scholarly journals The Novel Coronavirus Enigma: Phylogeny and Analyses of Coevolving Mutations Among the SARS-CoV-2 Viruses Circulating in India (Preprint)

2020 ◽  
Author(s):  
Anindita Banerjee ◽  
Rakesh Sarkar ◽  
Suvrotoa Mitra ◽  
Mahadeb Lo ◽  
Shanta Dutta ◽  
...  
Keyword(s):  
Evolutionary Dynamics ◽  
Transmission Rate ◽  
Nonstructural Protein ◽  
Phylogenetic Analyses ◽  
Evolutionary Genetics ◽  
Nucleotide Sequences ◽  
Major Group ◽  
The Novel ◽  
Indian States ◽  
Novel Coronavirus

BACKGROUND The RNA genome of the emerging novel coronavirus is rapidly mutating, and its human-to-human transmission rate is increasing. Hence, temporal dissection of their evolutionary dynamics, the nature of variations among different strains, and understanding the single nucleotide polymorphisms in the endemic settings are crucial. Delineating the heterogeneous genomic constellations of this novel virus will help us understand its complex behavior in a particular geographical region. OBJECTIVE This is a comprehensive analysis of 95 Indian SARS-CoV-2 genome sequences available from the Global Initiative on Sharing All Influenza Data (GISAID) repository during the first 6 months of 2020 (January through June). Evolutionary dynamics, gene-specific phylogeny, and the emergence of the novel coevolving mutations in 9 structural and nonstructural genes among circulating SARS-CoV-2 strains across 12 different Indian states were analyzed. METHODS A total of 95 SARS-CoV-2 nucleotide sequences submitted from India were downloaded from the GISAID database. Molecular Evolutionary Genetics Analysis, version X software was used to construct the 9 phylogenetic dendrograms based on nucleotide sequences of the SARS-CoV-2 genes. Analyses of the coevolving mutations were done in comparison to the prototype SARS-CoV-2 from Wuhan, China. The secondary structure of the RNA-dependent RNA polymerase/nonstructural protein NSP12 was predicted with respect to the novel A97V mutation. RESULTS Phylogenetic analyses revealed the evolution of “genome-type clusters” and adaptive selection of “L”-type SARS-CoV-2 strains with genetic closeness to the bat severe acute respiratory syndrome–like coronaviruses. These strains were distant to pangolin or Middle East respiratory syndrome–related coronavirus strains. With regard to the novel coevolving mutations, 2 groups have been seen circulating in India at present, the “major group” (66/95, 69.4%) and the “minor group” (21/95, 22.1%) , harboring 4 and 5 coexisting mutations, respectively. The “major group” mutations fall in the A2a clade. All the minor group mutations, except 11083G>T (L37F, NSP6 gene), were unique to the Indian isolates. CONCLUSIONS This study highlights the rapidly evolving SARS-CoV-2 virus and the cocirculation of multiple clades and subclades. This comprehensive study is a potential resource for monitoring the novel mutations in the viral genome, interpreting changes in viral pathogenesis, and designing vaccines or other therapeutics.

scholarly journals The Novel Coronavirus Enigma: Phylogeny and Analyses of Coevolving Mutations Among the SARS-CoV-2 Viruses Circulating in India

10.2196/20735 ◽  
2020 ◽  
Vol 1 (1) ◽  
pp. e20735 ◽  
Author(s):  
Anindita Banerjee ◽  
Rakesh Sarkar ◽  
Suvrotoa Mitra ◽  
Mahadeb Lo ◽  
Shanta Dutta ◽  
...  
Keyword(s):  
Evolutionary Dynamics ◽  
Transmission Rate ◽  
Nonstructural Protein ◽  
Phylogenetic Analyses ◽  
Evolutionary Genetics ◽  
Nucleotide Sequences ◽  
Major Group ◽  
The Novel ◽  
Indian States ◽  
Novel Coronavirus

Background The RNA genome of the emerging novel coronavirus is rapidly mutating, and its human-to-human transmission rate is increasing. Hence, temporal dissection of their evolutionary dynamics, the nature of variations among different strains, and understanding the single nucleotide polymorphisms in the endemic settings are crucial. Delineating the heterogeneous genomic constellations of this novel virus will help us understand its complex behavior in a particular geographical region. Objective This is a comprehensive analysis of 95 Indian SARS-CoV-2 genome sequences available from the Global Initiative on Sharing All Influenza Data (GISAID) repository during the first 6 months of 2020 (January through June). Evolutionary dynamics, gene-specific phylogeny, and the emergence of the novel coevolving mutations in 9 structural and nonstructural genes among circulating SARS-CoV-2 strains across 12 different Indian states were analyzed. Methods A total of 95 SARS-CoV-2 nucleotide sequences submitted from India were downloaded from the GISAID database. Molecular Evolutionary Genetics Analysis, version X software was used to construct the 9 phylogenetic dendrograms based on nucleotide sequences of the SARS-CoV-2 genes. Analyses of the coevolving mutations were done in comparison to the prototype SARS-CoV-2 from Wuhan, China. The secondary structure of the RNA-dependent RNA polymerase/nonstructural protein NSP12 was predicted with respect to the novel A97V mutation. Results Phylogenetic analyses revealed the evolution of “genome-type clusters” and adaptive selection of “L”-type SARS-CoV-2 strains with genetic closeness to the bat severe acute respiratory syndrome–like coronaviruses. These strains were distant to pangolin or Middle East respiratory syndrome–related coronavirus strains. With regard to the novel coevolving mutations, 2 groups have been seen circulating in India at present, the “major group” (66/95, 69.4%) and the “minor group” (21/95, 22.1%) , harboring 4 and 5 coexisting mutations, respectively. The “major group” mutations fall in the A2a clade. All the minor group mutations, except 11083G>T (L37F, NSP6 gene), were unique to the Indian isolates. Conclusions This study highlights the rapidly evolving SARS-CoV-2 virus and the cocirculation of multiple clades and subclades. This comprehensive study is a potential resource for monitoring the novel mutations in the viral genome, interpreting changes in viral pathogenesis, and designing vaccines or other therapeutics.

scholarly journals The novel Coronavirus enigma: Phylogeny and mutation analyses of SARS-CoV-2 viruses circulating in India during early 2020

2020 ◽  
Author(s):  
Anindita Banerjee ◽  
Rakesh Sarkar ◽  
Suvrotoa Mitra ◽  
Mahadeb Lo ◽  
Shanta Dutta ◽  
...  
Keyword(s):  
Evolutionary Dynamics ◽  
Phylogenetic Analyses ◽  
Major Group ◽  
Phylogenetic Study ◽  
The Novel ◽  
Structural Genes ◽  
Adaptive Selection ◽  
Potential Resource ◽  
Novel Coronavirus ◽  
Genetic Closeness

AbstractBackgroundThis is a comprehensive analysis of 46 Indian SARS-CoV-2 genome sequences available from the NCBI and GISAID repository during early 2020. Evolutionary dynamics, gene-specific phylogeny and emergence of the novel co-evolving mutations in nine structural and non-structural genes among circulating SARS-CoV-2 strains in ten states of India have been assessed.Materials and methods46 SARS-CoV-2 nucleotide sequences submitted from India were downloaded from the GISAID (39/46) or from NCBI (7/46) database. Phylogenetic study and analyses of mutation were based on the nine structural and non-structural genes of SARS-CoV-2 strains. Secondary structure of RdRP/NSP12 protein was predicted with respect to the novel A97V mutation.ResultsPhylogenetic analyses revealed the evolution of “genome-type clusters” and adaptive selection of “L” type SARS-CoV-2 strains with genetic closeness to the bat SARS-like coronaviruses than pangolin or MERS-CoVs. With regards to the novel co-evolving mutations, 2 groups are seen to circulate in India at present: the “major group” (52.2%) and the “minor group” (30.4%), harboring four and five co-existing mutations, respectively. The “major group” mutations fall in the A2a clade. All the minor group mutations, except 11083G>T (L37F, NSP6) were unique to the Indian isolates.ConclusionThe study highlights rapidly evolving SARS-CoV-2 virus and co-circulation of multiple clades and sub-clades, driving this pandemic worldwide. This comprehensive study is a potential resource for monitoring the novel mutations in the viral genome, changes in viral pathogenesis, for designing vaccines and other therapeutics.

scholarly journals Modeling the Novel Coronavirus (SARS-CoV-2) Outbreak in Sicily, Italy

2020 ◽  
Vol 17 (14) ◽  
pp. 4964 ◽  
Author(s):  
Andrea Maugeri ◽  
Martina Barchitta ◽  
Sebastiano Battiato ◽  
Antonella Agodi
Keyword(s):  
Transmission Rate ◽  
Control Measures ◽  
Transmission Dynamics ◽  
The Novel ◽  
Epidemic Spread ◽  
Transmission Rates ◽  
Contact Precautions ◽  
Travel Restrictions ◽  
Novel Coronavirus ◽  
Reported Data

Italy was the first country in Europe which imposed control measures of travel restrictions, quarantine and contact precautions to tackle the epidemic spread of the novel coronavirus (SARS-CoV-2) in all its regions. While such efforts are still ongoing, uncertainties regarding SARS-CoV-2 transmissibility and ascertainment of cases make it difficult to evaluate the effectiveness of restrictions. Here, we employed a Susceptible-Exposed-Infectious-Recovered-Dead (SEIRD) model to assess SARS-CoV-2 transmission dynamics, working on the number of reported patients in intensive care unit (ICU) and deaths in Sicily (Italy), from 24 February to 13 April. Overall, we obtained a good fit between estimated and reported data, with a fraction of unreported SARS-CoV-2 cases (18.4%; 95%CI = 0–34.0%) before 10 March lockdown. Interestingly, we estimated that transmission rate in the community was reduced by 32% (95%CI = 23–42%) after the first set of restrictions, and by 80% (95%CI = 70–89%) after those adopted on 23 March. Thus, our estimates delineated the characteristics of SARS-CoV2 epidemic before restrictions taking into account unreported data. Moreover, our findings suggested that transmission rates were reduced after the adoption of control measures. However, we cannot evaluate whether part of this reduction might be attributable to other unmeasured factors, and hence further research and more accurate data are needed to understand the extent to which restrictions contributed to the epidemic control.

scholarly journals Analysis of the COVID-19 epidemic in french overseas department Mayotte based on a modified deterministic and stochastic SEIR model

2020 ◽  
Author(s):  
Solym Mawaki Manou-Abi ◽  
Julien Balicchi
Keyword(s):  
Transmission Rate ◽  
Control Measure ◽  
Exponential Growth Phase ◽  
The Novel ◽  
Rate Parameter ◽  
Seir Model ◽  
Stochastic Epidemic ◽  
Access To Water ◽  
Novel Coronavirus ◽  
Death Cases

AbstractIn order to anticipate a future trends in the development of the novel coronavirus COVID-19 epidemic started early at march 13, in the french overseas department Mayotte, we consider in this paper a modified deterministic and stochastic epidemic model. The model divides the total population into several possible states or compartment: susceptible (S), exposed (E) infected and being under an incubation period, infected (I) being infectious, simple or mild removed RM, severe removed (including hospitalized) RS and death cases (D). The adding of the two new compartment RM and RS are driven by data which together replace the original R compartment in the classical SEIR model.We first fit the constant transmission rate parameter to the epidemic data in Mayotte during an early exponential growth phase using an algorithm with a package of the software R and based on a Maximum Likewood estimator. This allows us to predict the epidemic without any control in order to understand how the control measure and public policies designed are having the desired impact of controlling the epidemic. To do this, we introduce a temporally varying decreasing transmission rate parameter with a control or quarantine parameter q. Then we pointed out some values of q to maintain control which is critical in Mayotte given the fragility of its health infrastructure and the significant fraction of the population without access to water.

scholarly journals The Buffering Effects of Social Insurance for the Spread of Covid-19

2021 ◽  
Vol 12 (4(I)) ◽  
pp. 19-27
Author(s):  
Moein Mirani Ahangarkolaei ◽  
Eser Demir ◽  
Tolga Constantinou ◽  
Mostafa Toranji ◽  
Tadashi Adino ◽  
...  
Keyword(s):  
Social Insurance ◽  
Transmission Rate ◽  
The Novel ◽  
Negative Consequences ◽  
Welfare Programs ◽  
Monthly Data ◽  
The Social ◽  
Wide Range ◽  
Novel Coronavirus ◽  
Low Educated

Global pandemics are associated with substantial losses of human capital. The best strategy of policymakers in public health before a population-wide vaccination is to reduce the outbreak of the disease and finding ways to alleviate its negative consequences in society. Previous studies show that welfare programs have externalities in unintended areas and for unplanned outcomes including a wide range of health outcomes. In this paper, we show that payments under the Unemployment Insurance (UI) program have the potential to reduce the spread of the novel coronavirus. Applying a difference-in-difference technique on monthly data of all US counties from January 2020 to January 2021, we document that the social insurance under the umbrella of UI payments can reduce the transmission rate of Covid-19. The results show heterogeneity across subsample with the largest effects among blacks, poor, and low educated regions

scholarly journals The effects of the clinical symptoms pneumonia-confirmation strategy of the COVID-19 epidemic in Wuhan, China

2020 ◽  
Author(s):  
Yanjin Wang ◽  
Pei Wang ◽  
Shudao Zhang ◽  
Hao Pan
Keyword(s):  
Turning Point ◽  
Clinical Symptoms ◽  
Transmission Rate ◽  
Basic Reproductive Number ◽  
Reproductive Number ◽  
The Novel ◽  
Wuhan City ◽  
Start Date ◽  
Rapid Spread ◽  
Novel Coronavirus

Abstract Motivated by the quick control in Wuhan, China, and the rapid spread in other countries of COVID-19, we investigate the questions that what is the turning point in Wuhan by quantifying the variety of basic reproductive number after the lockdown city. The answer may help the world to control the COVID-19 epidemic. A modified SEIR model is used to study the COVID-19 epidemic in Wuhan city. Our model is calibrated by the hospitalized cases. The modeling result gives out that the means of basic reproductive numbers are 1.5517 (95% CI 1.1716-4.4283) for the period from Jan 25 to Feb 11, 2020, and 0.4738(95% CI 0.0997-0.8370) for the period from Feb 12 to Mar 10. The transmission rate fell after Feb 12, 2020 as a result of China’s COVID-19 strategy of keeping society distance and the medical support from all China, but principally because of the clinical symptoms to be used for the novel coronavirus pneumonia (NCP) confirmation in Wuhan since Feb 12, 2020. Clinical diagnosis can quicken up NCP-confirmation such that the COVID-19 patients can be isolated without delay. So the clinical symptoms pneumonia-confirmation is the turning point of the COVID-19 battle of Wuhan. The measure of clinical symptoms pneumonia-confirmation in Wuhan has delayed the growth and reduced size of the COVID-19 epidemic, decreased the peak number of the hospitalized cases by 96% in Wuhan. Our modeling also indicates that the earliest start date of COVID-19 in Wuhan may be Nov 2, 2019.

scholarly journals Changing Clusters of Indian States with respect to number of Cases of COVID-19 using incrementalKMN Method

2020 ◽  
Author(s):  
Rabinder Kumar Prasad ◽  
Rosy Sarmah ◽  
Subrata Chakraborty
Keyword(s):  
Growth Rate ◽  
High Risk ◽  
Doubling Time ◽  
The Other ◽  
Risk Category ◽  
The Novel ◽  
Indian States ◽  
High Risk Category ◽  
First Case ◽  
Novel Coronavirus

Abstract The novel Coronavirus (COVID-19) incidence in India is currently experiencing exponential rise with apparent spatial variation in growth rate and doubling time. We classify the states into five clusters with low to high-risk category and identify how the different states moved from one cluster to the other since the onset of the first case on $30^{th}$ January 2020 till the end of $15^{th}$ September 2020. We cluster the Indian states into $5$ groups using incrementalKMN clustering \cite{b1}. We observed and comment on the changing scenario of the formation of the clusters starting from before lockdown, through lockdown and the various unlock phases.

scholarly journals Dynamics of COVID-19 transmission including indirect transmission mechanisms: a mathematical analysis

2020 ◽  
Vol 148 ◽  
Author(s):  
A. Meiksin
Keyword(s):  
Transmission Rate ◽  
The Novel ◽  
Major Health ◽  
Indirect Transmission ◽  
Transmission Mechanisms ◽  
Novel Coronavirus ◽  
The Uk ◽  
Counterfactual Model ◽  
Respiratory Droplets ◽  
Significant Spread

Abstract The outbreak of the novel coronavirus severe acute respiratory syndrome-coronavirus-2 has raised major health policy questions and dilemmas. Whilst respiratory droplets are believed to be the dominant transmission mechanisms, indirect transmission may also occur through shared contact of contaminated common objects that is not directly curtailed by a lockdown. The conditions under which contaminated common objects may lead to significant spread of coronavirus disease 2019 during lockdown and its easing is examined using the susceptible-exposed-infectious-removed model with a fomite term added. Modelling the weekly death rate in the UK, a maximum-likelihood analysis finds a statistically significant fomite contribution, with 0.009 ± 0.001 (95% CI) infection-inducing fomites introduced into the environment per day per infectious person. Post-lockdown, comparison with the prediction of a corresponding counterfactual model with no fomite transmission suggests fomites, through enhancing the overall transmission rate, may have contributed to as much as 25% of the deaths following lockdown. It is suggested that adding a fomite term to more complex simulations may assist in the understanding of the spread of the illness and in making policy decisions to control it.

scholarly journals Evolutionary dynamics of GII.17 norovirus

PeerJ ◽  
2018 ◽  
Vol 6 ◽  
pp. e4333 ◽  
Author(s):  
Shaowei Sang ◽  
Xiaoyun Yang
Keyword(s):  
Binding Site ◽  
Evolutionary Dynamics ◽  
Phylogenetic Analyses ◽  
Recent Common Ancestor ◽  
Blood Group Antigens ◽  
The Novel ◽  
Nucleotide Substitutions ◽  
Most Recent Common Ancestor ◽  
Likelihood Analysis ◽  
Amino Acid Distance

Background During the winter of 2014–2015, a rarely reported norovirus (NoV) genotype GII.17 was found to have increased its frequency in norovirus outbreaks in East Asia, surpassing the GII.4 NoV infections. GII.17 genotype has been detected for over three decades in the world. The aim of this study is to examine the evolutionary dynamics of GII.17 over the last four decades. Methods NoV GII.17 sequences with complete or nearly complete VP1 were downloaded from GenBank and the phylogenetic analyses were then conducted. Results The maximum likelihood analysis showed that GII.17 genotype could be divided into four different clades (Clades A–D). The strains detected after 2012, which could be the cause of the outbreaks, were separated into Clades C–D with their mean amino acid distance being 4.5%. Bayesian Markov chain Monte Carlo analyses indicated that the rate of nucleotide substitution per sites was 1.68 × 10−3 nucleotide substitutions/site/year and the time of the most recent common ancestor was 1840. The P2 subdomain of GII.17 was highly variable with 44% (56/128) amino acids variations including two insertions at positions 295–296 and one deletion at position 385 (Clades C and D) and one insertion at position 375 (Clade D). Variations existed in Epitopes A, B and D corresponding to GII.4 and human histo-blood group antigens binding site I in P2 subdomain. Conclusion The novel GII.17 strains that caused outbreaks in 2013–2015 may have two new variants. The evolvement of HBGAs binding site and epitopes in P2 subdomain might contribute to the novel GII.17 strains predominance in some regions.

scholarly journals A fractional order approach to modeling and simulations of the novel COVID-19

2020 ◽  
Author(s):  
Isaac Owusu-Mensah ◽  
Lanre Akinyemi ◽  
Bismark Oduro ◽  
Olaniyi S. Iyiola
Keyword(s):  
Public Health ◽  
Fractional Order ◽  
Transmission Rate ◽  
The Novel ◽  
Modeling And Simulations ◽  
Modern Times ◽  
Important Benefit ◽  
Proposed Model ◽  
Public Health Challenges ◽  
Novel Coronavirus

Abstract The novel coronavirus (SARS-CoV-2.) has emerged and spread at fast speed globally; the disease has become an unprecedented threat to public health worldwide. It is one of the greatest public health challenges in modern times, with no proven cure or vaccine. In this paper, our focus is on a fractional order approach to modeling and simulations of the novel COVID-19. We introduce a fractional type Susceptible-Exposed-Infected-Recovered (SEIR) model to gain insight into the ongoing pandemic of COVID-19. Our proposed model incorporates transmission rate, testing rates, and transition rate (from asymptomatic to symptomatic population groups) for a holistic study of the coronavirus disease. The impacts of these parameters on the dynamics of the solution proles for the disease are simulated and discussed in detail. Furthermore, across all the different parameters, the effects of the fractional order derivative are also simulated and discussed in detail. Various simulations carried out enable us gain deep insights into the dynamics of the spread of COVID-19. The simulation results confirm that fractional calculus is an appropriate tool in modeling the spread of a complex infectious disease such as the novel COVID-19. In the absence of vaccine and treatment, our analysis strongly supports the significance reduction in the transmission rate as valuable strategy to curb the spread of the virus. Our results suggest that tracing and moving testing up has an important benefit. It reduces the number of infected individuals in the general public and thereby reduce the spread of the pandemic. Once the infected individuals are identified and isolated, the interaction between susceptible and infected individuals diminishes and transmission reduces. Furthermore, aggressive testing is also highly recommended.

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