Shifting the Burden of HIV/AIDS

As the economic burden of HIV/AIDS increases in sub-Saharan Africa, the allocation of the burden among levels and sectors of societies is changing. The private sector has greater scope than government, households, or NGOs to avoid the economic burden of AIDS, and a systematic shifting of the burden away from the private sector is underway. Common practices that shift the AIDS burden from businesses to households and government include pre-employment screening, reduced employee benefits, restructured employment contracts, outsourcing of less skilled jobs, selective retrenchments, and changes in production technologies. In South Africa, more than two thirds of large employers have reduced health care benefits or required larger contributions by employees. Most firms have replaced defined benefit retirement funds, which expose the firm to large annual costs but provide long-term support for families, with defined contribution funds, which eliminate firm risk but provide little to families of younger workers who die of AIDS. Contracting out of previously permanent jobs also shields firms from costs while leaving households and government to care for affected workers and their families. Many of these changes are responses to globalization and would have occurred in the absence of AIDS, but they are devastating for employees with HIV/AIDS. This paper argues that the shifting of the economic burden of AIDS is a predictable response by business to which a thoughtful public policy response is needed. Countries should make explicit decisions about each sector’s responsibilities if a socially desirable allocation is to be achieved.

Determining WWW User's Next Access and Its Application to Pre-fetching

World-Wide Web (WWW) services have grown to levels where significant delays are expected to happen. Techniques like pre-fetching are likely to help users to personalize their needs, reducing their waiting times. However, pre-fetching is only effective if the right documents are identified and if user's move is correctly predicted. Otherwise, pre-fetching will only waste bandwidth. Therefore, it is productive to determine whether a revisit will occur or not, before starting pre-fetching. In this paper we develop two user models that help determining user's next move. One model uses Random Walk approximation and the other is based on Digital Signal Processing techniques. We also give hints on how to use such models with a simple pre-fetching technique that we are developing.