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Improving Stillbirth and Neonatal Death Data Capture and Quality in Household Surveys: Big-Data Interdisciplinary Advances Using the Every Newborn-Indepth Multi-Country Survey Database

Joseph Akuze Waiswa of Makerere University College of Health Sciences, School of Public Health in Uganda will leverage their dataset on pregnancy outcomes collected by household survey in four African sites to improve the quality of data on stillbirth and neonatal death rates to optimize interventions and investments. Around half the global burden of stillbirths and neonatal deaths occurs in Africa. However, the total numbers are derived from household surveys, and the quality of the data is relatively poor, with missing events and misclassifications of the cause of death. To address this, they recently performed a large-scale multi-site study in Africa to collect relevant household survey data on over 68,000 pregnancies using an Android-based platform. They will further analyze this dataset to identify factors that influence the quality of the data collected, such as the type and structure of the questions, to develop more effective survey questions and inform training for interviewers.

More information about Data Science Approaches to Improve Maternal and Child Health in Africa

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