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

Author

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  • 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
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    References listed on IDEAS

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    1. 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.
    2. 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.
    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.
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