ArticleJournal of medical Internet research2021
Adaptive Susceptible-Infectious-Removed Model for Continuous Estimation of the COVID-19 Infection Rate and Reproduction Number in the United States: Modeling Study.
Article in Journal of medical Internet research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.
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Who cites it
11 citing papers in PubMed, 1 synthesis or guideline pooled it, 20 citations in OpenAlex.
- Gauging the Impact of Artificial Intelligence and Mathematical Modeling in Response to the COVID-19 Pandemic: A Systematic Review.BioMed research international · 2022Pooled it
- Enhancing Agent-Based Models with Real-Time Movement Data to Assess Impacts of Biosecurity Interventions on Disease Exposure in Healthcare Settings.ACM-BCB ... ... : the ... ACM Conference on Bioinformatics, Computational Biology and Biomedicine. ACM Conference on Bioinformatics, Computational Biology and Biomedicine · 2025Article
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- Temporally Local Maximum Likelihood with Application to SIS Model.Journal of time series econometrics · 2023Article
- Syndromic Surveillance Using Structured Telehealth Data: Case Study of the First Wave of COVID-19 in Brazil.JMIR public health and surveillance · 2023Article
- A Spatiotemporal Solution to Control COVID-19 Transmission at the Community Scale for Returning to Normalcy: COVID-19 Symptom Onset Risk Spatiotemporal Analysis.JMIR public health and surveillance · 2023Article
- Mathematical Models Supporting Control of COVID-19.China CDC weekly · 2022Article
- Modeling COVID-19 Incidence by the Renewal Equation after Removal of Administrative Bias and Noise.Biology · 2022Article
- Modeling Provincial Covid-19 Epidemic Data Using an Adjusted Time-Dependent SIRD Model.International journal of environmental research and public health · 2021Article
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Corrections and comments
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Authors and funding
4 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThe dynamics of the COVID-19 pandemic vary owing to local population density and policy measures. During decision-making, policymakers consider an estimate of the effective reproduction number R
objectiveWe propose a simple method for estimating the time-varying infection rate and the R
methodsWe used a sliding window approach with a Susceptible-Infectious-Removed (SIR) model. We estimated the infection rate from the reported cases over a 7-day window to obtain a continuous estimation of R
resultsThe aSIR model showed an excellent fit for the number of reported COVID-19 cases, and the 1-day forecast mean absolute prediction error was <2.6% across all states. However, the 7-day forecast mean absolute prediction error approached 16.2% and strongly overestimated the number of cases when the R
conclusionsThe aSIR model provides a simple and accurate computational tool for continuous R
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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.