Short-term forecasting of the coronavirus pandemic

Jurgen Doornik, Jennifer Castle and David Hendry

International Journal of Forecasting, 2022, vol. 38, issue 2, 453-466

Abstract: We have been publishing real-time forecasts of confirmed cases and deaths from coronavirus disease 2019 (COVID-19) since mid-March 2020 (published at www.doornik.com/COVID-19). These forecasts are short-term statistical extrapolations of past and current data. They assume that the underlying trend is informative regarding short-term developments but without requiring other assumptions about how the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus is spreading, or whether preventative policies are effective. Thus, they are complementary to the forecasts obtained from epidemiological models.

Keywords: Automatic forecasting; COVID-19; Epidemiology; Forecasting; Forecast averaging; Machine learning; Smoothing; Time series; Trend indicator saturation (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (8)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:intfor:v:38:y:2022:i:2:p:453-466

DOI: 10.1016/j.ijforecast.2020.09.003

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