Introduction Understanding the patterns of sexual partnering and structure of sexual networks is essential for understanding the epidemiological dynamics of sexually transmitted infections (STI) in human populations. This study aimed to develop an analytical understanding of non-cohabiting sex partnering in sub-Saharan Africa (SSA) by utilising nationally-representative sexual behaviour data.
Methods A non-homogenous Poisson stochastic process model was used to describe the dynamics of non-cohabiting sex. The model was applied to 25 countries in SSA and was fitted to Demographic and Health Survey (DHS) data. The country-specific means and variances of the distributions of number of non-cohabiting partners were estimated.
Results The model showed robust fits to the empirical distributions stratified by country, marital status and sex. The median across all country-specific means was highest for unmarried males at 0.574 non-cohabiting partners over the last 12 months, followed by that of unmarried females at 0.337, married males at 0.192, and married females at 0.038. The median of variances was highest for unmarried males at 0.127, followed by married males at 0.057, unmarried females at 0.003, and married females at 0.000. The largest variability in means across countries was for unmarried males (0.103 to 1.206), and the largest variability in variances was among unmarried females (0.000 to 1.994).
Conclusion Robust fits of our model to the empirical sexual behaviour data suggest that non-cohabiting sex partnering appears to be a random “opportunistic” phenomenon. Unmarried individuals have larger means than their married counterparts, and males have larger means than females. Unmarried individuals appear to play a key role in driving heterogeneity in sexual networks and STIs epidemiology.
Disclosure of interest statement No pharmaceutical grants were received in the development of this study.