Mathematical models of chlamydia transmission can help inform disease control policy decisions when direct empirical evaluation of alternatives is impractical. We reviewed published chlamydia models to understand the range of approaches used for policy analyses and how the studies have responded to developments in the field.
We performed a literature review by searching Medline and Google Scholar (up to October 2015) to identify publications describing dynamic chlamydia transmission models used to address public health policy questions. We extracted information on modeling methodology, interventions, and key findings.
We identified 47 publications (including two model comparison studies), which reported collectively on 29 distinct mathematical models. Nine models were individual-based, and 20 were deterministic compartmental models. The earliest studies evaluated the benefits of national-level screening programs and predicted potentially large benefits from increased screening. Subsequent trials and further modeling analyses suggested the impact might have been overestimated. Partner notification has been increasingly evaluated in mathematical modeling, whereas behavioral interventions have received relatively limited attention.
Our review provides an overview of chlamydia transmission models and gives a perspective on how mathematical modeling has responded to increasing empirical evidence and addressed policy questions related to prevention of chlamydia infection and sequelae.
A review describes the evolution of chlamydia transmission modeling in response to developments in the chlamydia prevention field.
From the *Prevention Policy Modeling Lab, Department of Global Health and Population, Harvard T. H. Chan School of Public Health, Boston, MA; †Division of STD Prevention, Centers for Disease Control and Prevention, Atlanta, GA; and ‡Division of STD Prevention & HIV/AIDS Surveillance, Massachusetts Department of Public Health, Boston, MA
Acknowledgements: The authors would like to thank David Connors for his much-appreciated help during the revision of the manuscript, and Ashleigh Tuite for helpful conversations during the writing of the manuscript.
Source of funding: The findings and conclusions in this report are those of the authors and do not necessarily represent the official position of the Centers for Disease Control and Prevention.
Conflict of interest: None declared.
Correspondence: Minttu Rönn, Department of Global Health and Population, Harvard T.H. Chan School of Public Health, 1633 Tremont St, Room 106, Boston, MA 02120. E-mail: email@example.com.
Received for publication May 17, 2016, and accepted January 16, 2017.
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