Leveraging Data Science for Global Health

• Corporate Author: SpringerLink (Online service)
• Other Authors: Celi, Leo Anthony (Editor), Majumder, Maimuna S. (Editor), Ordóñez, Patricia (Editor), Osorio, Juan Sebastian (Editor), Paik, Kenneth E. (Editor), Somai, Melek (Editor)
• Format: Electronic eBook
• Language: English
• Published: Cham : Springer International Publishing : Imprint: Springer, 2020.
• Edition: 1st ed. 2020.
• Subjects: Medical informatics.; Medical economics.; Health Informatics.; Health Economics.
• Online Access: Link to Metadata

This open access book explores ways to leverage information technology and machine learning to combat disease and promote health, especially in resource-constrained settings. It focuses on digital disease surveillance through the application of machine learning to non-traditional data sources. Developing countries are uniquely prone to large-scale emerging infectious disease outbreaks due to disruption of ecosystems, civil unrest, and poor healthcare infrastructure - and without comprehensive surveillance, delays in outbreak identification, resource deployment, and case management can be catastrophic. In combination with context-informed analytics, students will learn how non-traditional digital disease data sources - including news media, social media, Google Trends, and Google Street View - can fill critical knowledge gaps and help inform on-the-ground decision-making when formal surveillance systems are insufficient.