# Novel coronavirus 2019-nCoV (COVID-19): early estimation of epidemiological parameters and epidemic size estimates

“Novel coronavirus 2019-nCoV (COVID-19): early estimation of epidemiological parameters and epidemic size estimates” (2021), by Jonathan Michael Read et al. Mathematics research paper. Original abstract below, unchanged. No free PDF was found.

- Authors: Jonathan Michael Read, Jessica R. E. Bridgen, Derek A. T. Cummings, Antonia Ying Wai Ho, Chris Jewell
- Published: May 31, 2021
- Field: Mathematics
- DOI: https://doi.org/10.1098/rstb.2020.0265
- Source: https://doi.org/10.1098/rstb.2020.0265

## Abstract

Since first identified, the epidemic scale of the recently emerged novel coronavirus (2019-nCoV) in Wuhan, China, has increased rapidly, with cases arising across China and other countries and regions. using a transmission model, we estimate a basic reproductive number of 3.11 (95%CI, 2.39–4.13); 58–76% of transmissions must be prevented to stop increasing; Wuhan case ascertainment of 5.0% (3.6–7.4); 21022 (11090–33490) total infections in Wuhan 1 to 22 January. Changes to previous version case data updated to include 22 Jan 2020; we did not use cases reported after this period as cases were reported at the province level hereafter, and large-scale control interventions were initiated on 23 Jan 2020; improved likelihood function, better accounting for first 41 confirmed cases, and now using all infections (rather than just cases detected) in Wuhan for prediction of infection in international travellers; improved characterization of uncertainty in parameters, and calculation of epidemic trajectory confidence intervals using a more statistically rigorous method; extended range of latent period in sensitivity analysis to reflect reports of up to 6 day incubation period in household clusters; removed travel restriction analysis, as different modelling approaches (e.g. stochastic transmission, rather than deterministic transmission) are more appropriate to such analyses.

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