Higher variability in the number of sexual partners in males can contribute to a higher prevalence of sexually transmitted diseases in females.
By examining published, empirical data we show that men and women consistently differ in the shape of the distribution of the number of sexual partners. The female distribution is always relatively narrow-variance is low-with a big majority of women having a number of partners close to the average. The male distribution is much wider-variance is high-with many men having few sex partners and many others having more partners than most females. Using stochastic modelling we demonstrate that this difference in variance is, in principle, sufficient to cause a difference in the gender prevalence of sexually transmitted diseases: compared to the situation where the genders have identical sex partner distributions, men will reach a lower equilibrium value, while women will stay at the same level (meaning that female prevalence becomes higher than male). We carefully analyse model behaviour and derive approximate expressions for equilibrium prevalences in the two different scenarios. We find that the size of the difference in gender prevalence depends on the variance ratio (the ratio between the variances of the male and female sex partner distributions), on the expected number of life-time partners, and on the probability of disease transmission. We note that in addition to humans, the variance phenomenon described here is likely to play a role for sexually transmitted diseases in other species also. We also show, again by examining published, empirical data, that the female to male prevalence ratio increases with the overall prevalence of a sexually transmitted disease (i.e., the more widespread the disease, the more women are affected). We suggest that this pattern may be caused by the effect described above in highly prevalent sexually transmitted diseases, while its impact in low-prevalence epidemics is surpassed by the action of high-risk individuals (mostly males).
Gouveia-Oliveira
Rodrigo
R
Center for Biological Sequence Analysis, Department of Systems Biology, The Technical University of Denmark, Building 208, 2800 Lyngby, Denmark. rodrigo@cbs.dtu.dk
Pedersen
Anders Gorm
AG
D004196:Disease Outbreaks; D005260:Female; D006801:Humans; D008297:Male; D008954:Models, Biological; D009010:Monte Carlo Method; D015995:Prevalence; D017678:Sex Distribution; D012737:Sex Factors; D012725:Sexual Behavior / Q000706:statistics & numerical data*; D012747:Sexual Partners; D012749:Sexually Transmitted Diseases / Q000453:epidemiology* / Q000635:transmission*