BayesSMILES: Bayesian Segmentation Modeling for Longitudinal Epidemiological Studies
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Abstract
The coronavirus disease of 2019 (COVID-19) is a pandemic. To characterize its disease transmissibility, we propose a Bayesian change point detection model using daily actively infectious cases. Our model builds on a Bayesian Poisson segmented regression model that can 1) capture the epidemiological dynamics under the changing conditions caused by external or internal factors; 2) provide uncertainty estimates of both the number and locations of change points; and 3) adjust any explanatory time-varying covariates. Our model can be used to evaluate public health interventions, identify latent events associated with spreading rates, and yield better short-term forecasts.
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SciScore for 10.1101/2020.10.06.20208132: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
NIH rigor criteria are not applicable to paper type.Table 2: Resources
Experimental Models: Organisms/Strains Sentences Resources The vector bk = (b1,k, …, bp,k)T is a p-dimensional column vector of segment-specified coefficients that includes an intercept representing the proportion of infectious people at logarithmic scale, i.e. b1,k = log(I0/N), in segment k, and a slope accounting for the time-varying disease transmission rate, i.e. b2,k = βt−γ. b1suggested: NoneResults from OddPub: Thank you for sharing your code.
Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.Res…
SciScore for 10.1101/2020.10.06.20208132: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
NIH rigor criteria are not applicable to paper type.Table 2: Resources
Experimental Models: Organisms/Strains Sentences Resources The vector bk = (b1,k, …, bp,k)T is a p-dimensional column vector of segment-specified coefficients that includes an intercept representing the proportion of infectious people at logarithmic scale, i.e. b1,k = log(I0/N), in segment k, and a slope accounting for the time-varying disease transmission rate, i.e. b2,k = βt−γ. b1suggested: NoneResults from OddPub: Thank you for sharing your code.
Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.Results from TrialIdentifier: No clinical trial numbers were referenced.
Results from Barzooka: We did not find any issues relating to the usage of bar graphs.
Results from JetFighter: We did not find any issues relating to colormaps.
Results from rtransparent:- Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
- Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
- No protocol registration statement was detected.
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