Theoretical Biology and Medical Modelling 2006, 3:3doi:10.1186/1742-4682-3-3
Research
1 Health Protection Agency, Centre for Infections, 61 Colindale Ave, Colindale, London, NW9 5EQ, UK
2 London School of Hygiene & Tropical Medicine, Keppel Street, London WC1E 7HT, UK
3 Department of Primary Care and Population Sciences, University College London, Mortimer Market Centre, Mortimer Market, London WC1E 6AU, UK
The electronic version of this article is the complete one and can be found online at:
http://www.tbiomed.com/content/3/1/3
Published: 20 January 2006
© 2006 Turner et al; licensee BioMed Central Ltd.
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
A national chlamydia screening programme is currently being rolled out in the UK and other countries. However, much of the epidemiology remains poorly understood. In this paper we present a stochastic, individual based, dynamic sexual network model of chlamydia transmission and its parameterisation. Mathematical models provide a theoretical framework for understanding the key epidemiological features of chlamydia: sexual behaviour, health care seeking and transmission dynamics.
The model parameters were estimated either directly or by systematic fitting to a variety of appropriate data sources. The fitted model was representative of sexual behaviour, chlamydia epidemiology and health care use in England. We were able to recapture the observed age distribution of chlamydia prevalence.
Estimating parameters for models of sexual behaviour and transmission of chlamydia is complex. Most of the parameter values are highly correlated, highly variable and there is little empirical evidence to inform estimates. We used a novel approach to estimate the rate of active treatment seeking, by combining data sources, which improved the credibility of the model results. The model structure is flexible and is broadly applicable to other developed world settings and provides a practical tool for public health decision makers.
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