Epidemiological modelling is an important method for estimating the long-term impact of behavioural or medical interventions on the course of the human immunodeficiency virus (HIV) epidemic through calculation of HIV infections prevented, and quality adjusted life years (QALYs) saved. These models often analyse marginalized populations, such as men who have sex with men (MSM) or injecting drug users (IDUs), and their results depend upon the assumptions made about the risk and health profiles of these populations.

Some models introduce a strong assumption into their calculations: QALYs for IDUs are weighted, even when healthy, typically by a value of 0.9 [1,2]. Thus at every disease stage, from HIV-negative to acquired immune deficiency syndrome (AIDS), an IDU gains fewer QALYs from treatment or prevention than does an MSM or low-risk person at the same stage. QALYs are a crucial component of the calculation of cost-effectiveness, and the use of this ‘IDU weight’ is directly relevant to the conclusions of the studies.

This IDU weight has been justified because substance use disorder is a form of mental illness [2]. However, this mental illness is unrelated to the treatment outcome of the study, so the weight essentially introduces a cost–benefit analysis into the cost-effectiveness study, comparing money spent on IDUs with money spent on non-IDUs. Assigning an IDU weight in this way opens the field to an extremely complex and intractable problem, because a consistent application of this principle would require discounting to reflect increased all-cause morbidity in other populations, including age-related discounting, which remains a highly controversial proposal.

This IDU weight has practical effects in epidemiological models:

  • • 
    It underestimates the cost-effectiveness of interventions such as needle syringe programmes (NSP), which specifically target IDUs, even though they are known to be cheap and effective [3].
  • • 
    It undervalues the effect of treatment on IDUs, as it shows a lower QALY gain from treating an IDU at a given disease stage.
  • • 
    It underestimates the cost-effectiveness of any intervention used across the population, as QALYs gained by the IDU proportion of the population are systematically undervalued.

These practical effects can have significant policy outcomes. For example, the British National Institute for Health and Clinical Excellence (NICE) is able to recommend treatments for specific subpopulations, including those defined by ethnicity, sex or disability [4]. Under NICE's Principle 7, however, treatments can only be recommended for specific subpopulations on the basis of differential effectiveness. Any modelling that uses an IDU weight explicitly breaks NICE's Principle 7, and the concepts of distributional justice that underlie it.

Undervaluing outcomes in this way is counter to the World Health Organization's (WHO) principle of ‘Health for All’ and a clear mechanism by which health inequality is entered into the policy planning process. If extended to other forms of mental illness, this practice would lead to a systematic cost-effectiveness bias against the mentally ill. Just as policy makers should consider equality in implementing policy, people whose research will potentially impact upon policy decisions should also ensure that their work reflects these principles, regardless of the life-style or mental health status of the target population.


  1. Top of page
  2. Declarations of interest
  3. References
  • 1
    Long E. F., Brandeau M. L., Owens D. K. The cost-effectiveness and population outcomes of expanded HIV screening and antiretroviral treatment in the United States. Ann Intern Med 2010; 153: 77889.
  • 2
    Zaric G. S., Barnett P. G., Brandeau M. L. HIV transmission and the cost-effectiveness of methadone maintenance. Am J Public Health 2000; 90: 110011.
  • 3
    National Centre in HIV Epidemiology and Clinical Research (NCHECR). Return on Investment 2: evaluating the cost effectiveness of needle syringe programs in Australia: Department of Health and Ageing. Sydney, Australia: NCHECR; 2009.
  • 4
    National Institute for Health and Clinical Excellence (NICE). Social Value Judgments: Principles for the Development of NICE Guidance, 2nd edn. London: NICE; 2008.