Application Areas
Application Areas
Today we’re thrilled to announce that we’ve been awarded a grant from the Bill & Melinda Gates Foundation to build an open-access, AI-enabled measles forecasting model to empower proactive public health measures, such as immunization campaigns, in partnership with Northeastern University researchers Alessandro Vespignani and Sam Scarpino.
While the widespread availability of measles vaccines has dramatically reduced the disease burden over the past several decades, cases are on the rise in the U.S. this year, and global outbreaks continue to cause significant illness and mortality, particularly in low- and middle-income countries. These consequences are largely preventable through early interventions, but getting ahead of major outbreaks is difficult when access to data is limited.
With support from the Gates Foundation, expert epidemiologists and modelers from Ginkgo Bioworks and Northeastern University will develop a measles forecasting model to assess the risk of outbreaks and inform decision-making for timely interventions. Because measles reporting is often sparse, especially in low-resource settings, the model will draw upon traditional and non-traditional data, including public health reports, travel patterns, economic activity, and other factors, and utilize AI approaches such as machine learning and deep learning to structure and analyze a multitude of data sources to produce actionable insights.
“With support from the Gates Foundation, our project with Ginkgo Bioworks sets a new standard for what can be achieved when academia, industry, and philanthropy come together to develop global health solutions. By bringing together the expertise of multiple sectors and modern AI capabilities, we can create powerful, innovative tools that will provide critical information for safeguarding communities worldwide against the threat of measles.” - Alessandro Vespignani, Director of the Network Science Institute and Sternberg Family Distinguished Professor at Northeastern University
The forecasting model will be available open-access to help the global health community understand how likely it is that measles will emerge and spread within a given area, with the intent of enabling them to better allocate scarce resources and reduce the global burden of measles.
If we wait until large pockets of measles show up in hospital systems to launch public health responses, we are missing a critical window to act and slow the spread of this debilitating and highly contagious disease. Modern data and AI tools can shift the biosecurity and public health paradigm from reactive to proactive by helping global health leaders make more timely, effective decisions to prevent outbreaks from happening in the first place.
Posted by Matthew McKnight