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Clarifying predictions for COVID-19 from testing data: The example of New York State

With the spread of COVID-19 across the world, a large amount of data on reported cases has become available. We are studying here a potential bias induced by the daily number of tests which may be insufficient or vary over time. Indeed, tests are hard to produce at the early stage of the epidemic an...

Täydet tiedot

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Bibliografiset tiedot
Päätekijät: Quentin Griette, Pierre Magal
Aineistotyyppi: Artigo
Kieli:Inglês
Julkaistu: KeAi Communications Co., Ltd. 2021-01-01
Sarja:Infectious Disease Modelling
Aiheet:
Linkit:http://www.sciencedirect.com/science/article/pii/S2468042721000026
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