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Dengue is the fastest spreading arboviral disease, posing great challenges on global public health. A reproduceable and comparable global genotyping framework for contextualizing spatiotemporal epidemiological data of dengue virus (DENV) is essential for research studies and collaborative surveillance. Targeting DENV-1 spreading prominently in recent decades, by reconciling all qualified complete E gene sequences of 5003 DENV-1 strains with epidemiological information from 78 epidemic countries/areas ranging from 1944 to 2018, we established and characterized a unified global high-resolution genotyping framework using phylogenetics, population genetics, phylogeography, and phylodynamics. The defined framework was discriminated with three hierarchical layers of genotype, subgenotype and clade with respective mean pairwise distances 2–6%, 0.8–2%, and ≤ 0.8%. The global epidemic patterns of DENV-1 showed strong geographic constraints representing stratified spatial ....

United States , South Korea , Republic Of Korea , Koichiro Tamura , Monte Carlo , Sudhir Kumar , Masatoshi Nei , Pennsylvania State University , R Foundation For Statistical Computing , Virus Pathogen Resource , Hierarchical Bayesian Analysis , Population Structure , Tabless B , Bayesian Skyline , Markov Chain Monte Carlo , Trace Tracer , Statistical Computing ,