IDEAS home Printed from https://ideas.repec.org/a/eee/apmaco/v338y2018icp249-259.html

Calibration of a SEIR–SEI epidemic model to describe the Zika virus outbreak in Brazil

Author

Listed:
  • Dantas, Eber
  • Tosin, Michel
  • Cunha Jr, Americo

Abstract

Multiple instances of Zika virus epidemic have been reported around the world in the last two decades, turning the related illness into an international concern. In this context the use of mathematical models for epidemics is of great importance, since they are useful tools to study the underlying outbreak numbers and allow one to test the effectiveness of different strategies used to combat the associated diseases. This work deals with the development and calibration of an epidemic model to describe the 2016 outbreak of Zika virus in Brazil. A system of 8 differential equations with 8 parameters is employed to model the evolution of the infection through two populations. Nominal values for the model parameters are estimated from the literature. An inverse problem is formulated and solved by comparing the system response to real data from the outbreak. The calibrated results presents realistic parameters and returns reasonable descriptions, with the curve shape similar to the outbreak evolution and peak value close to the highest number of infected people during 2016. Considerations about the lack of data for some initial conditions are also made through an analysis over the response behavior according to their change in value.

Suggested Citation

  • Dantas, Eber & Tosin, Michel & Cunha Jr, Americo, 2018. "Calibration of a SEIR–SEI epidemic model to describe the Zika virus outbreak in Brazil," Applied Mathematics and Computation, Elsevier, vol. 338(C), pages 249-259.
  • Handle: RePEc:eee:apmaco:v:338:y:2018:i:c:p:249-259
    DOI: 10.1016/j.amc.2018.06.024
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0096300318305125
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.amc.2018.06.024?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

    for a different version of it.

    References listed on IDEAS

    as
    1. Cai, Yongli & Kang, Yun & Wang, Weiming, 2017. "A stochastic SIRS epidemic model with nonlinear incidence rate," Applied Mathematics and Computation, Elsevier, vol. 305(C), pages 221-240.
    2. Miranda Chan & Michael A Johansson, 2012. "The Incubation Periods of Dengue Viruses," PLOS ONE, Public Library of Science, vol. 7(11), pages 1-7, November.
    3. Wang, Xiaoyun & Wei, Lijuan & Zhang, Juan, 2014. "Dynamical analysis and perturbation solution of an SEIR epidemic model," Applied Mathematics and Computation, Elsevier, vol. 232(C), pages 479-486.
    4. Diaz, Paul & Constantine, Paul & Kalmbach, Kelsey & Jones, Eric & Pankavich, Stephen, 2018. "A modified SEIR model for the spread of Ebola in Western Africa and metrics for resource allocation," Applied Mathematics and Computation, Elsevier, vol. 324(C), pages 141-155.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Ariful Kabir, K.M. & Tanimoto, Jun, 2021. "A cyclic epidemic vaccination model: Embedding the attitude of individuals toward vaccination into SVIS dynamics through social interactions," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 581(C).
    2. Gergo Pinter & Imre Felde & Amir Mosavi & Pedram Ghamisi & Richard Gloaguen, 2020. "COVID-19 Pandemic Prediction for Hungary; A Hybrid Machine Learning Approach," Mathematics, MDPI, vol. 8(6), pages 1-20, June.
    3. Kabir, K.M. Ariful & Tanimoto, Jun, 2019. "Dynamical behaviors for vaccination can suppress infectious disease – A game theoretical approach," Chaos, Solitons & Fractals, Elsevier, vol. 123(C), pages 229-239.
    4. Kabir, K.M. Ariful & Kuga, Kazuki & Tanimoto, Jun, 2019. "Analysis of SIR epidemic model with information spreading of awareness," Chaos, Solitons & Fractals, Elsevier, vol. 119(C), pages 118-125.
    5. Wang, Mengyao & Pan, Qiuhui & He, Mingfeng, 2020. "The effect of individual attitude on cooperation in social dilemma," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 555(C).
    6. Jabili Angina & Anish Bachhu & Eesha Talati & Rishi Talati & Jan Rychtář & Dewey Taylor, 2022. "Game-Theoretical Model of the Voluntary Use of Insect Repellents to Prevent Zika Fever," Dynamic Games and Applications, Springer, vol. 12(1), pages 133-146, March.
    7. Yunhwan Kim & Ana Vivas Barber & Sunmi Lee, 2020. "Modeling influenza transmission dynamics with media coverage data of the 2009 H1N1 outbreak in Korea," PLOS ONE, Public Library of Science, vol. 15(6), pages 1-21, June.
    8. AlShamrani, N.H. & Elaiw, A.M. & Batarfi, H. & Hobiny, A.D. & Dutta, H., 2020. "Global stability analysis of a general nonlinear scabies dynamics model," Chaos, Solitons & Fractals, Elsevier, vol. 138(C).

    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. Cen Song & Sijia Zhou & Kyle Hunt & Jun Zhuang, 2022. "Comprehensive Evolution Analysis of Public Perceptions Related to Pediatric Care: A Sina Weibo Case Study (2013–2020)," SAGE Open, , vol. 12(1), pages 21582440221, March.
    2. Wang, Jinling & Jiang, Haijun & Ma, Tianlong & Hu, Cheng, 2019. "Global dynamics of the multi-lingual SIR rumor spreading model with cross-transmitted mechanism," Chaos, Solitons & Fractals, Elsevier, vol. 126(C), pages 148-157.
    3. Zhao, Yu & Zhang, Liping & Yuan, Sanling, 2018. "The effect of media coverage on threshold dynamics for a stochastic SIS epidemic model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 512(C), pages 248-260.
    4. Kazi Mizanur Rahman & Yushuf Sharker & Reza Ali Rumi & Mahboob-Ul Islam Khan & Mohammad Sohel Shomik & Muhammad Waliur Rahman & Sk Masum Billah & Mahmudur Rahman & Peter Kim Streatfield & David Harley, 2020. "An Association between Rainy Days with Clinical Dengue Fever in Dhaka, Bangladesh: Findings from a Hospital Based Study," IJERPH, MDPI, vol. 17(24), pages 1-9, December.
    5. Huyi Wang & Ge Zhang & Tao Chen & Zhiming Li, 2023. "Threshold Analysis of a Stochastic SIRS Epidemic Model with Logistic Birth and Nonlinear Incidence," Mathematics, MDPI, vol. 11(7), pages 1-17, April.
    6. Mateus C, Rafael & Zuluaga, Susana Alvarez & Orozco, Mariajose Franco & Marín, Paula Alejandra Escudero, 2021. "Modeling the propagation of the Dengue, Zika and Chikungunya virus in the city of Bello using Agent-Based Modeling and Simulation," OSF Preprints wmxzd, Center for Open Science.
    7. Zhou, Baoquan & Shi, Ningzhong, 2024. "Analysis of a stochastic SEIS epidemic model motivated by Black–Karasinski process: Probability density function," Chaos, Solitons & Fractals, Elsevier, vol. 189(P2).
    8. Liu, Qun & Jiang, Daqing & Hayat, Tasawar & Alsaedi, Ahmed & Ahmad, Bashir, 2020. "A stochastic SIRS epidemic model with logistic growth and general nonlinear incidence rate," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 551(C).
    9. Feng, Tao & Qiu, Zhipeng & Meng, Xinzhu & Rong, Libin, 2019. "Analysis of a stochastic HIV-1 infection model with degenerate diffusion," Applied Mathematics and Computation, Elsevier, vol. 348(C), pages 437-455.
    10. Liu, Qun & Jiang, Daqing & He, Xiuli & Hayat, Tasawar & Alsaedi, Ahmed, 2019. "Stationary distribution of a stochastic predator–prey model with distributed delay and general functional response," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 513(C), pages 273-287.
    11. Albano, Giuseppina & Giorno, Virginia & Pérez-Romero, Gema & Torres-Ruiz, Francisco de Asis, 2025. "Inference on a stochastic SIR model including growth curves," Computational Statistics & Data Analysis, Elsevier, vol. 212(C).
    12. Liu, Yan & Mei, Jingling & Li, Wenxue, 2018. "Stochastic stabilization problem of complex networks without strong connectedness," Applied Mathematics and Computation, Elsevier, vol. 332(C), pages 304-315.
    13. Wang, Yan & Qi, Kai & Jiang, Daqing, 2021. "An HIV latent infection model with cell-to-cell transmission and stochastic perturbation," Chaos, Solitons & Fractals, Elsevier, vol. 151(C).
    14. Dong, Suyalatu & Deng, Yanbin & Huang, Yong-Chang, 2019. "Exact analytic solution to nonlinear dynamic system of equations for information propagation in complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 521(C), pages 319-329.
    15. Ayu Rahayu & Utari Saraswati & Endah Supriyati & Dian Aruni Kumalawati & Rio Hermantara & Anwar Rovik & Edwin Widyanto Daniwijaya & Iva Fitriana & Sigit Setyawan & Riris Andono Ahmad & Dwi Satria Ward, 2019. "Prevalence and Distribution of Dengue Virus in Aedes aegypti in Yogyakarta City before Deployment of Wolbachia Infected Aedes aegypti," IJERPH, MDPI, vol. 16(10), pages 1-12, May.
    16. Gamboa, M. & López-García, M. & Lopez-Herrero, M.J., 2024. "On the exact and population bi-dimensional reproduction numbers in a stochastic SVIR model with imperfect vaccine," Applied Mathematics and Computation, Elsevier, vol. 468(C).
    17. Emmanuelle Sylvestre & Clarisse Joachim & Elsa Cécilia-Joseph & Guillaume Bouzillé & Boris Campillo-Gimenez & Marc Cuggia & André Cabié, 2022. "Data-driven methods for dengue prediction and surveillance using real-world and Big Data: A systematic review," PLOS Neglected Tropical Diseases, Public Library of Science, vol. 16(1), pages 1-22, January.
    18. Ran, Xue & Hu, Lin & Nie, Lin-Fei & Teng, Zhidong, 2021. "Effects of stochastic perturbation and vaccinated age on a vector-borne epidemic model with saturation incidence rate," Applied Mathematics and Computation, Elsevier, vol. 394(C).
    19. Liu, Qun & Jiang, Daqing, 2020. "Threshold behavior in a stochastic SIR epidemic model with Logistic birth," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 540(C).
    20. Yu, Zhenhua & Zhang, Jingmeng & Zhang, Yun & Cong, Xuya & Li, Xiaobo & Mostafa, Almetwally M., 2024. "Mathematical modeling and simulation for COVID-19 with mutant and quarantined strategy," Chaos, Solitons & Fractals, Elsevier, vol. 181(C).

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    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:apmaco:v:338:y:2018:i:c:p:249-259. 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: https://www.journals.elsevier.com/applied-mathematics-and-computation .

    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.