This open 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.
This open book is licensed under a Creative Commons License (CC BY). You can download Leveraging Data Science for Global Health ebook for free in PDF format (14.3 MB).
Leveraging Data Science for Global Health
This stimulating open access volume details the innovative work of the Pan Institution Network for Global Health in creating collaborative research-based answers to large-scale health issues. Equitable partnerships among member universities representing North America, Africa, Asia, and Europe reverse standard cross-national dynamics to develop loca...
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