infectious diseases; mathematical modelling; sexually transmitted infections; prevention; public health; Chlamydia trachomatis; screening
Herzog Sereina A, McClean Hugo, Carne Chris A, Low Nicola (2011), Variation in partner notification outcomes for chlamydia in UK genitourinary medicine clinics: multilevel study., in Sexually transmitted infections
, 87(5), 420-5.
Herzog S A, Paul M, Held L (2011), Heterogeneity in vaccination coverage explains the size and occurrence of measles epidemics in German surveillance data., in Epidemiology and infection
, 139(4), 505-15.
Heijne Janneke C M, Althaus Christian L, Herzog Sereina A, Kretzschmar Mirjam, Low Nicola (2011), The role of reinfection and partner notification in the efficacy of Chlamydia screening programs., in The Journal of infectious diseases
, 203(3), 372-7.
Herzog Sereina A, Heijne Janneke CM, Althaus Christian L, Low Nicola, Describing the progression from Chlamydia trachomatis and Neisseria gonorrhoeae to pelvic inflammatory disease: systematic review of mathematical modeling studies, in Sexually Transmitted Diseases
Heijne Janneke CM, Herzog Sereina A, Althaus Christian L, Tao Guoyu, Kent CK, Low N, Insights into the timing of repeated testing after treatment for Chlamydia trachomatis: data and modelling study, in Sexually Transmitted Infections
Background Predicting future epidemics of infectious diseases and how to control them have long intrigued scientists and policy makers alike. Integrating the work of epidemiologists and mathematical modellers is essential for public health science because understanding the complex, non-linear and indirect effects of infection transmission dynamics is necessary for effective infectious disease control. Chlamydia trachomatis, which is the most commonly reported infection in several developed countries, provides an excellent example for studying infection transmission systems. The non-random sexual behaviours that result in transmission and lack of lasting immunity induced by the infection provide challenges for both mathematical modelling, and for designing effective interventions. Individual-based dynamic network simulation models provide the most realistic way of studying these interactions. Epidemiological methods are needed to obtain the best estimates of input parameters, appropriate data for external validation, and to interpret model outputs. The Epidemiology and Mathematical Modelling for Infectious disease Control (EpideMMIC) project is a collaboration between epidemiologists with a strong record of research in sexually transmitted infection research and mathematical modellers who have developed the three most sophisticated network models of chlamydia transmission. Objectives and goals The overall goal of the project is to contribute to infection transmission science by integrating epidemiological and mathematical modelling techniques for investigating the impact of interventions to control infectious diseases, using Chlamydia trachomatis as an example. Specific objectives are: 1) Integration of existing mathematical models to improve the robustness of inferences from a realistic individual-based network model of C. trachomatis sexual transmission and development of sequelae; 2) To determine the likely impact of screening interventions, based on data from existing screening programmes, and to determine the parameters for which better data are needed; 3) To investigate the potential impact of natural immunity, and its loss, on chlamydia transmission.Methods of investigation 1) Three existing individual-based dynamic network models of C. trachomatis transmission will be used to comlpare and examine both parameter uncertainty and model uncertainty. The effects of incorporating sexual network data and alternative screening interventions on the transmission of chlamydia and progression to sequelae will then be examined. A modified model that incorporates sufficient detail to model C. trachomatis transmission realistically, but omits unnecessary complexity will be developed. 2) This model will be externally validated, using epidemiological data that provide information about both uptake and outcomes of organised chlamydia screening interventions. 3) The importance of key biological and behavioural factors influencing trends in transmission of C. trachomatis, including host immunity, changes in screening coverage and frequency, changes in sexual behaviour and changes in diagnostic testing patterns and performance will be examined. Timescale April 2009 to March 2012.Significance The EpideMMIC project provides a stimulating environment for a PhD student to contribute to an important area of public health policy and practice. The methods involved in the development, validation and modification of this model can then be applied to other infections. The project provides an opportunity for involvement in a lively international research collaboration, which can contribute to strengthening the public health research community in Switzerland. The project also offers benefits to public health policy decision-making by improving the evidence base for making decisions about appropriate interventions to control the most commonly reported sexually transmitted infection in developed countries.