The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence) ML and Epidemiology with Elaine Nsoesie - #396
Jul 30, 2020
Elaine Nsoesie, an assistant professor of global health at Boston University, brings her expertise in machine learning and epidemiology to discuss innovative approaches in public health. She delves into how data from social media and search engines can track health behaviors, particularly in African countries. The conversation also highlights the application of satellite imagery to assess obesity rates and the challenges faced by epidemiologists during the COVID-19 pandemic, focusing on health disparities among marginalized communities.
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Elaine's Path to Epidemiology
- Elaine Nsoesie, originally from Cameroon, studied math and pursued applied math due to her interest in health applications.
- Mentored at NIH, she transitioned to statistics at Virginia Tech and then specialized in computational epidemiology.
Restaurant Reviews and Public Health
- In 2014, Nsoesie pioneered using restaurant reviews from platforms like Yelp to track foodborne illnesses.
- This data helped health departments conduct targeted inspections and identify unreported outbreaks, improving public health surveillance.
Satellite Imagery for Disease Tracking
- Nsoesie's research used satellite imagery of hospital parking lots in Mexico, Chile, and Argentina to track influenza-like illnesses.
- Changes in parking lot usage correlated with reported cases, demonstrating a novel approach to disease surveillance.