Leveraging Data Science for Global Health

Leveraging Data Science for Global Health

Health Informatics

Big Data

Digital Disease Surveillance

Health Mapping

Health Records for Non-Communicable Diseases

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.

Leo Anthony Celi (Ed)

Patricia Ordóñez (Ed)

Juan Sebastian Osorio (Ed)

Maimuna S. Majumder (Ed)

Kenneth E. Paik (Ed)

Melek Somai (Ed)

https://link.springer.com/book/10.1007/978-3-030-47994-7#about

Springer, Cham

2020

Shiefti Dyah

http://creativecommons.org/licenses/by/4.0/

PDF

English

Textbooks

https://doi.org/10.1007/978-3-030-47994-7

ISBN 978-3-030-47994-7

Public Health