Individual and Population Level Effects of Partner Notification for Chlamydia trachomatis

Authored by Christian L Althaus, Janneke C M Heijne, Sereina A Herzog, Adrian Roellin, Nicola Low

Date Published: 2012

DOI: 10.1371/journal.pone.0051438

Sponsors: No sponsors listed

Platforms: C++

Model Documentation: Other Narrative Flow charts Pseudocode Mathematical description

Model Code URLs: Model code not found

Abstract

Partner notification (PN or contact tracing) is an important aspect of treating bacterial sexually transmitted infections (STIs), such as Chlamydia trachomatis. It facilitates the identification of new infected cases that can be treated through individual case management. PN also acts indirectly by limiting onward transmission in the general population. However, the impact of PN, both at the level of individuals and the population, remains unclear. Since it is difficult to study the effects of PN empirically, mathematical and computational models are useful tools for investigating its potential as a public health intervention. To this end, we developed an individual-based modeling framework called Rstisim. It allows the implementation of different models of STI transmission with various levels of complexity and the reconstruction of the complete dynamic sexual partnership network over any time period. A key feature of this framework is that we can trace an individual's partnership history in detail and investigate the outcome of different PN strategies for C. trachomatis. For individual case management, the results suggest that notifying three or more partners from the preceding 18 months yields substantial numbers of new cases. In contrast, the successful treatment of current partners is most important for preventing re-infection of index cases and reducing further transmission of C. trachomatis at the population level. The findings of this study demonstrate the difference between individual and population level outcomes of public health interventions for STIs.

Tags

networks Disease transmission Transmission dynamics United-states Model-based analysis Gonorrhea Sexually-transmitted infections Screening-programs Concurrent partnerships Moment closure