Welcome to metaCOVID!

metaCOVID is an R-Shiny application that runs in parallel to the COVID-NMA initiative. The aim of this application is to allow all the end-users of the COVID-NMA platform to perform their own meta-analyses through a user-friendly environment. All data-analyses are based on the COVID-NMA latest database. COVID-NMA is an international research initiative supported by the WHO and Cochrane.

For 2023, COVID-NMA revised its protocol and reduced its scope. We stopped including pharmacological treatments and prime vaccines. The database embedded in metaCOVID includes trials identified and included up to the last search date shown at the bottom of each forest plot.

You can perform meta-analysis for all treatment comparisons through the menu 'COVID-19 treatments'. Once you enter the menu you can start the analysis by selecting a treatment comparison and an outcome of interest. Once the forest plot is generated you can further adjust it to your preferences by using the rest of the options that are available.

You can perform meta-analysis for all vaccines through the menu 'COVID-19 vaccines'. Once you enter the menu you can start the analysis by selecting a vaccine type and an outcome of interest. Once the forest plot is generated you can further adjust it to your preferences by using the rest of the options that are available.

You can find details about our latest database updates here. . Last database update at 23/02/2023.

COVID-NMA platform

Welcome to metaCOVID!

For 2023, COVID-NMA revised its protocol and reduced its scope. We stopped including pharmacological treatments and prime vaccines. The database embedded in metaCOVID includes trials identified and included up to the last search date shown at the bottom of each forest plot.

Statistician-metaCOVID Developer

Theodoros Evrenoglou

COVID-NMA Leader

Prof. Isabelle Boutron

COVID-NMA Senior Statistician

Dr. Anna Chaimani

Select options

Select a treatment comparison

Select an outcome

Data Table

Click here: Comparisons not updated by COVID-NMA

Treatment comparisons not updated by COVID-NMA

Analysis options

Type of model

Heterogeneity estimator

Subgroup analysis

Sensitivity analysis

Risk of bias

Exclude preprints

Missing outcome data

Hartung-Knapp adjustment

Pooled results for odds ratio across different models

Pooled results for odds ratio across different models

Studies with zero events in one or all treatment arms are taken into account

Penalized likelihood, Mantel-Haenszel and Peto methods are more suitable for the analysis of rare events

Presentation options

Hide treatment dose

Hide population severity

Forest plot

References

1. Viechtbauer W (2010). 'Conducting meta-analyses in R with the metafor package.' Journal of Statistical Software, 36(3), 1-48. https://doi.org/10.18637/jss.v036.i03.

2. Balduzzi S, Ruecker G, Schwarzer G (2019). 'How to perform a meta-analysis with R: a practical tutorial.' Evidence-Based Mental Health, 153-160.

Select options

Select a type of vaccine

Select an outcome

Data Table

Analysis options

Type of model

Heterogeneity estimator

Include pooled results

Sensitivity analysis

Risk of bias

Exclude preprints

Hartung-Knapp adjustment

Pooled results for odds ratio across different models

Pooled results for odds ratio across different models

Studies with zero events in one or all treatment arms are taken into account

Penalized likelihood, Mantel-Haenszel and Peto methods are more suitable for the analysis of rare events

Forest plot

References

1. Viechtbauer W (2010). 'Conducting meta-analyses in R with the metafor package.' Journal of Statistical Software, 36(3), 1-48. https://doi.org/10.18637/jss.v036.i03.

2. Balduzzi S, Ruecker G, Schwarzer G (2019). 'How to perform a meta-analysis with R: a practical tutorial.' Evidence-Based Mental Health, 153-160.

Cite metaCOVID

For comments/queries on the metaCOVID application please contact us at: tevrenoglou@gmail.com