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Essential epidemiological parameters of COVID-19 for clinical and mathematical modeling purposes: a rapid review and meta-analysis

FONFRIA, E. S.; VIGO, M. I.; GARCIA-GARCIA, D.; HERRADOR, Z.; NAVARRO, M.; BORDEHORE, C.

2020-06-19 epidemiology
10.1101/2020.06.17.20133587 medRxiv
Show abstract

We present a literature review and meta-analysis of relevant epidemiological parameters (24 for adults, 7 for children) of COVID-19. Standardization of these parameters is key to performing valid clinical and mathematical modeling, as well as forecasts, helping us to improve our understanding about the characteristics and impact of the pandemic.

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The top 8 journals account for 50% of the predicted probability mass.

1
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"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.