A comparison of short-term probabilistic forecasts for the incidence of COVID-19 using mechanistic and statistical time series models
Nicolas Banholzer; Thomas Mellan; H Juliette T Unwin; Stefan Feuerriegel; Swapnil Mishra; Samir Bhatt · 2023 · arXiv
WASTE classifies this as Negative / Null Result Report · AI classification, approximate
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Abstract (excerpt)
Short-term forecasts of infectious disease spread are a critical component in risk evaluation and public health decision making. While different models for short-term forecasting have been developed, open questions about their relative performance remain. Here, we compare short-term probabilistic forecasts of popular mechanistic models based on the renewal equation with forecasts of statistical time series models. Our empirical comparison is based on data of the daily incidence of COVID-19 across six large US states over the first pandemic year. We find that, on average, probabilistic forecast
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Metadata source: arXiv