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Covid-19

This page contains some current resources for statisticians interested in the COVID-19 pandemic. We give links to some data sources, talks and preprints. The ISI Committee on the Public Voice of Statistics has prepared this page, but neither the Committee nor the ISI have evaluated or are endorsing the analyses.

 

General information:

World Health Organization Coronavirus disease 2019 pages

Oxford University COVID-19 Evidence Service

 

Data:

World Health Organization daily updates. These are the official counts from each country reporting, starting at January 21, 2020.

Johns Hopkins University outbreak map and data.

 

Models:

Tom Britton explains the susceptible-infected-removed (SIR) epidemic model and how social distancing can affect the epidemic curve (36 minutes).

A talk by Xihong Lin, Harvard Biostat, presenting lessons learned from Wuhan about limiting the spread of COVID-19. The main model is a latent SIR model, taking into account that we do not observe the actual cases but only the identified ones (56 minutes; talk starts at 1:10). The preprint is also available.

A preprint by Agosto and Giudici on a Poisson autoregressive model on COVID-19 contagion dynamics, applied to data from China, South Korea and Italy.

A preprint by Riou et al. an age-adjusted fatality of COVID-19 in China Jan-Feb 2020, taking into account under-reporting. Data and Stan code are available.

 

Covid19ita - Italy:

Covid19ita is developed by the Unit of Biostatistics, Epidemiology, and Public Health of the Department of Cardiac, Thoracic and Vascular Sciences and Public Health at Università degli Studi di Padova , in partnership with the Department of Clinical and Biological Sciences at Università degli Studi di Torino , and the Department of Translational Medicine at Università del Piemonte Orientale.

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