Book contents
- Frontmatter
- Contents
- Introduction
- Participants
- Non-Participant Contributors
- Part 1 Transmissible diseases with long development times and vaccination strategies
- Part 2 Dynamics of immunity (development of disease within individuals)
- Part 3 Population heterogeneity (mixing)
- Modeling heterogeneous mixing in infectious disease dynamics
- Behavior change and non-homogeneous mixing
- Sources and use of empirical observations to characterise networks of sexual behaviour
- Invited Discussion
- Invited Discussion
- Per-contact probabilities of heterosexual transmission of HIV, estimated from partner study data
- Heterosexual spread of HIV with biased sexual partner selection
- Dynamic simulation of sexual partner networks: which network properties are important in sexually transmitted disease (STD) epidemiology?
- The spread of an STD on a dynamic network of sexual contacts
- Network measures for epidemiology
- Spatial heterogeneity and the spread of infectious diseases
- Data analysis for estimating risk factor effects using transmission models
- Homosexual role behaviour and the spread of HIV
- Homogeneity tests for groupings of AIDS patient classifications
- Risk factors for heterosexual transmission of HIV
- The effect of behavioural change on the prediction of R0 in the transmission of AIDS
- The saturating contact rate in epidemic models
- A Liapunov function approach to computing R0
- Stochastic models for the eradication of poliomyelitis: minimum population size for polio virus persistence
- Part 4 Consequences of treatment interventions
- Part 5 Prediction
Sources and use of empirical observations to characterise networks of sexual behaviour
Published online by Cambridge University Press: 04 August 2010
- Frontmatter
- Contents
- Introduction
- Participants
- Non-Participant Contributors
- Part 1 Transmissible diseases with long development times and vaccination strategies
- Part 2 Dynamics of immunity (development of disease within individuals)
- Part 3 Population heterogeneity (mixing)
- Modeling heterogeneous mixing in infectious disease dynamics
- Behavior change and non-homogeneous mixing
- Sources and use of empirical observations to characterise networks of sexual behaviour
- Invited Discussion
- Invited Discussion
- Per-contact probabilities of heterosexual transmission of HIV, estimated from partner study data
- Heterosexual spread of HIV with biased sexual partner selection
- Dynamic simulation of sexual partner networks: which network properties are important in sexually transmitted disease (STD) epidemiology?
- The spread of an STD on a dynamic network of sexual contacts
- Network measures for epidemiology
- Spatial heterogeneity and the spread of infectious diseases
- Data analysis for estimating risk factor effects using transmission models
- Homosexual role behaviour and the spread of HIV
- Homogeneity tests for groupings of AIDS patient classifications
- Risk factors for heterosexual transmission of HIV
- The effect of behavioural change on the prediction of R0 in the transmission of AIDS
- The saturating contact rate in epidemic models
- A Liapunov function approach to computing R0
- Stochastic models for the eradication of poliomyelitis: minimum population size for polio virus persistence
- Part 4 Consequences of treatment interventions
- Part 5 Prediction
Summary
Introduction
Models of the transmission dynamics of sexually acquired infections have recently turned greater attention to the importance of sexual mixing patterns and sexual networks in the spread of such diseases (Hethcote and Yorke 1984, Ramstedt et al. 1992, Haraldsdottir et al. 1992). Apart from the theoretical problems of constructing models which can adequately characterise the complexity of human sexual partnership formation, there remain practical problems in obtaining sufficiently robust empirical data to measure parameters of interest for use by modellers. This paper addresses some aspects of empirical measurement and discusses the validity of some basic parameter estimates commonly used in models of sexually transmitted disease (STD) transmission, particularly where they are used to demonstrate quantitative rather than qualitative considerations.
Key parameters of interest in deterministic models include the population ‘rate of partner change’ and its variance, the probability of transmission per sexual partnership (or per act of intercourse) and the duration of infectiousness of the organism under consideration (Hethcote and Yorke 1984, Anderson and May 1988).
Recent studies of sexual behaviour (Johnson et al. 1992, ACSF investigators 1992, Catania et al 1992, MMWR. 1988) have emphasised the marked heterogeneity in sexual behaviour in human communities as measured by numbers of sexual partners in different time intervals. These distributions suggest that models need to take account not only of simple population means, but also to consider stratification of the population into high- and low-activity classes (Hethcote and Yorke 1984). This can, in part, be achieved by considering the demographic correlates of variability in sexual behaviour. These include, for example, varying effects in different cultures of age cohort, lifecourse, gender, marital and socio-economic status (Johnson et al. 1992).
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- Models for Infectious Human DiseasesTheir Structure and Relation to Data, pp. 253 - 262Publisher: Cambridge University PressPrint publication year: 1996
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