IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v630y2023ics0378437123007987.html
   My bibliography  Save this article

The impact of multiple population-wide testing and social distancing on the transmission of an infectious disease

Author

Listed:
  • Han, Lili
  • Song, Sha
  • Pan, Qiuhui
  • He, Mingfeng

Abstract

Under the background that asymptomatic virus carriers are contagious and the virus in the infected individuals has mild pathogenicity and enhanced transmissivity for an infectious disease, the phenomenon appears that the majority of infected people do not show any symptoms, but can infect others. Multiple population-wide testing can screen out asymptomatic virus carriers in time. Thus, we develop an infectious disease transmission dynamics model that includes three stages: non-testing period, testing period and testing interval, with multiple population-wide testing and social distancing to study the effects of the first testing time, total testing number, and testing interval time on the transmission of infectious diseases in this paper. The existence, uniqueness, boundedness and positivity of the solution, as well as the formulas of the basic reproduction number and the control reproduction number of the established model are established The numerical results show that the earlier the population-wide testing measure is implemented, the fewer the final size and necessary testing frequency. In the initial stage of the larger-scale spread of infectious disease, the existing virus carriers are not the most. But if population-wide testing measure is implemented during this period, the strongest testing force is required to contain the spread of the epidemic. Besides, population-wide testing combined with restrictive social distancing will significantly reduce the final size, necessary testing frequency, and duration of the epidemic. The testing interval time should be no longer than the incubation period of the virus to prevent and control the epidemic accurately. Therefore, the paper provides a theoretic basis for developing and implementing scientific testing strategies.

Suggested Citation

  • Han, Lili & Song, Sha & Pan, Qiuhui & He, Mingfeng, 2023. "The impact of multiple population-wide testing and social distancing on the transmission of an infectious disease," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 630(C).
    • Handle: RePEc:eee:phsmap:v:630:y:2023:i:c:s0378437123007987
    DOI: 10.1016/j.physa.2023.129243
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437123007987
    Download Restriction: Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000
    File URL: https://libkey.io/10.1016/j.physa.2023.129243?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Huiping Shuai & Jasper Fuk-Woo Chan & Bingjie Hu & Yue Chai & Terrence Tsz-Tai Yuen & Feifei Yin & Xiner Huang & Chaemin Yoon & Jing-Chu Hu & Huan Liu & Jialu Shi & Yuanchen Liu & Tianrenzheng Zhu & J, 2022. "Attenuated replication and pathogenicity of SARS-CoV-2 B.1.1.529 Omicron," Nature, Nature, vol. 603(7902), pages 693-699, March.
    2. Sarkar, Kankan & Khajanchi, Subhas & Nieto, Juan J., 2020. "Modeling and forecasting the COVID-19 pandemic in India," Chaos, Solitons & Fractals, Elsevier, vol. 139(C).
    3. Samui, Piu & Mondal, Jayanta & Khajanchi, Subhas, 2020. "A mathematical model for COVID-19 transmission dynamics with a case study of India," Chaos, Solitons & Fractals, Elsevier, vol. 140(C).
    4. Jang, Junyoung & Kwon, Hee-Dae & Lee, Jeehyun, 2020. "Optimal control problem of an SIR reaction–diffusion model with inequality constraints," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 171(C), pages 136-151.
    5. Luigi Cirrincione & Fulvio Plescia & Caterina Ledda & Venerando Rapisarda & Daniela Martorana & Raluca Emilia Moldovan & Kelly Theodoridou & Emanuele Cannizzaro, 2020. "COVID-19 Pandemic: Prevention and Protection Measures to Be Adopted at the Workplace," Sustainability, MDPI, vol. 12(9), pages 1-18, April.
    6. Khajanchi, Subhas & Bera, Sovan & Roy, Tapan Kumar, 2021. "Mathematical analysis of the global dynamics of a HTLV-I infection model, considering the role of cytotoxic T-lymphocytes," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 180(C), pages 354-378.
    7. Kenrie P. Y. Hui & John C. W. Ho & Man-chun Cheung & Ka-chun Ng & Rachel H. H. Ching & Ka-ling Lai & Tonia Tong Kam & Haogao Gu & Ko-Yung Sit & Michael K. Y. Hsin & Timmy W. K. Au & Leo L. M. Poon & M, 2022. "SARS-CoV-2 Omicron variant replication in human bronchus and lung ex vivo," Nature, Nature, vol. 603(7902), pages 715-720, March.
    8. Simon Cauchemez & Alain-Jacques Valleron & Pierre-Yves Boëlle & Antoine Flahault & Neil M. Ferguson, 2008. "Estimating the impact of school closure on influenza transmission from Sentinel data," Nature, Nature, vol. 452(7188), pages 750-754, April.
    9. Mingolla, Stefano & Lu, Zhongming, 2022. "Impact of implementation timing on the effectiveness of stay-at-home requirement under the COVID-19 pandemic: Lessons from the Italian Case," Health Policy, Elsevier, vol. 126(6), pages 504-511.
    10. Bera, Sovan & Khajanchi, Subhas & Roy, Tapan Kumar, 2022. "Dynamics of an HTLV-I infection model with delayed CTLs immune response," Applied Mathematics and Computation, Elsevier, vol. 430(C).
    11. Soyoung Kim & Youngsuk Ko & Yae-Jean Kim & Eunok Jung, 2020. "The impact of social distancing and public behavior changes on COVID-19 transmission dynamics in the Republic of Korea," PLOS ONE, Public Library of Science, vol. 15(9), pages 1-8, September.
    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. Zhang, Zhenzhen & Ma, Xia & Zhang, Yongxin & Sun, Guiquan & Zhang, Zi-Ke, 2023. "Identifying critical driving factors for human brucellosis in Inner Mongolia, China," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 626(C).
    2. Sharma, Natasha & Verma, Atul Kumar & Gupta, Arvind Kumar, 2021. "Spatial network based model forecasting transmission and control of COVID-19," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 581(C).
    3. Bandekar, Shraddha Ramdas & Ghosh, Mini, 2022. "A co-infection model on TB - COVID-19 with optimal control and sensitivity analysis," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 200(C), pages 1-31.
    4. Bera, Sovan & Khajanchi, Subhas & Roy, Tapan Kumar, 2022. "Dynamics of an HTLV-I infection model with delayed CTLs immune response," Applied Mathematics and Computation, Elsevier, vol. 430(C).
    5. Matouk, A.E., 2020. "Complex dynamics in susceptible-infected models for COVID-19 with multi-drug resistance," Chaos, Solitons & Fractals, Elsevier, vol. 140(C).
    6. Amar Nath Chatterjee & Fahad Al Basir & Bashir Ahmad & Ahmed Alsaedi, 2022. "A Fractional-Order Compartmental Model of Vaccination for COVID-19 with the Fear Factor," Mathematics, MDPI, vol. 10(9), pages 1-15, April.
    7. Ahmed M. Elaiw & Abdulsalam S. Shflot & Aatef D. Hobiny & Shaban A. Aly, 2023. "Global Dynamics of an HTLV-I and SARS-CoV-2 Co-Infection Model with Diffusion," Mathematics, MDPI, vol. 11(3), pages 1-33, January.
    8. Ahmed M. Elaiw & Abdulsalam S. Shflot & Aatef D. Hobiny, 2022. "Global Stability of Delayed SARS-CoV-2 and HTLV-I Coinfection Models within a Host," Mathematics, MDPI, vol. 10(24), pages 1-35, December.
    9. Taha Y. Taha & Irene P. Chen & Jennifer M. Hayashi & Takako Tabata & Keith Walcott & Gabriella R. Kimmerly & Abdullah M. Syed & Alison Ciling & Rahul K. Suryawanshi & Hannah S. Martin & Bryan H. Bach , 2023. "Rapid assembly of SARS-CoV-2 genomes reveals attenuation of the Omicron BA.1 variant through NSP6," Nature Communications, Nature, vol. 14(1), pages 1-13, December.
    10. Asamoah, Joshua Kiddy K. & Okyere, Eric & Yankson, Ernest & Opoku, Alex Akwasi & Adom-Konadu, Agnes & Acheampong, Edward & Arthur, Yarhands Dissou, 2022. "Non-fractional and fractional mathematical analysis and simulations for Q fever," Chaos, Solitons & Fractals, Elsevier, vol. 156(C).
    11. Mayer Alvo & Jingrui Mu, 2023. "COVID-19 Data Analysis Using Bayesian Models and Nonparametric Geostatistical Models," Mathematics, MDPI, vol. 11(6), pages 1-13, March.
    12. Talal Daghriri & Michael Proctor & Sarah Matthews, 2022. "Evolution of Select Epidemiological Modeling and the Rise of Population Sentiment Analysis: A Literature Review and COVID-19 Sentiment Illustration," IJERPH, MDPI, vol. 19(6), pages 1-20, March.
    13. Jialei Jiang & Eun-Mi Park & Seong-Taek Park, 2021. "The Impact of the COVID-19 on Economic Sustainability—A Case Study of Fluctuation in Stock Prices for China and South Korea," Sustainability, MDPI, vol. 13(12), pages 1-17, June.
    14. Cooper, Ian & Mondal, Argha & Antonopoulos, Chris G., 2020. "Dynamic tracking with model-based forecasting for the spread of the COVID-19 pandemic," Chaos, Solitons & Fractals, Elsevier, vol. 139(C).
    15. Shixian Luo & Jing Xie & Katsunori Furuya, 2021. "“We Need such a Space”: Residents’ Motives for Visiting Urban Green Spaces during the COVID-19 Pandemic," Sustainability, MDPI, vol. 13(12), pages 1-18, June.
    16. Hongfei Xiao & Deqin Lin & Shiyu Li, 2023. "Novel Method for Estimating Time-Varying COVID-19 Transmission Rate," Mathematics, MDPI, vol. 11(10), pages 1-18, May.
    17. Yin-Feng Kang & Cong Sun & Jing Sun & Chu Xie & Zhen Zhuang & Hui-Qin Xu & Zheng Liu & Yi-Hao Liu & Sui Peng & Run-Yu Yuan & Jin-Cun Zhao & Mu-Sheng Zeng, 2022. "Quadrivalent mosaic HexaPro-bearing nanoparticle vaccine protects against infection of SARS-CoV-2 variants," Nature Communications, Nature, vol. 13(1), pages 1-15, December.
    18. Zeng, Lang & Chen, Yushu & Liu, Yiwen & Tang, Ming & Liu, Ying & Jin, Zhen & Do, Younghae & Pelinovsky, E. & Kirillin, M. & Macau, E., 2024. "The impact of social interventions on COVID-19 spreading based on multilayer commuter networks," Chaos, Solitons & Fractals, Elsevier, vol. 185(C).
    19. Jérôme Adda, 2016. "Economic Activity and the Spread of Viral Diseases: Evidence from High Frequency Data," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 131(2), pages 891-941.
    20. Pan, Yuxuan & Zhu, Linhe, 2024. "Parameter identification method of information propagation models based on different network structures," Chaos, Solitons & Fractals, Elsevier, vol. 185(C).

    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:eee:phsmap:v:630:y:2023:i:c:s0378437123007987. 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: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/physica-a-statistical-mechpplications/ .

    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.