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Explore the development of a cutting-edge live streaming Lyme disease surveillance tool using Twitter data in this 25-minute conference talk. Discover how public health surveillance can be modernized to address the rising prevalence of Lyme disease in the United States. Learn about the integration of machine learning, Natural Language Processing (NLP), cloud computing, and data visualization techniques to create a nowcasting dashboard. Understand how this automated system geolocates tweets indicating Lyme disease presence in real-time, providing original tweet content, user information, and historical trends for selected locations. Gain insights into how this innovative approach can supplement traditional surveillance methods, improve operational efficiency in disease monitoring, and facilitate prompt interventions during outbreaks. Delve into the potential of social media data to capture disease prevalence signals and enhance the timeliness of reporting compared to conventional methods.
