In epidemiology, the next-generation matrix is used to derive the basic reproduction number, for a compartmental model of the spread of infectious diseases. In population dynamics it is used to compute the basic reproduction number for structured population models.[1] It is also used in multi-type branching models for analogous computations.[2]
The method to compute the basic reproduction ratio using the next-generation matrix is given by Diekmann et al. (1990)[3] and van den Driessche and Watmough (2002).[4] To calculate the basic reproduction number by using a next-generation matrix, the whole population is divided into compartments in which there are infected compartments. Let be the numbers of infected individuals in the infected compartment at time t. Now, the epidemic model is[citation needed]
- , where
In the above equations, represents the rate of appearance of new infections in compartment . represents the rate of transfer of individuals into compartment by all other means, and represents the rate of transfer of individuals out of compartment . The above model can also be written as
where
and
Let be the disease-free equilibrium. The values of the parts of the Jacobian matrix and are:
and
respectively.
Here, and are m × m matrices, defined as and .
Now, the matrix is known as the next-generation matrix. The basic reproduction number of the model is then given by the eigenvalue of with the largest absolute value (the spectral radius of ). Next generation matrices can be computationally evaluated from observational data, which is often the most productive approach where there are large numbers of compartments.[5]
See also
editReferences
edit- ^ Zhao, Xiao-Qiang (2017), "The Theory of Basic Reproduction Ratios", Dynamical Systems in Population Biology, CMS Books in Mathematics, Springer International Publishing, pp. 285–315, doi:10.1007/978-3-319-56433-3_11, ISBN 978-3-319-56432-6
- ^ Mode, Charles J., 1927- (1971). Multitype branching processes; theory and applications. New York: American Elsevier Pub. Co. ISBN 0-444-00086-0. OCLC 120182.
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: CS1 maint: multiple names: authors list (link) CS1 maint: numeric names: authors list (link) - ^ Diekmann, O.; Heesterbeek, J. A. P.; Metz, J. A. J. (1990). "On the definition and the computation of the basic reproduction ratio R0 in models for infectious diseases in heterogeneous populations". Journal of Mathematical Biology. 28 (4): 365–382. doi:10.1007/BF00178324. hdl:1874/8051. PMID 2117040. S2CID 22275430.
- ^ van den Driessche, P.; Watmough, J. (2002). "Reproduction numbers and sub-threshold endemic equilibria for compartmental models of disease transmission". Mathematical Biosciences. 180 (1–2): 29–48. doi:10.1016/S0025-5564(02)00108-6. PMID 12387915. S2CID 17313221.
- ^ von Csefalvay, Chris (2023), "Simple compartmental models", Computational Modeling of Infectious Disease, Elsevier, pp. 19–91, doi:10.1016/b978-0-32-395389-4.00011-6, ISBN 978-0-323-95389-4, retrieved 2023-02-28
Sources
edit- Ma, Zhien; Li, Jia (2009). Dynamical Modeling and analysis of Epidemics. World Scientific. ISBN 978-981-279-749-0. OCLC 225820441.
- Diekmann, O.; Heesterbeek, J. A. P. (2000). Mathematical Epidemiology of Infectious Disease. John Wiley & Son.
- Heffernan, J. M.; Smith, R. J.; Wahl, L. M. (2005). "Perspectives on the basic reproductive ratio". J. R. Soc. Interface. 2 (4): 281–93. doi:10.1098/rsif.2005.0042. PMC 1578275. PMID 16849186.