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Open Access

Correction

Correction: Bayesian space-time SIR modeling of Covid-19 in two US states during the 2020–2021 pandemic

  • Andrew B. Lawson,
  • Joanne Kim

The Supporting information files are missing labels and captions. Please see the correct Supporting information file labels and captions here.

Supporting information

S1 Fig. Daily case counts. Model risk estimates for SC under model 5A.

https://doi.org/10.1371/journal.pone.0307197.s001

(TIFF)

S2 Fig. Daily case counts. Model risk estimates for NJ model 5B.

https://doi.org/10.1371/journal.pone.0307197.s002

(TIFF)

S3 Fig. 3Day averaged data. Model risk estimates for SC for model 6.

https://doi.org/10.1371/journal.pone.0307197.s003

(TIFF)

S4 Fig. 3Day averaged data. Model risk estimates for NJ for model 6.

https://doi.org/10.1371/journal.pone.0307197.s004

(TIFF)

S5 Fig. Mobility data: Work index. Model risk estimates for SC for model 1.

https://doi.org/10.1371/journal.pone.0307197.s005

(TIFF)

S6 Fig. Mobility data: Work index. Model risk estimates for NJ for model 1.

https://doi.org/10.1371/journal.pone.0307197.s006

(TIFF)

Reference

  1. 1. Lawson AB, Kim J (2022) Bayesian space-time SIR modeling of Covid-19 in two US states during the 2020–2021 pandemic. PLOS ONE 17(12): e0278515. https://doi.org/10.1371/journal.pone.0278515 pmid:36548256

Citation: Lawson AB, Kim J (2024) Correction: Bayesian space-time SIR modeling of Covid-19 in two US states during the 2020–2021 pandemic. PLoS ONE 19(7): e0307197. https://doi.org/10.1371/journal.pone.0307197

Published: July 10, 2024

Copyright: © 2024 Lawson, Kim. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.