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

ABSTRACT:

Background

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.

Methods

We made weekly forecasts of daily COVID-19 hospital admissions for National Health Service (NHS) Trusts in England between August 2020 and April 2021 using three disease-agnostic forecasting models: a mean ensemble of autoregressive time series models, a linear regression model with 7-day-lagged local cases as a predictor, and a scaled convolution of local cases and a delay distribution. We compared th

SUBMITTER: Meakin S 

PROVIDER: S-EPMC8858706 | biostudies-literature | 2022 Feb

REPOSITORIES: biostudies-literature