Reliable cause-of-mortality data are essential to inform newborn and child survival strategies in Ethiopia, where evidence to understand the causes of death in children is scarce.1 To address this scarcity of data, the Child Health and Mortality Prevention Surveillance (CHAMPS) network is assessing specific causes of death for stillbirths, infants, and children by combining minimally invasive tissue sampling (MITS), clinical information, and information from caregivers as part of the verbal autopsy.2 This surveillance network, with a new site located in eastern Ethiopia has provided detailed information on the chain of events leading up to stillbirth and deaths among young children, as reported by Lola Madrid and colleagues in The Lancet Global Health.
The CHAMPS method is more advanced than a verbal autopsy alone, which is a widely applied cause of death identification process in Ethiopia. Studies have already recognized the limitations of verbal autopsy,
including recall bias and a lack of specificity in regard to causes of death reports. Using verbal autopsy to identify causes of stillbirth and deaths in newborns has been a major challenge. Meanwhile, the CHAMPS network has created a data system that combines health facilities’ data with population-based surveillance systems.
This is an important undertaking that shows the possibility of integrating digital health management information systems with population-based surveillance systems (also known as health and demographic surveillance systems [HDSS]) to generate reliable data for better child health practices.