A Prediction Model to Prioritize Individuals for a SARS-CoV-2 Test Built from National Symptom Surveys
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SciScore for 10.1101/2020.05.18.20105569: (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
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:While informative, our feature contribution analysis has several limitations. First, we did not include children in our datasets and thus, symptoms such as nausea or vomiting and diarrhea that were mostly described in children (7,8), may have a more significant part in models designed for younger age groups. Second, although we included a large set of prior medical conditions that may have a role in COVID-19 susceptibility, some of …
SciScore for 10.1101/2020.05.18.20105569: (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
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:While informative, our feature contribution analysis has several limitations. First, we did not include children in our datasets and thus, symptoms such as nausea or vomiting and diarrhea that were mostly described in children (7,8), may have a more significant part in models designed for younger age groups. Second, although we included a large set of prior medical conditions that may have a role in COVID-19 susceptibility, some of these conditions are not highly prevalent in our dataset and their contribution may thus be underestimated in our model. Finally, body temperature was the only non-mandatory question in our survey, and may thus have higher predictive power than portrayed within our model. Several studies attempted to simulate and predict different aspects of COVID-19, such as hospital admissions, diagnosis, prognosis and mortality risk, using mostly age, body temperature, medical tests and symptoms (19). Most diagnostic models published to date were based on datasets from China and included complex features that had to be extracted through blood tests and imaging scans (19). In this work, we devised a prediction model which was based solely on self-reported information, and as such it could be easily deployed and used instantly in other countries. Our study has several additional limitations. First, our data is biased by Israel’s MOH ever changing testing policy, such that at some point all of the COVID-19 positively diagnosed participants in our study had to be el...
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.
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