Real-time tracking of self-reported symptoms to predict potential COVID-19
This article has been Reviewed by the following groups
Listed in
- Evaluated articles (ScreenIT)
Abstract
Article activity feed
-
SciScore for 10.1101/2020.04.05.20048421: (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
Software and Algorithms Sentences Resources Prior to the modelling, to preserve the sample size, we imputed missing values for the symptoms of interest using missForest package in R 11]. missForestsuggested: (missForest, RRID:SCR_018543)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:Our study also has some limitations. First, all the data collected by us is self-reported. Second, at the moment, we don’t know …
SciScore for 10.1101/2020.04.05.20048421: (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
Software and Algorithms Sentences Resources Prior to the modelling, to preserve the sample size, we imputed missing values for the symptoms of interest using missForest package in R 11]. missForestsuggested: (missForest, RRID:SCR_018543)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:Our study also has some limitations. First, all the data collected by us is self-reported. Second, at the moment, we don’t know whether anosmia was acquired prior to other COVID-19 symptoms, during the illness or afterwards. This information will become available as the App actually tracks over time. Thirdly, the COVID-19 diagnosis is based on the RT-PCR test that has less than 100% sensitivity (true positive rate)13. More accurate tests would provide a more accurate diagnosis and our results might be slightly different. An important caveat is that the individuals on which the model was trained are highly selected because RT-PCR COVID-19 tests are not random. It is that they were tested because they either displayed severe symptoms, were in contact with Covid-19 individuals health workers, or travelled in an area of particular risk. Therefore, we may be overestimating the number of expected positives. Also, the estimates on the prevalence of COVID-19 derived from our model and from self-reported symptoms derived from the members of the public who took part in the app. This has self-selected a group not fully representative of the general population as the sex proportions of our respondents clearly show, with women being much more likely to respond than men and people under 60 representing the majority (>80%) of responders. Our data suggest that anosmia should be added by the World Health Organisation to their COVID-19 symptom list14. In the presence of other symptoms, people ...
Results from TrialIdentifier: No clinical trial numbers were referenced.
Results from Barzooka: We found bar graphs of continuous data. We recommend replacing bar graphs with more informative graphics, as many different datasets can lead to the same bar graph. The actual data may suggest different conclusions from the summary statistics. For more information, please see Weissgerber et al (2015).
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.
-
-
