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SIDIR: Extending SIR with Detected and Isolated Populations for Pandemic Modeling

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Authors: Joe Garman, Sean MacAvaney, Eugene Yang, Ophir Frieder

Appeared in: medRxiv

Links/IDs:
DOI 10.1101/2020.07.20.20157834 Google Scholar 7wWfoDgAAAAJ:ULOm3_A8WrAC Semantic Scholar fa59252ec75d6ae62c17714ecf72b36360459582 smac.pub medrxiv2020-sidir

Abstract:

We extend the Susceptible Infected Recovered (SIR) model to include Detected (D) and Isolated (I) compartments (SIDIR). SIDIR improves COVID-19 outbreak behavior modeling by identifying infected populations as subsequently quarantined to reduce the spread of the infection (either in a hospital or self-quarantined). We present the model and provide a case study on COVID-19. The model estimates undetected cases (i.e., those infected but unconfirmed) and extrapolates when no additional undetected active (rogue) cases will remain, potentially guiding policy decisions that help control the spread of COVID-19 and future epidemics. A live demonstration of SIDIR on COVID-19 is available at: http://ir.cs.georgetown.edu/sidir.

BibTeX @article{garman:medrxiv2020-sidir, author = {Garman, Joe and MacAvaney, Sean and Yang, Eugene and Frieder, Ophir}, title = {SIDIR: Extending SIR with Detected and Isolated Populations for Pandemic Modeling}, year = {2020}, doi = {10.1101/2020.07.20.20157834}, journal = {medRxiv}, volume = {10.1101/2020.07.20.20157834v1} }