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Comparative assessment of methods for short-term forecasts of COVID-19 hospital admissions in England at the local level

2022; BioMed Central; Volume: 20; Issue: 1 Linguagem: Inglês

10.1186/s12916-022-02271-x

1741-7015

Sophie Meakin, Sam Abbott, Nikos I Bosse, James D. Munday, Hugo Gruson, Joel Hellewell, Katharine Sherratt, Lloyd A. C. Chapman, Kiesha Prem, Petra Klepac, Thibaut Jombart, Gwenan M. Knight, Yalda Jafari, Stefan Flasche, William Waites, Mark Jit, Rosalind M. Eggo, Christian Julián Villabona‐Arenas, Timothy Russell, Graham F. Medley, W. John Edmunds, Nicholas G. Davies, Yang Liu, Stéphane Hué, Oliver J. Brady, Rachael Pung, Kaja Abbas, Amy Gimma, Paul Mee, Akira Endo, Samuel Clifford, Fiona Yueqian Sun, Ciara V. McCarthy, Billy J. Quilty, Alicia Roselló, Frank Sandmann, Rosanna C. Barnard, Adam Kucharski, Simon R. Procter, Christopher I Jarvis, Hamish Gibbs, David Hodgson, Rachel Lowe, Katherine E. Atkins, Mihály Koltai, Carl A. B. Pearson, Emilie Finch, Kerry LM Wong, Matthew Quaife, Kathleen O’Reilly, Damien C. Tully, Sebastian Funk,

Climate Change and Health Impacts

Forecasting healthcare demand is essential in epidemic settings, both to inform situational awareness and facilitate resource planning. Ideally, forecasts should be robust across time and locations. During the COVID-19 pandemic in England, it is an ongoing concern that demand for hospital care for COVID-19 patients in England will exceed available resources.