Networks of information token recurrences derived from genomic sequences may reveal hidden patterns in epidemic outbreaks: A case study of the 2019-nCoV coronavirus.

Profiling the genetic evolution and dynamic spreading of viruses is a crucial task when responding to epidemic outbreaks. We aim to devise novel ways to model, visualise and analyse the temporal dynamics of epidemic outbreaks in order to help researchers and other people involved in crisis response to make well-informed and targeted decisions about from which geographical locations and time periods more genetic samples may be required to fully understand the outbreak. Our approach relies on the application of Transcendental Information Cascades to a set of temporally ordered nucleotide sequences and we apply it to real-world data that was collected during the currently ongoing outbreak of the novel 2019-nCoV coronavirus. We assess information-theoretic and network-theoretic measures that characterise the resulting complex network and suggest touching points and temporal pathways that are of interest for deeper investigation by geneticists and epidemiologists.

[1]  Kieron O'Hara,et al.  What an entangled Web we weave: An information-centric approach to time-evolving socio-technical systems , 2018, PeerJ Prepr..

[2]  L. Fulton,et al.  Finding Functional Features in Saccharomyces Genomes by Phylogenetic Footprinting , 2003, Science.

[3]  A. Rambaut,et al.  BEAST: Bayesian evolutionary analysis by sampling trees , 2007, BMC Evolutionary Biology.

[4]  P. Sharp,et al.  The codon Adaptation Index--a measure of directional synonymous codon usage bias, and its potential applications. , 1987, Nucleic acids research.

[5]  Wenjun Ma,et al.  Transmission dynamics of 2019 novel coronavirus (2019-nCoV) , 2020, bioRxiv.

[6]  Jason Faulkner,et al.  Evolved Disease-Avoidance Mechanisms and Contemporary Xenophobic Attitudes , 2004 .

[7]  Alison S. Devonshire,et al.  Towards standardisation of cell-free DNA measurement in plasma: controls for extraction efficiency, fragment size bias and quantification , 2014, Analytical and Bioanalytical Chemistry.

[8]  H. Bandelt,et al.  Median-joining networks for inferring intraspecific phylogenies. , 1999, Molecular biology and evolution.

[9]  Z. Wang,et al.  The structure and dynamics of multilayer networks , 2014, Physics Reports.

[10]  Petter Holme,et al.  Detecting sequences of system states in temporal networks , 2018, Scientific Reports.

[11]  Silvia Angeletti,et al.  The 2019‐new coronavirus epidemic: Evidence for virus evolution , 2020, Journal of medical virology.

[12]  Nigel Shadbolt,et al.  From coincidence to purposeful flow? Properties of transcendental information cascades , 2015, 2015 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM).

[13]  Yifan Hu,et al.  Efficient, High-Quality Force-Directed Graph Drawing , 2006 .

[14]  S. Tavaré,et al.  A Bayesian approach to phylogeographic clustering , 2011, Interface Focus.

[15]  N. Dong,et al.  Genomic and protein structure modelling analysis depicts the origin and infectivity of 2019-nCoV, a new coronavirus which caused a pneumonia outbreak in Wuhan, China , 2020, bioRxiv.

[16]  Fabrizio D'Amico,et al.  Ebola Virus Disease 2013-2014 Outbreak in West Africa: An Analysis of the Epidemic Spread and Response , 2015, International journal of microbiology.

[17]  Jean-Loup Guillaume,et al.  Fast unfolding of communities in large networks , 2008, 0803.0476.

[18]  Chun Li,et al.  Similarity analysis of DNA sequences based on codon usage , 2008 .

[19]  Richard D. Smith.  Responding to global infectious disease outbreaks: Lessons from SARS on the role of risk perception, communication and management , 2006, Social Science & Medicine.

[20]  Mason A. Porter,et al.  Nonlinearity + Networks: A 2020 Vision , 2019, Emerging Frontiers in Nonlinear Science.

[21]  M. Scharf,et al.  Rapid evolutionary responses to insecticide resistance management interventions by the German cockroach (Blattella germanica L.) , 2019, Scientific Reports.

[22]  B. Birren,et al.  Sequencing and comparison of yeast species to identify genes and regulatory elements , 2003, Nature.

[23]  P. Farabaugh,et al.  How translational accuracy influences reading frame maintenance , 1999, The EMBO journal.