The Global Network Neonatal Cause of Death algorithm for low-resource settings

Area of Science:

• Global Health
• Neonatal Medicine
• Epidemiology

Background:

• Neonatal mortality disproportionately affects low-resource areas, accounting for 98% of global deaths.
• Accurate identification of causes of death is crucial for developing effective public health strategies.

Purpose of the Study:

• To estimate the causes of neonatal death in low-resource settings using a validated algorithm.
• To assess the reliability of the Global Network Cause of Death algorithm in diverse populations.

Main Methods:

• A prospective cohort study enrolled women in six low-resource countries (India, Pakistan, Guatemala, DRC, Kenya, Zambia) from 2014-2016.
• Data on antenatal care, delivery, and newborn outcomes up to 28 days were collected via questionnaires and clinical examinations.
• The Global Network Cause of Death algorithm was applied to assign causes of neonatal mortality.

Main Results:

• Suspected infection (33.1%), prematurity (30.8%), and birth asphyxia (21.2%) were the primary causes of neonatal death.
• Deaths from prematurity and asphyxia were concentrated on the first day of life.
• Infection-related deaths predominantly occurred after the first day of life.

Conclusions:

• The Global Network Cause of Death algorithm is a reliable tool for determining neonatal mortality causes in resource-limited environments.
• Findings can inform targeted public health interventions to reduce neonatal mortality.