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α: calibrated so average coauthorship-adjusted count equals average raw count
Using nationwide longitudinal household survey data from rural Kenya (1997–2004) and Zambia (2001–2004), we estimate probit models to identify the socio-economic correlates of disease-related mortality of individuals between the ages of 15 and 59. We compare these results with the rural sample of the Demographic Health Surveys (DHS) from Kenya and Zambia. Our findings show no clear relationship between wealth status, education, and the probability of mortality. With the roll-out of anti-retroviral drugs it is likely that the relationship between mortality and HIV status is no longer straight forward. It is likely that the disease has spread broadly into all socio-economic groups and that a range of transmission pathways, including ones driven by both wealth and poverty, are now at play.