Measuring Icebergs: Using Different Methods to Estimate the Number of COVID-19 Cases in Portugal and Spain
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Abstract
The world is suffering from a pandemic called COVID-19, caused by the SARS-CoV-2 virus. The different national governments have problems evaluating the reach of the epidemic, having limited resources and tests at their disposal. Hence, any means to evaluate the number of persons with symptoms compatible with COVID-19 with reasonable level of accuracy is useful. In this paper we present the initial results of the @CoronaSurveys project. The objective of this project is the collection and publication of data concerning the number of people that show symptoms compatible with COVID-19 in different countries using open anonymous surveys. While this data may be biased, we conjecture that it is still useful to estimate the number of infected persons with the COVID-19 virus at a given point in time in these countries, and the evolution of this number over time. We show here the initial results of the @CoronaSurveys project in Spain and Portugal.
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SciScore for 10.1101/2020.04.20.20073056: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
Institutional Review Board Statement not detected. Randomization not detected. Blinding not detected. Power Analysis not detected. Sex as a biological variable 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:In this first report we draw attention to the limitations of relying only on confirmed cases to measure the true size of a growing pandemic. From existing data it is possible to derive other measures, and, surprisingly, it is also possible to do simple surveying approaches that, while simple and maybe crude, are clearly non …
SciScore for 10.1101/2020.04.20.20073056: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
Institutional Review Board Statement not detected. Randomization not detected. Blinding not detected. Power Analysis not detected. Sex as a biological variable 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:In this first report we draw attention to the limitations of relying only on confirmed cases to measure the true size of a growing pandemic. From existing data it is possible to derive other measures, and, surprisingly, it is also possible to do simple surveying approaches that, while simple and maybe crude, are clearly non invasive of privacy, and still get meaningful data. In particular @CoronaSurveys can be relevant in countries with a decent digital infrastructure but lacking in laboratory resources. When measuring icebergs, there are many strategies.
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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