Abstract
We have seen that, under suitable assumptions such as homogeneous mixing, the basic reproduction number R 0, defined at the start of the epidemic and given by (4.2) in Chap. 4, transcends to the asymptotic equilibrium (t →∞) outcomes such as the final size (5.32) in a closed population or the endemic equilibrium \(x(\infty )=\lim _{t\rightarrow \infty }S_{d}(t)/m\rightarrow R_{0}^{-1}\) in a constant population. Meanwhile, we have also seen that, in compartment transmission models of the SEIRS type (in Chap. 5) with exponentially distributed durations, R 0 is expressed as a function of parameters representing rates in these models, such as R 0 = β∕γ in SEIRS models without mortality or other in-flow and out-flow of the population, or (5.70) in SEIRS models with mortality or other in-flow and out-flow of the population.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Cobelli, C., & Romanin-Jacur, G. (1976). Controllability, observability and structural identifiability of multi input and multi output biological compartmental systems. IEEE Transactions on Biomedical Engineering, 23, 93–100.
Ferguson, N. M., Cummings, D. A. T., Cauchemez, S., Fraser, C., Riley, S., Meeyai, A., et al. (2005). Strategies for containing an emerging influenza pandemic in Southeast Asia. Nature, 437(7056), 209.
Funk, S., Gilad, E., Watkins, C., & Jansen, V. A. (2009). The spread of awareness and its impact on epidemic outbreaks. Proceedings of the National Academy of Sciences, 106(16), 6872–6877.
Funk, S., Salathé, M., & Jansen, V. A. (2010). Modelling the influence of human behaviour on the spread of infectious diseases: A review. Journal of the Royal Society Interface, 7(50), 1247–1256.
Gani, R., Hughes, H., Fleming, D., Griffin, T., Medlock, J., & Leach, S. (2005). Potential impact of antiviral drug use during influenza pandemic. Emerging Infectious Diseases, 11(9), 1355–1362.
Goldstein, S. (1932). Operational representation of Whittaker’s confluent hypergeometric function and Weber’s parabolic cylinder function. Proceedings of the London Mathematical Society, 2, 103–125.
Halloran, M. E., Longini, I. M., & Struchiner, C. J. (2009). Design and analysis of vaccine studies. New York, NY: Springer.
Lefèvre, C., & Picard, P. (1995). Collective epidemic processes: A general modelling approach to the final outcome of SIR infectious diseases. In D. Mollison (Ed.), Epidemic models: Their structure and relation to data (pp. 53–70). Cambridge: Cambridge University Press.
Ludwig, D. (1975). Final size distributions for epidemics. Mathematical Biosciences, 23, 33–46.
Ma, J., & Earn, D. J. (2006). Generality of the final size formula for an epidemic of a newly invading infectious disease. Bulletin of Mathematical Biology, 68, 679–702.
Marshall, A. W., & Olkin, I. (2007). Life distributions, structure of nonparametric, semiparametric and parametric families. New York, NY: Springer.
Martin-Löf, A. (1988). The final size of a nearly critical epidemic, and the first passage time of a Wienner process to a parabolic barrier. Journal of Applied Probability, 35, 671–682.
Mode, C. J., & Sleeman, C. K. (2000). Stochastic processes in epidemiology, HIV/AIDS, other infectious diseases and computers. Singapore: World Scientific.
Nelson, K. E., Williams, C. M., & Graham, N. M. H. (2001). Infectious disease epidemiology: Theory and practice. Gaithersburg, MD: An Aspen Publication.
Perra, N., Balcan, D., Gonçalves, B., & Vespignani, A. (2011). Towards a characterization of behavior-disease models. PloS One, 6(8), e23084.
Scalia-Tomba, G. (1985). Asymptotic final size distribution for some chain binomial processes. Advances in Applied Probability, 17, 477–495.
van den Driessche, P., & Watmough, J. (2008). Further notes on the basic reproduction number. In: F. Brauer, P. van den Driessche, & J. Wu (Eds.) Mathematical epidemiology. Lecture notes in mathematics (Vol. 1945). Berlin: Springer.
von Bahr, B., & Martin-Löf, A. (1980). Threshold limit theorems for some epidemic processes. Advances in Applied Probability, 12, 319–349.
Yan, P. (2018). A frailty model for intervention effectiveness against disease transmission when implemented with unobservable heterogeneity. Mathematical Biosciences & Engineering, 15(1), 275–298.
Yan, P., & Feng, Z. (2010). Variability order of the latent and the infectious periods in a deterministic SEIR epidemic model and evaluation of control effectiveness. Mathematical Biosciences, 224, 43–52.
Author information
Authors and Affiliations
Rights and permissions
Copyright information
© 2019 Crown
About this chapter
Cite this chapter
Yan, P., Chowell, G. (2019). More Complex Models and Control Measures. In: Quantitative Methods for Investigating Infectious Disease Outbreaks. Texts in Applied Mathematics, vol 70. Springer, Cham. https://doi.org/10.1007/978-3-030-21923-9_6
Download citation
DOI: https://doi.org/10.1007/978-3-030-21923-9_6
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-21922-2
Online ISBN: 978-3-030-21923-9
eBook Packages: Mathematics and StatisticsMathematics and Statistics (R0)