Rationing Antiretroviral Therapy for HIV/AIDS in Africa: Efficiency, Equity, and Reality

Background: Rationing of access to antiretroviral therapy already exists in sub-Saharan Africa and will intensify as national treatment programs develop. The number of people who are medically eligible for therapy will far exceed the human, infrastructural, and financial resources available, making rationing of public treatment services inevitable. Methods: We identified 15 criteria by which antiretroviral therapy could be rationed in African countries and analyzed the resulting rationing systems across 5 domains: clinical effectiveness, implementation feasibility, cost, economic efficiency, and social equity. Findings: Rationing can be explicit or implicit. Access to treatment can be explicitly targeted to priority subpopulations such as mothers of newborns, skilled workers, students, or poor people. Explicit conditions can also be set that cause differential access, such as residence in a designated geographic area, co-payment, access to testing, or a demonstrated commitment to adhere to therapy. Implicit rationing on the basis of first-come, first-served or queuing will arise when no explicit system is enforced; implicit systems almost always allow a high degree of queue-jumping by the elite. There is a direct tradeoff between economic efficiency and social equity. Interpretation: Rationing is inevitable in most countries for some period of time. Without deliberate social policy decisions, implicit rationing systems that are neither efficient nor equitable will prevail. Governments that make deliberate choices, and then explain and defend those choices to their constituencies, are more likely to achieve a socially desirable outcome from the large investments now being made than are those that allow queuing and queue-jumping to dominate.

Task Assignment in a Distributed System: Improving Performance by Unbalancing Load

We consider the problem of task assignment in a distributed system (such as a distributed Web server) in which task sizes are drawn from a heavy-tailed distribution. Many task assignment algorithms are based on the heuristic that balancing the load at the server hosts will result in optimal performance. We show this conventional wisdom is less true when the task size distribution is heavy-tailed (as is the case for Web file sizes). We introduce a new task assignment policy, called Size Interval Task Assignment with Variable Load (SITA-V). SITA-V purposely operates the server hosts at different loads, and directs smaller tasks to the lighter-loaded hosts. The result is that SITA-V provably decreases the mean task slowdown by significant factors (up to 1000 or more) where the more heavy-tailed the workload, the greater the improvement factor. We evaluate the tradeoff between improvement in slowdown and increase in waiting time in a system using SITA-V, and show conditions under which SITA-V represents a particularly appealing policy. We conclude with a discussion of the use of SITA-V in a distributed Web server, and show that it is attractive because it has a simple implementation which requires no communication from the server hosts back to the task router.