The Imperial College model, 2010

A mathematical model by London’s Imperial College Infectious Disease Epidemiology group published in 2010 found that the 'test-and-treat' prevention approach might not have to be universal to succeed. Treating everyone to halt the HIV epidemic in the worst-affected countries might not be the most cost-effective use of antiretroviral drugs as a prevention tool, and universal treatment and annual testing might not always be necessary to achieve profound reductions in new infections. 

The Imperial College group forecast that, in some circumstances, expanding treatment coverage to 80% of those with CD4 counts below 350 cells/mm³, and getting everyone to take an HIV test every four to five years, could be the most cost-efficient strategy for reducing new infections. 

The Imperial College model differed from the WHO model in several key respects. Firstly, it looked at the effects of treatment and testing in populations with different patterns of sexual behaviour. It also looked at the effects of different thresholds for initiating treatment, and different frequencies of testing, on long-term HIV prevalence and incidence. 

The modelling exercise broadly confirmed the results of the WHO and British Columbia models. Scaling up treatment coverage in 'hyperendemic' countries would have a profound impact on new HIV infections. 

However, the model also forecast that impact would be highly dependent on the character of the local epidemic. In settings where people with large numbers of sexual partners frequently had sexual contacts with people who had a very small number of lifetime partners, new infections would be reduced by 85% but would not be eliminated. 

The model also showed considerable variation in the necessary frequency of testing according to the sexual-behaviour pattern in the population. In a setting where the level of sexual mixing between 'high risk' and 'low risk' was relatively low, testing people every two years would be necessary to bring down incidence by 90%. But where more sexual mixing took place, it might be necessary to diagnose every person with HIV within one month of infection to achieve a similar impact. 

Depending on the epidemiologic context, say the authors, incidence might be reduced by 95% if 80% of the population were to be tested only every three to four years, and started treatment at a CD4 count around 400 cells/mm³. 

Their analysis of the cost efficiency of different frequencies of testing and treatment similarly found that in some epidemics the most cost-efficient strategy would be to test everyone every four to five years and initiate treatment at a CD4 cell count of 350 to 400 cells/mm³. 

Only in the most 'robust' epidemics, where incidence had stubbornly failed to decline despite years of prevention efforts, would more frequent testing prove to be cost-efficient. In these settings, testing 80% of people every two to three years and initiating treatment at a CD4 count above 450 cells/mm³ would be the optimal strategy. 

“It is likely that the 'test and treat' approach is much better suited to some populations and poorly suited to others,” they conclude. “There are diminishing returns for increasing testing frequencies to once-per-year levels. 

“Failing to achieve sufficiently high coverage levels or failing to test frequently enough could just lead to a dramatic spiralling of treatment costs.” 

Reductions in incidence of 85 to 95% would take around 30 years to achieve, so – in the short term – treatment costs would rise. 

They also speculate that targeting particular population groups or locations for testing, such as truck drivers or beer halls, might prove particularly effective.