A New Paper Framework to Increase Reproducibility: Example Relating to Web Pharmacovigilance During COVID-19 in Italy

Reproducibility and transparency represent some of the main problems of scientific publishing. Currently, the editorial requests of academic journals and peer reviewers can divert the authors attention from an accurate description of the methods adopted, thus compromising these fundamental scientific aspects. This paves the way for the voluntary falsification of data to obtain striking results. Furthermore, the excessive expansion of introduction and discussion sections increases the likelihood of introducing evaluation bias. Since peer reviewers are generally unpaid for their work, they are not required to reproduce the analysis of the studies they review but only to assess methodological accuracy, reproducibility, and plausibility. Therefore, this paper aims to emphasize that the methods and results sections are the central parts of quantitative analysis. In this regard, we firmly believe that the peer review process should, whenever possible, reproduce the analysis from scratch. Consequently, authors must be required to provide a simple and straightforward tutorial to reproduce the analysis as it was conceived both methodologically and chronologically. Ideas, insights, and discussions among the authors must also be reported. This complete description can be provided as integrative material published with the main manuscript, which is nothing more than a summary of methods and results. Such a procedure would represent the first step to improving the quality of scientific publications, waiting for unscientific concepts such as "publish or perish" to be eradicated from the academic world. In this manuscript, we provide a framework that can serve as a fully reproducible and transparent example of analysis. The aim is to investigate the Italian netizens web interest in paracetamol, ibuprofen, and nimesulide from 2015 to 2022, searching for causal associations with the fever symptom and COVID-19. The infodemiological tool "Google Trends" has been used to collect the data. Correlational analysis showed plausible causal associations between paracetamol, ibuprofen, and fever due to seasonal flu and COVID-19 and, although to a minor extent, COVID-19 vaccines side effects. Paracetamol was the most historically searched substance. However, the trend of ibuprofen has caught up with that of paracetamol in 2022. Interest in paracetamol, ibuprofen, and nimesulide increased substantially during the COVID-19 pandemic period. We conclude that web pharmacovigilance via Google Trends can provide relevant evidence for monitoring drug intake in relation to epidemiologically significant events such as epidemics and mass vaccination campaigns.