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1.
Viruses ; 13(9)2021 09 03.
Article in English | MEDLINE | ID: covidwho-1390792

ABSTRACT

Surveillance of the evolving SARS-CoV-2 genome combined with epidemiological monitoring and emerging vaccination became paramount tasks to control the pandemic which is rapidly changing in time and space. Genomic surveillance must combine generation and sharing sequence data with appropriate bioinformatics monitoring and analysis methods. We applied molecular portrayal using self-organizing maps machine learning (SOM portrayal) to characterize the diversity of the virus genomes, their mutual relatedness and development since the beginning of the pandemic. The genetic landscape obtained visualizes the relevant mutations in a lineage-specific fashion and provides developmental paths in genetic state space from early lineages towards the variants of concern alpha, beta, gamma and delta. The different genes of the virus have specific footprints in the landscape reflecting their biological impact. SOM portrayal provides a novel option for 'bioinformatics surveillance' of the pandemic, with strong odds regarding visualization, intuitive perception and 'personalization' of the mutational patterns of the virus genomes.


Subject(s)
COVID-19/virology , Evolution, Molecular , Genetic Variation , Genome, Viral , SARS-CoV-2/genetics , COVID-19/epidemiology , Computational Biology , Genomics/methods , Humans , Incidence , Mutation , Pandemics , Phylogeny , Polymorphism, Single Nucleotide , SARS-CoV-2/classification
2.
Viruses ; 12(7):777, 2020.
Article | WHO COVID | ID: covidwho-651461

ABSTRACT

The Covid-19 pandemic is developing worldwide with common dynamics but also with marked differences between regions and countries. These are not completely understood, but presumably, provide a clue to find ways to mitigate epidemics until strategies leading to its eradication become available. We describe an iteractive monitoring tool available in the internet. It enables inspection of the dynamic state of the epidemic in 187 countries using trajectories that visualize the transmission and removal rates of the epidemic and in this way bridge epi-curve tracking with modelling approaches. Examples were provided which characterize state of epidemic in different regions of the world in terms of fast and slow growing and decaying regimes and estimate associated rate factors. The basic spread of the disease is associated with transmission between two individuals every two-three days on the average. Non-pharmaceutical interventions decrease this value to up to ten days, whereas "complete lock down"measures are required to stop the epidemic. Comparison of trajectories revealed marked differences between the countries regarding efficiency of measures taken against the epidemic. Trajectories also reveal marked country-specific recovery and death rate dynamics. The results presented refer to the pandemic state in May to July 2020 and can serve as "working instruction"for timely monitoring using the interactive monitoring tool as a sort of "seismometer"for the evaluation of the state of epidemic, e.g., the possible effect of measures taken in both, lock-down and lock-up directions. Comparison of trajectories between countries and regions will support developing hypotheses and models to better understand regional differences of dynamics of Covid-19.

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