The Biostatistics Unit, a recent addition to the technologies and services offered by the German Institute Trias i Puyol (IGTP), is comprised of a team of statisticians and mathematicians who conduct and support biomedical research. They recently published two notable articles. The first paper was scientific report, reveals the role of socio-economic inequalities and vaccination in the spread of the COVID-19 pandemic. The second one was published in BMC Medical Research MethodologyIntroducing REDCapDM, a new R package designed to increase the efficiency and reliability of managing research data collected through the popular REDCap platform.
The impact of COVID-19 in Catalonia: socio-economic inequalities and vaccination
New scientific research published in scientific report Researchers Pau Satra, Cristian Teve and colleagues shed light on the development and impact of the coronavirus pandemic in Catalonia. This analysis uses a spatiotemporal Bayesian model to reveal how viral incidence and hospitalizations have changed over time across different basic health sectors (ABS) and to determine the impact of these trends. We have highlighted the main factors that may have contributed to this.
The findings show that urban areas have higher rates of infection and hospitalization than rural areas, suggesting a link between population density and living conditions in these areas. This highlights the need for specific public health strategies in densely populated urban environments.
The study also points to the influence of socio-economic inequalities on the impact of the pandemic. Hospitalization rates are higher in ABS with higher levels of socio-economic poverty, highlighting how socio-economic conditions can exacerbate the effects of a global health crisis.
One of the most important findings was the protective effect of full vaccination against the virus at the ABS level, indicating the critical importance of vaccination campaigns in fighting the pandemic. Full vaccination has been shown to significantly reduce the risk of infection and hospitalization, making it an important public health tool to control the spread and impact of the virus. message has been reconfirmed.
The study used open data provided by the Government of Catalonia, underscoring the importance of access to reliable and transparent information to advance epidemiological research. The findings of this study not only contribute to a better understanding of the dynamics of COVID-19 at the local level, but also link vaccination interventions and socio-economic inequalities as key elements in an effective response to the pandemic. This highlights the importance of paying attention to
“The use of Bayesian hierarchical modeling was extremely helpful in explaining the spatial, temporal and spatiotemporal trends of the COVID-19 outbreak in Catalonia.”says Pau Satra, lead author of this article. “We know that while urban basic health care areas are at higher risk of COVID-19 infection and hospitalization than rural areas, their socio-economic poverty is a risk factor for hospitalization. “We also demonstrated that vaccination fully covered basic health care areas,” and that there was a protective effect on the risk of coronavirus infection and hospitalization in each region. ”.
REDCapDM: R package for data management in REDCap projects
In this second article, led by João Carmezim and Pau Satorra, IGTP's Biostatistics Division developed REDCapDM. REDCapDM is a new R package aimed at facilitating data management for REDCap projects and is a web application for creating and managing databases and online surveys. REDCap is widely used in clinical research due to its flexibility and security features. However, managing REDCap data through R can be complex and often requires programming effort to maximize efficiency. The REDCapDM package addresses this need and provides specific functionality for importing, transforming, identifying discrepancies, and managing data.
REDCapDM allows researchers to optimize clinical data management processes while ensuring the quality and reliability of the information being analyzed. This tool is of particular interest to data scientists and clinical data managers using REDCap and R, providing a comprehensive solution for research data management tasks.
The implementation of REDCapDM version 4.3.0 in R and its availability through the Comprehensive R Archive Network (CRAN) opens new doors for efficient data management in clinical research. This package not only simplifies the import and processing of data from REDCap to R, but also enhances the data validation process essential for producing high-quality data in research.
The development of REDCapDM represents a step forward in automating and improving data management in clinical research, providing researchers with powerful tools for data analysis and validation. With continued support from the R community and integration with other packages and tools, REDCapDM is poised to become a valuable resource for the global clinical research community.
The implementation of REDCapDM in R version 4.3.0 and its availability via CRAN and Github ensures open access and transparency to this tool, which is essential to the advancement of scientific research. This project is available for all operating systems under the GNU General Public License, version 2, and demonstrates the positive impact of open collaboration and the use of open source technologies in advancing medical research. .
What is an R package?
An R package is a collection of functions, data, and documentation developed to extend the functionality of the R statistical software. Packages enable users to add new analytical techniques, statistical methods, graphics, data import and export capabilities, and more to their R work environment. These packages are created by a community of R users and researchers with the purpose of sharing solutions and facilitating work on specific projects or specific research areas.
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German Trias i Puyol Institute
References:
- Satra, P., Tebe, C. (2024). A Bayesian spatiotemporal analysis of the COVID-19 pandemic in Catalonia. scientific report. doi.org/10.1038/s41598-024-53527-w.
- Karmezim, J. other. (2024) REDCapDM: An R package with a set of data management tools for REDCap projects. BMC Medical Research Methodology. doi.org/10.1186/s12874-024-02178-6.