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SIR Model


An SIR model is a compartmental epidemiological model for the time evolution of a closed population divided into susceptible people S(t), infectious people I(t), and removed people R(t). Depending on the model, removed people may have recovered with immunity, been isolated, or died. One of the simplest SIR models is the Kermack-McKendrick model.

A common generalization allows the transmission and removal rates to vary with time, giving

(dS)/(dt)=-beta(t)SI
(1)
(dI)/(dt)=beta(t)SI-gamma(t)I
(2)
(dR)/(dt)=gamma(t)I.
(3)

Since the three derivatives sum to 0, the total population is conserved,

 S(t)+I(t)+R(t)=N.
(4)

Estimating the functions beta(t) and gamma(t) from observations of S(t) and I(t) is a coefficient-identification inverse problem (Marinov et al. 2014, Marinov and Marinova 2020).

An intervention can be modeled by replacing beta(t) with (1-u(t))beta(t), where the control u(t) takes values between 0 and 1. For the constant-rate SIR model with S(0),I(0)>0, Britton and Leskelä (2023) proved that among piecewise continuous controls satisfying int_0^inftyu(t)dt<=c_1 and 0<=u(t)<=c_infty, where c_1>0 and 0<c_infty<=1, total incidence (the fraction of initially susceptible people eventually infected) is minimized by applying the maximum control c_infty on one interval of length c_1/c_infty. The optimal starting time is unique.

The Season 1 episode "Vector" (2005) of the television crime drama NUMB3RS features SIR models.


See also

Control Theory, Inverse Problem, Kermack-McKendrick Model

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References

Britton, T. and Leskelä, L. "Optimal Intervention Strategies for Minimizing Total Incidence During an Epidemic." SIAM J. Appl. Math. 83, 354-373, 2023. https://doi.org/10.1137/22M1504433.Callahan, J. "The Spread of a Contagious Illness." https://web.archive.org/web/20050227190741/http://maven.smith.edu:80/~callahan/ili/pde.html.Kermack, W. O. and McKendrick, A. G. "A Contribution to the Mathematical Theory of Epidemics." Proc. Roy. Soc. Lond. A 115, 700-721, 1927. https://doi.org/10.1098/rspa.1927.0118.Marinov, T. T. and Marinova, R. S. "Dynamics of COVID-19 Using Inverse Problem for Coefficient Identification in SIR Epidemic Models." Chaos, Solitons & Fractals: X 5, 100041, 2020. https://doi.org/10.1016/j.csfx.2020.100041.Marinov, T. T.; Marinova, R. S.; Omojola, J.; and Jackson, M. "Inverse Problem for Coefficient Identification in SIR Epidemic Models." Comput. Math. Appl. 67, 2218-2227, 2014. https://doi.org/10.1016/j.camwa.2014.02.002.

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SIR Model

Cite this as:

Weisstein, Eric W. "SIR Model." From MathWorld--A Wolfram Resource. https://mathworld.wolfram.com/SIRModel.html

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