How generation intervals shape the relationship between growth rates and reproductive numbers

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  • J Wallinga
    Department of Infectious Diseases Epidemiology, National Institute of Public Health and the EnvironmentPO Box 1, 3720 BA Bilthoven, The Netherlands
  • M Lipsitch
    Department of Epidemiology and Department of Immunology and Infectious Diseases, Harvard School of Public Health677 Huntington Avenue, Boston, MA 02115, USA

書誌事項

公開日
2006-11-28
権利情報
  • https://royalsociety.org/journals/ethics-policies/data-sharing-mining/
DOI
  • 10.1098/rspb.2006.3754
公開者
The Royal Society

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説明

<jats:p> Mathematical models of transmission have become invaluable management tools in planning for the control of emerging infectious diseases. A key variable in such models is the reproductive number <jats:italic>R</jats:italic> . For new emerging infectious diseases, the value of the reproductive number can only be inferred indirectly from the observed exponential epidemic growth rate <jats:italic>r</jats:italic> . Such inference is ambiguous as several different equations exist that relate the reproductive number to the growth rate, and it is unclear which of these equations might apply to a new infection. Here, we show that these different equations differ only with respect to their assumed shape of the generation interval distribution. Therefore, the shape of the generation interval distribution determines which equation is appropriate for inferring the reproductive number from the observed growth rate. We show that by assuming all generation intervals to be equal to the mean, we obtain an upper bound to the range of possible values that the reproductive number may attain for a given growth rate. Furthermore, we show that by taking the generation interval distribution equal to the observed distribution, it is possible to obtain an empirical estimate of the reproductive number. </jats:p>

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