Novel indicators for evaluating topological threats to populations from pandemics applied to COVID-19
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Abstract
BACKGROUND
To deal with pandemics, evaluating the temporal status of an outbreak is important. However, prevailing standards in this respect are mostly empirical and arbitrary. As an alternative, we focus on a novel approach which configures indicators that evaluate topological threats to populations due to the COVID-19 pandemic.
METHODS
We extended the current PzDom model to calculate a threshold of the model for accelerated growth, an indicator of growth extent Re( v ), covariance Re( s ), a topological number E ( l ), and expected sums of possibly increasing numbers of infected people. We term this the exPzDom model.
RESULTS
The indicators in the exPzDom model adhere well to the empirical dynamics of SARS-CoV-2 infected people and align appropriately with actual policies instituted by the Japanese government.
CONCLUSIONS
The described indicators could be leveraged pursuant of objective evaluation based on mathematics. Further testing of the reliability and robustness of exPzDom model in other pandemic contexts is warranted.
Article activity feed
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SciScore for 10.1101/2020.05.29.20116491: (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:A limitation of this study is that it utilizes new cases of infection as data, not actual onsets of the disease, which would reflect biological dynamics better. Further exploration of the reliability and robustness of the exPzDom model using data from other pandemics is warranted to better develop objective indicators which can be effectively used in decision-making contexts.
Results from TrialIdentifier: No clinical trial numbers were …
SciScore for 10.1101/2020.05.29.20116491: (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:A limitation of this study is that it utilizes new cases of infection as data, not actual onsets of the disease, which would reflect biological dynamics better. Further exploration of the reliability and robustness of the exPzDom model using data from other pandemics is warranted to better develop objective indicators which can be effectively used in decision-making contexts.
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.
- No funding statement was detected.
- No protocol registration statement was detected.
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