A machine learning model for nowcasting epidemic incidence

DOI10.1016/j.mbs.2021.108677zbMath1482.92011OpenAlexW3215014065MaRDI QIDQ2118464

Srinivasan Parthasarathy, Saket Gurukar, Saumya Yashmohini Sahai, Wasiur R. KhudaBukhsh, Grzegorz A. Rempała

Publication date: 22 March 2022

Published in: Mathematical Biosciences (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.mbs.2021.108677

zbMATH Keywords

nowcastingrandom forestCOVID-19 incidencebackfilling

Mathematics Subject Classification ID

Epidemiology (92D30) Computational methods for problems pertaining to biology (92-08) Mathematical modeling or simulation for problems pertaining to biology (92-10)

Uses Software

• CausalImpact

Cites Work

• Inferring causal impact using Bayesian structural time-series models
• Adjustments for Reporting Delays and the Prediction of Occurred but Not Reported Events
• Multivariate hierarchical frameworks for modeling delayed reporting in count data
• Random forests

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