Trend Analysis of COVID-19 Based on Network Topology Description

被引：3
|
作者：
Zhu, Jun [1 ]
Jiang, Yangqianzi [1 ]
Li, Tianrui [1 ]
Li, Huining [2 ]
Liu, Qingshan [1 ]
机构：
[1] Southeast Univ, Sch Math, Nanjing, Peoples R China
[2] Southeast Univ, Sch Informat Sci & Engn, Nanjing, Peoples R China
来源：
FRONTIERS IN PHYSICS | 2020年 / 8卷
基金：
中国国家自然科学基金;
关键词：
COVID-19; sliding window; network topology; dynamic evolution; trend analysis; SEIR EPIDEMIC MODEL; DYNAMICS; TRANSMISSION; DISEASES;
D O I：
10.3389/fphy.2020.564061
中图分类号：
O4 [物理学];
学科分类号：
0702 ;
摘要：
In this study, the trend of the epidemic situation of COVID-19 is analyzed based on the analysis method for network topology. Combining with the sliding window method, the dynamic networks with different topologies for each window are built to reflect the relationship of the data on different days. Then, the static statistical features on network topologies at different times are extracted during the dynamic evolution of complex networks. A new trend function defined on the average degree and clustering coefficient of the network is tailored to measure the characteristics of the trend. Through the value of the trend function, we can analyze the trend of the epidemic situation in real time. It is found that if the value of the trend function tends to decrease, it means that the epidemic will have to be effectively controlled. Finally, we put forward some suggestions for early control of the epidemic.
引用
收藏
页数：6
相关论文
共 50 条
  • [1] Outcome of COVID-19: A trend analysis
    Chandu, Kavitha
    Dasari, Madhavaprasad
    BIOMEDICAL AND BIOTECHNOLOGY RESEARCH JOURNAL, 2020, 4 (05): : 96 - 98
  • [2] An Interactive Simulator for COVID-19 Trend Analysis
    Deshmukh, Jayati
    Subbanarasimha, Raksha Pavagada
    Bassin, Pooja
    Bitra, Venkat Suprabath
    Srinivasa, Srinath
    Sharma, Anupama
    CODS-COMAD 2021: PROCEEDINGS OF THE 3RD ACM INDIA JOINT INTERNATIONAL CONFERENCE ON DATA SCIENCE & MANAGEMENT OF DATA (8TH ACM IKDD CODS & 26TH COMAD), 2021, : 385 - 389
  • [3] A topic trend analysis on COVID-19 literature
    Urru, Sara
    Sciannameo, Veronica
    Lanera, Corrado
    Salaris, Silvano
    Gregori, Dario
    Berchialla, Paola
    DIGITAL HEALTH, 2022, 8
  • [4] Simulation Analysis of Epidemic Trend for COVID-19 Based on SEIRS Model
    Gel, Jike
    Zhang, Lanzhu
    Chen, Zugin
    Chen, Guorong
    Peng, Jun
    PROCEEDINGS OF 2020 IEEE 19TH INTERNATIONAL CONFERENCE ON COGNITIVE INFORMATICS & COGNITIVE COMPUTING (ICCI*CC 2020), 2020, : 158 - 161
  • [5] Bioinformatics/network topology analysis of acupuncture in the treatment of COVID-19: response to methodological issues
    Zhao, Meidan
    Wang, Pengqian
    Zhang, Kai
    BRIEFINGS IN BIOINFORMATICS, 2022, 23 (03)
  • [6] Trend Analysis of CLABSI During COVID-19 Pandemic
    Bhagat, U.
    Chandna, S.
    Karna, S. S.
    Agrawal, A.
    Recinos, L.
    Toquica, C.
    Priya, A.
    AMERICAN JOURNAL OF RESPIRATORY AND CRITICAL CARE MEDICINE, 2023, 207
  • [7] COVID-19 Trend Analysis in Mexican States and Cities
    Paiva, Henrique Mohallem
    Magalhaes Afonso, Rubens Junqueira
    Sanches, Davi Goncalves
    Ribeiro Pelogia, Frederico Jose
    2021 43RD ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE & BIOLOGY SOCIETY (EMBC), 2021, : 1820 - 1823
  • [8] COVID-19 and waste production in households: A trend analysis
    Filho, Walter Leal
    Voronova, Viktoria
    Kloga, Marija
    Paco, Arminda
    Minhas, Aprajita
    Salvia, Amanda Lange
    Ferreira, Celia Dias
    Sivapalan, Subarna
    SCIENCE OF THE TOTAL ENVIRONMENT, 2021, 777
  • [9] Linking FDI and trade network topology with the COVID-19 pandemic
    Roberto Antonietti
    Giulia De Masi
    Giorgio Ricchiuti
    Journal of Economic Interaction and Coordination, 2023, 18 : 807 - 833
  • [10] A dynamic ensemble approach based on trend analysis to COVID-19 incidence forecast
    de Sales, Jair Paulino
    Neto, Paulo S. G. de Mattos
    Firmino, Paulo R. A.
    BIOMEDICAL SIGNAL PROCESSING AND CONTROL, 2024, 95
12345