Increasing concentration of COVID-19 by socioeconomic determinants and geography in Toronto, Canada: an observational study
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SciScore for 10.1101/2021.04.01.21254585: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
Institutional Review Board Statement IRB: Ethics approval: The University of Toronto Health Sciences Research Ethics Board (protocol no. Randomization not detected. Blinding not detected. Power Analysis not detected. Sex as a biological variable not detected. Table 2: Resources
Software and Algorithms Sentences Resources All analyses were conducted in R (version 4.0.2), and spatial maps were generated using ArcGIS (version 10.7). ArcGISsuggested: (ArcGIS for Desktop Basic, RRID:SCR_011081)Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).
Results from LimitationRecognizer: We detected the following …SciScore for 10.1101/2021.04.01.21254585: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
Institutional Review Board Statement IRB: Ethics approval: The University of Toronto Health Sciences Research Ethics Board (protocol no. Randomization not detected. Blinding not detected. Power Analysis not detected. Sex as a biological variable not detected. Table 2: Resources
Software and Algorithms Sentences Resources All analyses were conducted in R (version 4.0.2), and spatial maps were generated using ArcGIS (version 10.7). ArcGISsuggested: (ArcGIS for Desktop Basic, RRID:SCR_011081)Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).
Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:This finding is consistent with data on social networks suggesting variable degrees of assortativity,(40) with connections between social networks through occupation-such as caregivers.(41, 42) The observed pattern of rapid and then persistent concentration of COVID-19 by social determinants, such as household density for example, has been consistent across high-income countries(43, 44) and in several low-and middle-income countries as well.(3, 4) Where reported, occupations not amenable to remote work have also been identified as an important risk factor for COVID-19.(15) In our study setting, essential services workers intersected with multi-generational households suggesting a connection between workplace exposures and those in home communities amplified by high rates of transmission within larger households.(45) These results should be considered in the light of limitations. We relied on area-based measures of the social determinants of health and thus our findings may be subject to ecological fallacy. There are two reassuring elements supporting validity of these findings including the use of the smallest geographical area available (DA) and the congruence of these results with individual data characterizing race and income among people with COVID-19.(46) We were also limited to broad categories with respect to occupation, and thus cannot infer concentration of cases by specific occupational exposures. Finally, these metrics for concentration or inequities are descriptiv...
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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