ArticleNPJ digital medicine2021
A prospective evaluation of AI-augmented epidemiology to forecast COVID-19 in the USA and Japan.
Article in NPJ digital medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 2 of them syntheses that pooled it.
What it found
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
17 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Data-driven strategies for model-informed decision-making during the COVID-19 pandemic: a systematic review.BMJ open · 2026Pooled it
- Machine Learning Used in Communicable Disease Control: A Scoping Review.Public health reviews · 2026Pooled it
- Global, regional, and National burden of hepatitis C from 1990 to 2021 and projections until 2030.BMC infectious diseases · 2025Article
- AI Methods Tailored to Influenza, RSV, HIV, and SARS-CoV-2: A Focused Review.Pathogens (Basel, Switzerland) · 2025Review
- Integrating artificial intelligence with mechanistic epidemiological modeling: a scoping review of opportunities and challenges.Nature communications · 2025Article
- Towards Improved XAI-Based Epidemiological Research into the Next Potential Pandemic.Life (Basel, Switzerland) · 2024Review
- Forecasting COVID-19 spreading through an ensemble of classical and machine learning models: Spain's case study.Scientific reports · 2023Article
- Network Biology and Medicine to Rescue: Applications for Retinal Disease Mechanisms and Therapy.Advances in experimental medicine and biology · 2023Article
- Article
- Innovative applications of artificial intelligence in zoonotic disease management.Science in One Health · 2023Review
- National and subnational short-term forecasting of COVID-19 in Germany and Poland during early 2021.Communications medicine · 2022Article
- Explanation of hand, foot, and mouth disease cases in Japan using Google Trends before and during the COVID-19: infodemiology study.BMC infectious diseases · 2022Article
- Algorithmic fairness in pandemic forecasting: lessons from COVID-19.NPJ digital medicine · 2022Review
- On the accuracy of Covid-19 forecasting methods in Russia for two years.Procedia computer science · 2022Article
- The projections of global and regional rheumatic heart disease burden from 2020 to 2030.Frontiers in cardiovascular medicine · 2022Article
- Analyzing Patient Trajectories With Artificial Intelligence.Journal of medical Internet research · 2021Article
- Mobility Patterns in Different Age Groups in Japan during the COVID-19 Pandemic: a Small Area Time Series Analysis through March 2021.Journal of urban health : bulletin of the New York Academy of Medicine · 2021Article
Corrections and comments
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Authors and funding
29 authors.
Funding
No grant is acknowledged in the PubMed record.
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 demographic differences across different geographic locations. We further demonstrate that our framework provides meaningful explanatory insights with the models accurately adapting to local and national policy interventions. Our framework enables counterfactual simulations, which indicate continuing Non-Pharmaceutical Interventions alongside vaccinations is essential for faster recovery from the pandemic, delaying the application of interventions has a detrimental effect, and allow exploration of the consequences of different vaccination strategies. The COVID-19 pandemic remains a global emergency. In the face of substantial challenges ahead, the approach presented here has the potential to inform critical decisions.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.