ArticleISA transactions2022
Data-driven modeling and forecasting of COVID-19 outbreak for public policy making.
Article in ISA transactions, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers, 2 of them syntheses that pooled it.
What it found
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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
19 citing papers in PubMed, 2 syntheses or guidelines pooled it, 34 citations in OpenAlex.
- Spatio-Temporal COVID-19 Modeling: A Global Systematic Review of Data Integration, Equity, and Lessons for Pandemic Preparedness.International journal of environmental research and public health · 2026Pooled it
- Data-driven strategies for model-informed decision-making during the COVID-19 pandemic: a systematic review.BMJ open · 2026Pooled it
- Estimating vaccine efficacy during open-label follow-up of COVID-19 vaccine trials based on population-level surveillance data.Epidemics · 2024Trial
- A self-driven ESN-DSS approach for effective COVID-19 time series prediction and modelling.Epidemiology and infection · 2024Article
- The epidemic forest reveals the spatial pattern of the spread of acute respiratory infections in Jakarta, Indonesia.Scientific reports · 2024Article
- The Epidemiological and Economic Impact of COVID-19 in Kazakhstan: An Agent-Based Modeling.Healthcare (Basel, Switzerland) · 2023Article
- Article
- Is It Possible to Predict COVID-19? Stochastic System Dynamic Model of Infection Spread in Kazakhstan.Healthcare (Basel, Switzerland) · 2023Article
- Article
- Deep Spatiotemporal Model for COVID-19 Forecasting.Sensors (Basel, Switzerland) · 2022Article
- Disinfection chain: A novel method for cheap reusable and chemical free disinfection of public places from SARS-CoV-2.ISA transactions · 2022Article
- Analysis of COVID-19 Spread in Tokyo through an Agent-Based Model with Data Assimilation.Journal of clinical medicine · 2022Article
- Data-assimilation and state estimation for contact-based spreading processes using the ensemble kalman filter: Application to COVID-19.Chaos, solitons, and fractals · 2022Article
- Space-Distributed Traffic-Enhanced LSTM-Based Machine Learning Model for COVID-19 Incidence Forecasting.Computational intelligence and neuroscience · 2022Article
- Rigorous Policy-Making Amid COVID-19 and Beyond: Literature Review and Critical Insights.International journal of environmental research and public health · 2021Review
- Linear parameter varying model of COVID-19 pandemic exploiting basis functions.Biomedical signal processing and control · 2021Article
- Modeling the COVID-19 Epidemic With Multi-Population and Control Strategies in the United States.Frontiers in public health · 2021Article
- Article
- Understanding Health Care Administrators' Data and Information Needs for Decision Making during the COVID-19 Pandemic: A Qualitative Study at an Academic Health System.MDM policy & practiceArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 4 institutions in 4 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
This paper presents a data-driven approach for COVID-19 modeling and forecasting, which can be used by public policy and decision makers to control the outbreak through Non-Pharmaceutical Interventions (NPI). First, we apply an extended Kalman filter (EKF) to a discrete-time stochastic augmented compartmental model to estimate the time-varying effective reproduction number (R
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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.