A prospective evaluation of AI-augmented epidemiology to forecast COVID-19 in the USA and Japan.

ABSTRACT: The COVID-19 pandemic has highlighted the global need for reliable models of disease spread. We propose an AI-augmented forecast modeling framework that provides daily predictions of the expected number of confirmed COVID-19 deaths, cases, and hospitalizations during the following 4 weeks. We present an international, prospective evaluation of our models' performance across all states and counties in the USA and prefectures in Japan. Nationally, incident mean absolute percentage error (MAPE) for predicting COVID-19 associated deaths during prospective deployment remained consistently <8% (US) and <29% (Japan), while cumulative MAPE remained <2% (US) and <10% (Japan). We show that our models perform well even during periods of considerable change in population behavior, and are robust to de

SUBMITTER: Arık SO 

PROVIDER: S-EPMC8501040 | biostudies-literature | 2021 Oct

REPOSITORIES: biostudies-literature