ArticleScientific reports2021
A differential equations model-fitting analysis of COVID-19 epidemiological data to explain multi-wave dynamics.
Article in Scientific reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
7 citing papers in PubMed, 32 citations in OpenAlex.
- Predicting the evolutionary and epidemiological dynamics of SARS-CoV-2 in South Africa.Virulence · 2025Article
- Study on the impact of COVID-19 epidemic and agent disease risk simulation model based on individual factors in Xi'an City.Frontiers in cellular and infection microbiology · 2025Article
- On fast simulation of dynamical system with neural vector enhanced numerical solver.Scientific reports · 2023Article
- Attention based parameter estimation and states forecasting of COVID-19 pandemic using modified SIQRD Model.Chaos, solitons, and fractals · 2022Article
- Comparative Dynamics of Delta and Omicron SARS-CoV-2 Variants across and between California and Mexico.Viruses · 2022Article
- Article
- Editorial: Epidemiological considerations in COVID-19 forecasting.Frontiers in epidemiology · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Compartmental epidemiological models are, by far, the most popular in the study of dynamics related with infectious diseases. It is, therefore, not surprising that they are frequently used to study the current COVID-19 pandemic. Taking advantage of the real-time availability of COVID-19 related data, we perform a compartmental model fitting analysis of the portuguese case, using an online open-access platform with the integrated capability of solving systems of differential equations. This analysis enabled the data-driven validation of the used model and was the basis for robust projections of different future scenarios, namely, increasing the detected infected population, reopening schools at different moments, allowing Easter celebrations to take place and population vaccination. The method presented in this work can easily be used to perform the non-trivial task of simultaneously fitting differential equation solutions to different epidemiological data sets, regardless of the model or country that might be considered in the analysis.
Indexed as
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.