Concurrent partnerships and their impacts on HIV transmission

Ka Yin Leung summarizes her YSSP research on how concurrent sexual partnerships impact the spread of HIV.

K.Y. Leung

K.Y. Leung


Many societies have monogamous partnerships as a social norm, with most individuals having at most one partner at a time. If, instead, a society has concurrent partnerships as a social norm, so that individuals may have multiple partners at a time, does this enhance the spread of sexually transmitted infections such as HIV? Opinions differ on this. This debate is particularly important with regard to the HIV epidemic in sub-Saharan Africa. In that region, HIV is widespread among heterosexual populations. This is very different from the rest of the world. If concurrency is driving the HIV epidemic in this region, then prevention and intervention programs will need to account for their epidemiological implications. Therefore, we need to understand how concurrent partnerships actually impact the spread of HIV.


Prior to YSSP, I developed a mathematical framework for dynamic sexual networks that incorporates demography and allows for concurrent partnerships [1]. In this same work, two measures for concurrency were defined. Finally, UNAIDS (Joint United Nations program on HIV/AIDS) proposed a consensus indicator for concurrency [2]). In this project, we focused on understanding these three measures theoretically in the context of the mathematical framework and studied if the measures would capture disease dynamics in the same manner. The second part of the project was to use linear regression analysis to try to understand the correlation between the concurrency measures and the epidemiological quantity called the basic reproduction ratio.


We found that all three concurrency measures increase when expected lifetime number of partners and expected partnership duration increases. Concerning the disease dynamics, we found that the expected lifetime number of partners is a very good predictor for the basic reproduction number. The prediction improved if we added a concurrency measure as explanatory variable.


The three concurrency measures behave according to interpretation, as far as expected lifetime number of partners and expected partnership duration are concerned. The concurrency measures all seem to correlate positively with the basic reproduction number. Concerning this epidemiological quantity, all three measures capture this part of the disease dynamics in the same way.


[1] Leung KY, Kretzschmar MEE & Diekmann O (2012). Dynamic concurrent partnership networks incorporating demography. Theoretical Population Biology, 82: 229–239.

[2] UNAIDS Reference Group on Modeling, Estimates and Projections: working group on measuring concurrent sexual partnerships (2010). HIV: consensus indicators are needed for concurrency. Lancet, 375: 621–622.


Ka Yin Leung, of the Mathematical Institute of Utrecht University, and the Julius Centre for Primary Care and Health Sciences of the University Medical Centre Utrecht, is a citizen of the Netherlands. She was funded by IIASA's Dutch National Member Organization and worked in the Evolution and Ecology (EEP) Program during the YSSP.

Please note these Proceedings have received limited or no review from supervisors and IIASA program directors, and the views and results expressed therein do not necessarily represent IIASA, its National Member Organizations, or other organizations supporting the work.

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Last edited: 19 August 2015


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