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

Proceedings of the Royal Society B Biological Sciences · 2006 · Vol. 274(1609) · pp. 599–604
Jacco WallingaMarc Lipsitch

Abstract

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 R. For new emerging infectious diseases, the value of the reproductive number can only be inferred indirectly from the observed exponential epidemic growth rate r. 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.

COVID-19 epidemiological studiesMathematical and Theoretical Epidemiology and Ecology ModelsEvolution and Genetic DynamicsGeneration timeInterval (graph theory)MathematicsStatisticsBasic reproduction numberGrowth rateDistribution (mathematics)Exponential growthExponential distributionApplied mathematics

MeSH terms

Disease OutbreaksHumansInfluenza, HumanModels, BiologicalCohort Effect

Funding

  • National Institute of General Medical Sciences
Citations
1,388
FWCI
13.69
field-weighted impact
References
28
Percentile
99%
vs. same field & year
Citations per year
References
Infectious Diseases of Humans: Dynamics and Control
Annals of Internal Medicine · 1992 · 8,011 citations
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