The COVID-19<\/a> pandemic has inspired an unprecedented amount of healthcare-related research in various fields, from drug and vaccine development to epidemiological modelling. Preprints abound, but some warn about the dangers of releasing research without proper verification.<\/p>\n\n\n\n You may also like: Warnings about Potential Treatments for COVID-19<\/a><\/p>\n\n\n\n \u201cI am impressed by how quickly the scientific community has put together a lot of work, and has collaborated on making the results open \u2013 that hadn\u2019t happen so much in the past,\u201d says Prof. Andy Tatem, Professor of Spatial Demography and Epidemiology at University of Southampton, in his interview in the upcoming HealthManagement.org The Journal<\/a><\/em> special issue, COVID-19 Care Continuum<\/em>. <\/p>\n\n\n\n The concerns, however, are growing about the quality of such \u2018accelerated\u2019 research studies. \u201cOne usually would not recommend therapy unless the benefit reaches statistical certainty in two prospective randomized controlled studies. However, we do not have years to wait for these studies, we are forced to act on best evidence, but in some cases the evidence is less than actionable,\u201d Kevin Kavanagh and Lindsay Calderon\u00a0write<\/a>in\u00a0Infection Control Today<\/em>. In their piece, they provide examples of how initial favourable reports on the effectiveness on certain COVID-19 treatments, such as hydroxychloroquine,\u00a0angiotensin converting enzyme inhibitors (ACEi) or angiotensin receptor blockers (ARB),\u00a0have not been confirmed by consequent studies. \u201cIn the new reality of making decisions with limited and incomplete data, it is important that decision makers and scientists are free from biases,\u201d they conclude, warning against carelessness \u201cin both reporting and interpreting messaging, including the results of unconfirmed research.\u201d\u00a0<\/p>\n\n\n\n