limiting the internalization of the alpha variant, which relies on TMPRSS2 for cellular entry.

Dispersal dynamics and introduction patterns of SARS-CoV-2 lineages in Iran

Understanding the dispersal patterns of Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) lineages is crucial to public health decision-making, especially in countries with limited access to viral genomic sequencing. This study provides a comprehensive epidemiological and phylodynamic perspective on SARS-CoV-2 lineage dispersal in Iran from February 2020 to July 2022. We explored the genomic epidemiology of SARS-CoV-2 combining 1281 genome sequences with spatial data in a phylogeographic framework. Our analyses shed light on multiple international imports seeding subsequent waves and on domestic dispersal dynamics. Lineage B.4 was identified to have been circulating in Iran, 29 days (95% highest probability density interval: 21-47) before non-pharmaceutical interventions were implemented. The importation dynamics throughout subsequent waves were primarily driven from the country or region where the variant was first reported and gradually shifted to other regions. At the national level, Tehran was the main source of dissemination across the country. Our study highlights the crucial role of continuous genomic surveillance and international collaboration for future pandemic preparedness and efforts to control viral transmission.

Learning the fitness dynamics of pathogens from phylogenies

The dynamics of the genetic diversity of pathogens, including the emergence of lineages with increased fitness, is a foundational concept of disease ecology with key public-health implications. However, the identification of such lineages and estimation of associated fitness remain challenging, and is rarely done outside densely sampled systems1,2. Here we present phylowave, a scalable approach that summarizes changes in population composition in phylogenetic trees, enabling the automatic detection of lineages based on shared fitness and evolutionary relationships. We use our approach on a broad set of viruses and bacteria (SARS-CoV-2, influenza A subtype H3N2, Bordetella pertussis and Mycobacterium tuberculosis), which include both well-studied and understudied threats to human health. We show that phylowave recovers the main known circulating lineages for each pathogen and that it can detect specific amino acid changes linked to fitness changes. Furthermore, phylowave identifies previously undetected lineages with increased fitness, including three co-circulating B. pertussis lineages. Inference using phylowave is robust to uneven and limited observations. This widely applicable approach provides an avenue to monitor evolution in real time to support public-health action and explore fundamental drivers of pathogen fitness.

Phylogeogenomic analysis of the earliest reported sequences of SARS-CoV-2 from 161 countries

The SARS-CoV-2 is the causative agent of COVID-19 whose evolutionary path with geographical context forms the focus of present study. The first reported sequence from each of the 161 countries was downloaded from the GISAID database. Multiple sequence alignment was performed using MAFFT v.7, and a TCS-based network was constructed using PopART v.1.7. A total of 27 proteins were analyzed including structural and non-structural proteins. NSP3 and NSP12, responsible for viral replication and RNA synthesis, respectively, had the highest mutation incidence and frequency among non-structural proteins. The spike (S) protein, critical for viral attachment and entry, had the highest prevalence and frequency of mutations. ORF3a had the highest mutation incidence and frequency among accessory proteins. The phylogeogenomic network identified six haplogroups containing 35 sequences, while the remaining sequences belonged to different haplotypes. The virus's genetic distinctiveness was higher in European genomes, with four haplogroups dominated by Europe-linked sequences. The triangular-shaped pattern observed in the virus's evolutionary path suggests that it spread to different continents from Asia. Multiple transmission pathways connecting different countries affirm the virus's ability to emerge in multiple countries by early 2020. The possibility of new species emergence through "saltation" due to the pandemic is also discussed.

CRISPR-Cas technology in forensic investigations: Principles, applications, and ethical considerations

CRISPR-Cas (Clustered Regularly Interspaced Short Palindromic Repeats and CRISPR-associated proteins) systems are adaptive immune systems originally present in bacteria, where they are essential to protect against external genetic elements, including viruses and plasmids. Taking advantage of this system, CRISPR-Cas-based technologies have emerged as incredible tools for precise genome editing, thus significantly advancing several research fields. Forensic sciences represent a multidisciplinary field that explores scientific methods to investigate and resolve legal issues, particularly criminal investigations and subject identification. Consequently, it plays a critical role in the justice system, providing scientific evidence to support judicial investigations. Although less explored, CRISPR-Cas-based methodologies demonstrate strong potential in the field of forensic sciences due to their high accuracy and sensitivity, including DNA profiling and identification, interpretation of crime scene investigations, detection of food contamination or fraud, and other aspects related to environmental forensics. However, using CRISPR-Cas-based methodologies in human samples raises several ethical issues and concerns regarding the potential misuse of individual genetic information. In this manuscript, we provide an overview of potential applications of CRISPR-Cas-based methodologies in several areas of forensic sciences and discuss the legal implications that challenge their routine implementation in this research field.

Integrating dynamical modeling and phylogeographic inference to characterize global influenza circulation

Global seasonal influenza circulation involves a complex interplay between local (seasonality, demography, host immunity) and global factors (international mobility) shaping recurrent epidemic patterns. No studies so far have reconciled the two spatial levels, evaluating the coupling between national epidemics, considering heterogeneous coverage of epidemiological, and virological data, integrating different data sources. We propose a novel-combined approach based on a dynamical model of global influenza spread (GLEAM), integrating high-resolution demographic, and mobility data, and a generalized linear model of phylogeographic diffusion that accounts for time-varying migration rates. Seasonal migration fluxes across countries simulated with GLEAM are tested as phylogeographic predictors to provide model validation and calibration based on genetic data. Seasonal fluxes obtained with a specific transmissibility peak time and recurrent travel outperformed the raw air-transportation predictor, previously considered as optimal indicator of global influenza migration. Influenza A subtypes supported autumn-winter reproductive number as high as 2.25 and an average immunity duration of 2 years. Similar dynamics were preferred by influenza B lineages, with a lower autumn-winter reproductive number. Comparing simulated epidemic profiles against FluNet data offered comparatively limited resolution power. The multiscale approach enables model selection yielding a novel computational framework for describing global influenza dynamics at different scales-local transmission and national epidemics vs. international coupling through mobility and imported cases. Our findings have important implications to improve preparedness against seasonal influenza epidemics. The approach can be generalized to other epidemic contexts, such as emerging disease outbreaks to improve the flexibility and predictive power of modeling.

Patterns and drivers of excess mortality during the COVID-19 pandemic in 13 Western European countries

BACKGROUND

Important differences in excess mortality between European countries during the COVID-19 pandemic have been reported. Understanding the drivers of these differences is essential to pandemic preparedness.

METHODS

We examined patterns in age- and sex-standardized cumulative excess mortality in 13 Western European countries during the first 30 months of the COVID-19 pandemic and the correlation of country-level characteristics of interest with excess mortality.

RESULTS

In a timeline analysis, we identified notable differences in seeding events, particularly in early 2020 and when the Alpha variant emerged, likely contributing to notable differences in excess mortality between countries (lowest in Denmark during that period). These differences were more limited from July 2021 onwards. Lower excess mortality was associated with implementing stringent non-pharmaceutical interventions (NPIs) when hospital admissions were still low in 2020 (correlation coefficient rho = 0.65, p = 0.03) and rapid rollout of vaccines in the elderly in early 2021 (rho =  - 0.76, p = 0.002). Countries which implemented NPIs while hospital admissions were low tended to experience lower gross domestic product (GDP) losses in 2020 (rho =  - 0.55, p = 0.08). Structural factors, such as high trust in the national government (rho =  - 0.77, p = 0.002) and low ratio of population at risk of poverty (rho = 0.55, p = 0.05), were also associated with lower excess mortality.

CONCLUSIONS

These results suggest the benefit of early implementation of NPIs and swift rollout of vaccines to the most vulnerable. Further analyses are required at a more granular level to better understand how these factors impacted excess mortality and help guide pandemic preparedness plans.

Integrated analyses of the transmission history of SARS-CoV-2 and its association with molecular evolution of the virus underlining the pandemic outbreaks in Italy, 2019-2023

BACKGROUND

Italy was significantly affected by the COVID-19 pandemic, experiencing multiple waves of infection following the sequential emergence of new variants. Understanding the transmission patterns and evolution of SARS-CoV-2 is vital for future preparedness.

METHODS

We conducted an analysis of viral genome sequences, integrating epidemiological and phylodynamic approaches, to characterize how SARS-CoV-2 variants have spread within the country.

RESULTS

Our findings indicate bidirectional international transmission, with Italy transitioning between importing and exporting the virus. Italy experienced four distinct epidemic waves, each associated with a significant reduction in fatalities from 2021 to 2023. These waves were primarily driven by the emergence of VOCs such as Alpha, Delta, and Omicron, which were reflected in observed transmission dynamics and effectiveness of public health measures.

CONCLUSIONS

The changing patterns of viral spread and variant prevalence throughout Italy's pandemic response underscore the continued importance of flexible public health strategies and genomic surveillance, both of which are crucial for tracking the evolution of variants and adapting control measures effectively to ensure preparedness for future outbreaks.

Attitudes of pregnant women toward vaccination against COVID-19 - a study conducted in Poland in the first quarter of 2022

OBJECTIVES

The study aimed to assess the attitudes of pregnant women toward vaccination against COVID-19.

METHODS

The research was conducted using a diagnostic survey with our original questionnaire among 283 pregnant women. The survey was carried out in Poland in the first quarter of 2022. Statistical analyses were performed using IBM SPSS 26.0 (p < 0.05).

RESULTS

It was shown that 140 (49.5%) pregnant women were vaccinated against COVID-19, of which 90 (64.3%) received vaccination during pregnancy. In the group of 143 (50%) unvaccinated people, only 11.9% of respondents expressed willingness to be vaccinated against COVID-19. The most frequently cited arguments for receiving the vaccine were fear of a severe course of the disease (37.5%) and the possibility of passing antibodies to a child (37.1%). Women who did not undergo vaccination believed that they did not want to put themselves and their babies at risk (39.9%) and were concerned about adverse post-vaccination reactions (35.2%) and the safety of the vaccine (32.5%). Women with higher education and professionally active (p = 0.004) were vaccinated more often than respondents with a lower level of education (p < 0.001). Age (p = 0.101) and place of residence (p = 0.179) did not indicate statistically significant differences in decision-making regarding vaccination against COVID-19.

CONCLUSION

Pregnant women presented both pro- and anti-vaccination attitudes. Less than half of the respondents were vaccinated against COVID-19, and most of the women took the preparation during pregnancy. Selected socio-demographic factors determined women's attitudes toward vaccinations against COVID-19. Medical personnel should play a role in deciding whether a pregnant woman is vaccinated.

Evaluation of risk-based travel policy for the COVID-19 epidemic in Scotland: a population-based surveillance study

OBJECTIVES

We aimed to assess the effects of risk-based travel restrictions on (1) international travel frequency, (2) SARS-CoV-2 case importation risk, (3) national SARS-CoV-2 incidence and (4) importation of SARS-CoV-2 variants into Scotland.

DESIGN

Population-based surveillance study.

SETTING

The study utilises SARS-CoV-2 community testing from February 2021 to May 2022 in Scotland, UK and spans the introduction of the UK's 'traffic light system' policy in May 2021.

PRIMARY OUTCOME MEASURES

Travel-related cases of COVID-19 were defined as PCR-positive Scottish residents self-reporting international travel within 14 days of booking a postarrival travel test. The Red-Amber-Green (RAG) status of the reported travel destination was determined through data linkage using country and date.

RESULTS

International flight passengers arriving into Scotland increased by 754% during the traffic light period. Amber list countries were the most frequently visited and ranked highly for both SARS-CoV-2 importations and contribution to national case incidence. Rates of international travel and associated SARS-CoV-2 case rates varied significantly across age, health board and deprivation groups. Multivariable logistic regression revealed SARS-CoV-2 case detections were less likely through travel-based than community-based surveillance systems, although increased from green-to-amber and amber-to-red lists. When examined according to travel destination, SARS-CoV-2 importation risks did not strictly follow RAG designations, and red lists did not prevent establishment of novel SARS-CoV-2 variants.

CONCLUSIONS

Our findings suggest that country-specific postarrival screening undertaken in Scotland did not prohibit the public health impact of COVID-19 in Scotland. Travel rates likely contributed to patterns of SARS-CoV-2 case importation and population incidence.

Spatiotemporal evolution and transmission dynamics of Alpha and Delta SARS-CoV-2 variants contributing to sequential outbreaks in Cambodia during 2021

BACKGROUND

Tracking the emergence, introduction and spread of SARS-CoV-2 variants of concern are essential for informing public health strategies. In 2021, Cambodia faced two major epidemic waves of SARS-CoV-2 triggered by the successive rise of the Alpha and Delta variants.

METHODS

Phylodynamic analysis of 1,163 complete SARS-CoV-2 genomes from Cambodia, along with global sequences, were conducted between February and September 2021 to infer viral introductions, molecular epidemiology and population dynamics. The relationship between epidemic trends and control strategies were evaluated. Bayesian phylogeographic reconstruction was employed to estimate and contrast the spatiotemporal dynamics of the Alpha and Delta variants over time.

RESULTS

Here we reveal that the Alpha variant displays rapid lineage diversification, accompanied by the acquisition of a spike E484K mutation that coincides with the national implementation of mass COVID-19 vaccination. Despite nationwide control strategies and increased vaccination coverage, the Alpha variant was quickly displaced by Delta variants that exhibits a higher effective reproductive number. Phylogeographic inference indicates that the Alpha variant was introduced through south-central region of Cambodia, with strong diffusion rates from the capital of Phnom Penh to other provinces, while the Delta variant likely entered the country via the northern border provinces.

CONCLUSIONS

Continual genomic surveillance and sequencing efforts, in combination with public health strategies, play a vital role in effectively tracking and responding to the emergence, evolution and dissemination of future emerging variants.

Genomic surveillance as a scalable framework for precision phage therapy against antibiotic-resistant pathogens

Phage therapy is gaining increasing interest in the fight against critically antibiotic-resistant nosocomial pathogens. However, the narrow host range of bacteriophages hampers the development of broadly effective phage therapeutics and demands precision approaches. Here, we combine large-scale phylogeographic analysis with high-throughput phage typing to guide the development of precision phage cocktails targeting carbapenem-resistant Acinetobacter baumannii, a top-priority pathogen. Our analysis reveals that a few strain types dominate infections in each world region, with their geographical distribution remaining stable within 6 years. As we demonstrate in Eastern Europe, this spatiotemporal distribution enables preemptive preparation of region-specific phage collections that target most local infections. Finally, we showcase the efficacy of phage cocktails against prevalent strain types using in vitro and animal infection models. Ultimately, genomic surveillance identifies patients benefiting from the same phages across geographical scales, thus providing a scalable framework for precision phage therapy.

Discordant phylodynamic and spatiotemporal transmission patterns driving the long-term persistence and evolution of human coronaviruses

Four distinct species of human coronaviruses (HCoVs) circulate in humans. Despite the recent attention due to SARS-CoV-2, a comprehensive understanding of the molecular epidemiology and genomic evolution of HCoVs remains unclear. Here, we employed primary differentiated human nasal epithelial cells for the successful isolation and genome sequencing of HCoVs derived from two retrospective cohorts in Singapore and Tanzania. Phylodynamic inference shows that HCoV-229E and HCoV-OC43 were subject to stronger genetic drift and reduced purifying selection from the early 2000s onwards, primarily targeting spike Domain A and B. This resulted in increased lineage diversification, coinciding with a higher effective reproductive number (Re>1.0). However, HCoV-NL63 and HCoV-HKU1 experienced weaker genetic drift and selective pressure with prolonged regional persistence. Our findings suggest that HCoV-229E and HCoV-OC43 viruses are adept at generating new variants and achieving widespread intercontinental dissemination driven by continuous genetic drift, recombination, and complex migration patterns.

Characterisation of the antibody-mediated selective pressure driving intra-host evolution of SARS-CoV-2 in prolonged infection

Neutralising antibodies against the SARS-CoV-2 spike (S) protein are major determinants of protective immunity, though insufficient antibody responses may cause the emergence of escape mutants. We studied the humoral immune response causing intra-host evolution in a B-cell depleted, haemato-oncologic patient experiencing clinically severe, prolonged SARS-CoV-2 infection with a virus of lineage B.1.177.81. Following bamlanivimab treatment at an early stage of infection, the patient developed a bamlanivimab-resistant mutation, S:S494P. After five weeks of apparent genetic stability, the emergence of additional substitutions and deletions within the N-terminal domain (NTD) and the receptor binding domain (RBD) of S was observed. Notably, the composition and frequency of escape mutations changed in a short period with an unprecedented dynamic. The triple mutant S:Delta141-4 E484K S494P became dominant until virus elimination. Routine serology revealed no evidence of an antibody response in the patient. A detailed analysis of the variant-specific immune response by pseudotyped virus neutralisation test, surrogate virus neutralisation test, and immunoglobulin-capture enzyme immunoassay showed that the onset of an IgM-dominated antibody response coincided with the appearance of escape mutations. The formation of neutralising antibodies against S:Delta141-4 E484K S494P correlated with virus elimination. One year later, the patient experienced clinically mild re-infection with Omicron BA.1.18, which was treated with sotrovimab and resulted in an increase in Omicron-reactive antibodies. In conclusion, the onset of an IgM-dominated endogenous immune response in an immunocompromised patient coincided with the appearance of additional mutations in the NTD and RBD of S in a bamlanivimab-resistant virus. Although virus elimination was ultimately achieved, this humoral immune response escaped detection by routine diagnosis and created a situation temporarily favouring the rapid emergence of various antibody escape mutants with known epidemiological relevance.

Early unrecognised SARS-CoV-2 introductions shaped the first pandemic wave, Sweden, 2020

BackgroundDespite the unprecedented measures implemented globally in early 2020 to prevent the spread of SARS-CoV-2, Sweden, as many other countries, experienced a severe first wave during the COVID-19 pandemic.AimWe investigated the introduction and spread of SARS-CoV-2 into Sweden.MethodsWe analysed stored respiratory specimens (n = 1,979), sampled 7 February-2 April 2020, by PCR for SARS-CoV-2 and sequenced PCR-positive specimens. Sequences generated from newly detected cases and stored positive specimens February-June 2020 (n = 954) were combined with sequences (Sweden: n = 730; other countries: n = 129,913) retrieved from other sources for Nextstrain clade assignment and phylogenetic analyses.ResultsTwelve previously unrecognised SARS-CoV-2 cases were identified: the earliest was sampled on 3 March, 1 week before recognised community transmission. We showed an early influx of clades 20A and 20B from Italy (201/328, 61% of cases exposed abroad) and clades 19A and 20C from Austria (61/328, 19%). Clade 20C dominated the first wave (20C: 908/1,684, 54%; 20B: 438/1,684, 26%; 20A: 263/1,684, 16%), and 800 of 1,684 (48%) Swedish sequences formed a country-specific 20C cluster defined by a spike mutation (G24368T). At the regional level, the proportion of clade 20C sequences correlated with an earlier weighted mean date of COVID-19 deaths.ConclusionCommunity transmission in Sweden started when mitigation efforts still focused on preventing influx. This created a transmission advantage for clade 20C, likely introduced from ongoing cryptic spread in Austria. Therefore, pandemic preparedness should have a comprehensive approach, including capacity for large-scale diagnostics to allow early detection of travel-related cases and community transmission.

COVID-19 in Relation to Polypharmacy and Immunization (2020-2024)

BACKGROUND

Observational studies reported worse COVID-19 evolution in relation to polypharmacy and reductions in COVID-19 hospital admissions and death in patients receiving chronic antihistamine treatment. The current profile of hospitalized patients with regard to different variants was analyzed to identify specific targets for future prospective trials.

METHODS

COVID-19 admissions to the Hospital of Terrassa (11 March 2020-28 August 2024 (n = 1457), from the integral Consorci Sanitari de Terrassa population (n = 167,386 people) were studied. Age, gender, the number of chronic treatments (nT), and immunization status were analyzed.

RESULTS

After 5 May 2023, 291 patients (54% females) required COVID hospitalization. Of these, 39% received >8 nT (23% receiving 5-7 nT), 70.2% were >70 years, and 93.4% survived. In total, 12% of patients admitted after 5 May 2024 were not vaccinated, while 59% received ≥4 vaccines (43% within the last 12 months). In total, 49% of admitted patients presented no previous infection (while 3% presented infection during the last year). Delta or Omicron variants would have accounted for ≥80% of admissions > 60 years compared to the first pandemic wave if no vaccines existed.

CONCLUSIONS

Patients > 70 years who receive ≥5 nT, without prior COVID-19 infections, should be the priority for prevention, with updated vaccination and early treatments to reduce hospitalizations.

Virology-The next fifty years

Virology has made enormous advances in the last 50 years but has never faced such scrutiny as it does today. Herein, we outline some of the major advances made in virology during this period, particularly in light of the COVID-19 pandemic, and suggest some areas that may be of research importance in the next 50 years. We focus on several linked themes: cataloging the genomic and phenotypic diversity of the virosphere; understanding disease emergence; future directions in viral disease therapies, vaccines, and interventions; host-virus interactions; the role of viruses in chronic diseases; and viruses as tools for cell biology. We highlight the challenges that virology will face moving forward-not just the scientific and technical but also the social and political. Although there are inherent limitations in trying to outline the virology of the future, we hope this article will help inspire the next generation of virologists.

The evolutionary and transmission dynamics of HIV-1 CRF08_BC

HIV-1 CRF08_BC is a significant subtype in China, though its origin and spread remain incompletely understood. Previous studies using partial genomic data have provided insights but lack comprehensive analysis. Here, we investigate the early evolutionary and spatiotemporal dynamics of HIV-1 CRF08_BC in China and Myanmar using near-complete genome sequences. We analyzed 28 near-complete HIV-1 CRF08_BC genomes from China and Myanmar (1997-2013). Phylogenetic, molecular clock, and Bayesian discrete trait analyses were performed to infer the virus's origin, spread, and associated risk groups. Based on Bayesian time-scaled inference with the best-fitting combination of models determined by marginal likelihood estimation (MLE), we inferred the time to the most recent common ancestor (TMRCA) and evolutionary rate of HIV-1 CRF08_BC to be at 3 October 1991 (95% HPD: 22 February1989-27 November 1993) and 2.30 × 10-3 substitutions per site per year (95% HPD: 1.96 × 10-3-2.63 × 10-3), respectively. Our analysis suggests that HIV-1 CRF08_BC originated in Yunnan Province, China, among injecting drug users, and subsequently spread to other regions. This study provides valuable insights into the early dynamics of HIV-1 CRF08_BC through combined genomic and epidemiological data, which may inform effective prevention and mitigation efforts. However, the limited genomic data influenced the extent of our findings, and challenges in collecting accurate risk group information during surveillance were evident.

Human gut microbiota composition associated with international travels

OBJECTIVE

The objective of this study was to evaluate whether long stays in non-European countries influence the composition, diversity, and dynamics of gut microbiota, considering the potential impact of travelling, close contact with new people, and consumption of water and food.

METHODS

Two prospective cohorts were analyzed: (i) A longitudinal cohort comprising long-term travellers who provided fecal samples before and after their travels. (ii) A cohort consisting of long-term travellers and recently arrived migrants from non-European countries, which was compared with non-traveller controls. Each participant self-collected fecal samples and provided demographic and epidemiological data. Microbiota was characterized through 16 S rRNA gene sequencing.

RESULTS

The longitudinal cohort comprised 17 subjects. A trend toward higher bacterial diversity was observed after travelling (Shannon index 3.12vs3.26). When comparing 84 travellers/migrants with 97 non-travellers, a confirmed association of higher diversity levels with travelling was observed (Phylogenetic diversity: 22.1vs20.9). Specific genera enriched in travellers' gut microbiota were identified, including Escherichia/Shigella, Bacteroides, and Parabacteroides. The analysis revealed three major clusters with profound differences in their bacterial composition, which exhibited differential distribution between travellers and non-travellers (Adonis P < 0.001; R2 = 30.6 %). Two clusters were more frequently observed in travellers: The first cluster, characterized by dominance of Escherichia/Shigella, exhibited the lowest levels of richness and diversity. The second cluster, dominated by Faecalibacterium and Bacteroides, displayed the highest richness and diversity patterns.

CONCLUSION

These findings highlight the diverse impact of international travel on gut microbiota composition and underscore the importance of considering microbiota resilience and diversity in understanding the health implications.

High-resolution epidemiological landscape from ~290,000 SARS-CoV-2 genomes from Denmark

Vast amounts of pathogen genomic, demographic and spatial data are transforming our understanding of SARS-CoV-2 emergence and spread. We examined the drivers of molecular evolution and spread of 291,791 SARS-CoV-2 genomes from Denmark in 2021. With a sequencing rate consistently exceeding 60%, and up to 80% of PCR-positive samples between March and November, the viral genome set is broadly whole-epidemic representative. We identify a consistent rise in viral diversity over time, with notable spikes upon the importation of novel variants (e.g., Delta and Omicron). By linking genomic data with rich individual-level demographic data from national registers, we find that individuals aged  < 15 and  > 75 years had a lower contribution to molecular change (i.e., branch lengths) compared to other age groups, but similar molecular evolutionary rates, suggesting a lower likelihood of introducing novel variants. Similarly, we find greater molecular change among vaccinated individuals, suggestive of immune evasion. We also observe evidence of transmission in rural areas to follow predictable diffusion processes. Conversely, urban areas are expectedly more complex due to their high mobility, emphasising the role of population structure in driving virus spread. Our analyses highlight the added value of integrating genomic data with detailed demographic and spatial information, particularly in the absence of structured infection surveys.

The impact of insularity on SARS-CoV-2 diffusion: Recapitulating three years of COVID-19 pandemic in the island of Sardinia

BACKGROUND

Italy has been the first European Country dealing with SARS-CoV-2, whose diffusion on the territory has not been homogeneous. Among Italian regions, Sardinia represented one of the lowest incidence areas, likely due to its insular nature. Despite this, the impact of insularity on SARS-CoV-2 genetic diversity has not been comprehensively described.

METHODS

In the present study, we performed the high throughput sequencing of 888 SARS-CoV-2 genomes collected in Sardinia during the first 23 months of pandemics. In addition, 1439 high-coverage SARS-CoV-2 genomes circulating in Sardinia along three years (December 2019 - January 2023) were downloaded from GISAID, for a total of 2327 viral sequences that were characterized in terms of phylogeny and genomic diversity.

RESULTS

Overall, COVID-19 pandemic in Sardinia showed substantial differences with respect to the national panorama, with additional peaks of infections and uncommon lineages that reflects the national and regional policies of re-opening and the subsequent touristic arrivals. Sardinia has been interested by the circulation of at least 87 SARS-CoV-2 lineages, including some that were poorly represented at national and European level, likely linked to multiple importation events. The relative frequency of Sardinian SARS-CoV-2 lineages has been compared to other Mediterranean Islands, revealing a unique composition.

CONCLUSIONS

The genomic diversity of SARS-CoV-2 in Sardinia has been shaped by a complex interplay of insular geography, low population density, and touristic arrivals, leading on the one side to the importation of lineages remaining rare at the national level, and resulting on the other side in the delayed entry of otherwise common variants.

Phylogenetic signatures reveal multilevel selection and fitness costs in SARS-CoV-2

Background

Large-scale sequencing of SARS-CoV-2 has enabled the study of viral evolution during the COVID-19 pandemic. Some viral mutations may be advantageous to viral replication within hosts but detrimental to transmission, thus carrying a transient fitness advantage. By affecting the number of descendants, persistence times and growth rates of associated clades, these mutations generate localised imbalance in phylogenies. Quantifying these features in closely-related clades with and without recurring mutations can elucidate the tradeoffs between within-host replication and between-host transmission.

Methods

We implemented a novel phylogenetic clustering algorithm ( mlscluster, https://github.com/mrc-ide/mlscluster) to systematically explore time-scaled phylogenies for mutations under transient/multilevel selection. We applied this method to a SARS-CoV-2 time-calibrated phylogeny with >1.2 million sequences from England, and characterised these recurrent mutations that may influence transmission fitness across PANGO-lineages and genomic regions using Poisson regressions and summary statistics.

Results

We found no major differences across two epidemic stages (before and after Omicron), PANGO-lineages, and genomic regions. However, spike, nucleocapsid, and ORF3a were proportionally more enriched for transmission fitness polymorphisms (TFP)-homoplasies than other proteins. We provide a catalog of SARS-CoV-2 sites under multilevel selection, which can guide experimental investigations within and beyond the spike protein.

Conclusions

This study provides empirical evidence for the existence of important tradeoffs between within-host replication and between-host transmission shaping the fitness landscape of SARS-CoV-2. This method may be used as a fast and scalable means to shortlist large sequence databases for sites under putative multilevel selection which may warrant subsequent confirmatory analyses and experimental confirmation.

CMAPLE: Efficient Phylogenetic Inference in the Pandemic Era

We have recently introduced MAPLE (MAximum Parsimonious Likelihood Estimation), a new pandemic-scale phylogenetic inference method exclusively designed for genomic epidemiology. In response to the need for enhancing MAPLE's performance and scalability, here we present two key components: (i) CMAPLE software, a highly optimized C++ reimplementation of MAPLE with many new features and advancements, and (ii) CMAPLE library, a suite of application programming interfaces to facilitate the integration of the CMAPLE algorithm into existing phylogenetic inference packages. Notably, we have successfully integrated CMAPLE into the widely used IQ-TREE 2 software, enabling its rapid adoption in the scientific community. These advancements serve as a vital step toward better preparedness for future pandemics, offering researchers powerful tools for large-scale pathogen genomic analysis.

Dispersal history of SARS-CoV-2 in Galicia, Spain

The dynamics of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission are influenced by a variety of factors, including social restrictions and the emergence of distinct variants. In this study, we delve into the origins and dissemination of the Alpha, Delta, and Omicron-BA.1 variants of concern in Galicia, northwest Spain. For this, we leveraged genomic data collected by the EPICOVIGAL Consortium and from the GISAID database, along with mobility information from other Spanish regions and foreign countries. Our analysis indicates that initial introductions during the Alpha phase were predominantly from other Spanish regions and France. However, as the pandemic progressed, introductions from Portugal and the United States became increasingly significant. The number of detected introductions varied from 96 and 101 for Alpha and Delta to 39 for Omicron-BA.1. Most of these introductions left a low number of descendants (<10), suggesting a limited impact on the evolution of the pandemic in Galicia. Notably, Galicia's major coastal cities emerged as critical hubs for viral transmission, highlighting their role in sustaining and spreading the virus. This research emphasizes the critical role of regional connectivity in the spread of SARS-CoV-2 and offers essential insights for enhancing public health strategies and surveillance measures.

Importations of SARS-CoV-2 lineages decline after nonpharmaceutical interventions in phylogeographic analyses

During the early stages of the SARS-CoV-2 pandemic, before vaccines were available, nonpharmaceutical interventions (NPIs) such as reducing contacts or antigenic testing were used to control viral spread. Quantifying their success is therefore key for future pandemic preparedness. Using 1.8 million SARS-CoV-2 genomes from systematic surveillance, we study viral lineage importations into Germany for the third pandemic wave from late 2020 to early 2021, using large-scale Bayesian phylogenetic and phylogeographic analysis with a longitudinal assessment of lineage importation dynamics over multiple sampling strategies. All major nationwide NPIs were followed by fewer importations, with the strongest decreases seen for free rapid tests, the strengthening of regulations on mask-wearing in public transport and stores, as well as on internal movements and gatherings. Most SARS-CoV-2 lineages first appeared in the three most populous states with most cases, and spread from there within the country. Importations rose before and peaked shortly after the Christmas holidays. The substantial effects of free rapid tests and obligatory medical/surgical mask-wearing suggests these as key for pandemic preparedness, given their relatively few negative socioeconomic effects. The approach relates environmental factors at the host population level to viral lineage dissemination, facilitating similar analyses of rapidly evolving pathogens in the future.

Geospatial patterns of excess mortality in Belgium: Insights from the first year of the COVID-19 pandemic

OBJECTIVES

Belgium experienced multiple COVID-19 waves that hit various groups in the population, which changed the mortality pattern compared to periods before the pandemic. In this study, we investigated the geographical excess mortality trend in Belgium during the first year of the COVID-19 pandemic.

METHODS

We retrieved the number of deaths and population data in 2020 based on gender, age, and municipality of residence, and we made a comparison with the mortality data in 2017-2019 using a spatially discrete model.

RESULTS

Excess mortality was significantly associated with age, gender, and COVID-19 incidence, with larger effects in the second half of 2020. Most municipalities had higher risks of mortality with a number of exceptions in the northeastern part of Belgium. Some discrepancies in excess mortality were observed between the north and south regions.

CONCLUSIONS

This study offers useful insight into excess mortality and will aid local and regional authorities in monitoring mortality trends.

Mathematical modeling of SARS-CoV-2 variant substitutions in European countries: transmission dynamics and epidemiological insights

Background

Countries across Europe have faced similar evolutions of SARS-CoV-2 variants of concern, including the Alpha, Delta, and Omicron variants.

Materials and methods

We used data from GISAID and applied a robust, automated mathematical substitution model to study the dynamics of COVID-19 variants in Europe over a period of more than 2 years, from late 2020 to early 2023. This model identifies variant substitution patterns and distinguishes between residual and dominant behavior. We used weekly sequencing data from 19 European countries to estimate the increase in transmissibility  ( Δ β )   between consecutive SARS-CoV-2 variants. In addition, we focused on large countries with separate regional outbreaks and complex scenarios of multiple competing variants.

Results

Our model accurately reproduced the observed substitution patterns between the Alpha, Delta, and Omicron major variants. We estimated the daily variant prevalence and calculated Δ β between variants, revealing that: ( i ) Δ β increased progressively from the Alpha to the Omicron variant; ( i i ) Δ β showed a high degree of variability within Omicron variants; ( i i i ) a higher Δ β was associated with a later emergence of the variant within a country; ( i v ) a higher degree of immunization of the population against previous variants was associated with a higher Δ β for the Delta variant; ( v ) larger countries exhibited smaller Δ β ,  suggesting regionally diverse outbreaks within the same country; and finally ( v i ) the model reliably captures the dynamics of competing variants, even in complex scenarios.

Conclusion

The use of mathematical models allows for precise and reliable estimation of daily cases of each variant. By quantifying Δ β ,  we have tracked the spread of the different variants across Europe, highlighting a robust increase in transmissibility trend from Alpha to Omicron. Additionally, we have shown that the geographical characteristics of a country, as well as the timing of new variant entrances, can explain some of the observed differences in variant substitution dynamics across countries.

INSaFLU-TELEVIR: an open web-based bioinformatics suite for viral metagenomic detection and routine genomic surveillance

BACKGROUND

Implementation of clinical metagenomics and pathogen genomic surveillance can be particularly challenging due to the lack of bioinformatics tools and/or expertise. In order to face this challenge, we have previously developed INSaFLU, a free web-based bioinformatics platform for virus next-generation sequencing data analysis. Here, we considerably expanded its genomic surveillance component and developed a new module (TELEVIR) for metagenomic virus identification.

RESULTS

The routine genomic surveillance component was strengthened with new workflows and functionalities, including (i) a reference-based genome assembly pipeline for Oxford Nanopore technologies (ONT) data; (ii) automated SARS-CoV-2 lineage classification; (iii) Nextclade analysis; (iv) Nextstrain phylogeographic and temporal analysis (SARS-CoV-2, human and avian influenza, monkeypox, respiratory syncytial virus (RSV A/B), as well as a "generic" build for other viruses); and (v) algn2pheno for screening mutations of interest. Both INSaFLU pipelines for reference-based consensus generation (Illumina and ONT) were benchmarked against commonly used command line bioinformatics workflows for SARS-CoV-2, and an INSaFLU snakemake version was released. In parallel, a new module (TELEVIR) for virus detection was developed, after extensive benchmarking of state-of-the-art metagenomics software and following up-to-date recommendations and practices in the field. TELEVIR allows running complex workflows, covering several combinations of steps (e.g., with/without viral enrichment or host depletion), classification software (e.g., Kaiju, Kraken2, Centrifuge, FastViromeExplorer), and databases (RefSeq viral genome, Virosaurus, etc.), while culminating in user- and diagnosis-oriented reports. Finally, to potentiate real-time virus detection during ONT runs, we developed findONTime, a tool aimed at reducing costs and the time between sample reception and diagnosis.

CONCLUSIONS

The accessibility, versatility, and functionality of INSaFLU-TELEVIR are expected to supply public and animal health laboratories and researchers with a user-oriented and pan-viral bioinformatics framework that promotes a strengthened and timely viral metagenomic detection and routine genomics surveillance. INSaFLU-TELEVIR is compatible with Illumina, Ion Torrent, and ONT data and is freely available at https://insaflu.insa.pt/ (online tool) and https://github.com/INSaFLU (code).

SARS-CoV-2 remodels the landscape of small non-coding RNAs with infection time and symptom severity

The COVID-19 pandemic caused by the coronavirus SARS-CoV-2 has significantly impacted global health, stressing the necessity of basic understanding of the host response to this viral infection. In this study, we investigated how SARS-CoV-2 remodels the landscape of small non-coding RNAs (sncRNA) from a large collection of nasopharyngeal swab samples taken at various time points from patients with distinct symptom severity. High-throughput RNA sequencing analysis revealed a global alteration of the sncRNA landscape, with abundance peaks related to species of 21-23 and 32-33 nucleotides. Host-derived sncRNAs, including microRNAs (miRNAs), transfer RNA-derived small RNAs (tsRNAs), and small nucleolar RNA-derived small RNAs (sdRNAs) exhibited significant differential expression in infected patients compared to controls. Importantly, miRNA expression was predominantly down-regulated in response to SARS-CoV-2 infection, especially in patients with severe symptoms. Furthermore, we identified specific tsRNAs derived from Glu- and Gly-tRNAs as major altered elements upon infection, with 5' tRNA halves being the most abundant species and suggesting their potential as biomarkers for viral presence and disease severity prediction. Additionally, down-regulation of C/D-box sdRNAs and altered expression of tinyRNAs (tyRNAs) were observed in infected patients. These findings provide valuable insights into the host sncRNA response to SARS-CoV-2 infection and may contribute to the development of further diagnostic and therapeutic strategies in the clinic.

Functional dissection of the spike glycoprotein S1 subunit and identification of cellular cofactors for regulation of swine acute diarrhea syndrome coronavirus entry

Swine acute diarrhea syndrome coronavirus (SADS-CoV) is a novel porcine enteric coronavirus, and the broad interspecies infection of SADS-CoV poses a potential threat to human health. This study provides experimental evidence to dissect the roles of distinct domains within the SADS-CoV spike S1 subunit in cellular entry. Specifically, we expressed the S1 and its subdomains, S1A and S1B. Cell binding and invasion inhibition assays revealed a preference for the S1B subdomain in binding to the receptors on the cell surface, and this unknown receptor is not utilized by the porcine epidemic diarrhea virus. Nanoparticle display demonstrated hemagglutination of erythrocytes from pigs, humans, and mice, linking the S1A subdomain to the binding of sialic acid (Sia) involved in virus attachment. We successfully rescued GFP-labeled SADS-CoV (rSADS-GFP) from a recombinant cDNA clone to track viral infection. Antisera raised against S1, S1A, or S1B contained highly potent neutralizing antibodies, with anti-S1B showing better efficiency in neutralizing rSADS-GFP infection compared to anti-S1A. Furthermore, depletion of heparan sulfate (HS) by heparinase treatment or pre-incubation of rSADS-GFP with HS or constituent monosaccharides could inhibit SADS-CoV entry. Finally, we demonstrated that active furin cleavage of S glycoprotein and the presence of type II transmembrane serine protease (TMPRSS2) are essential for SADS-CoV infection. These combined observations suggest that the wide cell tropism of SADS-CoV may be related to the distribution of Sia or HS on the cell surface, whereas the S1B contains the main protein receptor binding site. Specific host proteases also play important roles in facilitating SADS-CoV entry.IMPORTANCESwine acute diarrhea syndrome coronavirus (SADS-CoV) is a novel pathogen infecting piglet, and its unique genetic evolution characteristics and broad species tropism suggest the potential for cross-species transmission. The virus enters cells through its spike (S) glycoprotein. In this study, we identify the receptor binding domain on the C-terminal part of the S1 subunit (S1B) of SADS-CoV, whereas the sugar-binding domain located at the S1 N-terminal part of S1 (S1A). Sialic acid, heparan sulfate, and specific host proteases play essential roles in viral attachment and entry. The dissection of SADS-CoV S1 subunit's functional domains and identification of cellular entry cofactors will help to explore the receptors used by SADS-CoV, which may contribute to exploring the mechanisms behind cross-species transmission and host tropism.

Prediction of cross-border spread of the COVID-19 pandemic: A predictive model for imported cases outside China

The COVID-19 pandemic has been present globally for more than three years, and cross-border transmission has played an important role in its spread. Currently, most predictions of COVID-19 spread are limited to a country (or a region), and models for cross-border transmission risk assessment remain lacking. Information on imported COVID-19 cases reported from March 2020 to June 2022 was collected from the National Health Commission of China, and COVID-19 epidemic data of the countries of origin of the imported cases were collected on data websites such as WHO and Our World in Data. It is proposed to establish a prediction model suitable for the prevention and control of overseas importation of COVID-19. Firstly, the SIR model was used to fit the epidemic infection status of the countries where the cases were exported, and most of the r2 values of the fitted curves obtained were above 0.75, which indicated that the SIR model could well fit different countries and the infection status of the region. After fitting the epidemic infection status data of overseas exporting countries, on this basis, a SIR-multiple linear regression overseas import risk prediction combination model was established, which can predict the risk of overseas case importation, and the established overseas import risk model overall P <0.05, the adjusted R2 = 0.7, indicating that the SIR-multivariate linear regression overseas import risk prediction combination model can obtain better prediction results. Our model effectively estimates the risk of imported cases of COVID-19 from abroad.

Accurate Detection of Convergent Mutations in Large Protein Alignments With ConDor

Evolutionary convergences are observed at all levels, from phenotype to DNA and protein sequences, and changes at these different levels tend to be correlated. Notably, convergent mutations can lead to convergent changes in phenotype, such as changes in metabolism, drug resistance, and other adaptations to changing environments. We propose a two-component approach to detect mutations subject to convergent evolution in protein alignments. The "Emergence" component selects mutations that emerge more often than expected, while the "Correlation" component selects mutations that correlate with the convergent phenotype under study. With regard to Emergence, a phylogeny deduced from the alignment is provided by the user and is used to simulate the evolution of each alignment position. These simulations allow us to estimate the expected number of mutations in a neutral model, which is compared to the observed number of mutations in the data studied. In Correlation, a comparative phylogenetic approach, is used to measure whether the presence of each of the observed mutations is correlated with the convergent phenotype. Each component can be used on its own, for example Emergence when no phenotype is available. Our method is implemented in a standalone workflow and a webserver, called ConDor. We evaluate the properties of ConDor using simulated data, and we apply it to three real datasets: sedge PEPC proteins, HIV reverse transcriptase, and fish rhodopsin. The results show that the two components of ConDor complement each other, with an overall accuracy that compares favorably to other available tools, especially on large datasets.

Lineage frequency time series reveal elevated levels of genetic drift in SARS-CoV-2 transmission in England

Genetic drift in infectious disease transmission results from randomness of transmission and host recovery or death. The strength of genetic drift for SARS-CoV-2 transmission is expected to be high due to high levels of superspreading, and this is expected to substantially impact disease epidemiology and evolution. However, we don't yet have an understanding of how genetic drift changes over time or across locations. Furthermore, noise that results from data collection can potentially confound estimates of genetic drift. To address this challenge, we develop and validate a method to jointly infer genetic drift and measurement noise from time-series lineage frequency data. Our method is highly scalable to increasingly large genomic datasets, which overcomes a limitation in commonly used phylogenetic methods. We apply this method to over 490,000 SARS-CoV-2 genomic sequences from England collected between March 2020 and December 2021 by the COVID-19 Genomics UK (COG-UK) consortium and separately infer the strength of genetic drift for pre-B.1.177, B.1.177, Alpha, and Delta. We find that even after correcting for measurement noise, the strength of genetic drift is consistently, throughout time, higher than that expected from the observed number of COVID-19 positive individuals in England by 1 to 3 orders of magnitude, which cannot be explained by literature values of superspreading. Our estimates of genetic drift suggest low and time-varying establishment probabilities for new mutations, inform the parametrization of SARS-CoV-2 evolutionary models, and motivate future studies of the potential mechanisms for increased stochasticity in this system.

Assessing the Clinical Impact of the SARS-CoV-2 Gamma Variant on Intensive Care Unit Admissions: Insights from a Reference Hospital in Northeastern Brazil

The global challenge posed by the prolonged COVID-19 pandemic underscores the critical need for ongoing genomic surveillance to identify emerging variants and formulate effective public health strategies. This retrospective observational study, conducted in a reference hospital in Northeast Brazil and comprising 2116 cases, employed PCR genotyping together with epidemiological data to elucidate the impact of the Gamma variant during its emergence, revealing distinct patterns in hospitalization rates, severity of illness, and outcomes. The study emphasizes the challenges posed by the variant, particularly an increased tendency for ICU admissions and respiratory support, especially among adults aged 18 to 59 without comorbidities. Laboratory analyses further demonstrate elevated inflammatory, coagulation, and hepatic markers in the Gamma variant cohort, suggesting a more severe systemic response. Despite limitations, including a retrospective approach and single-institution data, the study underscores the importance of ongoing genomic surveillance. Overall, this research contributes valuable insights into the impact of the Gamma variant on COVID-19 dynamics, advocating for continued research and surveillance to inform effective public health strategies regarding evolving viral variants.

Drivers and impact of the early silent invasion of SARS-CoV-2 Alpha

SARS-CoV-2 variants of concern (VOCs) circulated cryptically before being identified as a threat, delaying interventions. Here we studied the drivers of such silent spread and its epidemic impact to inform future response planning. We focused on Alpha spread out of the UK. We integrated spatio-temporal records of international mobility, local epidemic growth and genomic surveillance into a Bayesian framework to reconstruct the first three months after Alpha emergence. We found that silent circulation lasted from days to months and decreased with the logarithm of sequencing coverage. Social restrictions in some countries likely delayed the establishment of local transmission, mitigating the negative consequences of late detection. Revisiting the initial spread of Alpha supports local mitigation at the destination in case of emerging events.

Scalable neighbour search and alignment with uvaia

Despite millions of SARS-CoV-2 genomes being sequenced and shared globally, manipulating such data sets is still challenging, especially selecting sequences for focused phylogenetic analysis. We present a novel method, uvaia, which is based on partial and exact sequence similarity for quickly extracting database sequences similar to query sequences of interest. Many SARS-CoV-2 phylogenetic analyses rely on very low numbers of ambiguous sites as a measure of quality since ambiguous sites do not contribute to single nucleotide polymorphism (SNP) differences. Uvaia overcomes this limitation by using measures of sequence similarity which consider partially ambiguous sites, allowing for more ambiguous sequences to be included in the analysis if needed. Such fine-grained definition of similarity allows not only for better phylogenetic analyses, but could also lead to improved classification and biogeographical inferences. Uvaia works natively with compressed files, can use multiple cores and efficiently utilises memory, being able to analyse large data sets on a standard desktop.

Dynamic Evolution of SARS-CoV-2 in West Sumatra: Analyzing S Gene Mutations Across Variants and Their Impact on Public Health and Vaccine Strategies

<b>Background and Objective:</b> The global SARS-CoV-2 pandemic highlights the importance of tracking virus evolution through genomic surveillance, especially concerning mutations in the SARS-CoV-2 spike protein, crucial for vaccine development. Despite global concern over variants, regions like West Sumatra, Indonesia, lack thorough genomic analysis, prompting this study to analyze S gene mutations across three pandemic waves in West Sumatra. <b>Materials and Methods:</b> Next-generation sequencing was conducted through the Illumina MiSeq instrument to leverage a dataset of 352 anonymized samples collected between March, 2020 and November, 2022 and rigorous analysis of S gene mutation using CLC Genomics Workbench^® 21 version 21.0.3 were employed. Statistical analyses assessed mutation prevalence over time, exploring associations with clinical outcomes. <b>Results:</b> The findings revealed significant variability in mutation profiles across different variants. Notably, the Omicron variant (21K) exhibited a high mutation rate, suggesting enhanced immune evasion capabilities. Comparative analysis highlighted evolutionary trends, from early variants with fewer mutations to highly adapted forms like Delta (21I) and Omicron. The dynamic nature of SARS-CoV-2 evolution underscores the importance of continuous surveillance, rapid public health response and vaccine adaptation. <b>Conclusion:</b> This study contributes valuable insights into the virus's evolving landscape, emphasizing the need for ongoing research, global collaboration and adaptable vaccine strategies to manage the evolving threat of COVID-19 effectively.

Dispersion patterns of SARS-CoV-2 variants Gamma, Lambda and Mu in Latin America and the Caribbean

Latin America and Caribbean (LAC) regions were an important epicenter of the COVID-19 pandemic and SARS-CoV-2 evolution. Through the COVID-19 Genomic Surveillance Regional Network (COVIGEN), LAC countries produced an important number of genomic sequencing data that made possible an enhanced SARS-CoV-2 genomic surveillance capacity in the Americas, paving the way for characterization of emerging variants and helping to guide the public health response. In this study we analyzed approximately 300,000 SARS-CoV-2 sequences generated between February 2020 and March 2022 by multiple genomic surveillance efforts in LAC and reconstructed the diffusion patterns of the main variants of concern (VOCs) and of interest (VOIs) possibly originated in the Region. Our phylogenetic analysis revealed that the spread of variants Gamma, Lambda and Mu reflects human mobility patterns due to variations of international air passenger transportation and gradual lifting of social distance measures previously implemented in countries. Our results highlight the potential of genetic data to reconstruct viral spread and unveil preferential routes of viral migrations that are shaped by human mobility patterns.