Aggregating computational models and human judgment for more accurate forecasts of the US COVID-19 outbreak
Midas Coordination Center Urgent Grant Program – New Initiatives
People: Thomas McAndrew
2020 – 2021
Thomas McAndrew
Assistant Professor
Education
Affiliations
Projects
STATISTICAL METHODS FOR REAL-TIME FORECASTS OF INFECTIOUS DISEASE: DYNAMIC TIME-SERIES AND MACHINE LEARNING APPROACHES
National Institutes of Health, National Institute of General Medical Sciences
People: Nutcha Wattanachit, Thomas McAndrew, Nicholas Reich, Teresa Yamana, Evan Ray
2016 – 2021
Papers
McAndrew TC, Reich NG. (2020). An expert judgment model to predict early stages of the COVID-19 outbreak in the United States. medRxiv : the preprint server for health sciences
McAndrew T, Wattanachit N, Gibson GC, Reich NG. (2020). Aggregating predictions from experts: a review of statistical methods, experiments, and applications. Wiley interdisciplinary reviews. Computational statistics, 13(2)
McAndrew TC, Guseva EA, Bagrow JP. (2017). Reply & Supply: Efficient crowdsourcing when workers do more than answer questions. PLoS One, 12(8)
McAndrew TC, Danforth CM, Bagrow JP. (2015). Robustness of spatial micronetworks. Physical review. E, Statistical, nonlinear, and soft matter physics, 91(4)
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