IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v18y2021i14p7594-d595783.html
   My bibliography  Save this article

Modeling of the Long-Term Epidemic Dynamics of COVID-19 in the United States

Author

Listed:
  • Derek Huang

    (Wuhan Britain-China School, No.10 Gutian Rd., Qiaokou District, Wuhan 430022, China)

  • Huanyu Tao

    (Institute of Biophysics, School of Physics, Huazhong University of Science and Technology, Wuhan 430074, China)

  • Qilong Wu

    (Institute of Biophysics, School of Physics, Huazhong University of Science and Technology, Wuhan 430074, China)

  • Sheng-You Huang

    (Institute of Biophysics, School of Physics, Huazhong University of Science and Technology, Wuhan 430074, China)

  • Yi Xiao

    (Institute of Biophysics, School of Physics, Huazhong University of Science and Technology, Wuhan 430074, China)

Abstract

Coronavirus 2019 (COVID-19) is causing a severe pandemic that has resulted in millions of confirmed cases and deaths around the world. In the absence of effective drugs for treatment, non-pharmaceutical interventions are the most effective approaches to control the disease. Although some countries have the pandemic under control, all countries around the world, including the United States (US), are still in the process of controlling COVID-19, which calls for an effective epidemic model to describe the transmission dynamics of COVID-19. Meeting this need, we have extensively investigated the transmission dynamics of COVID-19 from 22 January 2020 to 14 February 2021 for the 50 states of the United States, which revealed the general principles underlying the spread of the virus in terms of intervention measures and demographic properties. We further proposed a time-dependent epidemic model, named T-SIR, to model the long-term transmission dynamics of COVID-19 in the US. It was shown in this paper that our T-SIR model could effectively model the epidemic dynamics of COVID-19 for all 50 states, which provided insights into the transmission dynamics of COVID-19 in the US. The present study will be valuable to help understand the epidemic dynamics of COVID-19 and thus help governments determine and implement effective intervention measures or vaccine prioritization to control the pandemic.

Suggested Citation

  • Derek Huang & Huanyu Tao & Qilong Wu & Sheng-You Huang & Yi Xiao, 2021. "Modeling of the Long-Term Epidemic Dynamics of COVID-19 in the United States," IJERPH, MDPI, vol. 18(14), pages 1-17, July.
    • Handle: RePEc:gam:jijerp:v:18:y:2021:i:14:p:7594-:d:595783
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/18/14/7594/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1660-4601/18/14/7594/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Giovanni Gabutti & Erica d’Anchera & Francesco De Motoli & Marta Savio & Armando Stefanati, 2021. "The Epidemiological Characteristics of the COVID-19 Pandemic in Europe: Focus on Italy," IJERPH, MDPI, vol. 18(6), pages 1-14, March.
    2. Shao, Zhi-Gang & Tan, Zhi-Jie & Zou, Xian-Wu & Jin, Zhun-Zhi, 2006. "Epidemics with pathogen mutation on small-world networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 363(2), pages 561-566.
    3. Vageesh Jain & Lara Schwarz & Paula Lorgelly, 2021. "A Rapid Review of COVID-19 Vaccine Prioritization in the U.S.: Alignment between Federal Guidance and State Practice," IJERPH, MDPI, vol. 18(7), pages 1-10, March.
    4. Uxue Alfonso Viguria & Núria Casamitjana, 2021. "Early Interventions and Impact of COVID-19 in Spain," IJERPH, MDPI, vol. 18(8), pages 1-15, April.
    5. Xingjie Hao & Shanshan Cheng & Degang Wu & Tangchun Wu & Xihong Lin & Chaolong Wang, 2020. "Reconstruction of the full transmission dynamics of COVID-19 in Wuhan," Nature, Nature, vol. 584(7821), pages 420-424, August.
    6. Edouard Mathieu & Hannah Ritchie & Esteban Ortiz-Ospina & Max Roser & Joe Hasell & Cameron Appel & Charlie Giattino & Lucas Rodés-Guirao, 2021. "A global database of COVID-19 vaccinations," Nature Human Behaviour, Nature, vol. 5(7), pages 947-953, July.
    7. Alexandros Leontitsis & Abiola Senok & Alawi Alsheikh-Ali & Younus Al Nasser & Tom Loney & Aamena Alshamsi, 2021. "SEAHIR: A Specialized Compartmental Model for COVID-19," IJERPH, MDPI, vol. 18(5), pages 1-11, March.
    8. Nikola Anđelić & Sandi Baressi Šegota & Ivan Lorencin & Zdravko Jurilj & Tijana Šušteršič & Anđela Blagojević & Alen Protić & Tomislav Ćabov & Nenad Filipović & Zlatan Car, 2021. "Estimation of COVID-19 Epidemiology Curve of the United States Using Genetic Programming Algorithm," IJERPH, MDPI, vol. 18(3), pages 1-26, January.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Davide Barbieri & Enrico Giuliani & Anna Del Prete & Amanda Losi & Matteo Villani & Alberto Barbieri, 2021. "How Artificial Intelligence and New Technologies Can Help the Management of the COVID-19 Pandemic," IJERPH, MDPI, vol. 18(14), pages 1-10, July.
    2. Hwang, Eunju, 2022. "Prediction intervals of the COVID-19 cases by HAR models with growth rates and vaccination rates in top eight affected countries: Bootstrap improvement," Chaos, Solitons & Fractals, Elsevier, vol. 155(C).
    3. Wood, Reed M. & Juanchich, Marie & Ramirez, Mark & Zhang, Shenghao, 2023. "Promoting COVID-19 vaccine confidence through public responses to misinformation: The joint influence of message source and message content," Social Science & Medicine, Elsevier, vol. 324(C).
    4. S. D. Sreeganga & Ajay Chandra & Arkalgud Ramaprasad, 2021. "Ontological Analysis of COVID-19 Vaccine Roll out Strategies: A Comparison of India and the United States of America," IJERPH, MDPI, vol. 18(14), pages 1-18, July.
    5. Moritz Kersting & Andreas Bossert & Leif Sörensen & Benjamin Wacker & Jan Chr. Schlüter, 2021. "Predicting effectiveness of countermeasures during the COVID-19 outbreak in South Africa using agent-based simulation," Palgrave Communications, Palgrave Macmillan, vol. 8(1), pages 1-15, December.
    6. Boeing, Philipp & Wang, Yihan, 2021. "Decoding China's Covid-19 "virus exceptionalism": Community-based digital contact tracing in Wuhan," ZEW Discussion Papers 21-028, ZEW - Leibniz Centre for European Economic Research.
    7. Schenkel, Marina, 2024. "Health emergencies, science contrarianism and populism: A scoping review," Social Science & Medicine, Elsevier, vol. 346(C).
    8. Quan-Hoang Vuong & Tam-Tri Le & Viet-Phuong La & Huyen Thanh Thanh Nguyen & Manh-Toan Ho & Quy Khuc & Minh-Hoang Nguyen, 2022. "Covid-19 vaccines production and societal immunization under the serendipity-mindsponge-3D knowledge management theory and conceptual framework," Palgrave Communications, Palgrave Macmillan, vol. 9(1), pages 1-12, December.
    9. Tianzhen Hu & Li Li & Chuanxue Lin & Zikun Yang & Cheng Chow & Zhipeng Lu & Chen You, 2022. "An Analysis of the Willingness to the COVID-19 Vaccine Booster Shots among Urban Employees: Evidence from a Megacity H in Eastern China," IJERPH, MDPI, vol. 19(4), pages 1-14, February.
    10. Carlotta Amantea & Maria Francesca Rossi & Paolo Emilio Santoro & Flavia Beccia & Maria Rosaria Gualano & Ivan Borrelli & Joana Pinto da Costa & Alessandra Daniele & Antonio Tumminello & Stefania Bocc, 2022. "Medical Liability of the Vaccinating Doctor: Comparing Policies in European Union Countries during the COVID-19 Pandemic," IJERPH, MDPI, vol. 19(12), pages 1-11, June.
    11. Christian Gillitzer & Nalini Prasad, 2023. "The Effect Of School Closures On Standardized Test Scores: Evidence From A Zero-Covid Environment," Working Papers 2023-09, University of Sydney, School of Economics.
    12. Kun Sun & Tian-Fang Zhao & Xiao-Kun Wu & Kai-Sheng Lai & Wei-Neng Chen & Jin-Sheng Zhang, 2022. "Incorporating Fuzzy Cognitive Inference for Vaccine Hesitancy Measuring," Sustainability, MDPI, vol. 14(14), pages 1-18, July.
    13. Lifeng Zhang & Roy E. Welsch & Zhi Cao, 2022. "The Transmission, Infection Prevention, and Control during the COVID-19 Pandemic in China: A Retrospective Study," IJERPH, MDPI, vol. 19(5), pages 1-15, March.
    14. Ilias Chronopoulos & Katerina Chrysikou & George Kapetanios & James Mitchell & Aristeidis Raftapostolos, 2023. "Deep Neural Network Estimation in Panel Data Models," Working Papers 23-15, Federal Reserve Bank of Cleveland.
    15. Rastko Jovanović & Miloš Davidović & Ivan Lazović & Maja Jovanović & Milena Jovašević-Stojanović, 2021. "Modelling Voluntary General Population Vaccination Strategies during COVID-19 Outbreak: Influence of Disease Prevalence," IJERPH, MDPI, vol. 18(12), pages 1-18, June.
    16. Jo Daniels & Hannah Rettie, 2022. "The Mental Health Impact of the COVID-19 Pandemic Second Wave on Shielders and Their Family Members," IJERPH, MDPI, vol. 19(12), pages 1-17, June.
    17. Antoni Wilinski & Irena Bach-Dabrowska, 2022. "COVID-19: Changes in the Ranking of Polish Regions According to the Criterion Taking into Account both the Reluctance to Vaccinate and the Number of Deaths," European Research Studies Journal, European Research Studies Journal, vol. 0(1), pages 423-432.
    18. Wang Xiang & Li Chen & Qunjie Peng & Bing Wang & Xiaobing Liu, 2022. "How Effective Is a Traffic Control Policy in Blocking the Spread of COVID-19? A Case Study of Changsha, China," IJERPH, MDPI, vol. 19(13), pages 1-17, June.
    19. Zhang, Hui & Xu, Min & Ouyang, Min, 2024. "A multi-perspective functionality loss assessment of coupled railway and airline systems under extreme events," Reliability Engineering and System Safety, Elsevier, vol. 243(C).
    20. Kolawole Ogundari, 2022. "The COVID-19 vaccine rollout and labor market recovery in the U.S: a note," SN Business & Economics, Springer, vol. 2(7), pages 1-13, July.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jijerp:v:18:y:2021:i:14:p:7594-:d:595783. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.