Concurrent sexual partnerships and primary HIV infection: a critical interaction

Sexual transmission and concurrency

Concurrent sexual partnerships and primary HIV infection: a critical interaction

The combination of long-term concurrent sexual partnerships and high infectiousness early in HIV infection has been suggested as a key driver of the extensive spread of HIV in general populations in sub-Saharan Africa, but this has never been scientifically investigated. Eaton and colleagues use a mathematical model to simulate HIV spreading on sexual networks with different amounts of concurrency. The models show that if HIV infectiousness is constant over the duration of infection, the amount of concurrency has much less influence on HIV spread compared to when infectiousness varies over three stages of infection with high infectiousness in the first months. The proportion of transmissions during primary infection is sensitive to the amount of concurrency and, in this model, is estimated to be between 16 and 28% in spreading epidemics with increasing concurrency. The sensitivity of epidemic spread to the amount of concurrency is greater than predicted by models that do not include primary HIV infection.

Editors’ note: Concurrent sexual partnerships are those that overlap in time – concurrency increases the numbers of partners exposed to HIV infection for a given number of lifetime sexual partners. This modelling exercise examined the influence of 11 different levels of concurrency and varied transmission probabilities during three stages of HIV: primary infection (2.9 months), asymptomatic infection (8.4 years), and symptomatic infection/AIDS (9.0 months), assuming that there is no transmission risk during the remaining 10 months before death. The result is that although primary infection amplifies the importance of concurrent sexual partnerships substantially, this combo does not completely explain diverse epidemics in sub-Saharan Africa. Small populations of people with a greater number of sexual partners and co-factors that increase HIV transmission (e.g. herpes simplex infection) also contribute to accelerating HIV spread. Nonetheless, the model suggests that reducing concurrency could play a crucial role in reducing HIV incidence.