Optimizing respiratory virus surveillance networks using uncertainty propagation

Lack of a widespread surveillance network hampers accurate infectious disease forecasting. Here the authors provide a framework to optimize the selection of surveillance site locations and show that accurate forecasting of respiratory diseases for locations without surveillance is feasible.

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Auteurs principaux: Sen Pei, Xian Teng, Paul Lewis, Jeffrey Shaman
Format: article
Langue:EN
Publié: Nature Portfolio 2021
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Q
Accès en ligne:https://doaj.org/article/bd001cfa88104dd3ba7885b7b337e01a
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