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A Note on Observation Processes in Epidemic Models

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Abstract

Many disease models focus on characterizing the underlying transmission mechanism but make simple, possibly naive assumptions about how infections are reported. In this note, we use a simple deterministic Susceptible-Infected-Removed (SIR) model to compare two common assumptions about disease incidence reports: Individuals can report their infection as soon as they become infected or as soon as they recover. We show that incorrect assumptions about the underlying observation processes can bias estimates of the basic reproduction number and lead to overly narrow confidence intervals.

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Acknowledgements

We thank David Earn for providing helpful comments on the manuscript. BMB is supported by an NSERC Discovery grant.

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Authors and Affiliations

  1. Department of Ecology and Evolutionary Biology, Princeton University, Princeton, NJ, USA

    Sang Woo Park

  2. Department of Mathematics and Statistics, McMaster University, Hamilton, ON, Canada

    Sang Woo Park & Benjamin M. Bolker

  3. Department of Biology, McMaster University, Hamilton, ON, Canada

    Benjamin M. Bolker

  4. Michael G. DeGroote Institute for Infectious Disease Research, McMaster University, Hamilton, ON, Canada

    Benjamin M. Bolker

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  1. Sang Woo Park
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  2. Benjamin M. Bolker
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Correspondence to Sang Woo Park.

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Park, S.W., Bolker, B.M. A Note on Observation Processes in Epidemic Models. Bull Math Biol 82, 37 (2020). https://doi.org/10.1007/s11538-020-00713-2

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