The DOI matches its Crossref record; 6 of the 6 references it cites were found in a registry or an index.
The construction of next-generation matrices for compartmental epidemic models
Open accessAbstract
The basic reproduction number ℛ 0 is arguably the most important quantity in infectious disease epidemiology. The next-generation matrix (NGM) is the natural basis for the definition and calculation of ℛ 0 where finitely many different categories of individuals are recognized. We clear up confusion that has been around in the literature concerning the construction of this matrix, specifically for the most frequently used so-called compartmental models. We present a detailed easy recipe for the construction of the NGM from basic ingredients derived directly from the specifications of the model. We show that two related matrices exist which we define to be the NGM with large domain and the NGM with small domain . The three matrices together reflect the range of possibilities encountered in the literature for the characterization of ℛ 0 . We show how they are connected and how their construction follows from the basic model ingredients, and establish that they have the same non-zero eigenvalues, the largest of which is the basic reproduction number ℛ 0 . Although we present formal recipes based on linear algebra, we encourage the construction of the NGM by way of direct epidemiological reasoning, using the clear interpretation of the elements of the NGM and of the model ingredients. We present a selection of examples as a practical guide to our methods. In the appendix we present an elementary but complete proof that ℛ 0 defined as the dominant eigenvalue of the NGM for compartmental systems and the Malthusian parameter r , the real-time exponential growth rate in the early phase of an outbreak, are connected by the properties that ℛ 0 > 1 if and only if r > 0, and ℛ 0 = 1 if and only if r = 0.
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Cites
van den Driessche, P., & Watmough, J. (2002) · Mathematical Biosciences · doi:10.1016/s0025-5564(02)00108-6 · Cited by 9,977
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Self-citationMathematical Epidemiology of Infectious Diseases: Model Building, Analysis and Interpretation
Diekmann, O., & Heesterbeek, H. (2000) · Socio-Environmental Systems Modeling · Cited by 1,833
Self-citationMathematical Epidemiology of Infectious Diseases: Model Building, Analysis and Interpretation
Roddam, A. W. (2001) · International Journal of Epidemiology · doi:10.1093/ije/30.1.186 · Cited by 1,443
Thieme, H. R. (2009) · SIAM Journal on Applied Mathematics · doi:10.1137/080732870 · Cited by 594
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Cited by
Li, R., Pei, S., Chen, B., Song, Y., Zhang, T., Yang, W., & Shaman, J. (2020) · Science · doi:10.1126/science.abb3221 · Cited by 3,633
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Gatto, M., Bertuzzo, E., Mari, L., Miccoli, S., Carraro, L., Casagrandi, R., & Rinaldo, A. (2020) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2004978117 · Cited by 1,051
Quantifying the impact of physical distance measures on the transmission of COVID-19 in the UK
CMMID COVID-19 working group, Jarvis, C. I., Van Zandvoort, K., Gimma, A., Prem, K., Klepac, P., Rubin, G. J., & Edmunds, W. J. (2020) · BMC Medicine · doi:10.1186/s12916-020-01597-8 · Cited by 720
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(2020) · doi:10.1126/sciadv.abd6370 · Cited by 366
Shocket, M. S., Verwillow, A. B., Numazu, M. G., Slamani, H., Cohen, J. M., El Moustaid, F., Rohr, J., Johnson, L. R., & Mordecai, E. A. (2020) · eLife · doi:10.7554/elife.58511 · Cited by 192
Metadata
- Authors
- Diekmann, O., Heesterbeek, J. A. P., & Roberts, M. G.
- Venue
- Journal of The Royal Society Interface
- Publisher
- The Royal Society
- Published
- 2009-11-05
- Volume
- 7
- Issue
- 47
- Pages
- 873-885
- ISSN
- 1742-5662 (ISSN-L)
- 1742-5689
- OpenAlex
- W2113797309
- Cited by
- 2,119
- References
- 6
- FWCI
- 16.06
- Type
- journal article
- Language
- en
- Open access
- green
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