The Citation of Retracted COVID-19 Papers is Common and Rarely Critical

BackgroundRetraction is the final safeguard against research error/misconduct. In principle, retraction exists to prevent serious issues identified in published research through post-publication review. Our study investigated the citing of clinical research papers retracted during the COVID-19 pandemic. MethodsWe used the Retraction Watch database extracted as of 27/01/2022 to identify retracted COVID-19 papers and the Google Scholar citation function to gather a dataset of citations of retracted clinical research. We reviewed key aspects of the citing research. ResultsIn total, the Retraction Watch database included 212 entries for retracted COVID-19 papers. Of these, 53 papers were clinical. There were a total of 1,141 citations of retracted papers, with 105 errors, leaving 1,036 citations to analyze. The majority (86%) of citations were not critical. The majority (80%) of papers citing retracted research were published after the retraction date. ConclusionsThe citation of retracted and withdrawn COVID-19 clinical studies is common, and rarely critical. Most researchers who cite retracted research do not identify that the paper is retracted, even when submitting long after the paper has been withdrawn. This has serious implications for the reliability of published research and the academic literature, which need to be addressed.

Assessing the Burden of COVID-19 in Developing Countries: Systematic Review, Meta-Analysis, and Public Policy Implications

IntroductionThe infection-fatality rate (IFR) of COVID-19 has been carefully measured and analyzed in high-income countries, whereas there has been no systematic analysis of age-specific seroprevalence or IFR for developing countries. MethodsWe systematically reviewed the literature to identify all COVID-19 serology studies in developing countries that were conducted using population representative samples collected by early 2021. For each of the antibody assays used in these serology studies, we identified data on assay characteristics, including the extent of seroreversion over time. We analyzed the serology data using a Bayesian model that incorporates conventional sampling uncertainty as well as uncertainties about assay sensitivity and specificity. We then calculated IFRs using individual case reports or aggregated public health updates, including age-specific estimates whenever feasible. ResultsSeroprevalence in many developing country locations was markedly higher than in high-income countries. In most locations, seroprevalence among older adults was similar to that of younger age cohorts, underscoring the limited capacity that these nations have to protect older age groups. Age-specific IFRs were roughly 2x higher than in high-income countries. The median value of the population IFR was about 0.5%, similar to that of high-income countries, because disparities in healthcare access were roughly offset by differences in population age structure. ConclusionThe burden of COVID-19 is far higher in developing countries than in high-income countries, reflecting a combination of elevated transmission to middle-aged and older adults as well as limited access to adequate healthcare. These results underscore the critical need to accelerate the provision of vaccine doses to populations in developing countries. Key Points- Age-stratified infection fatality rates (IFRs) of COVID-19 in developing countries are about twice those of high-income countries. - Seroprevalence (as measured by antibodies against SARS-CoV-2) is broadly similar across age cohorts, underscoring the challenges of protecting older age groups in developing countries. - Population IFR in developing countries is similar to that of high-income countries, because differences in population age structure are roughly offset by disparities in healthcare access as well as elevated infection rates among older age cohorts. - These results underscore the urgency of disseminating vaccines throughout the developing world.

Open Science Saves Lives: Lessons from the COVID-19 Pandemic

In the last decade Open Science principles have been successfully advocated for and are being slowly adopted in different research communities. In response to the COVID-19 pandemic many publishers and researchers have sped up their adoption of Open Science practices, sometimes embracing them fully and sometimes partially or in a sub-optimal manner. In this article, we express concerns about the violation of some of the Open Science principles and its potential impact on the quality of research output. We provide evidence of the misuses of these principles at different stages of the scientific process. We call for a wider adoption of Open Science practices in the hope that this work will encourage a broader endorsement of Open Science principles and serve as a reminder that science should always be a rigorous process, reliable and transparent, especially in the context of a pandemic where research findings are being translated into practice even more rapidly. We provide all data and scripts at https://osf.io/renxy/.