Methods To Obtain and Incorporate Crowdsourced Data For Improved Public Health

Lecture / Panel
For NYU Community

Speaker: Rumi Chunara, Harvard Medical School


Today, Internet and mobile connectivity have enabled a plethora of new data sources that offer unprecedented opportunities for improving the health of societies. The real-time, quantitative and geo-located data generated through these crowdsourced sensors can improve population-public health surveillance, which suffers from limits due to latency, high cost, inherent contributor biases and imprecise resolution. Simultaneously, the observational and informal nature of these data sources present some common and new computational and engineering challenges; data from these tools is predominately being generated directly by individuals as opposed to laboratories or healthcare systems and thus is generally unstructured, unvalidated and noisy. As well, the data must be integrated in a manner that is sensitive to the disease epidemiology. Thus my research focuses on building new tools for obtaining crowdsourced data and developing computational methods that use inference, natural language processing, time series and network analyses and machine learning, and applies this data to advance current challenges in public health.

In this talk I will discuss how I have obtained data from Internet-connected sensors including social media, mobile phones and point-of-care bio-molecular diagnostics and integrated the data into epidemiological models for a variety of infectious and chronic disease settings. Going beyond assessing correlations, I will demonstrate how we can use these tools for understanding disease incidence and spatio-temporal drivers of disease and health behaviors on a local and real-time basis.


Rumi Chunara is an Instructor at Harvard Medical School. Her research focuses on building novel information sources and computational techniques to describe and predict population-level public health issues. Dr. Chunara received her Ph.D. in Electrical and Medical Engineering at the Harvard-MIT Division of Health Sciences and Technology, her S.M. in Electrical Engineering and Computer Science at MIT and her B.Sc. (Honors) in Electrical Engineering at Caltech. She is a recipient of a Caltech Merit Scholarship, the MIT Presidential Fellowship, and was named an MIT Technology Review Innovator Under 35 in 2014.