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

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 presen...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:NPJ digital medicine 2021-10, Vol.4 (1), p.146-146, Article 146
Hauptverfasser: Arık, Sercan Ö., Shor, Joel, Sinha, Rajarishi, Yoon, Jinsung, Ledsam, Joseph R., Le, Long T., Dusenberry, Michael W., Yoder, Nathanael C., Popendorf, Kris, Epshteyn, Arkady, Euphrosine, Johan, Kanal, Elli, Jones, Isaac, Li, Chun-Liang, Luan, Beth, Mckenna, Joe, Menon, Vikas, Singh, Shashank, Sun, Mimi, Ravi, Ashwin Sura, Zhang, Leyou, Sava, Dario, Cunningham, Kane, Kayama, Hiroki, Tsai, Thomas, Yoneoka, Daisuke, Nomura, Shuhei, Miyata, Hiroaki, Pfister, Tomas
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung: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
ISSN:2398-6352
2398-6352
DOI:10.1038/s41746-021-00511-7