ArticlePloS one2020
Estimation of COVID-19 spread curves integrating global data and borrowing information.
Article in PloS one, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers.
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Who cites it
26 citing papers in PubMed, 172 citations in OpenAlex.
- Nonlinear mixed models and related approaches in infectious disease modeling: A systematic and critical review.Infectious Disease Modelling · 2025Review
- PTNS: patent citation trajectory prediction based on temporal network snapshots.Scientific reports · 2024Article
- Dynamic fair balancing of COVID-19 patients over hospitals based on forecasts of bed occupancy.Omega · 2023Article
- Developing a Community-Oriented and Place-Based Strategy to Improve COVID-19 Vaccine Accessibility.The Permanente journal · 2023Article
- Richards's curve induced Banach space valued ordinary and fractional neural network approximation.Revista de la Real Academia de Ciencias Exactas, Fisicas y Naturales. Serie A, Matematicas · 2023Article
- A Novel and Accurate Method for Estimating Deaths and Cases During Outbreaks of Infectious Diseases Including COVID-19.International journal of general medicine · 2023Article
- Richards's curve induced Banach space valued multivariate neural network approximation.Arabian journal of mathematics · 2023Article
- Assessing the impact of COVID-19 mass testing in South Tyrol using a semi-parametric growth model.Scientific reports · 2022Article
- A phenomenological model for COVID-19 data taking into account neighboring-provinces effect and random noise.Statistica Neerlandica · 2022Article
- An evaluation of prospective COVID-19 modelling studies in the USA: from data to science translation.The Lancet. Digital health · 2022Review
- Importation, Local Transmission, and Model Selection in Estimating the Transmissibility of COVID-19: The Outbreak in Shaanxi Province of China as a Case Study.Tropical medicine and infectious disease · 2022Article
- Gompertz model in COVID-19 spreading simulation.Chaos, solitons, and fractals · 2022Article
- A stochastic Bayesian bootstrapping model for COVID-19 data.Stochastic environmental research and risk assessment : research journal · 2022Article
- Convex-Concave fitting to successively updated data and its application to covid-19 analysis.Journal of combinatorial optimization · 2022Article
- Association of COVID-19 Lockdown With the Tumor Burden in Patients With Newly Diagnosed Metastatic Colorectal Cancer.JAMA network open · 2021Article
- A particle swarm optimization approach for predicting the number of COVID-19 deaths.Scientific reports · 2021Review
- Nowcasting COVID-19 incidence indicators during the Italian first outbreak.Statistics in medicine · 2021Article
- Comprehensive Survey of Using Machine Learning in the COVID-19 Pandemic.Diagnostics (Basel, Switzerland) · 2021Review
- Real-time forecasting of COVID-19 bed occupancy in wards and Intensive Care Units.Health care management science · 2021Article
- A simple model for the total number of SARS-CoV-2 infections on a national level.Epidemiology and infection · 2021Article
Corrections and comments
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Authors and funding
3 authors at 1 institution in 1 country.
Funding
Abstract
Currently, novel coronavirus disease 2019 (COVID-19) is a big threat to global health. The rapid spread of the virus has created pandemic, and countries all over the world are struggling with a surge in COVID-19 infected cases. There are no drugs or other therapeutics approved by the US Food and Drug Administration to prevent or treat COVID-19: information on the disease is very limited and scattered even if it exists. This motivates the use of data integration, combining data from diverse sources and eliciting useful information with a unified view of them. In this paper, we propose a Bayesian hierarchical model that integrates global data for real-time prediction of infection trajectory for multiple countries. Because the proposed model takes advantage of borrowing information across multiple countries, it outperforms an existing individual country-based model. As fully Bayesian way has been adopted, the model provides a powerful predictive tool endowed with uncertainty quantification. Additionally, a joint variable selection technique has been integrated into the proposed modeling scheme, which aimed to identify possible country-level risk factors for severe disease due to COVID-19.
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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.