Limited impact of contact tracing in a University setting for COVID-19 due to asymptomatic transmission and social distancing
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SciScore for 10.1101/2021.11.10.21265739: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
Ethics not detected. Sex as a biological variable not detected. Randomization not detected. Blinding not detected. Power Analysis not detected. Table 2: Resources
No key resources detected.
Results from OddPub: Thank you for sharing your code and data.
Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:Further limitations of the model are that alters are not connected, and the assumption is made that social networks are isolated from each other, where in reality population level connections do exist. More extensive data collection such as that done by the SCS, where respondents reported which of their contacts had met each other, would provide …
SciScore for 10.1101/2021.11.10.21265739: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
Ethics not detected. Sex as a biological variable not detected. Randomization not detected. Blinding not detected. Power Analysis not detected. Table 2: Resources
No key resources detected.
Results from OddPub: Thank you for sharing your code and data.
Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:Further limitations of the model are that alters are not connected, and the assumption is made that social networks are isolated from each other, where in reality population level connections do exist. More extensive data collection such as that done by the SCS, where respondents reported which of their contacts had met each other, would provide information on transitive links. In the absence of these data, algorithms such as preferential attachment, an observed social phenomenon [5, 26], could be used. With regards to population-level networks, more targeted data collection could be conducted on schools or departments within universities [6, 9, 33], collecting information on whole cohort interactions. Data collection on this scale can be expensive and at times impractical, so synthetic social networks can be construct via algorithms. Previous research [16] has modelled COVID-19 transmission assuming a scale-free degree distribution exists at a population level, and investigated how different population-level social restrictions can reduce the critical levels for herd immunity. However, both the SCS and CON-QUEST data suggest that the degree distribution of a university population is power-law distributed only in the tail. Better population-level networks could be constructed through data-driven algorithms, such as exponential random graph models.
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.
Results from scite Reference Check: We found no unreliable references.
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