IDEAS home Printed from https://ideas.repec.org/a/taf/mpopst/v17y2010i2p101-111.html
   My bibliography  Save this article

Bayesian Melding Estimation of a Stochastic SEIR Model

Author

Listed:
  • LUIZ HOTTA

Abstract

One of the main problems in estimating stochastic SEIR models is that the data are not completely observed. In this case, the estimation is usually done by least squares or by MCMC. The Bayesian melding method is proposed to estimate SEIR models and to evaluate the likelihood in the presence of incomplete data. The method is illustrated by estimating a model for HIV/TB interaction in the population of a prison.

Suggested Citation

  • Luiz Hotta, 2010. "Bayesian Melding Estimation of a Stochastic SEIR Model," Mathematical Population Studies, Taylor & Francis Journals, vol. 17(2), pages 101-111.
    • Handle: RePEc:taf:mpopst:v:17:y:2010:i:2:p:101-111
    DOI: 10.1080/08898481003689528
    as

    Download full text from publisher

    File URL: http://www.tandfonline.com/doi/abs/10.1080/08898481003689528
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1080/08898481003689528?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. Phenyo E. Lekone & Bärbel F. Finkenstädt, 2006. "Statistical Inference in a Stochastic Epidemic SEIR Model with Control Intervention: Ebola as a Case Study," Biometrics, The International Biometric Society, vol. 62(4), pages 1170-1177, December.
    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. Artalejo, J.R. & Economou, A. & Lopez-Herrero, M.J., 2015. "The stochastic SEIR model before extinction: Computational approaches," Applied Mathematics and Computation, Elsevier, vol. 265(C), pages 1026-1043.

    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. Kamara, Abdul A. & Wang, Xiangjun & Mouanguissa, Lagès Nadège, 2020. "Analytical solution for post-death transmission model of Ebola epidemics," Applied Mathematics and Computation, Elsevier, vol. 367(C).
    2. 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.
    3. Erik Pruyt & Willem L. Auping & Jan H. Kwakkel, 2015. "Ebola in West Africa: Model-Based Exploration of Social Psychological Effects and Interventions," Systems Research and Behavioral Science, Wiley Blackwell, vol. 32(1), pages 2-14, January.
    4. Robin N Thompson & Christopher A Gilligan & Nik J Cunniffe, 2016. "Detecting Presymptomatic Infection Is Necessary to Forecast Major Epidemics in the Earliest Stages of Infectious Disease Outbreaks," PLOS Computational Biology, Public Library of Science, vol. 12(4), pages 1-18, April.
    5. Maria Vittoria Barbarossa & Attila Dénes & Gábor Kiss & Yukihiko Nakata & Gergely Röst & Zsolt Vizi, 2015. "Transmission Dynamics and Final Epidemic Size of Ebola Virus Disease Outbreaks with Varying Interventions," PLOS ONE, Public Library of Science, vol. 10(7), pages 1-21, July.
    6. Attar, M. Aykut & Tekin-Koru, Ayça, 2022. "Latent social distancing: Identification, causes and consequences," Economic Systems, Elsevier, vol. 46(1).
    7. Leigh Fisher & Jon Wakefield & Cici Bauer & Steve Self, 2017. "Time series modeling of pathogen-specific disease probabilities with subsampled data," Biometrics, The International Biometric Society, vol. 73(1), pages 283-293, March.
    8. Dongya Liu & Xinqi Zheng & Lei Zhang, 2021. "Simulation of Spatiotemporal Relationship between COVID-19 Propagation and Regional Economic Development in China," Land, MDPI, vol. 10(6), pages 1-15, June.
    9. Marie V. Ozanne & Grant D. Brown & Angela J. Toepp & Breanna M. Scorza & Jacob J. Oleson & Mary E. Wilson & Christine A. Petersen, 2020. "Bayesian compartmental models and associated reproductive numbers for an infection with multiple transmission modes," Biometrics, The International Biometric Society, vol. 76(3), pages 711-721, September.
    10. Carbone, Giuseppe & De Vincenzo, Ilario, 2022. "A general theory for infectious disease dynamics," Chaos, Solitons & Fractals, Elsevier, vol. 165(P2).
    11. Ghufran Ahmad & Furqan Ahmed & Muhammad Suhail Rizwan & Javed Muhammad & Syeda Hira Fatima & Aamer Ikram & Hajo Zeeb, 2021. "Evaluating data-driven methods for short-term forecasts of cumulative SARS-CoV2 cases," PLOS ONE, Public Library of Science, vol. 16(5), pages 1-21, May.
    12. Noureddine Ouerfelli & Narcisa Vrinceanu & Diana Coman & Adriana Lavinia Cioca, 2022. "Empirical Modeling of COVID-19 Evolution with High/Direct Impact on Public Health and Risk Assessment," IJERPH, MDPI, vol. 19(6), pages 1-13, March.
    13. Ndaïrou, Faïçal & Khalighi, Moein & Lahti, Leo, 2023. "Ebola epidemic model with dynamic population and memory," Chaos, Solitons & Fractals, Elsevier, vol. 170(C).
    14. Aaron T. Porter & Jacob J. Oleson, 2013. "A Path-Specific SEIR Model for use with General Latent and Infectious Time Distributions," Biometrics, The International Biometric Society, vol. 69(1), pages 101-108, March.
    15. Qingqing Ji & Xu Zhao & Hanlin Ma & Qing Liu & Yiwen Liu & Qiyue Guan, 2021. "Estimation of COVID-19 Transmission and Advice on Public Health Interventions," Mathematics, MDPI, vol. 9(22), pages 1-18, November.
    16. Ben Balmford & James D. Annan & Julia C. Hargreaves & Marina Altoè & Ian J. Bateman, 2020. "Cross-Country Comparisons of Covid-19: Policy, Politics and the Price of Life," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 76(4), pages 525-551, August.
    17. McKinley Trevelyan & Cook Alex R & Deardon Robert, 2009. "Inference in Epidemic Models without Likelihoods," The International Journal of Biostatistics, De Gruyter, vol. 5(1), pages 1-40, July.
    18. Lu Tang & Yiwang Zhou & Lili Wang & Soumik Purkayastha & Leyao Zhang & Jie He & Fei Wang & Peter X.‐K. Song, 2020. "A Review of Multi‐Compartment Infectious Disease Models," International Statistical Review, International Statistical Institute, vol. 88(2), pages 462-513, August.
    19. Jianbin Tan & Ye Shen & Yang Ge & Leonardo Martinez & Hui Huang, 2023. "Age‐related model for estimating the symptomatic and asymptomatic transmissibility of COVID‐19 patients," Biometrics, The International Biometric Society, vol. 79(3), pages 2525-2536, September.
    20. Ndanguza, Denis & Mbalawata, Isambi S. & Haario, Heikki & Tchuenche, Jean M., 2017. "Analysis of bias in an Ebola epidemic model by extended Kalman filter approach," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 142(C), pages 113-129.

    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:taf:mpopst:v:17:y:2010:i:2:p:101-111. 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: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/GMPS20 .

    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.