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Introduction The coronavirus disease 2019 (COVID-19) pandemic has been unprecedented in recent history. The rapid global spread has demonstrated how the emergence of a novel pathogen necessitates new information to advise both healthcare systems and policy-makers. The directives for the management of COVID-19 have been limited to infection control measures and treatment of patients, which has left physicians and researchers alone to navigate the massive amount of research being published while searching for evidence-based strategies to care for patients. To tackle this barrier, we launched CovidReview.ca, an open-access, continually updated, online platform that screens available COVID-19 research to determine higher quality publications. This paper uses data from this review process to explore the activity and trends of COVID-19 research worldwide over time, while specifically looking at the types of studies being published. Materials and Methods The literature search was conducted on PubMed. Search terms included "COVID-19", "severe acute respiratory syndrome coronavirus 2", "coronavirus 19", "SARS-COV-2", and "2019-nCoV". All articles captured by this strategy were reviewed by a minimum of two reviewers and categorized by type of research, relevant medical specialties, and type of publication. Criteria were developed to allow for inclusion or exclusion to the website. Due to the volume of research, only a level 1 (title and abstract) screen was performed. Results The time period for the analysis was January 17, 2020, to May 10, 2020. The total number of papers captured by the search criteria was 10,685, of which 2,742 were included on the website and 7,943 were excluded. The greatest increase in the types of studies over the 16 weeks was narrative review/expert opinion papers followed by case series/reports. Meta-analyses, systematic reviews, and randomized controlled trials remained the least published types of studies. Conclusions The surge of research that accompanied the COVID-19 pandemic is unparalleled in recent years. From our analysis, it is clear that case reports and narrative reviews were the most widely published, particularly in the earlier days of this pandemic. Continued research that falls higher on the evidence pyramid and is more applicable to clinical settings is warranted.
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Analysis of daily solar irradiation variability and predictability in space and time is important for energy resources planning, development, and management. The natural variability of solar irradiation is being complicated by atmospheric conditions (in particular cloudiness) and orography, which introduce additional complexity into the phenomenological records. To address this question for daily solar irradiation data recorded during the years 2013, 2014 and 2015 at 11 stations measuring solar irradiance on La Reunion French tropical Indian Ocean Island, we use a set of novel quantitative tools: Kolmogorov complexity (KC) with its derivative associated measures and Hamming distance (HAM) and their combination to assess complexity and corresponding predictability. We find that all half-day (from sunrise to sunset) solar irradiation series exhibit high complexity. However, all of them can be classified into three groups strongly influenced by trade winds that circulate in a "flow around" regime: the windward side (trade winds slow down), the leeward side (diurnal thermally-induced circulations dominate) and the coast parallel to trade winds (winds are accelerated due to Venturi effect). We introduce Kolmogorov time (KT) that quantifies the time span beyond which randomness significantly influences predictability.
