Project Summary The Under-5 Mortality Rate (U5MR) is a key and widely-used indicator of child health, but it conceals important information about how this mortality is distributed by age. For better understanding and monitoring of child health, it is critical to examine how the risk of death varies within the 0-5 age range. This includes age breakdowns beyond the standard cut-off points of 28 days (for neonatal mortality) and 1 year (for infant mortality). In many populations, however, the age pattern of under-5 mortality is not well known. Less- developed countries, in particular, lack the high-quality detailed vital registration information necessary for the analysis of such age patterns. Sample surveys collecting retrospective birth histories do not satisfactorily fill this gap, because they are subject to systematic biases that are particularly consequential for estimating age patterns. This makes the need for high-quality information on age patterns of under-5 mortality even more critical, because regularities in these age patterns can be used as a powerful tool for evaluating and correcting data when sources are deficient. In the parent project of this competing revision application, we are improving our understanding of age patterns of under-5 mortality by: gathering the largest database to date on high- quality global mortality information by detailed age (by days, weeks, months, and years of age) from birth until age 5, by sex; developing models summarizing regularities about how under-5 mortality is distributed by detailed age in human populations; using these models for evaluating and correcting under-5 mortality information by detailed age in less-developed countries; addressing specific substantive questions about how and why age patterns of under-5 mortality vary by sex, time, and place, with important programmatic implications. The goal of this administrative supplement project is to expand the aims of the parent project by tracking and retrospectively obtaining a pregnancy and birth history (as used in the DHS) with selected participants (live births, stillbirths and neonatal deaths) from a prospective pregnancy cohort study in rural Nepal. This will help us determine if the DHS over or underestimates neonatal mortality and whether misclassification of stillbirths and early neonatal deaths plays a role. These results will add to the literature on the validity of DHS vital event estimation.