Nowcasting the spread of SARS-CoV-2

Hagai Rossman; Eran Segal

doi:10.1038/s41564-021-01035-2

Nowcasting the spread of SARS-CoV-2

Hagai Rossman, Eran Segal

Department of Computer Science and Applied Mathematics

Weizmann Institute of Science

Research output: Contribution to journal › Comment/debate › peer-review

Abstract

A statistical framework that integrates data from a fine-scale targeted testing scheme and regular randomized surveillance surveys provides unbiased and fine-grained estimates of key SARS-CoV-2 epidemiological parameters that are critical for real-time policy decision-making.

Original language	English
Pages (from-to)	16-17
Number of pages	2
Journal	Nature Microbiology
Volume	7
Issue number	1
DOIs	https://doi.org/10.1038/s41564-021-01035-2
State	Published - Jan 2022

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Nowcasting the spread of SARS-CoV-2

Abstract

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