ArticleScience advances2023
Using digital traces to build prospective and real-time county-level early warning systems to anticipate COVID-19 outbreaks in the United States.
Article in Science advances, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers, 1 of them a synthesis that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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
26 citing papers in PubMed, 1 synthesis or guideline pooled it, 48 citations in OpenAlex.
- Internet-based Surveillance Systems and Infectious Diseases Prediction: An Updated Review of the Last 10 Years and Lessons from the COVID-19 Pandemic.Journal of epidemiology and global health · 2024Pooled it
- A real-time early warning system to anticipate respiratory disease outbreaks using transfer learning.Nature communications · 2026Article
- Research priorities for improved pandemic and epidemic intelligence.The Lancet. Global health · 2026Review
- Individual and population level uncertainty interact to determine the performance of outbreak surveillance systems.PLoS computational biology · 2026Article
- Uncovering the post-pandemic timing of influenza, RSV, and COVID-19 driving seasonal influenza-like illness in the United States: a retrospective ecological study.Lancet regional health. Americas · 2026Article
- Article
- Can past variants of SARS-CoV-2 predict the impact of future variants? Machine learning for early warning of US counties at risk.Health care management science · 2025Article
- Article
- Nowcasting epidemic trends using hospital- and community-based virologic test data.Nature communications · 2025Article
- From Peer Support to Program Supervision: Qualitative Insights on WhatsApp as Informal Digital Infrastructure for Community Health Workers and Public Health Officers in an Indian High-Priority Aspirational District.Healthcare (Basel, Switzerland) · 2025Article
- The generative revolution: AI foundation models in geospatial health-applications, challenges and future research.International journal of health geographics · 2025Article
- Geosocial Media's Early Warning Capabilities Across US County-Level Political Clusters: Observational Study.JMIR infodemiology · 2025Observational
- Has the COVID-19 pandemic enhanced the capacity of rural public health emergency management? Evidence from Jiangsu Province of China.Frontiers in public health · 2025Article
- An explainable GeoAI approach for the multimodal analysis of urban human dynamics: a case study for the COVID-19 pandemic in Rio de Janeiro.Computational urban science · 2025Article
- How politics affect pandemic forecasting: spatio-temporal early warning capabilities of different geo-social media topics in the context of state-level political leaning.Frontiers in public health · 2025Article
- Asymmetric limits on timely interventions from noisy epidemic data.Communications physics · 2025Article
- How mathematical modelling can inform outbreak response vaccination.BMC infectious diseases · 2024Review
- Mobile health clinics for distribution of vaccinations to underserved communities during health emergencies: A COVID-19 case study.Public health in practice (Oxford, England) · 2024Article
- Emergence of the reproduction matrix in epidemic forecasting.Journal of the Royal Society, Interface · 2024Article
- Innovations in public health surveillance: An overview of novel use of data and analytic methods.Canada communicable disease report = Releve des maladies transmissibles au Canada · 2024Article
Corrections and comments
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Authors and funding
8 authors at 6 institutions in 4 countries.
Funding
Abstract
Coronavirus disease 2019 (COVID-19) continues to affect the world, and the design of strategies to curb disease outbreaks requires close monitoring of their trajectories. We present machine learning methods that leverage internet-based digital traces to anticipate sharp increases in COVID-19 activity in U.S. counties. In a complementary direction to the efforts led by the Centers for Disease Control and Prevention (CDC), our models are designed to detect the time when an uptrend in COVID-19 activity will occur. Motivated by the need for finer spatial resolution epidemiological insights, we build upon previous efforts conceived at the state level. Our methods-tested in an out-of-sample manner, as events were unfolding, in 97 counties representative of multiple population sizes across the United States-frequently anticipated increases in COVID-19 activity 1 to 6 weeks before local outbreaks, defined when the effective reproduction number
Identifiers
What OpenQuestion holds
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.