Meta-analysis and adjusted estimation of COVID-19 case fatality risk in India and its association with the underlying comorbidities
This article has been Reviewed by the following groups
Discuss this preprint
Start a discussion What are Sciety discussions?Listed in
- Evaluated articles (ScreenIT)
Abstract
Article activity feed
-
-
SciScore for 10.1101/2020.10.08.20209163: (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
Software and Algorithms Sentences Resources Statistical analyses: Statistical analyses were conducted using R (R statistical package version 3.4.0, R Development Core Team [2015], http://www.r-project.org). R Development Coresuggested: (R Project for Statistical Computing, RRID:SCR_001905)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: We detected the following sentences addressing limitations in the study:We agreed with a previous study that this approach is simple, albeit likely to …
SciScore for 10.1101/2020.10.08.20209163: (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
Software and Algorithms Sentences Resources Statistical analyses: Statistical analyses were conducted using R (R statistical package version 3.4.0, R Development Core Team [2015], http://www.r-project.org). R Development Coresuggested: (R Project for Statistical Computing, RRID:SCR_001905)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: We detected the following sentences addressing limitations in the study:We agreed with a previous study that this approach is simple, albeit likely to be superseded when accurate studies to overcome associated limitations become available (14). In addition, asymptomatic cases, testing criteria and capacity further complicate COVID-19 case estimations. Using the random- and fixed-effect models, the estimated aCFR was 1.42 (95% CI 1.19 – 1.70) and 2.97 (95% CI 2.94 – 3.00), respectively. Due to high heterogeneity, estimates using the random-effects model were more likely to represent the true aCFR for India. Previous studies used random-effect models to estimate the CFR of COVID-19 (26, 27) or presented CFR using both random-effects and fixed-effect models (28). Using a random effects model, we ensured that states with high numbers of cases and deaths received more weight compared to states with fewer cases and deaths. For India, the aCFR appeared to be lower than in many European countries. This might be due to the fact that only 6.38% of the population in India was above 65 years of age in 2019 (29). Elderly people (>60 years) have been reported to be at a higher risk of death due to COVID-19 (30, 31). However, many other health and social indicators, changes in the virulence of SARS-CoV2 in regions over time, and country-specific COVID-19 response indicators may be associated with CFR, and this needs to be investigated. Heterogeneity was as high as 99.57% in the effect sizes in state-specific aCFRs (both fixed- and random-effect models), perhaps...
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.
-
