Sex disparities in COVID-19 mortality vary considerably across time: The case of New York State
This article has been Reviewed by the following groups
Listed in
- Evaluated articles (ScreenIT)
Abstract
In order to characterize how sex disparities in COVID-19 mortality evolved over time in New York State (NY), we analyzed sex-disaggregated data from the US Gender/Sex COVID-19 Data Tracker from March 14, 2020 to August 28, 2021. We defined six different time periods and calculated mortality rates by sex and mortality rate ratios, both cumulatively and for each time period separately. As of August 28, 2021, 19 227 (44.2%) women and 24 295 (55.8%) men died from COVID-19 in NY. 72.7% of the cumulative difference in the number of COVID-19 deaths between women and men was accrued between March 14 and May 4, 2020. During this period, the COVID-19 mortality rate ratio for men compared to women was 1.56 (95% CI: 1.52-1.61). In the five subsequent time periods, the corresponding ratio ranged between 1.08 (0.98-1.18) and 1.24 (1.15-1.34). While the cumulative mortality rate ratio of men compared to women was 1.34 (1.31-1.37), the ratio equals 1.19 (1.16-1.22) if deaths during the initial COVID-19 surge are excluded from the analysis. This article shows that in NY the magnitude of sex disparities in COVID-19 mortality was not stable across time. While the initial surge in COVID-19 mortality was characterized by stark sex disparities, these were greatly attenuated after the introduction of public health controls.
Article activity feed
-
SciScore for 10.1101/2022.01.11.22269104: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
Ethics not detected. Sex as a biological variable 14, 2020 through August 28, 2021.5 Fatality data reported by the Tracker include all individuals categorized as women or men who died from COVID-19 in NY, as reported by the New York State Department of Health.8 Data used in this analysis were publicly available and de-identified and are exempt from IRB oversight. Randomization not detected. Blinding not detected. Power Analysis 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 …SciScore for 10.1101/2022.01.11.22269104: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
Ethics not detected. Sex as a biological variable 14, 2020 through August 28, 2021.5 Fatality data reported by the Tracker include all individuals categorized as women or men who died from COVID-19 in NY, as reported by the New York State Department of Health.8 Data used in this analysis were publicly available and de-identified and are exempt from IRB oversight. Randomization not detected. Blinding not detected. Power Analysis 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.
Results from scite Reference Check: We found no unreliable references.
-
