Project

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Epidemiology and Mathematical Modelling for Infectious disease Control (EpideMMIC)

English title Epidemiology and Mathematical Modelling for Infectious disease Control (EpideMMIC)
Applicant Low Nicola Minling
Number 124952
Funding scheme ProDoc
Research institution Institut für Sozial- und Präventivmedizin Universität Bern
Institution of higher education University of Berne - BE
Main discipline Methods of Epidemiology and Preventive Medicine
Start/End 01.04.2009 - 31.03.2012
Approved amount 167'787.00
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All Disciplines (3)

Discipline
Methods of Epidemiology and Preventive Medicine
Public Health and Health Services
Infectious Diseases

Keywords (7)

infectious diseases; mathematical modelling; sexually transmitted infections; prevention; public health; Chlamydia trachomatis; screening

Lay Summary (English)

Lead
Lay summary
Chlamydia trachomatis is the most commonly reported sexually transmitted infection in many countries, including Switzerland, and the most common preventable cause of tubal infertility. This project aims to improve predictions from mathematical models about the potential impact of preventive interventions. Background
Scientists, policy makers, and the general public have always been interested in predicting future epidemics of infectious diseases and how to control them. Prediction is complicated, however, because of uncertainty about factors such as human behaviour, how infectious the organism is, how long it remains infectious, and whether a person becomes immune. Chlamydia trachomatis is usually asymptomatic, it spreads through networks of sexual partnerships, and re-infection is common. Yearly screening for sexually active under 25 year olds is widely promoted as an effective intervention. There is, however, little high quality research evidence about long term effectiveness and sustainability. Mathematical models can be used to understand how screening affects chlamydia transmission and prevents the development of complications. Individual-based models are the most appropriate type of model for these questions, but are also the most complex. The models used so far reach different conclusions about the likely impact of chlamydia screening programmes.
Aims
The overall goal of the project is to enable better decisions to be made about how to control sexually transmitted Chlamydia trachomatis infections. Objectives are: 1) To improve an existing individual-based model of chlamydia transmission through comparison with other models; 2) To improve predictions of the impact of screening on chlamydia transmission and progression to female fertility complications; 3) To investigate the potential impact of immunity on chlamydia transmission and control.
Significance
The EpideMMIC project will improve the quality of predictions from individual-based models of C. trachomatis transmission. In collaboration with other research groups we will compare model structures, the way that sexual networks are programmed, and the parameters describing infection transmission and progression. We will modify our model to incorporate the most plausible and essential features and validate the predictions using newly available data. The project will help public health decision-makers by improving the evidence base for decisions about controlling sexually transmitted infections in developed countries and will strengthen the public health research community in Switzerland.
Direct link to Lay Summary Last update: 21.02.2013

Responsible applicant and co-applicants

Employees

Publications

Publication
Variation in partner notification outcomes for chlamydia in UK genitourinary medicine clinics: multilevel study.
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.
Heterogeneity in vaccination coverage explains the size and occurrence of measles epidemics in German surveillance data.
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.
The role of reinfection and partner notification in the efficacy of Chlamydia screening programs.
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.
Describing the progression from Chlamydia trachomatis and Neisseria gonorrhoeae to pelvic inflammatory disease: systematic review of mathematical modeling studies
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.
Insights into the timing of repeated testing after treatment for Chlamydia trachomatis: data and modelling study
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, 88.

Scientific events

Active participation

Title Type of contribution Title of article or contribution Date Place Persons involved
Graduate School Symposium 2012 01.02.2012 Bern, Switzerland
3rd Epidemics congress 29.11.2011 Boston, US
19th International Society for STD Research conference 14.07.2011 Québec-City, Canada
Graduate School Symposium 2011 28.01.2011 Bern, Switzerland
Meeting of the HTA Partner Notification modelling project 29.04.2010 London, UK


Awards

Title Year
Indiana University Annual STD Lecturer 2012
SSPH+ Award 2011. Best published article in Public Health 2011

Associated projects

Number Title Start Funding scheme
118424 Integrating epidemiology and mathematical modelling to investigate the impact of interventions to control infectious diseases 01.05.2008 Project funding (Div. I-III)
136737 Acute and chronic dynamics of HIV and HCV infections, within-host evolution and epidemiological outcomes 01.10.2011 Ambizione
135654 Epidemiology and Mathematical Modelling for Infectious disease Control (EpideMMIC) 01.05.2011 Project funding (Div. I-III)
133960 Investigating the transmissibility and early dynamics of Chlamydia trachomatis infections 01.11.2010 International Exploratory Workshops
160320 Epidemiology and Mathematical Modelling for Infectious disease Control (EpideMMIC) 01.08.2015 Project funding (Div. I-III)
119477 SSPH+ PhD Program in Public Health 01.10.2008 ProDoc

Abstract

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.
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