Abstract
Infectious diseases exhibit a lot of interesting patterns when they spread in host populations. Detailed data are especially available on infectious diseases in human populations. Many typical infectious diseases of childhood, like measles and rubella, show clear seasonality with period of one year [2, 7, 8, 9, 12]. In addition to such annual patterns, they also show periodicity with period more than one year, eg., two years, five years, etc. The period of the same disease may be different in different places and in some places there may be chaotic patterns rather than periodic patterns. Moving focus from such childhood diseases to those of adulthood or adolescents, sexually transmitted diseases (or STDs for short, hereafter) also have interesting patterns although they cannot be clearly observed like childhood diseases. In most studies of pattern formation, some interesting pattern is generated similar to a shadow of some other preceding pattern. In the analysis of STDs, we may find cases where a pattern of more interest exists behind the apparently observed pattern. By the analysis of patterns observed in incidences of STDs, we can find patterns of human sexual behavior, the detail of which is usually hidden although questionnaire surveys can sometimes shed light on it. Some patterns of STDs are common to infectious diseases of childhood. The growth of the number of infected people is exponential at the beginning phase of spread. Another typical pattern is one observed in incidences according to the age of hosts. We first briefly show descriptive epidemiology of STDs in Japan below. The data are collected on the outpatients who visited urological, dermatological, obstetric or gynecological clinics in 1999. After reviewing some observed patterns in epidemiology, we try to explain these patterns by mathematical models of infectious diseases.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Anderson, R. M. and Garnett, G. P. (2000). Mathematical models of the transmission and control of sexually transmitted diseases. Sexually Transmitted Diseases, 27 (10): 636–643.
Balker, B. M. and Grenfell, B. T. (1993). Chaos and biological complexity in measles dynamics. Proc. R. Soc. Land. B 251 (1330): 75–81.
Dietz, K. (1988). On the transmission dynamics of HIV. Math. Biosci. 90: 397–414.
Dietz, K. (1988). The dynamics of spread of HIV infection in the heterosexual populations. In: Statistical Analysis and Mathematical Modelling of AIDS. (J. C. Jager and E. J. Ruitenberg, eds. ), Oxford University Press.
Garnett, G. P. and Anderson, R. M. (1993). Factors controlling the spread of HIV in heterosexual communities in developing countries: patterns of mixing between different age and sexual activity classes. Phil. Trans. R. Soc. Land. B 342: 137–159.
Garnett, G. P., and Anderson, R. M. (1995). Strategies for limiting the spread of HIV in developing countries: conclusions based on studies of the transmission dynamics of the virus. Journal of Acquired Immune Deficiency Syndrome and Human Retrovirology 9: 500–513.
Grenfell, B. T. (1992). Chance and chaos in measles dynamics. Journal of Royal Statistical Society, B54: 383–398.
Grenfell, B. T. and Dobson, A. P. (1995). Ecology of Infectious Diseases in Natural Populations. Cambridge University Press.
Grenfell, B. T., Kleczkowski, A., Gilligan, C. A. and Bolker, B. M. (1995). Spatial heterogeneity, nonlinear dynamics and chaos in infectious diseases. Statistical Methods in Medical Research, 4 (2): 160–83.
Kakehashi, M. (1998). A mathematical analysis of the spread of H1V/AIDS in Japan. IMA Journal of Mathematics Applied in Medicine and Biology 15: 299–311.
Kakehashi, M. (2000). Validity of simple pair formation model for HIV spread with realistic parameter setting. Mathematical Population. Studies 8 (3): 279–292.
Keeling, M. and Grenfell, B. T. (1999). Stochastic dynamics and a power law for measles variability. Phil. Trans. R. Soc. Land. B 354: 769–776.
Sheldon, B. C. and Read, A. F. (1997). Comparative biology and disease ecology. Trends in Evolution and Ecology 12 (2): 43–44.
Waldstätter, R. (1989). Pair formation in sexually-transmitted disease. In: Mathematical and Statistical Approaches to AIDS Epidemiology. (C. Castillo-Chavez, ed.) Lecture Notes in Biom.athematics 83. Springer-Verlag.
Williams, J. R. and Anderson, R. M. (1994). Mathematical models of the transmission dynamics of Human Immunodeficiency Virus in England and Wales: Mixing between different risk groups. Journal of Royal Statististical Society A 157: 69–87.
Yamaguchi, F and Kakehashi, M. (2002). A prefectural index of the spread of sexually transmitted diseases and the related socioeconomic factors. Kosei no Shihyo. 49(10): 24–30 (In Japanese).
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2003 Springer Japan
About this chapter
Cite this chapter
Kakehashi, M. (2003). Patterns in Epidemiology of Sexually Transmitted Diseases in Human Populations. In: Sekimura, T., Noji, S., Ueno, N., Maini, P.K. (eds) Morphogenesis and Pattern Formation in Biological Systems. Springer, Tokyo. https://doi.org/10.1007/978-4-431-65958-7_22
Download citation
DOI: https://doi.org/10.1007/978-4-431-65958-7_22
Publisher Name: Springer, Tokyo
Print ISBN: 978-4-431-65960-0
Online ISBN: 978-4-431-65958-7
eBook Packages: Springer Book Archive