Timing the SARS-CoV-2 index case in Hubei province

Random-effects substitution models for phylogenetics via scalable gradient approximations

Phylogenetic and discrete-trait evolutionary inference depend heavily on an appropriate characterization of the underlying character substitution process. In this paper, we present random-effects substitution models that extend common continuous-time Markov chain models into a richer class of processes capable of capturing a wider variety of substitution dynamics. As these random-effects substitution models often require many more parameters than their usual counterparts, inference can be both statistically and computationally challenging. Thus, we also propose an efficient approach to compute an approximation to the gradient of the data likelihood with respect to all unknown substitution model parameters. We demonstrate that this approximate gradient enables scaling of sampling-based inference, namely Bayesian inference via Hamiltonian Monte Carlo, under random-effects substitution models across large trees and state-spaces. Applied to a dataset of 583 SARS-CoV-2 sequences, an HKY model with random-effects shows strong signals of nonreversibility in the substitution process, and posterior predictive model checks clearly show that it is a more adequate model than a reversible model. When analyzing the pattern of phylogeographic spread of 1441 influenza A virus (H3N2) sequences between 14 regions, a random-effects phylogeographic substitution model infers that air travel volume adequately predicts almost all dispersal rates. A random-effects state-dependent substitution model reveals no evidence for an effect of arboreality on the swimming mode in the tree frog subfamily Hylinae. Simulations reveal that random-effects substitution models can accommodate both negligible and radical departures from the underlying base substitution model. We show that our gradient-based inference approach is over an order of magnitude more time efficient than conventional approaches.

Classification of a Massive Number of Viral Genomes and Estimation of Time of Most Recent Common Ancestor (tMRCA) of SARS-CoV-2 Using Phylodynamic Analysis

Estimating the time of most recent common ancestor (tMRCA) is important to trace the origin of pathogenic viruses. This analysis is based on the genetic diversity accumulated in a certain time period. There have been thousands of mutant sites occurring in the genomes of SARS-CoV-2 since the COVID-19 pandemic started; six highly linked mutation sites occurred early before the start of the pandemic and can be used to classify the genomes into three main haplotypes. Tracing the origin of those three haplotypes may help to understand the origin of SARS-CoV-2. In this article, we present a complete protocol for the classification of SARS-CoV-2 genomes and calculating tMRCA using Bayesian phylodynamic method. This protocol may also be used in the analysis of other viral genomes. Key features • Filtering and alignment of a massive number of viral genomes using custom scripts and ViralMSA. • Classification of genomes based on highly linked sites using custom scripts. • Phylodynamic analysis of viral genomes using Bayesian evolutionary analysis sampling trees (BEAST). • Visualization of posterior distribution of tMRCA using Tracer.v1.7.2. • Optimized for the SARS-CoV-2.

Evolutionary trajectory of diverse SARS-CoV-2 variants at the beginning of COVID-19 outbreak

Despite extensive scientific efforts directed toward the evolutionary trajectory of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in humans at the beginning of the COVID-19 epidemic, it remains unclear how the virus jumped into and evolved in humans so far. Herein, we recruited almost all adult coronavirus disease 2019 (COVID-19) cases appeared locally or imported from abroad during the first 8 months of the outbreak in Shanghai. From these patients, SARS-CoV-2 genomes occupying the important phylogenetic positions in the virus phylogeny were recovered. Phylogenetic and mutational landscape analyses of viral genomes recovered here and those collected in and outside of China revealed that all known SARS-CoV-2 variants exhibited the evolutionary continuity despite the co-circulation of multiple lineages during the early period of the epidemic. Various mutations have driven the rapid SARS-CoV-2 diversification, and some of them favor its better adaptation and circulation in humans, which may have determined the waxing and waning of various lineages.

Integrating Fréchet distance and AI reveals the evolutionary trajectory and origin of SARS-CoV-2

A genome, composed of a precisely ordered sequence of four nucleotides (ATCG), encompasses a multitude of specific genome features like AAA motif. Mutations occurring within a genome disrupt the sequential order and composition of these features, thereby influencing the evolutionary trajectories and yielding variants. The evolutionary relatedness between a variant and its ancestor can be estimated by assessing evolutionary distances across a spectrum of genome features. This study develops a novel, alignment-free algorithm that considers both the sequential order and composition of genome features, enabling computation of the Fréchet distance (Fr) across multiple genome features to quantify the evolutionary status of a variant. Integrating this algorithm with an artificial recurrent neural network (RNN) reveals the quantitative evolutionary trajectory and origin of SARS-CoV-2, a puzzle unsolved by alignment-based phylogenetics. The RNN generates the evolutionary trajectory from Fr data at two levels: genome sequence mutations and organism variants. At the genome sequence level, SARS-CoV-2 evolutionarily shortens its genome to enhance its infectious capacity. Mutating signature features, such as TTA and GCT, increases its infectious potential and drives its evolution. At the organism level, variants mutating a single biomarker possess low infectious potential. However, mutating multiple markers dramatically increases their infectious capacity, propelling the COVID-19 pandemic. SARS-CoV-2 likely originates from mink coronavirus variants, with its origin trajectory traced as follows: mink, cat, tiger, mouse, hamster, dog, lion, gorilla, leopard, bat, and pangolin. Together, mutating multiple signature features and biomarkers delineates the evolutionary trajectory of mink-origin SARS-CoV-2, leading to the COVID-19 pandemic.

Using early detection data to estimate the date of emergence of an epidemic outbreak

While the first infection of an emerging disease is often unknown, information on early cases can be used to date it. In the context of the COVID-19 pandemic, previous studies have estimated dates of emergence (e.g., first human SARS-CoV-2 infection, emergence of the Alpha SARS-CoV-2 variant) using mainly genomic data. Another dating attempt used a stochastic population dynamics approach and the date of the first reported case. Here, we extend this approach to use a larger set of early reported cases to estimate the delay from first infection to the Nth case. We first validate our framework by running our model on simulated data. We then apply our model using data on Alpha variant infections in the UK, dating the first Alpha infection at (median) August 21, 2020 (95% interpercentile range across retained simulations (IPR): July 23-September 5, 2020). Next, we apply our model to data on COVID-19 cases with symptom onset before mid-January 2020. We date the first SARS-CoV-2 infection in Wuhan at (median) November 28, 2019 (95% IPR: November 2-December 9, 2019). Our results fall within ranges previously estimated by studies relying on genomic data. Our population dynamics-based modelling framework is generic and flexible, and thus can be applied to estimate the starting time of outbreaks in contexts other than COVID-19.

Quantitatively assessing early detection strategies for mitigating COVID-19 and future pandemics

Researchers and policymakers have proposed systems to detect novel pathogens earlier than existing surveillance systems by monitoring samples from hospital patients, wastewater, and air travel, in order to mitigate future pandemics. How much benefit would such systems offer? We developed, empirically validated, and mathematically characterized a quantitative model that simulates disease spread and detection time for any given disease and detection system. We find that hospital monitoring could have detected COVID-19 in Wuhan 0.4 weeks earlier than it was actually discovered, at 2,300 cases (standard error: 76 cases) compared to 3,400 (standard error: 161 cases). Wastewater monitoring would not have accelerated COVID-19 detection in Wuhan, but provides benefit in smaller catchments and for asymptomatic or long-incubation diseases like polio or HIV/AIDS. Air travel monitoring does not accelerate outbreak detection in most scenarios we evaluated. In sum, early detection systems can substantially mitigate some future pandemics, but would not have changed the course of COVID-19.

An ncRNA transcriptomics-based approach to design siRNA molecules against SARS-CoV-2 double membrane vesicle formation and accessory genes

BACKGROUND

The corona virus SARS-CoV-2 is the causative agent of recent most global pandemic. Its genome encodes various proteins categorized as non-structural, accessory, and structural proteins. The non-structural proteins, NSP1-16, are located within the ORF1ab. The NSP3, 4, and 6 together are involved in formation of double membrane vesicle (DMV) in host Golgi apparatus. These vesicles provide anchorage to viral replicative complexes, thus assist replication inside the host cell. While the accessory genes coded by ORFs 3a, 3b, 6, 7a, 7b, 8a, 8b, 9b, 9c, and 10 contribute in cell entry, immunoevasion, and pathological progression.

METHODS

This in silico study is focused on designing sequence specific siRNA molecules as a tool for silencing the non-structural and accessory genes of the virus. The gene sequences of NSP3, 4, and 6 along with ORF3a, 6, 7a, 8, and 10 were retrieved for conservation, phylogenetic, and sequence logo analyses. siRNA candidates were predicted using siDirect 2.0 targeting these genes. The GC content, melting temperatures, and various validation scores were calculated. Secondary structures of the guide strands and siRNA-target duplexes were predicted. Finally, tertiary structures were predicted and subjected to structural validations.

RESULTS

This study revealed that NSP3, 4, and 6 and accessory genes ORF3a, 6, 7a, 8, and 10 have high levels of conservation across globally circulating SARS-CoV-2 strains. A total of 71 siRNA molecules were predicted against the selected genes. Following rigorous screening including binary validations and minimum free energies, final siRNAs with high therapeutic potential were identified, including 7, 2, and 1 against NSP3, NSP4, and NSP6, as well as 3, 1, 2, and 1 targeting ORF3a, ORF7a, ORF8, and ORF10, respectively.

CONCLUSION

Our novel in silico pipeline integrates effective methods from previous studies to predict and validate siRNA molecules, having the potential to inhibit viral replication pathway in vitro. In total, this study identified 17 highly specific siRNA molecules targeting NSP3, 4, and 6 and accessory genes ORF3a, 7a, 8, and 10 of SARS-CoV-2, which might be used as an additional antiviral treatment option especially in the cases of life-threatening urgencies.

Development of an EBOV MiniG plus system as an advanced tool for anti-Ebola virus drug screening

The incidence of zoonotic diseases, such as coronavirus disease 2019 and Ebola virus disease, is increasing worldwide. However, drug and vaccine development for zoonotic diseases has been hampered because the experiments involving live viruses are limited to high-containment laboratories. The Ebola virus minigenome system enables researchers to study the Ebola virus under BSL-2 conditions. Here, we found that the addition of the nucleocapsid protein of human coronaviruses, such as severe acute respiratory syndrome coronavirus 2, can increase the ratio of green fluorescent protein-positive cells by 1.5-2 folds in the Ebola virus minigenome system. Further analysis showed that the nucleocapsid protein acts as an activator of the Ebola virus minigenome system. Here, we developed an EBOV MiniG Plus system based on the Ebola virus minigenome system by adding the SARS-CoV-2 nucleocapsid protein. By evaluating the antiviral effect of remdesivir and rupintrivir, we demonstrated that compared to that of the traditional Ebola virus minigenome system, significant concentration-dependent activity was observed in the EBOV MiniG Plus system. Taken together, these results demonstrate the utility of adding nucleocapsid protein to the Ebola virus minigenome system to create a powerful platform for screening antiviral drugs against the Ebola virus.

Quantitatively assessing early detection strategies for mitigating COVID-19 and future pandemics

Researchers and policymakers have proposed systems to detect novel pathogens earlier than existing surveillance systems by monitoring samples from hospital patients, wastewater, and air travel, in order to mitigate future pandemics. How much benefit would such systems offer? We developed, empirically validated, and mathematically characterized a quantitative model that simulates disease spread and detection time for any given disease and detection system. We find that hospital monitoring could have detected COVID-19 in Wuhan 0.4 weeks earlier than it was actually discovered, at 2,300 cases (standard error: 76 cases) compared to 3,400 (standard error: 161 cases). Wastewater monitoring would not have accelerated COVID-19 detection in Wuhan, but provides benefit in smaller catchments and for asymptomatic or long-incubation diseases like polio or HIV/AIDS. Monitoring of air travel provides little benefit in most scenarios we evaluated. In sum, early detection systems can substantially mitigate some future pandemics, but would not have changed the course of COVID-19.

An epigenetic clock in plants

DNA methylation can identify evolutionary relationships among close plant lineages.

Genetic tracing of market wildlife and viruses at the epicenter of the COVID-19 pandemic

Zoonotic spillovers of viruses have occurred through the animal trade worldwide. The start of the COVID-19 pandemic was traced epidemiologically to the Huanan Wholesale Seafood Market, the site with the most reported wildlife vendors in the city of Wuhan, China. Here, we analyze publicly available qPCR and sequencing data from environmental samples collected in the Huanan market in early 2020. We demonstrate that the SARS-CoV-2 genetic diversity linked to this market is consistent with market emergence, and find increased SARS-CoV-2 positivity near and within a particular wildlife stall. We identify wildlife DNA in all SARS-CoV-2 positive samples from this stall. This includes species such as civets, bamboo rats, porcupines, hedgehogs, and one species, raccoon dogs, known to be capable of SARS-CoV-2 transmission. We also detect other animal viruses that infect raccoon dogs, civets, and bamboo rats. Combining metagenomic and phylogenetic approaches, we recover genotypes of market animals and compare them to those from other markets. This analysis provides the genetic basis for a short list of potential intermediate hosts of SARS-CoV-2 to prioritize for retrospective serological testing and viral sampling.

Threat Net: A Metagenomic Surveillance Network for Biothreat Detection and Early Warning

Early detection of novel pathogens can prevent or substantially mitigate biological incidents, including pandemics. Metagenomic next-generation sequencing (mNGS) of symptomatic clinical samples may enable detection early enough to contain outbreaks, limit international spread, and expedite countermeasure development. In this article, we propose a clinical mNGS architecture we call "Threat Net," which focuses on the hospital emergency department as a high-yield surveillance location. We develop a susceptible-exposed-infected-removed (SEIR) simulation model to estimate the effectiveness of Threat Net in detecting novel respiratory pathogen outbreaks. Our analysis serves to quantify the value of routine clinical mNGS for respiratory pandemic detection by estimating the cost and epidemiological effectiveness at differing degrees of hospital coverage across the United States. We estimate that a biological threat detection network such as Threat Net could be deployed across hospitals covering 30% of the population in the United States. Threat Net would cost between $400 million and $800 million annually and have a 95% chance of detecting a novel respiratory pathogen with traits of SARS-CoV-2 after 10 emergency department presentations and 79 infections across the United States. Our analyses suggest that implementing Threat Net could help prevent or substantially mitigate the spread of a respiratory pandemic pathogen in the United States.

Genome characterization based on the Spike-614 and NS8-84 loci of SARS-CoV-2 reveals two major possible onsets of the COVID-19 pandemic

The global COVID-19 pandemic has lasted for 3 years since its outbreak, however its origin is still unknown. Here, we analyzed the genotypes of 3.14 million SARS-CoV-2 genomes based on the amino acid 614 of the Spike (S) and the amino acid 84 of NS8 (nonstructural protein 8), and identified 16 linkage haplotypes. The GL haplotype (S_614G and NS8_84L) was the major haplotype driving the global pandemic and accounted for 99.2% of the sequenced genomes, while the DL haplotype (S_614D and NS8_84L) caused the pandemic in China in the spring of 2020 and accounted for approximately 60% of the genomes in China and 0.45% of the global genomes. The GS (S_614G and NS8_84S), DS (S_614D and NS8_84S), and NS (S_614N and NS8_84S) haplotypes accounted for 0.26%, 0.06%, and 0.0067% of the genomes, respectively. The main evolutionary trajectory of SARS-CoV-2 is DS→DL→GL, whereas the other haplotypes are minor byproducts in the evolution. Surprisingly, the newest haplotype GL had the oldest time of most recent common ancestor (tMRCA), which was May 1 2019 by mean, while the oldest haplotype DS had the newest tMRCA with a mean of October 17, indicating that the ancestral strains that gave birth to GL had been extinct and replaced by the more adapted newcomer at the place of its origin, just like the sequential rise and fall of the delta and omicron variants. However, the haplotype DL arrived and evolved into toxic strains and ignited a pandemic in China where the GL strains had not arrived in by the end of 2019. The GL strains had spread all over the world before they were discovered, and ignited the global pandemic, which had not been noticed until the virus was declared in China. However, the GL haplotype had little influence in China during the early phase of the pandemic due to its late arrival as well as the strict transmission controls in China. Therefore, we propose two major onsets of the COVID-19 pandemic, one was mainly driven by the haplotype DL in China, the other was driven by the haplotype GL globally.

Epidemiological inference for emerging viruses using segregating sites

Epidemiological models are commonly fit to case and pathogen sequence data to estimate parameters and to infer unobserved disease dynamics. Here, we present an inference approach based on sequence data that is well suited for model fitting early on during the expansion of a viral lineage. Our approach relies on a trajectory of segregating sites to infer epidemiological parameters within a Sequential Monte Carlo framework. Using simulated data, we first show that our approach accurately recovers key epidemiological quantities under a single-introduction scenario. We then apply our approach to SARS-CoV-2 sequence data from France, estimating a basic reproduction number of approximately 2.3-2.7 under an epidemiological model that allows for multiple introductions. Our approach presented here indicates that inference approaches that rely on simple population genetic summary statistics can be informative of epidemiological parameters and can be used for reconstructing infectious disease dynamics during the early expansion of a viral lineage.

The species coalescent indicates possible bat and pangolin origins of the COVID-19 pandemic

A consensus species tree is reconstructed from 11 gene trees for human, bat, and pangolin beta coronaviruses from samples taken early in the pandemic (prior to April 1, 2020). Using coalescent theory, the shallow (short branches relative to the hosts) consensus species tree provides evidence of recent gene flow events between bat and pangolin beta coronaviruses predating the zoonotic transfer to humans. The consensus species tree was also used to reconstruct the ancestral sequence of human SARS-CoV-2, which was 2 nucleotides different from the Wuhan sequence. The time to most recent common ancestor was estimated to be Dec 8, 2019 with a bat origin. Some human, bat, and pangolin coronavirus lineages found in China are phylogenetically distinct, a rare example of a class II phylogeography pattern (Avise et al. in Ann Rev Eco Syst 18:489-422, 1987). The consensus species tree is a product of evolutionary factors, providing evidence of repeated zoonotic transfers between bat and pangolin as a reservoir for future zoonotic transfers to humans.

Rooting and Dating Large SARS-CoV-2 Trees by Modeling Evolutionary Rate as a Function of Time

Almost all published rooting and dating studies on SARS-CoV-2 assumed that (1) evolutionary rate does not change over time although different lineages can have different evolutionary rates (uncorrelated relaxed clock), and (2) a zoonotic transmission occurred in Wuhan and the culprit was immediately captured, so that only the SARS-CoV-2 genomes obtained in 2019 and the first few months of 2020 (resulting from the first wave of the global expansion from Wuhan) are sufficient for dating the common ancestor. Empirical data contradict the first assumption. The second assumption is not warranted because mounting evidence suggests the presence of early SARS-CoV-2 lineages cocirculating with the Wuhan strains. Large trees with SARS-CoV-2 genomes beyond the first few months are needed to increase the likelihood of finding SARS-CoV-2 lineages that might have originated at the same time as (or even before) those early Wuhan strains. I extended a previously published rapid rooting method to model evolutionary rate as a linear function instead of a constant. This substantially improves the dating of the common ancestor of sampled SARS-CoV-2 genomes. Based on two large trees with 83,688 and 970,777 high-quality and full-length SARS-CoV-2 genomes that contain complete sample collection dates, the common ancestor was dated to 12 June 2019 and 7 July 2019 with the two trees, respectively. The two data sets would give dramatically different or even absurd estimates if the rate was treated as a constant. The large trees were also crucial for overcoming the high rate-heterogeneity among different viral lineages. The improved method was implemented in the software TRAD.

Logistical challenges with an emphasis on organizing specialized triage in the conditions of a newly emerging, epidemiologically significant infectious pathogen for humans – SARS-CoV2

Background: UMHATEM „N.I. Pirogov“ Sofia, is one of the largest and busiest hospitals for emergency medical care in Bulgaria. It is the legal successor of the former Institute of Emergency Medicine „N.I. Pirogov“, and it can be said that at the moment it is the only diagnostic- therapeutic, prophylactic and scientific-educational structure of this type within the Bulgarian healthcare system. The concept of adequate functioning and development of this type of hospital does not consider structuring an Infectious Diseases diagnostic-treatment unit. This reality makes necessary the formation of a radically different organization for the admission and treatment of patients in the hospital, both for those with symptoms of Covid 19 and for all other emergency patients. The organization created in this way must absolutely guarantee safety for both streams of patients.

In the conditions of a pandemic, in case of a real threat to public health, the main task of triage in the Emergency Department is to establish indications for urgent hospitalization, or to refuse it in the absence of indications. The characteristic course of the disease, the prolonged treatment, the manifestations within the so-called „post-Covid syndrome“, require serious planning not only of the diagnostic-treatment and rehabilitation period, but also adequate monitoring in the first months after the patient‘s discharge.

Within the national reorganization measures, during the determined periods, the main changes concerning the MED (Multi-profile emergency department) of Pirogov are implemented, with an emphasis on the formation of a specialized triage for the diagnosis and clinical evaluation of patients with a coronavirus infection. The main goal is the adequate diagnosis, treatment and follow-up of patients with coronavirus infection who have passed through the organized Covid-triage in a period of extreme pressure on the emergency structures and on the hospital system in the country as a whole.

Objective: For a MED, which at the time of declaring an epidemic situation does not have a concept for the diagnosis and treatment of infectious diseases, to systematize the main urgently implemented organizational and structural changes, which turned out to be absolutely necessary to meet a newly emerging epidemiologically significant infectious disease.

Aims: To systematize the organizational changes imposed by the situation and urgently implemented in the MED (multi-profile emergency department).

To systematize the structural changes imposed by the situation and urgently implemented in the work of the MED.

To analyze the organizational and structural changes carried out in this way and to differentiate the main difficulties caused by the regulations existing at the time of the announcement of the epidemic situation.

Miniaturized retractable thin-film sensor for wearable multifunctional respiratory monitoring

As extremely important physiological indicators, respiratory signals can often reflect or predict the depth and urgency of various diseases. However, designing a wearable respiratory monitoring system with convenience, excellent durability, and high precision is still an urgent challenge. Here, we designed an easy-fabricate, lightweight, and badge reel-like retractable self-powered sensor (RSPS) with high precision, sensitivity, and durability for continuous detection of important indicators such as respiratory rate, apnea, and respiratory ventilation. By using three groups of interdigital electrode structures with phase differences, combined with flexible printed circuit boards (FPCBs) processing technology, a miniature rotating thin-film triboelectric nanogenerator (RTF-TENG) was developed. Based on discrete sensing technology, the RSPS has a sensing resolution of 0.13 mm, sensitivity of 7 P·mm-1, and durability more than 1 million stretching cycles, with low hysteresis and excellent anti-environmental interference ability. Additionally, to demonstrate its wearability, real-time, and convenience of respiratory monitoring, a multifunctional wearable respiratory monitoring system (MWRMS) was designed. The MWRMS demonstrated in this study is expected to provide a new and practical strategy and technology for daily human respiratory monitoring and clinical diagnosis.

Electronic Supplementary Material

Supplementary material (additional figures and movies, including the production process of respiratory monitoring straps, the mechanical analysis of RSPS, RTF-TENG versus vector TENG sensors, the simulation studies of TE-TENG and FT-TENG, the additional characterization of RTF-TENG, the tensile and robustness tests of RSPS, the characterizations of the MWRMS during different sleeping positions, detailed circuit schematic of the MWRMS, the displacements and phase relations of RSPS, MWRMS for multifunctional respiratory monitoring) is available in the online version of this article at 10.1007/s12274-023-5420-1.

Molecular Evolution of SARS-CoV-2 during the COVID-19 Pandemic

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) produced diverse molecular variants during its recent expansion in humans that caused different transmissibility and severity of the associated disease as well as resistance to monoclonal antibodies and polyclonal sera, among other treatments. In order to understand the causes and consequences of the observed SARS-CoV-2 molecular diversity, a variety of recent studies investigated the molecular evolution of this virus during its expansion in humans. In general, this virus evolves with a moderate rate of evolution, in the order of 10-3-10-4 substitutions per site and per year, which presents continuous fluctuations over time. Despite its origin being frequently associated with recombination events between related coronaviruses, little evidence of recombination was detected, and it was mostly located in the spike coding region. Molecular adaptation is heterogeneous among SARS-CoV-2 genes. Although most of the genes evolved under purifying selection, several genes showed genetic signatures of diversifying selection, including a number of positively selected sites that affect proteins relevant for the virus replication. Here, we review current knowledge about the molecular evolution of SARS-CoV-2 in humans, including the emergence and establishment of variants of concern. We also clarify relationships between the nomenclatures of SARS-CoV-2 lineages. We conclude that the molecular evolution of this virus should be monitored over time for predicting relevant phenotypic consequences and designing future efficient treatments.

Origin, Genetic Variation and Molecular Epidemiology of SARS-CoV-2 Strains Circulating in Sardinia (Italy) during the First and Second COVID-19 Epidemic Waves

Understanding how geography and human mobility shape the patterns and spread of infectious diseases such as COVID-19 is key to control future epidemics. An interesting example is provided by the second wave of the COVID-19 epidemic in Europe, which was facilitated by the intense movement of tourists around the Mediterranean coast in summer 2020. The Italian island of Sardinia is a major tourist destination and is widely believed to be the origin of the second Italian wave. In this study, we characterize the genetic variation among SARS-CoV-2 strains circulating in northern Sardinia during the first and second Italian waves using both Illumina and Oxford Nanopore Technologies Next Generation Sequencing methods. Most viruses were placed into a single clade, implying that despite substantial virus inflow, most outbreaks did not spread widely. The second epidemic wave on the island was actually driven by local transmission of a single B.1.177 subclade. Phylogeographic analyses further suggest that those viral strains circulating on the island were not a relevant source for the second epidemic wave in Italy. This result, however, does not rule out the possibility of intense mixing and transmission of the virus among tourists as a major contributor to the second Italian wave.

RNA structure-altering mutations underlying positive selection on Spike protein reveal novel putative signatures to trace crossing host-species barriers in Betacoronavirus

Similar to other RNA viruses, the emergence of Betacoronavirus relies on cross-species viral transmission, which requires careful health surveillance monitoring of protein-coding information as well as genome-wide analysis. Although the evolutionary jump from natural reservoirs to humans may be mainly traced-back by studying the effect that hotspot mutations have on viral proteins, it is largely unexplored if other impacts might emerge on the structured RNA genome of Betacoronavirus. In this survey, the protein-coding and viral genome architecture were simultaneously studied to uncover novel insights into cross-species horizontal transmission events. We analysed 1,252,952 viral genomes of SARS-CoV, MERS-CoV, and SARS-CoV-2 distributed across the world in bats, intermediate animals, and humans to build a new landscape of changes in the RNA viral genome. Phylogenetic analyses suggest that bat viruses are the most closely related to the time of most recent common ancestor of Betacoronavirus, and missense mutations in viral proteins, mainly in the S protein S1 subunit: SARS-CoV (G > T; A577S); MERS-CoV (C > T; S746R and C > T; N762A); and SARS-CoV-2 (A > G; D614G) appear to have driven viral diversification. We also found that codon sites under positive selection on S protein overlap with non-compensatory mutations that disrupt secondary RNA structures in the RNA genome complement. These findings provide pivotal factors that might be underlying the eventual jumping the species barrier from bats to intermediate hosts. Lastly, we discovered that nearly half of the Betacoronavirus genomes carry highly conserved RNA structures, and more than 90% of these RNA structures show negative selection signals, suggesting essential functions in the biology of Betacoronavirus that have not been investigated to date. Further research is needed on negatively selected RNA structures to scan for emerging functions like the potential of coding virus-derived small RNAs and to develop new candidate antiviral therapeutic strategies.

Alpha and Omicron SARS-CoV-2 Adaptation in an Upper Respiratory Tract Model

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is currently causing an unprecedented pandemic. Although vaccines and antivirals are limiting the spread, SARS-CoV-2 is still under selective pressure in human and animal populations, as demonstrated by the emergence of variants of concern. To better understand the driving forces leading to new subtypes of SARS-CoV-2, we infected an ex vivo cell model of the human upper respiratory tract with Alpha and Omicron BA.1 variants for one month. Although viral RNA was detected during the entire course of the infection, infectious virus production decreased over time. Sequencing analysis did not show any adaptation in the spike protein, suggesting a key role for the adaptive immune response or adaptation to other anatomical sites for the evolution of SARS-CoV-2.

Treatment of patients with coronavirus disease 2019 and cross-infection in dental clinics in Korea

OBJECTIVES

The aim of the study was to investigate patients with coronavirus disease 2019 (COVID-19) who visited dental clinics for treatment and to analyse the occurrence of additional COVID-19-confirmed cases according to the type of dental treatment and use of personal protective equipment (PPE).

METHODS

Interviews were conducted in November 2021 via telephone, and written questionnaires were administered to dental hygienists working at the 24 dental clinics selected for the study, visited by patients with COVID-19. The survey focused on the visit date, the treatment received, whether or not the dental personnel wore PPE while treating the patient, and how the dental clinic and the public health centre with jurisdiction over the clinic responded after the patient's visit.

RESULTS

Additional confirmed cases occurred in two of the 24 dental clinics included. In both cases, scaling was performed, dental personnel did not use a face shield, and patients with COVID-19 were asymptomatic. In 14 of the 22 dental clinics where additional confirmed cases did not occur, the dental personnel did not use face shields, and in 10 clinics, the dental personnel wore dental masks but not a KF94 mask. Based on these findings, which were obtained before the advent of the omicron variant, COVID-19 cross-infection did not appear to be high in dental clinics.

CONCLUSION

The rate of COVID-19 cross-infection before the advent of the omicron variant appeared to be low in dental clinics in Korea. Therefore, patients have no reason to delay necessary dental treatment if dental personnel put effort into wearing PPE.

Molecular evidence for SARS-CoV-2 in samples collected from patients with morbilliform eruptions since late 2019 in Lombardy, northern Italy

As a reference laboratory for measles and rubella surveillance in Lombardy, we evaluated the association between SARS-CoV-2 infection and measles-like syndromes, providing preliminary evidence for undetected early circulation of SARS-CoV-2. Overall, 435 samples from 156 cases were investigated. RNA from oropharyngeal swabs (N = 148) and urine (N = 141) was screened with four hemi-nested PCRs and molecular evidence for SARS-CoV-2 infection was found in 13 subjects. Two of the positive patients were from the pandemic period (2/12, 16.7%, March 2020-March 2021) and 11 were from the pre-pandemic period (11/44, 25%, August 2019-February 2020). Sera (N = 146) were tested for anti-SARS-CoV-2 IgG, IgM, and IgA antibodies. Five of the RNA-positive individuals also had detectable anti-SARS-CoV-2 antibodies. No strong evidence of infection was found in samples collected between August 2018 and July 2019 from 100 patients. The earliest sample with evidence of SARS-CoV-2 RNA was from September 12, 2019, and the positive patient was also positive for anti-SARS-CoV-2 antibodies (IgG and IgM). Mutations typical of B.1 strains previously reported to have emerged in January 2020 (C3037T, C14408T, and A23403G), were identified in samples collected as early as October 2019 in Lombardy. One of these mutations (C14408T) was also identified among sequences downloaded from public databases that were obtained by others from samples collected in Brazil in November 2019. We conclude that a SARS-CoV-2 progenitor capable of producing a measles-like syndrome may have emerged in late June-late July 2019 and that viruses with mutations characterizing B.1 strain may have been spreading globally before the first Wuhan outbreak. Our findings should be complemented by high-throughput sequencing to obtain additional sequence information. We highlight the importance of retrospective surveillance studies in understanding the early dynamics of COVID-19 spread and we encourage other groups to perform retrospective investigations to seek confirmatory proofs of early SARS-CoV-2 circulation.

Non-uniform aspects of the SARS-CoV-2 intraspecies evolution reopen question of its origin

Several hypotheses have been presented on the origin of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) from its identification as the agent causing the current coronavirus disease 19 (COVID-19) pandemic. So far, no solid evidence has been found to support any hypothesis on the origin of this virus, and the issue continue to resurface over and over again. Here we have unfolded a pattern of distribution of several mutations in the SARS-CoV-2 proteins in 24 geo-locations across different continents. The results showed an evenly uneven distribution of the unique protein variants, distinct mutations, unique frequency of common conserved residues, and mutational residues across these 24 geo-locations. Furthermore, ample mutations were identified in the evolutionarily conserved invariant regions in the SARS-CoV-2 proteins across almost all geo-locations studied. This pattern of mutations potentially breaches the law of evolutionary conserved functional units of the beta-coronavirus genus. These mutations may lead to several novel SARS-CoV-2 variants with a high degree of transmissibility and virulence. A thorough investigation on the origin and characteristics of SARS-CoV-2 needs to be conducted in the interest of science and for the preparation of meeting the challenges of potential future pandemics.

Predicting health crises from early warning signs in patient medical records

The COVID-19 global pandemic has caused unprecedented worldwide changes in healthcare delivery. While containment and mitigation approaches have been intensified, the progressive increase in the number of cases has overwhelmed health systems globally, highlighting the need for anticipation and prediction to be the basis of an efficient response system. This study demonstrates the role of population health metrics as early warning signs of future health crises. We retrospectively collected data from the emergency department of a large academic hospital in the northeastern United States from 01/01/2019 to 08/07/2021. A total of 377,694 patient records and 303 features were included for analysis. Departing from a multivariate artificial intelligence (AI) model initially developed to predict the risk of high-flow oxygen therapy or mechanical ventilation requirement during the COVID-19 pandemic, a total of 19 original variables and eight engineered features showing to be most predictive of the outcome were selected for further analysis. The temporal trends of the selected variables before and during the pandemic were characterized to determine their potential roles as early warning signs of future health crises. Temporal analysis of the individual variables included in the high-flow oxygen model showed that at a population level, the respiratory rate, temperature, low oxygen saturation, number of diagnoses during the first encounter, heart rate, BMI, age, sex, and neutrophil percentage demonstrated observable and traceable changes eight weeks before the first COVID-19 public health emergency declaration. Additionally, the engineered rule-based features built from the original variables also exhibited a pre-pandemic surge that preceded the first pandemic wave in spring 2020. Our findings suggest that the changes in routine population health metrics may serve as early warnings of future crises. This justifies the development of patient health surveillance systems, that can continuously monitor population health features, and alarm of new approaching public health crises before they become devastating.

Forensic Analysis of Novel SARS2r-CoV Identified in Game Animal Datasets in China Shows Evolutionary Relationship to Pangolin GX CoV Clade and Apparent Genetic Experimentation

Pangolins are the only animals other than bats proposed to have been infected with SARS-CoV-2 related coronaviruses (SARS2r-CoVs) prior to the COVID-19 pandemic. Here, we examine the novel SARS2r-CoV we previously identified in game animal metatranscriptomic datasets sequenced by the Nanjing Agricultural University in 2022, and find that sections of the partial genome phylogenetically group with Guangxi pangolin CoVs (GX PCoVs), while the full RdRp sequence groups with bat-SL-CoVZC45. While the novel SARS2r-CoV is found in 6 pangolin datasets, it is also found in 10 additional NGS datasets from 5 separate mammalian species and is likely related to contamination by a laboratory researched virus. Absence of bat mitochondrial sequences from the datasets, the fragmentary nature of the virus sequence and the presence of a partial sequence of a cloning vector attached to a SARS2r-CoV read suggests that it has been cloned. We find that NGS datasets containing the novel SARS2r-CoV are contaminated with significant Homo sapiens genetic material, and numerous viruses not associated with the host animals sampled. We further identify the dominant human haplogroup of the contaminating H. sapiens genetic material to be F1c1a1, which is of East Asian provenance. The association of this novel SARS2r-CoV with both bat CoV and the GX PCoV clades is an important step towards identifying the origin of the GX PCoVs.

Demographic patterns of exposure and transmission for a rural Canadian community outbreak of COVID-19, 2020

Background

A coronavirus disease 2019 (COVID-19) community outbreak was declared October 5-December 3, 2020, in the Restigouche region of New Brunswick, Canada. This article describes the epidemiological characteristics of the outbreak and assesses factors associated with its transmission in rural communities, informing public health measures and programming.

Methods

A provincial line list was developed from case and contact interviews. Descriptive epidemiological methods were used to characterize the outbreak. Incidence rates among contacts, and by gender for the regional population were estimated.

Results

There were 83 laboratory-confirmed cases of COVID-19 identified during the observation period. The case ages ranged from 10-89 years of age (median age group was 40-59 years of age) and 51.2% of the cases were male. Symptom onset dates ranged from September 27-October 27, 2020, with 83% of cases being symptomatic. A cluster of early cases at a social event led to multiple workplace outbreaks, though the majority of cases were linked to household transmission. Complex and overlapping social networks resulted in multiple exposure events and that obscured transmission pathways. The incidence rate among men was higher than women, men were significantly more likely to have transmission exposure at their workplace than women, and men were the most common index cases within a household. No transmission in school settings among children was documented despite multiple exposures.

Conclusion

This investigation highlighted the gendered nature and complexity of a COVID-19 outbreak in a rural Canadian community. Targeted action at workplaces and strategic messaging towards men are likely required to increase awareness and adherence to public health measures to reduce transmission in these settings.

Covid-19: Early Cases and Disease Spread

The emergence and global spread of the Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) is critical to understanding how to prevent or control a future viral pandemic. We review the tools used for this retrospective search, their limits, and results obtained from China, France, Italy and the USA. We examine possible scenarios for the emergence of SARS-CoV-2 in the human population. We consider the Chinese city of Wuhan where the first cases of atypical pneumonia were attributed to SARS-CoV-2 and from where the disease spread worldwide. Possible superspreading events include the Wuhan-based 7^th Military World Games on October 18–27, 2019 and the Chinese New Year holidays from January 25 to February 2, 2020. Several clues point to an early regional circulation of SARS-CoV-2 in northern Italy (Lombardi) as soon as September/October 2019 and in France in November/December 2019, if not before. With the goal of preventing future pandemics, we call for additional retrospective studies designed to trace the origin of SARS-CoV-2.

The stochastic world of emerging viruses

The acquisition of new hosts is a fundamental mechanism by which parasitic organisms expand their host range and perpetuate themselves on an evolutionary scale. Among pathogens, viruses, due to their speed of evolution, are particularly efficient in producing new emergence events. However, even though these phenomena are particularly important to the human species and therefore specifically studied, the processes of virus emergence in a new host species are very complex and difficult to comprehend in their entirety. In order to provide a structured framework for understanding emergence in a species (including humans), a comprehensive qualitative model is an indispensable cornerstone. This model explicitly describes all the stages necessary for a virus circulating in the wild to come to the crossing of the epidemic threshold. We have therefore developed a complete descriptive model explaining all the steps necessary for a virus circulating in host populations to emerge in a new species. This description of the parameters presiding over the emergence of a new virus allows us to understand their nature and importance in the emergence process.

Innovation: It's in Our DNA

Colleen M. Kigin, PT, DPT, MS, MPA, FAPTA, the 52nd Mary McMillan Lecturer, is a consultant focused on innovation. She is a visiting clinical professor at the University of Colorado physical therapy program, University of Colorado School of Medicine, and an adjunct associate professor at the MGH Institute of Health Professions (MGH IHP). From 1998-2014, she held the positions of chief of staff and program manager for the Center of Integration of Medicine and Innovative Technology, a 12-institution consortium based in Boston, Massachusetts, developing innovative solutions to health care problems. She subsequently has served as a consultant to such efforts as the University of Manchester, Manchester Academic Health Science Centre, United Kingdom, to develop an innovation culture. In 1994, she joined the newly formed Partners HealthCare System in Boston, coordinating the system's cost reduction efforts through 1998. Kigin previously served as director of physical therapy services at Massachusetts General Hospital (MGH) (1977-1984) and as assistant professor at MGH IHP (1980-1994). While at MGH, she was responsible for the merger of 2 separate physical therapy departments, the establishment of the first nonphysician specialist position, and practice without referral for the physical therapy services. Kigin has held numerous positions within the American Physical Therapy Association (APTA), serving on the Board of Directors from 1988-1997, including as vice president; co-chair of The Physical Therapy Summit in 2007; and co-chair of FiRST, the Frontiers in Rehabilitation, Science and Technology Council. She also served as prior chair of the APTA Committee on Clinical Residencies and served on the American Board of Physical Therapy Specialties. Kigin earned a bachelor of science degree in physical therapy at the University of Colorado, a master of science degree at Boston University, a master's degree in public administration from the Harvard Kennedy School of Government, and a doctor in physical therapy degree from the MGH IHP.

The Huanan Seafood Wholesale Market in Wuhan was the early epicenter of the COVID-19 pandemic

Understanding how severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) emerged in 2019 is critical to preventing future zoonotic outbreaks before they become the next pandemic. The Huanan Seafood Wholesale Market in Wuhan, China, was identified as a likely source of cases in early reports, but later this conclusion became controversial. We show here that the earliest known COVID-19 cases from December 2019, including those without reported direct links, were geographically centered on this market. We report that live SARS-CoV-2-susceptible mammals were sold at the market in late 2019 and that within the market, SARS-CoV-2-positive environmental samples were spatially associated with vendors selling live mammals. Although there is insufficient evidence to define upstream events, and exact circumstances remain obscure, our analyses indicate that the emergence of SARS-CoV-2 occurred through the live wildlife trade in China and show that the Huanan market was the epicenter of the COVID-19 pandemic.

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

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

COVID-19 and preventive strategy

In December 2019, an unprecedented outbreak of the novel coronavirus disease 2019 (COVID-19), an infectious disease caused by the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) began to spread internationally, now impacting more than 293,750,692 patients with 5,454,131 deaths globally as of January 5, 2022. COVID-19 is highly pathogenic and contagious which has caused a large-scale epidemic impacting more deaths than the severe acute respiratory syndrome (SARS) epidemic in 2002-2003 or the Middle East respiratory syndrome (MERS) epidemic in 2012-2013. Although COVID-19 symptoms are mild in most people, in those with pre-existing comorbidities there is an increased risk of progression to severe disease and death. In an attempt to mitigate this pandemic, urgent public health measures including quarantining exposed individuals and social distancing have been implemented in most states, while some states have even started the process of re-opening after considering both the economic and public health consequences of social distancing measures. While prevention is crucial, both novel agents and medications already in use with other indications are being investigated in clinical trials for patients with COVID-19. The collaboration between healthcare providers, health systems, patients, private sectors, and local and national governments is needed to protect both healthcare providers and patients to ultimately overcome this pandemic. The purpose of this review is to summarize the peer-reviewed and preprint literature on the epidemiology, transmission, clinical presentation, and available therapies as well as to propose a preventive strategy to overcome the present global pandemic.

FRET-based hACE2 receptor mimic peptide conjugated nanoprobe for simple detection of SARS-CoV-2

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection has led to a pandemic of acute respiratory disease, namely coronavirus disease (COVID-19). This disease threatens human health and public safety. Early diagnosis, isolation, and prevention are important to suppress the outbreak of COVID 19 given the lack of specific antiviral drugs to treat this disease and the emergence of various variants of the virus that cause breakthrough infections even after vaccine administration. Simple and prompt testing is paramount to preventing further spread of the virus. However, current testing methods, namely RT-PCR, is time-consuming. Binding of the SARS-CoV-2 spike (S) glycoprotein to human angiotensin-converting enzyme 2 (hACE2) receptor plays a pivotal role in host cell entry. In the present study, we developed a hACE2 mimic peptide beacon (COVID19-PEB) for simple detection of SARS-CoV-2 using a fluorescence resonance energy transfer system. COVID19-PEB exhibits minimal fluorescence in its ''closed'' hairpin structure; however, in the presence of SARS-CoV-2, the specific recognition of the S protein receptor-binding domain by COVID19-PEB causes the beacon to assume an ''open'' structure that emits strong fluorescence. COVID19-PEB can detect SARS-CoV-2 within 3 h or even 50 min and exhibits strong fluorescence even at low viral concentrations, with a detection limit of 4 × 10³ plaque-forming unit/test. Furthermore, in SARS-CoV-2-infected patient samples confirmed using polymerase chain reaction, COVID19-PEB accurately detected the virus. COVID19-PEB could be developed as a rapid and accurate diagnostic tool for COVID-19.

Contrasting patterns in the early stage of SARS-CoV-2 evolution between humans and minks

One of the unique features of SARS-CoV-2 is its apparent neutral evolution during the early pandemic (before February 2020). This contrasts with the preceding SARS-CoV epidemics, where viruses evolved adaptively. SARS-CoV-2 may exhibit a unique or adaptive feature which deviates from other coronaviruses. Alternatively, the virus may have been cryptically circulating in humans for a sufficient time to have acquired adaptive changes before the onset of the current pandemic. To test the scenarios above, we analyzed the SARS-CoV-2 sequences from minks (Neovision vision) and parental humans. In the early phase of the mink epidemic (April to May 2020), nonsynonymous to synonymous mutation ratio per site in the spike protein is 2.93, indicating a selection process favoring adaptive amino acid changes. Mutations in the spike protein were concentrated within its receptor binding domain and receptor binding motif. An excess of high frequency derived variants produced by genetic hitchhiking was found during the middle (June to July 2020) and late phase I (August to September 2020) of the mink epidemic. In contrast, the site frequency spectra of early SARS-CoV-2 in humans only show an excess of low frequency mutations, consistent with the recent outbreak of the virus. Strong positive selection in the mink SARS-CoV-2 implies the virus may not be pre-adapted to a wide range of hosts and illustrates how a virus evolves to establish a continuous infection in a new host. Therefore, the lack of positive selection signal during the early pandemic in humans deserves further investigation.

Uncertainty Modeling of a Modified SEIR Epidemic Model for COVID-19

Based on SEIR (susceptible-exposed-infectious-removed) epidemic model, we propose a modified epidemic mathematical model to describe the spread of the coronavirus disease 2019 (COVID-19) epidemic in Wuhan, China. Using public data, the uncertainty parameters of the proposed model for COVID-19 in Wuhan were calibrated. The uncertainty of the control basic reproduction number was studied with the posterior probability density function of the uncertainty model parameters. The mathematical model was used to inverse deduce the earliest start date of COVID-19 infection in Wuhan with consideration of the lack of information for the initial conditions of the model. The result of the uncertainty analysis of the model is in line with the observed data for COVID-19 in Wuhan, China. The numerical results show that the modified mathematical model could model the spread of COVID-19 epidemics.

An Examination of SARS-CoV-2 Transmission Based on Classroom Distancing in Schools With Other Preventive Measures in Place—Missouri, January–March 2021

Objectives:

Classroom layout plays a central role in maintaining physical distancing as part of a multicomponent prevention strategy for safe in-person learning during the COVID-19 pandemic. We conducted a school investigation to assess layouts and physical distancing in classroom settings with and without in-school SARS-CoV-2 transmission.

Methods:

We assessed, measured, and mapped 90 K-12 (kindergarten through grade 12) classrooms in 3 Missouri public school districts during January–March 2021, prior to widespread prevalence of the Delta variant; distances between students, teachers, and people with COVID-19 and their contacts were analyzed. We used whole-genome sequencing to further evaluate potential transmission events.

Results:

The investigation evaluated the classrooms of 34 students and staff members who were potentially infectious with COVID-19 in a classroom. Of 42 close contacts (15 tested) who sat within 3 ft of possibly infectious people, 1 (2%) probable transmission event occurred (from a symptomatic student with a longer exposure period [5 days]); of 122 contacts (23 tested) who sat more than 3 ft away from possibly infectious people with shorter exposure periods, no transmission events occurred.

Conclusions:

Reduced student physical distancing is one component of mitigation strategies that can allow for increased classroom capacity and support in-person learning. In the pre–Delta variant period, limited physical distancing (<6 ft) among students in K-12 schools was not associated with increased SARS-CoV-2 transmission.

Epidemiology of COVID-19 in Individuals under 18 Years Old in Cartagena, Colombia: An Ecological Study of the First 14 Months of the Pandemic

The epidemiology of the coronavirus disease (COVID-19) has been scarcely described in individuals under 18 years old, particularly during the first months of the pandemic. The study aimed to describe the COVID-19 epidemiology in the Colombian department of Bolívar from March 2020 to April 2021 among individuals under 18 years. Furthermore, we explored whether the use of data generated by a Bolívar reference laboratory captures the departmental epidemiology. Two information sources were used; the national COVID-19 surveillance system and the Bolívar COVID-19 reference laboratory. In using a population-based ecological approach and information from confirmed symptomatic cases, epidemic curves and heat maps were constructed to assess the COVID-19 dynamics and patterns by sex, age, and residence (Cartagena vs. 45 other municipalities). The COVID-19 incidence was comparable between males and females but varied by age group, being higher in children aged 10 years and older. Cartagena had a significantly higher number of cases and experienced early epidemic peaks. Our analyses suggest that information generated by the reference laboratory does not capture the COVID-19 departmental epidemiology, despite conducting population-based surveillance across Bolívar. The study provides a retrospective characterization of the COVID-19 epidemiology in an understudied population and information that may be useful for future evidence-based responses.

The Ecology of Viral Emergence

The coronavirus disease 2019 (COVID-19) pandemic has had a profound impact on human health, economic well-being, and societal function. It is essential that we use this generational experience to better understand the processes that underpin the emergence of COVID-19 and other zoonotic diseases. Herein, I review the mechanisms that determine why and how viruses emerge in new hosts, as well as the barriers to this process. I show that traditional studies of virus emergence have an inherent anthropocentric bias, with disease in humans considered the inevitable outcome of virus emergence, when in reality viruses are integral components of a global ecosystem characterized by continual host jumping with humans also transmitting their viruses to other animals. I illustrate these points using coronaviruses, including severe acute respiratory syndrome coronavirus 2, as a case study. I also outline the potential steps that can be followed to help mitigate and prevent future pandemics, with combating climate change a central component. Expected final online publication date for the Annual Review of Virology, Volume 9 is September 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

The spike glycoprotein of SARS-CoV-2: A review of how mutations of spike glycoproteins have driven the emergence of variants with high transmissibility and immune escape

Late in 2019, SARS-CoV-2 (severe acute respiratory syndrome coronavirus-2) emerged, causing an unknown type of pneumonia today called coronaviruses disease 2019 (COVID-19). COVID-19 is still an ongoing global outbreak that has claimed and threatened many lives worldwide. Along with the fastest vaccine developed in history to fight SARS-CoV-2 came a critical problem, SARS-CoV-2. These new variants are a result of the accumulation of mutations in the sequence and structure of spike (S) glycoprotein, which is by far the most critical protein for SARS-CoV-2 to recognize cells and escape the immune system, in addition to playing a role in SARS-CoV-2 infection, pathogenicity, transmission, and evolution. In this review, we discuss mutation of S protein and how these mutations have led to new variants that are usually more transmissible and can thus mitigate the immunity produced by vaccination. Here, analysis of S protein sequences and structures from variants point out the mutations among them, how they emerge, and the behavior of S protein from each variant. This review brings details in an understandable way about how the variants of SARS-CoV-2 are a result of mutations in S protein, making them more transmissible and even more aggressive than their relatives.

Identification of the first COVID-19 infections in the US using a retrospective analysis (REMEDID)

Accurate detection of early COVID-19 cases is crucial to reduce infections and deaths, however, it remains a challenge. Here, we used the results from a seroprevalence study in 50 US states to apply our Retrospective Methodology to Estimate Daily Infections from Deaths (REMEDID) with the aim of analyzing the initial spread of SARS-CoV-2 infections across the US. Our analysis revealed that the virus likely entered the country through California on December 28, 2019, which corresponds to 16 days prior to the officially recognized entry date established by the Centers of Disease Control and Prevention. Furthermore, the REMEDID algorithm provides evidence that SARS-CoV-2 entered, on average, a month earlier than previously reflected in official data for each US state. Collectively, our mathematical modeling provides more accurate estimates of the initial COVID-19 cases in the US, and has the ability to be extrapolated to other countries and used to retrospectively track the progress of the pandemic. The use of approaches such as REMEDID are highly recommended to better understand the early stages of an outbreak, which will enable health authorities to improve mitigation and preventive measures in the future.

Optimal timing and effectiveness of COVID-19 outbreak responses in China: a modelling study

Background

In January 2020, an outbreak of atypical pneumonia caused by a novel coronavirus, SARS-CoV-2, was reported in Wuhan, China. On Jan 23, 2020, the Chinese government instituted mitigation strategies to control spread. Most modeling studies have focused on projecting epidemiological outcomes throughout the pandemic. However, the impact and optimal timing of different mitigation approaches have not been well-studied.

Methods

We developed a mathematical model reflecting SARS-CoV-2 transmission dynamics in an age-stratified population. The model simulates health and economic outcomes from Dec 1, 2019 through Mar 31, 2020 for cities including Wuhan, Chongqing, Beijing, and Shanghai in China. We considered differences in timing and duration of three mitigation strategies in the early phase of the epidemic: city-wide quarantine on Wuhan, travel history screening and isolation of travelers from Wuhan to other Chinese cities, and general social distancing.

Results

Our model estimated that implementing all three mitigation strategies one week earlier would have averted 35% of deaths in Wuhan (50% in other cities) with a 7% increase in economic impacts (16-18% in other cities). One week’s delay in mitigation strategy initiation was estimated to decrease economic cost by the same amount, but with 35% more deaths in Wuhan and more than 80% more deaths in the other cities. Of the three mitigation approaches, infections and deaths increased most rapidly if initiation of social distancing was delayed. Furthermore, social distancing of working-age adults was most critical to reducing COVID-19 outcomes versus social distancing among children and/or the elderly.

Conclusions

Optimizing the timing of epidemic mitigation strategies is paramount and involves weighing trade-offs between preventing infections and deaths and incurring immense economic impacts. City-wide quarantine was not as effective as city-wide social distancing due to its much higher daily cost than social distancing. Under typical economic evaluation standards, the optimal timing for the full set of control measures would have been much later than Jan 23, 2020 (status quo).

Supplementary Information

The online version contains supplementary material available at (10.1186/s12889-022-12659-2).

On the Origin and Propagation of the COVID-19 Outbreak in the Italian Province of Trento, a Tourist Region of Northern Italy

Background: Trentino is an Italian province with a tourism-based economy, bordering the regions of Lombardy and Veneto, where the two earliest and largest outbreaks of COVID-19 occurred in Italy. The earliest cases in Trentino were reported in the first week of March 2020, with most of the cases occurring in the winter sport areas in the Dolomites mountain range. The number of reported cases decreased over the summer months and was followed by a second wave in the autumn and winter of 2020. Methods: we performed high-coverage Oxford Nanopore sequencing of 253 positive SARS-CoV-2 swabs collected in Trentino between March and December 2020. Results: in this work, we analyzed genome sequences to trace the routes through which the virus entered the area, and assessed whether the autumnal resurgence could be attributed to lineages persisting undetected during summer, or as a consequence of new introductions. Conclusions: Comparing the draft genomes analyzed with a large selection of European sequences retrieved from GISAID we found that multiple introductions of the virus occurred at the early stage of the epidemics; the two epidemic waves were unrelated; the second wave was due to reintroductions of the virus in summer when traveling restrictions were uplifted.

Waiting for the truth: is reluctance in accepting an early origin hypothesis for SARS-CoV-2 delaying our understanding of viral emergence?

Two years after the start of the COVID-19 pandemic, key questions about the emergence of its aetiological agent (SARS-CoV-2) remain a matter of considerable debate. Identifying when SARS-CoV-2 began spreading among people is one of those questions. Although the current canonically accepted timeline hypothesises viral emergence in Wuhan, China, in November or December 2019, a growing body of diverse studies provides evidence that the virus may have been spreading worldwide weeks, or even months, prior to that time. However, the hypothesis of earlier SARS-CoV-2 circulation is often dismissed with prejudicial scepticism and experimental studies pointing to early origins are frequently and speculatively attributed to false-positive tests. In this paper, we critically review current evidence that SARS-CoV-2 had been circulating prior to December of 2019, and emphasise how, despite some scientific limitations, this hypothesis should no longer be ignored and considered sufficient to warrant further larger-scale studies to determine its veracity.