Response to COVID-19 with Probabilistic Programming

EasyChair Preprint 6949

2 pages•Date: October 30, 2021

Assem Zhunis, Tung-Duong Mai and Sundong Kim

Abstract

This work provides an end-to-end pipeline to simulate the COVID-19 virus spread and the incurred loss of various non-pharmaceutical interventions.

Keyphrases: COVID-19 spread, SEIRD model, economic impact, policy making, probabilistic programming

Links:

https://easychair.org/publications/preprint/j9mD

BibTeX entry

BibTeX does not have the right entry for preprints. This is a hack for producing the correct reference:

@booklet{EasyChair:6949,
  author    = {Assem Zhunis and Tung-Duong Mai and Sundong Kim},
  title     = {Response to COVID-19 with Probabilistic Programming},
  howpublished = {EasyChair Preprint 6949},
  year      = {EasyChair, 2021}}

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