A Method to Identify the Missing COVID-19 Cases in the U.S. and Results for mid-April 2020
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Abstract
I use the COVID-19 death rate in South Korea and a method relating the ratio of death rates in a U.S. state to its share of cumulative positive tests to estimate the total cases of COVID-19 in the U.S. and to estimate the extent of infection and the unidentified share of the infected population in each of the lower-48 states and in New York City in mid-April, 2020. I identify a logarithmic relationship between the cumulative death rate in a state and its cumulative positive share of tests. Using this relationship, I find that 4.3-5.4 million people, 1.4-1.7% of the U.S. population, were infected, with rates of infection that ranged from 0.1% in more rural states to 8-10% in New York state and 11-13% in New York City. Only 16-20% of these infected individuals were identified later through testing.
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SciScore for 10.1101/2020.04.28.20083782: (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: 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: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.Results from TrialIdentifier: No clinical trial numbers were referenced.
Results from Barzooka: We did not find any issues relating to the usage of bar …
SciScore for 10.1101/2020.04.28.20083782: (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: 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: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.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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