5 Matching Annotations
  1. Sep 2020
  2. www.medrxiv.org www.medrxiv.org
    COVID-19 scenarios for the United States
    1
    1. ErikStuchly 07 Sep 2020

      Team, I. C.-19 F., & Hay, S. I. (2020). COVID-19 scenarios for the United States. MedRxiv, 2020.07.12.20151191. https://doi.org/10.1101/2020.07.12.20151191

      is:preprint lang:en COVID-19 scenario analysis modeling USA prediction epidemiology transmission compartmental model mortality intervention efficacy face mask safety measure public health
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    medrxiv.org/cgi/content/10.1101/2020.07.12.20151191
  3. Aug 2020
  4. www.pnas.org www.pnas.org
    A network-based explanation of why most COVID-19 infection curves are linear
    1
    1. Danaeioak 28 Aug 2020

      Thurner, S., Klimek, P., & Hanel, R. (2020). A network-based explanation of why most COVID-19 infection curves are linear. Proceedings of the National Academy of Sciences. https://doi.org/10.1073/pnas.2010398117

      is:article lang:en COVID-19 compartmental mean-field (well mixed) approximation social contact network network theory epidemiology modeling
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    pnas.org/content/early/2020/08/21/2010398117
  5. Jul 2020
  6. osf.io osf.io
    Disease Detectives: Using Mathematics to Forecast the Spread of Infectious Diseases
    1
    1. ErikStuchly 12 Jul 2020

      Brooks, H. Z., Kanjanasaratool, U., Kureh, Y. H., & Porter, M. A. (2020). Disease Detectives: Using Mathematics to Forecast the Spread of Infectious Diseases [Preprint]. SocArXiv. https://doi.org/10.31235/osf.io/mvn9z

      is:preprint lang:en COVID-19 transmission modeling prediction loosening restrictions policy compartmental model data analysis behavior physical distancing
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    osf.io/preprints/socarxiv/mvn9z/
  7. Jun 2020
  8. statmodeling.stat.columbia.edu statmodeling.stat.columbia.edu
    (Some) forecasting for COVID-19 has failed: a discussion of Taleb and Ioannidis et al. « Statistical Modeling, Causal Inference, and Social Science
    1
    1. katietaylor_99 18 Jun 2020

      Tsolaki, Vasiliki, George E. Zakynthinos, and Dimosthenis Makris. ‘The ARDSnet Protocol May Be Detrimental in COVID-19’. Critical Care 24, no. 1 (December 2020): 351. https://doi.org/10.1186/s13054-020-03081-4.

      is:article lang:en COVID-19 media media-certified experts forcasts compartmental modelling cellular automata estimation decision making predictions unpredictable consequences
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    statmodeling.stat.columbia.edu/2020/06/17/some-forecasting-for-covid-19-has-failed-a-discussion-of-taleb-and-ioannidis-et-al/
  9. wellcomeopenresearch.org wellcomeopenresearch.org
    Dynamic causal modelling of COVID-19
    1
    1. AnyaAgg 14 Jun 2020

      Friston KJ, Parr T, Zeidman P et al. Dynamic causal modelling of COVID-19 [version 1; peer review: awaiting peer review]. Wellcome Open Res 2020, 5:89 (https://doi.org/10.12688/wellcomeopenres.15881.1)

      is:article lang:en COVID coronavirus epidemiology compartmental models dynamic causal modelling variational Bayesian uncertainty interventions neuronal predictions test pandemic estimation
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    wellcomeopenresearch.org/articles/5-89