IDEAS home Printed from https://ideas.repec.org/a/eee/thpobi/v119y2018icp26-36.html
   My bibliography  Save this article

Estimating the basic reproductive number during the early stages of an emerging epidemic

Author

Listed:
  • Rebuli, Nicolas P.
  • Bean, N.G.
  • Ross, J.V.

Abstract

A novel outbreak will generally not be detected until such a time that it has become established. When such an outbreak is detected, public health officials must determine the potential of the outbreak, for which the basic reproductive numberR0 is an important factor. However, it is often the case that the resulting estimate of R0 is positively-biased for a number of reasons. One commonly overlooked reason is that the outbreak was not detected until such a time that it had become established, and therefore did not experience initial fade out. We propose a method which accounts for this bias by conditioning the underlying epidemic model on becoming established and demonstrate that this approach leads to a less-biased estimate of R0 during the early stages of an outbreak. We also present a computationally-efficient approximation scheme which is suitable for large data sets in which the number of notified cases is large. This methodology is applied to an outbreak of pandemic influenza in Western Australia, recorded in 2009.

Suggested Citation

  • Rebuli, Nicolas P. & Bean, N.G. & Ross, J.V., 2018. "Estimating the basic reproductive number during the early stages of an emerging epidemic," Theoretical Population Biology, Elsevier, vol. 119(C), pages 26-36.
    • Handle: RePEc:eee:thpobi:v:119:y:2018:i:c:p:26-36
    DOI: 10.1016/j.tpb.2017.10.004
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0040580917300114
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.tpb.2017.10.004?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. Simonsen, L. & Clarke, M.J. & Williamson, G.D. & Stroup, D.F. & Arden, N.H. & Schonberger, L.B., 1997. "The impact of influenza epidemics on mortality: Introducing a severity index," American Journal of Public Health, American Public Health Association, vol. 87(12), pages 1944-1950.
    2. Ross, J.V., 2012. "On parameter estimation in population models III: Time-inhomogeneous processes and observation error," Theoretical Population Biology, Elsevier, vol. 82(1), pages 1-17.
    3. Ross, J.V. & Pagendam, D.E. & Pollett, P.K., 2009. "On parameter estimation in population models II: Multi-dimensional processes and transient dynamics," Theoretical Population Biology, Elsevier, vol. 75(2), pages 123-132.
    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. Grass, D. & Wrzaczek, S. & Caulkins, J.P. & Feichtinger, G. & Hartl, R.F. & Kort, P.M. & Kuhn, M. & Prskawetz, A. & Sanchez-Romero, M. & Seidl, A., 2024. "Riding the waves from epidemic to endemic: Viral mutations, immunological change and policy responses," Theoretical Population Biology, Elsevier, vol. 156(C), pages 46-65.

    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. Xiaoli Wang & Shuangsheng Wu & C Raina MacIntyre & Hongbin Zhang & Weixian Shi & Xiaomin Peng & Wei Duan & Peng Yang & Yi Zhang & Quanyi Wang, 2015. "Using an Adjusted Serfling Regression Model to Improve the Early Warning at the Arrival of Peak Timing of Influenza in Beijing," PLOS ONE, Public Library of Science, vol. 10(3), pages 1-14, March.
    2. Arthi, Vellore & Parman, John, 2021. "Disease, downturns, and wellbeing: Economic history and the long-run impacts of COVID-19," Explorations in Economic History, Elsevier, vol. 79(C).
    3. 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).
    4. Christian H. Weiß & Philip K. Pollett, 2012. "Chain Binomial Models and Binomial Autoregressive Processes," Biometrics, The International Biometric Society, vol. 68(3), pages 815-824, September.
    5. Artalejo, J.R. & Lopez-Herrero, M.J., 2011. "The SIS and SIR stochastic epidemic models: A maximum entropy approach," Theoretical Population Biology, Elsevier, vol. 80(4), pages 256-264.
    6. Alex Huynh & Aaron Bruhn & Bridget Browne, 2013. "A Review of Catastrophic Risks for Life Insurers," Risk Management and Insurance Review, American Risk and Insurance Association, vol. 16(2), pages 233-266, September.
    7. Julia B Wenger & Elena N Naumova, 2010. "Seasonal Synchronization of Influenza in the United States Older Adult Population," PLOS ONE, Public Library of Science, vol. 5(4), pages 1-11, April.
    8. Campillo, F. & Joannides, M. & Larramendy-Valverde, I., 2011. "Stochastic modeling of the chemostat," Ecological Modelling, Elsevier, vol. 222(15), pages 2676-2689.
    9. Ross, J.V., 2012. "On parameter estimation in population models III: Time-inhomogeneous processes and observation error," Theoretical Population Biology, Elsevier, vol. 82(1), pages 1-17.
    10. Maria Mavrouli & Spyridon Mavroulis & Efthymios Lekkas & Athanassios Tsakris, 2021. "Respiratory Infections Following Earthquake-Induced Tsunamis: Transmission Risk Factors and Lessons Learned for Disaster Risk Management," IJERPH, MDPI, vol. 18(9), pages 1-18, May.
    11. David Wilson & Rosemary Lester & Anne Taylor & Tiffany Gill & Eleonora Grande & John Litt & Ann Kempe & Margaret Campbell & Nan Miller & Gay Rixon & Jo Schell & Brenda White & Sandra Klason, 2002. "Prevalence of influenza immunisation in Australia and suggestions for future targeting of campaigns," International Journal of Public Health, Springer;Swiss School of Public Health (SSPH+), vol. 47(2), pages 91-99, March.
    12. Ka Chun Chong & William Goggins & Benny Chung Ying Zee & Maggie Haitian Wang, 2015. "Identifying Meteorological Drivers for the Seasonal Variations of Influenza Infections in a Subtropical City — Hong Kong," IJERPH, MDPI, vol. 12(2), pages 1-17, January.
    13. Jonathan Fintzi & Jon Wakefield & Vladimir N. Minin, 2022. "A linear noise approximation for stochastic epidemic models fit to partially observed incidence counts," Biometrics, The International Biometric Society, vol. 78(4), pages 1530-1541, December.
    14. Enrique Acosta & Stacey A. Hallman & Lisa Y. Dillon & Nadine Ouellette & Robert Bourbeau & D. Ann Herring & Kris Inwood & David J. D. Earn & Joaquin Madrenas & Matthew S. Miller & Alain Gagnon, 2019. "Determinants of Influenza Mortality Trends: Age-Period-Cohort Analysis of Influenza Mortality in the United States, 1959–2016," Demography, Springer;Population Association of America (PAA), vol. 56(5), pages 1723-1746, October.
    15. Keeling, M.J. & Ross, J.V., 2009. "Efficient methods for studying stochastic disease and population dynamics," Theoretical Population Biology, Elsevier, vol. 75(2), pages 133-141.

    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:thpobi:v:119:y:2018:i:c:p:26-36. 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/intelligence .

    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.