Measuring and correcting biased child mortality statistics in countries with generalized epidemics of HIV infection.

Objective: Under Millennium Development Goal 4, countries are required to reduce child mortality by two-thirds between 1990 and 2015. In countries with generalized epidemics of human immunodeficiency virus (HIV) infection, standard statistics based on fertility history may misrepresent progress towards this target owing to the correlation between deaths among mothers and early childhood deaths from acquired immunodeficiency syndrome.

Methods: To empirically estimate this bias, child mortality data and fertility history, including births to deceased women, were collected through prospective household surveys in eastern Zimbabwe during 1998-2005. A mathematical model was then used to investigate the determinants and temporal dynamics of the bias, first in Zimbabwe and then in other countries with different background mortality rates and HIV-related epidemic profiles.

Findings: According to the empirical data, standard cross-sectional survey statistics underestimated true infant and under-5 mortality by 6.7% and 9.8%, respectively. These estimates were in agreement with the output from the model, in which the bias varied according to the magnitude and stage of the epidemic of HIV infection and background mortality rates. The bias was greater the longer the period elapsed before the survey and in later stages of the epidemic. Bias could substantially distort the measured effect of interventions to reduce non-HIV-related mortality and of programmes to prevent mother-to-child transmission, especially when trends are based on data from a single survey.

Conclusion: The correlation between the HIV-related deaths of mothers and their children can bias survey estimates of early child mortality. A mathematical model with a user-friendly interface is available to correct for this bias when measuring progress towards Millennium Development Goal 4 in countries with generalized epidemics of HIV infection.