ArticlePloS one2020
A data-driven model to describe and forecast the dynamics of COVID-19 transmission.
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 20 papers.
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Who cites it
20 citing papers in PubMed.
- Article
- Fitting Early Phases of the COVID-19 Outbreak: A Comparison of the Performances of Used Models.Healthcare (Basel, Switzerland) · 2023Article
- Incorporating variant frequencies data into short-term forecasting for COVID-19 cases and deaths in the USA: a deep learning approach.EBioMedicine · 2023Article
- A machine learning-driven spatio-temporal vulnerability appraisal based on socio-economic data for COVID-19 impact prevention in the U.S. counties.Sustainable cities and society · 2022Article
- Discovering dynamic models of COVID-19 transmission.Transboundary and emerging diseases · 2022Article
- Comparative study of a mathematical epidemic model, statistical modeling, and deep learning for COVID-19 forecasting and management.Socio-economic planning sciences · 2022Article
- A random forest model for forecasting regional COVID-19 cases utilizing reproduction number estimates and demographic data.Chaos, solitons, and fractals · 2022Article
- Automatic system for high-throughput and high-sensitivity diagnosis of SARS-CoV-2.Bioprocess and biosystems engineering · 2022Article
- Interval forecasts of weekly incident and cumulative COVID-19 mortality in the United States: A comparison of combining methods.PloS one · 2022Article
- Pandemic fatigue impact on COVID-19 spread: A mathematical modelling answer to the Italian scenario.Results in physics · 2021Article
- A computational tool for trend analysis and forecast of the COVID-19 pandemic.Applied soft computing · 2021Article
- A classification of countries and regions by degree of the spread of coronavirus based on statistical criteria.Expert systems with applications · 2021Article
- Pandemic risk management using engineering safety principles.Process safety and environmental protection : transactions of the Institution of Chemical Engineers, Part B · 2021Article
- Modeling Early Phases of COVID-19 Pandemic in Northern Italy and Its Implication for Outbreak Diffusion.Frontiers in public health · 2021Article
- Simple discrete-time self-exciting models can describe complex dynamic processes: A case study of COVID-19.PloS one · 2021Article
- Study of the COVID-19 pandemic trending behavior in Israeli cities.IFAC-PapersOnLine · 2021Article
- Article
- Article
- A cohort study of 676 patients indicates D-dimer is a critical risk factor for the mortality of COVID-19.PloS one · 2020Article
- 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
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
This paper proposes a dynamic model to describe and forecast the dynamics of the coronavirus disease COVID-19 transmission. The model is based on an approach previously used to describe the Middle East Respiratory Syndrome (MERS) epidemic. This methodology is used to describe the COVID-19 dynamics in six countries where the pandemic is widely spread, namely China, Italy, Spain, France, Germany, and the USA. For this purpose, data from the European Centre for Disease Prevention and Control (ECDC) are adopted. It is shown how the model can be used to forecast new infection cases and new deceased and how the uncertainties associated to this prediction can be quantified. This approach has the advantage of being relatively simple, grouping in few mathematical parameters the many conditions which affect the spreading of the disease. On the other hand, it requires previous data from the disease transmission in the country, being better suited for regions where the epidemic is not at a very early stage. With the estimated parameters at hand, one can use the model to predict the evolution of the disease, which in turn enables authorities to plan their actions. Moreover, one key advantage is the straightforward interpretation of these parameters and their influence over the evolution of the disease, which enables altering some of them, so that one can evaluate the effect of public policy, such as social distancing. The results presented for the selected countries confirm the accuracy to perform predictions.
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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.