Skip to main content

Advertisement

Log in

A Single-Parameter Model of the Immune Response to Bacterial Invasion

  • Original Article
  • Published:
Bulletin of Mathematical Biology Aims and scope Submit manuscript

Abstract

The human immune response to bacterial pathogens is a remarkably complex process, involving many different cell types, chemical signals, and extensive lines of communication. Mathematical models of this system have become increasingly high-dimensional and complicated, as researchers seek to capture many of the major dynamics. In this paper, we argue that, in some important instances, preference should be given to low-dimensional models of immune response, as opposed to their high-dimensional counterparts. One such model is analyzed and shown to reflect many of the key phenomenological properties of the immune response in humans. Notably, this model includes a single parameter that, when combined with a single set of reference parameter values, may be used to quantify the overall immunocompetence of individual hosts.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9

Similar content being viewed by others

References

  • Antia, R., Bergstrom, C. T., Pilyugin, S. S., Kaech, S. M., & Ahmed, R. (2003). Models of CD8+ responses: 1. What is the antigen-independent proliferation program. J. Theor. Biol., 221(4), 585–598.

    Article  MathSciNet  Google Scholar 

  • Asachenkov, A., Pogozhev, I., & Zuev, S. (1993). Parametrization in mathematical models of immune-physiological processes. Russ. J. Numer. Anal. Math. Model., 8(1), 31–46.

    Article  MATH  Google Scholar 

  • Asachenkov, A., Marchuk, G., Mohler, R., & Zuev, S. (1994). Disease dynamics. Boston: Birkhäuser.

    Google Scholar 

  • Beck, K. (1981). A mathematical model of t-cell effects in the humoral immune response. J. Theor. Biol., 89, 593–610.

    Article  Google Scholar 

  • Bell, G. I. (1973). Predator–prey equations simulating an immune response. Math. Biosci., 16, 291–314.

    Article  MATH  Google Scholar 

  • De Boer, R. J., & Boerlijst, M. C. (1994). Diversity and virulence thresholds in aids. Proc. Natl. Acad. Sci. USA, 94, 544–548.

    Article  Google Scholar 

  • Boman, H. G. (2000). Innate immunity and the normal microflora. Immunol. Rev., 173, 5–16.

    Article  Google Scholar 

  • Bruni, C., Giovenco, M. A., Koch, G., & Strom, R. (1975). A dynamical model of humoral immune response. Math. Biosci., 27, 191–211.

    Article  MATH  Google Scholar 

  • Caudill, L., & Lawson, B. (2013). A hybrid agent-based and differential equations model for simulating antibiotic resistance in a hospital ward. Technical report TR-13-01, University of Richmond Mathematics and Computer Science.

  • Chaui-Berlinck, J. G., Barbuto, J. A. M., & Monteiro, L. H. A. (2004). Conditions for pathogen elimination by immune systems. Theory Biosci., 123, 195–208.

    Article  Google Scholar 

  • Elgert, K. D. (2009). Immunology (2nd ed.). New York: Wiley-Blackwell.

    Google Scholar 

  • Fishman, M. A., & Perelson, A. S. (1993). Modeling t cell-antigen presenting cell interactions. J. Theor. Biol., 160, 311–342.

    Article  Google Scholar 

  • Fouchet, D., & Regoes, R. (2008). A population dynamics analysis of the interaction between adaptive regulatory t cells and antigen presenting cells. PLoS ONE, 3(5), e2306.

    Article  Google Scholar 

  • Goldmann, D. A., Weinstein, R. A., Wenzel, R. P., Tablan, O. C., Duma, R. J., Gaynes, R. P., Schlosser, J., & Martone, W. J. (1996). Strategies to prevent and control the emergence and spread of antimicrobial-resistant microorganisms in hospitals. JAMA, 275(3), 234–240.

    Article  Google Scholar 

  • Grossman, Z., Asofsky, R., & DeLisi, C. (1980). The dynamics of antibody-secreting cell production: regulation of growth and oscillations in the response to t-independent antigen. J. Theor. Biol., 84(1), 49–92.

    Article  Google Scholar 

  • Huang, X.-C. (1990). Uniqueness of limit cycles in a predator–prey model simulating an immune response. In R. Mohler & A. Asachenkov (Eds.), Selected topics on mathematical models in immunology and medicine, Laxenburg, Austria (pp. 147–153). IIASA.

    Google Scholar 

  • Klein, P., & Dolezal, J. (1980). A mathematical model of antibody response dynamics. Probl. Control Inf. Theory, 9, 407–419.

    MATH  Google Scholar 

  • Lee, H. Y., Topham, D. J., Park, S. Y., Hollenbaugh, J., Treanor, J., Mosmann, T. R., Jin, X., Ward, B. M., Miao, H., Holden-Wiltse, J., Perelson, A. S., Zand, M., & Wu, H. (2009). Simulation and prediction of the adaptive immune response to influenza a virus infection. J. Virol., 83(14), 7151–7165.

    Article  Google Scholar 

  • Mackay, I., & Rosen, F. S. (2000). Advances in immunology. N. Engl. J. Med., 343, 338–344.

    Article  Google Scholar 

  • Marchuk, G. I. (1997). Mathematical modeling of immune response in infectious diseases. Boston: Kluwer.

    Book  Google Scholar 

  • McLean, A. R. (1994). Modeling t cell memory. J. Theor. Biol., 170, 63–74.

    Article  Google Scholar 

  • Moellering, R., & Blumgart, H. (2002). Understanding antibiotic resistance development in the immunocompromised host. Int. J. Infect. Dis., 6, S3–S4.

    Article  Google Scholar 

  • Mohler, R. R., Barton, C. F., & Hsu, C.-S. (1978). T and b cells in the immune system. In G. I. Bell, A. S. Perelson, & G. H. Pimbley (Eds.), Theoretical immunology (pp. 415–435). New York: Marcel-Dekker.

    Google Scholar 

  • Nowak, M. A., & Bangham, C. R. M. (1996). Population dynamics of immune responses to persistent viruses. Science (NS), 272(5258), 74–79.

    Article  Google Scholar 

  • Nowak, M. A., May, R. M., & Sigmund, K. (1995). Immune responses against multiple epitopes. J. Theor. Biol., 175, 325–353.

    Article  Google Scholar 

  • Pogozhev, I., Usmanov, R., & Zuev, S. (1993). Models of processes in organism and population characteristics. Russ. J. Numer. Anal. Math. Model., 8(5), 441–452.

    Article  MATH  Google Scholar 

  • Prikrylova, D., Jilek, M., & Waniewski, J. (1992). Mathematical modeling of the immune response. Boca Raton: CRC Press.

    MATH  Google Scholar 

  • Rundell, A., DeCarlo, R., HogenEsch, H., & Doerschuk, P. (1998). The humoral immune response hemophilus influenzae type: a mathematical model based on t-zone ad germinal center b-cell dynamics. J. Theor. Biol., 194, 341–381.

    Article  Google Scholar 

  • Spellberg, B., Guidos, R., Gilbert, D., Bradley, J., Boucher, H. W., Scheld, W. M., Bartlett, J. G., & Edwards, J. (2008). The epidemic of antibiotic-resistant infections: a call to action for the medical community from the Infectious Diseases Society of America. Clin. Infect. Dis., 46, 155–164.

    Article  Google Scholar 

  • Usmanov, R., & Zuev, S. (1993). Parametrization in mathematical models of diseases. Russ. J. Numer. Anal. Math. Model., 8(3), 275–284.

    Article  MathSciNet  MATH  Google Scholar 

  • Waltman, P. (1978). A threshold model of antigen-stimulated antibody production. In G. I. Bell, A. S. Perelson, & G. H. Pimbley (Eds.), Theoretical immunology (pp. 437–453). New York: Marcel-Dekker.

    Google Scholar 

  • Weinand, R. G., & Conrad, M. (1988). Maturation of the immune response: a computational model. J. Theor. Biol., 133, 409–428.

    Article  Google Scholar 

  • Wodarz, D., & Nowak, M. A. (2000). Correlates of cytotoxic T-lymphocytemediated virus control: implications for immuno-suppressive infections and their treatment. Philos. Trans. R. Soc. Lond. B, 355, 1059–1070.

    Article  Google Scholar 

Download references

Acknowledgements

I am grateful to the University of Richmond for providing summer research support, and to Dr. Krista Stenger (Department of Biology, University of Richmond) for sharing her expertise in immunology.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Lester F. Caudill Jr..

Rights and permissions

Reprints and permissions

About this article

Cite this article

Caudill, L.F. A Single-Parameter Model of the Immune Response to Bacterial Invasion. Bull Math Biol 75, 1434–1449 (2013). https://doi.org/10.1007/s11538-013-9854-1

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11538-013-9854-1

Keywords

Navigation