The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
How generation intervals shape the relationship between growth rates and reproductive numbers
Open accessAbstract
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.
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Cited by
Estimated transmissibility and impact of SARS-CoV-2 lineage B.1.1.7 in England
Davies, N. G., Abbott, S., Barnard, R. C., Jarvis, C. I., Kucharski, A. J., Munday, J. D., Pearson, C. A. B., Russell, T. W., Tully, D. C., Washburne, A. D., et al. (2021) · Science · doi:10.1126/science.abg3055 · Cited by 2,581
“116) 50 (47-52) 85 (81-90) UK sequence separate-slopes multinomial spline model REGION * ns(DATE, df=2) a UK B.”
BackgroundInfluentialProjecting the transmission dynamics of SARS-CoV-2 through the postpandemic period
Kissler, S. M., Tedijanto, C., Goldstein, E., Grad, Y. H., & Lipsitch, M. (2020) · Science · doi:10.1126/science.abb5793 · Cited by 2,611
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Assessing transmissibility of SARS-CoV-2 lineage B.1.1.7 in England
The COVID-19 Genomics UK (COG-UK) consortium, Volz, E., Mishra, S., Chand, M., Barrett, J. C., Johnson, R., Geidelberg, L., Hinsley, W. R., Laydon, D. J., Dabrera, G., et al. (2021) · Nature · doi:10.1038/s41586-021-03470-x · Cited by 1,611
Markov, P. V., Ghafari, M., Beer, M., Lythgoe, K., Simmonds, P., Stilianakis, N. I., & Katzourakis, A. (2023) · Nature Reviews Microbiology · doi:10.1038/s41579-023-00878-2 · Cited by 1,179
Metadata
- Authors
- Wallinga, J., & Lipsitch, M.
- Venue
- Proceedings of the Royal Society B: Biological Sciences
- Publisher
- The Royal Society
- Published
- 2006-11-28
- Volume
- 274
- Issue
- 1609
- Pages
- 599-604
- ISSN
- 0080-4649 (ISSN-L)
- 0962-8452
- 1471-2954
- OpenAlex
- W2117002055
- Cited by
- 1,213
- References
- 1
- FWCI
- 19.58
- Type
- journal article
- Language
- en
- Open access
- green
- Licence
- royalsociety.org/journals/ethics-policies/data-sharing-mining/ (tdm)
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