ArticleViruses2020
A Mutation Network Method for Transmission Analysis of Human Influenza H3N2.
Article in Viruses, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
3 citing papers in PubMed.
- Global Circulation Dynamics and Its Determinants of Dengue Virus: A Network Evolution and Model Study from 1990 to 2019.Viruses · 2025Article
- Variation in synonymous evolutionary rates in the SARS-CoV-2 genome.Frontiers in microbiology · 2023Article
- New framework for recombination and adaptive evolution analysis with application to the novel coronavirus SARS-CoV-2.Briefings in bioinformatics · 2021Article
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Authors and funding
14 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Characterizing the spatial transmission pattern is critical for better surveillance and control of human influenza. Here, we propose a mutation network framework that utilizes network theory to study the transmission of human influenza H3N2. On the basis of the mutation network, the transmission analysis captured the circulation pattern from a global simulation of human influenza H3N2. Furthermore, this method was applied to explore, in detail, the transmission patterns within Europe, the United States, and China, revealing the regional spread of human influenza H3N2. The mutation network framework proposed here could facilitate the understanding, surveillance, and control of other infectious diseases.
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