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arxiv: 2004.00117 · v1 · pith:CEHNV7GX · submitted 2020-03-31 · q-bio.PE

Challenges in control of Covid-19: short doubling time and long delay to effect of interventions

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classification q-bio.PE
keywords covid-19interventionsdatadaysdoublingearlyexpectedthree
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Early assessments of the spreading rate of COVID-19 were subject to significant uncertainty, as expected with limited data and difficulties in case ascertainment, but more reliable inferences can now be made. Here, we estimate from European data that COVID-19 cases are expected to double initially every three days, until social distancing interventions slow this growth, and that the impact of such measures is typically only seen nine days - i.e. three doubling times - after their implementation. We argue that such temporal patterns are more critical than precise estimates of the basic reproduction number for initiating interventions. This observation has particular implications for the low- and middle-income countries currently in the early stages of their local epidemics.

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Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score.

  1. Convolutional Sparse Support Estimator Based Covid-19 Recognition from X-ray Images

    eess.IV 2020-05 unverdicted novelty 4.0

    Introduces CSEN, a non-iterative network bridging sparse representation and deep learning, for Covid-19 detection from X-ray images with limited training data.