IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0002185.html
   My bibliography  Save this article

Real Time Bayesian Estimation of the Epidemic Potential of Emerging Infectious Diseases

Author

Listed:
  • Luís M A Bettencourt
  • Ruy M Ribeiro

Abstract

Background: Fast changes in human demographics worldwide, coupled with increased mobility, and modified land uses make the threat of emerging infectious diseases increasingly important. Currently there is worldwide alert for H5N1 avian influenza becoming as transmissible in humans as seasonal influenza, and potentially causing a pandemic of unprecedented proportions. Here we show how epidemiological surveillance data for emerging infectious diseases can be interpreted in real time to assess changes in transmissibility with quantified uncertainty, and to perform running time predictions of new cases and guide logistics allocations. Methodology/Principal Findings: We develop an extension of standard epidemiological models, appropriate for emerging infectious diseases, that describes the probabilistic progression of case numbers due to the concurrent effects of (incipient) human transmission and multiple introductions from a reservoir. The model is cast in terms of surveillance observables and immediately suggests a simple graphical estimation procedure for the effective reproductive number R (mean number of cases generated by an infectious individual) of standard epidemics. For emerging infectious diseases, which typically show large relative case number fluctuations over time, we develop a Bayesian scheme for real time estimation of the probability distribution of the effective reproduction number and show how to use such inferences to formulate significance tests on future epidemiological observations. Conclusions/Significance: Violations of these significance tests define statistical anomalies that may signal changes in the epidemiology of emerging diseases and should trigger further field investigation. We apply the methodology to case data from World Health Organization reports to place bounds on the current transmissibility of H5N1 influenza in humans and establish a statistical basis for monitoring its evolution in real time.

Suggested Citation

  • Luís M A Bettencourt & Ruy M Ribeiro, 2008. "Real Time Bayesian Estimation of the Epidemic Potential of Emerging Infectious Diseases," PLOS ONE, Public Library of Science, vol. 3(5), pages 1-9, May.
    • Handle: RePEc:plo:pone00:0002185
    DOI: 10.1371/journal.pone.0002185
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0002185
    Download Restriction: no
    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0002185&type=printable
    Download Restriction: no
    File URL: https://libkey.io/10.1371/journal.pone.0002185?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
    ---><---

    References listed on IDEAS

    as
    1. Alison Abbott & Helen Pearson, 2004. "Fear of human pandemic grows as bird flu sweeps through Asia," Nature, Nature, vol. 427(6974), pages 472-473, February.
    2. H. Chen & G. J. D. Smith & S. Y. Zhang & K. Qin & J. Wang & K. S. Li & R. G. Webster & J. S. M. Peiris & Y. Guan, 2005. "H5N1 virus outbreak in migratory waterfowl," Nature, Nature, vol. 436(7048), pages 191-192, July.
    3. Anthony S. Fauci, 2005. "Race against time," Nature, Nature, vol. 435(7041), pages 423-424, May.
    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. Kernel Prieto & M Victoria Chávez–Hernández & Jhoana P Romero–Leiton, 2022. "On mobility trends analysis of COVID–19 dissemination in Mexico City," PLOS ONE, Public Library of Science, vol. 17(2), pages 1-25, February.
    2. Anup Malani & Satej Soman & Sabareesh Ramachandran & Alice Chen & Darius N. Lakdawalla, 2022. "Vaccine Allocation Priorities Using Disease Surveillance and Economic Data," NBER Working Papers 29682, National Bureau of Economic Research, Inc.
    3. Chad Cotti & Bryan Engelhardt & Joshua Foster & Erik Nesson & Paul Niekamp, 2021. "The relationship between in‐person voting and COVID‐19: Evidence from the Wisconsin primary," Contemporary Economic Policy, Western Economic Association International, vol. 39(4), pages 760-777, October.
    4. Ida Johnsson & M. Hashem Pesaran & Cynthia Fan Yang, 2023. "Structural Econometric Estimation of the Basic Reproduction Number for Covid-19 across U.S. States and Selected Countries," CESifo Working Paper Series 10659, CESifo.
    5. Imelda Trejo & Nicolas W Hengartner, 2022. "A modified Susceptible-Infected-Recovered model for observed under-reported incidence data," PLOS ONE, Public Library of Science, vol. 17(2), pages 1-23, February.
    6. Singh, Anurag & Arquam, Md, 2022. "Epidemiological modeling for COVID-19 spread in India with the effect of testing," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 592(C).
    7. Christoph Zimmer & Reza Yaesoubi & Ted Cohen, 2017. "A Likelihood Approach for Real-Time Calibration of Stochastic Compartmental Epidemic Models," PLOS Computational Biology, Public Library of Science, vol. 13(1), pages 1-21, January.
    8. Victor W. Chu & Raymond K. Wong & Chi-Hung Chi & Wei Zhou & Ivan Ho, 2017. "The design of a cloud-based tracker platform based on system-of-systems service architecture," Information Systems Frontiers, Springer, vol. 19(6), pages 1283-1299, December.
    9. De Simone, Andrea & Piangerelli, Marco, 2020. "A Bayesian approach for monitoring epidemics in presence of undetected cases," Chaos, Solitons & Fractals, Elsevier, vol. 140(C).
    10. Kernel Prieto, 2022. "Current forecast of COVID-19 in Mexico: A Bayesian and machine learning approaches," PLOS ONE, Public Library of Science, vol. 17(1), pages 1-21, January.
    11. Sean ELLIOTT & Christian GOURIEROUX, 2020. "Uncertainty on the Reproduction Ratio in the SIR Model," Working Papers 2020-31, Center for Research in Economics and Statistics.
    12. Schimit, P.H.T. & Monteiro, L.H.A., 2012. "On estimating the basic reproduction number in distinct stages of a contagious disease spreading," Ecological Modelling, Elsevier, vol. 240(C), pages 156-160.
    13. Maeno, Yoshiharu, 2016. "Detecting a trend change in cross-border epidemic transmission," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 457(C), pages 73-81.
    14. Adam Brzezinski & David Van Dijcke & Valentin Kecht, 2020. "The Cost of Staying Open: Voluntary Social Distancing and Lockdowns in the US," Economics Series Working Papers 910, University of Oxford, Department of Economics.
    15. Bo Huang & Zhihui Huang & Chen Chen & Jian Lin & Tony Tam & Yingyi Hong & Sen Pei, 2022. "Social vulnerability amplifies the disparate impact of mobility on COVID-19 transmissibility across the United States," Palgrave Communications, Palgrave Macmillan, vol. 9(1), pages 1-13, December.
    16. Kyle S Hickmann & Geoffrey Fairchild & Reid Priedhorsky & Nicholas Generous & James M Hyman & Alina Deshpande & Sara Y Del Valle, 2015. "Forecasting the 2013–2014 Influenza Season Using Wikipedia," PLOS Computational Biology, Public Library of Science, vol. 11(5), pages 1-29, May.
    17. Mostafa Adimy & Julien Molina & Laurent Pujo-Menjouet & Grégoire Ranson & Jianhong Wu, 2022. "Forecasting the Effect of Pre-Exposure Prophylaxis (PrEP) on HIV Propagation with a System of Differential–Difference Equations with Delay," Mathematics, MDPI, vol. 10(21), pages 1-24, November.
    18. Flávio Codeço Coelho & Cláudia Torres Codeço & M Gabriela M Gomes, 2011. "A Bayesian Framework for Parameter Estimation in Dynamical Models," PLOS ONE, Public Library of Science, vol. 6(5), pages 1-6, May.
    19. Kris V. Parag & Robin N. Thompson & Christl A. Donnelly, 2022. "Are epidemic growth rates more informative than reproduction numbers?," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 185(S1), pages 5-15, November.
    20. José Ulises Márquez Urbina & Graciela González Farías & L Leticia Ramírez Ramírez & D Iván Rodríguez González, 2022. "A multi-source global-local model for epidemic management," PLOS ONE, Public Library of Science, vol. 17(1), pages 1-26, January.
    21. Fajar, Muhammad, 2020. "Estimasi angka reproduksi Novel Coronavirus (COVID-19), Kasus Indonesia (Estimation of COVID-19 reproductive number, case of Indonesia [Estimation Of Covid-19 Reproductive Number (Case Of Indonesia," MPRA Paper 105099, University Library of Munich, Germany, revised 28 Mar 2020.
    22. 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.
    23. Sean Elliott & Christian Gourieroux, 2020. "Uncertainty on the Reproduction Ratio in the SIR Model," Papers 2012.11542, arXiv.org.
    24. Anup Malani & Satej Soman & Sam Asher & Paul Novosad & Clement Imbert & Vaidehi Tandel & Anish Agarwal & Abdullah Alomar & Arnab Sarker & Devavrat Shah & Dennis Shen & Jonathan Gruber & Stuti Sachdeva, 2020. "Adaptive Control of COVID-19 Outbreaks in India: Local, Gradual, and Trigger-based Exit Paths from Lockdown," NBER Working Papers 27532, National Bureau of Economic Research, Inc.
    25. Jean-Paul Renne & Guillaume Roussellet & Gustavo Schwenkler, 2020. "Preventing COVID-19 Fatalities: State versus Federal Policies," Papers 2010.15263, arXiv.org, revised Dec 2020.

    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, Yan & Chen, Shihua & Gao, Shujing & Fan, Kuangang & Wang, Qingyun, 2017. "A new non-autonomous model for migratory birds with Leslie–Gower Holling-type II schemes and saturation recovery rate," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 132(C), pages 289-306.
    2. Samuel S Shepard & C Todd Davis & Justin Bahl & Pierre Rivailler & Ian A York & Ruben O Donis, 2014. "LABEL: Fast and Accurate Lineage Assignment with Assessment of H5N1 and H9N2 Influenza A Hemagglutinins," PLOS ONE, Public Library of Science, vol. 9(1), pages 1-12, January.
    3. Marcello Basili & Mauriziop Franzini, 2005. "The Avian Flu Disease: A Case of Precautionary Failure," Department of Economics University of Siena 454, Department of Economics, University of Siena.
    4. Marcello Basili & Maurizio Franzini, 2006. "Understanding the Risk of an Avian Flu Pandemic: Rational Waiting or Precautionary Failure?," Risk Analysis, John Wiley & Sons, vol. 26(3), pages 617-630, June.
    5. Tian, Huaiyu & Zhou, Sen & Dong, Lu & Van Boeckel, Thomas P. & Pei, Yao & Wu, Qizhong & Yuan, Wenping & Guo, Yan & Huang, Shanqian & Chen, Wenhuan & Lu, Xueliang & Liu, Zhen & Bai, Yuqi & Yue, Tianxia, 2015. "Climate change suggests a shift of H5N1 risk in migratory birds," Ecological Modelling, Elsevier, vol. 306(C), pages 6-15.

    More about this item

    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:plo:pone00:0002185. 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: plosone (email available below). General contact details of provider: https://journals.plos.org/plosone/ .

    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.