COVID Risk | Research protocol

Research Protocol


Factors associated with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and related outcomes: an online platform for evidence mapping

Endre Szigethy, Adrienn Herczeg


Background

The global epidemic caused by severe acute respiratory syndrome coronavirus 2 (SARS COV-2) infections has resulted in thousands of deaths every day [CSSE]. The first case of infection was found on 17 November 2019 [Livescience]. Due to the novelty of the infection and its associated disease, Coronavirus Disease 2019 (COVID-19), limited prior knowledge is available about the factors associated with SARS COV-2 infections and the development and progression of COVID-19. However, research communities are actively working around the word to provide scientific evidence. Thousands of new articles have been published on PubMed related to SARS-CoV-2 and COVID-19, and the number of publications increases by dozens each day [Pubmed]. The rapidly spreading epidemic and the growing information base makes global understanding of the disease characteristics difficult [XU et al 2020]. Traditional scientific publication techniques can hardly keep up with the rapidly growing information and with the hunger for immediate, evidence-based, up-to-date information.

Our goal is to establish an open-access, online platform that provides an interface for summarizing data from available studies on factors associated with SARS-CoV-2 infection and its related outcomes. Our secondary objective is to build a background algorithm to perform an immediate, expandable, adjustable, and dynamic summary of the data entered in the database, providing users with the calculated pooled effect of the individual estimations for each risk factor and outcome association. This comprehensive, up-to-date summary of the extent and nature of presumed protective factors and risk factors for COVID-19 are facilitate the identification of possible further actions.


Methods

Evidence mapping is being conducted based on the methodology proposed by The Global Evidence Mapping Initiative [Bragge et al 2011], through systematic searches in PubMed, and medRxiv, and screening references of included studies. We adapt the search strategy according to the specific characteristics of each database. Primary observational studies, interventional studies, and review articles describing factors associated with SARS-CoV-2 infection and related outcomes are searched. We select articles describing the measure of association between factors and SARS-CoV-2 infection and related outcomes, including the development of COVID-19, disease progression, death, or discharge. The search term employs combinations of associated keywords:

"COVID-19"[All Fields] OR "COVID-2019"[All Fields] OR "severe acute respiratory syndrome coronavirus 2"[Supplementary Concept] OR "severe acute respiratory syndrome coronavirus 2"[All Fields] OR "2019-nCoV"[All Fields] OR "SARS CoV-2"[All Fields] OR "2019nCoV"[All Fields] OR "coronavirus 2"[All Fields] OR (wuhan AND "coronavirus"[MeSH Terms]) AND (odds ratio* OR risk ratio* OR relative risk* OR hazard ratio* OR rate ratio* OR prevalence ratio* OR univari* OR multivari* OR relationship OR "associated with" OR risk factor* OR Logistic Model* OR Protective Factor* OR Preventive Factor* OR predictive factor* OR Risk Assessment* OR "Risk"[Mesh])

The search term limits results to those published in the English language. Publications reporting primary quantitative data and review articles with a sample size of over 10 patients are included. The search is repeated on a weekly basis at minimum. Search results are managed with a reference management software and the Rayyan QCRI Systematic Reviews web app [Ouzzani et al 2016]. After removing duplicates, search results are screened by two reviewers for eligibility by titles and abstracts. For a final decision, full texts of potentially relevant articles are obtained. Disagreements are solved through consensus or by a third reviewer if necessary. The observational study quality evaluation criteria recommended by the American Agency for Health Research and Quality are used to evaluate the study quality. Data extraction comprises information on study characteristics (authors, full reference, year of publication, study setting, data source, objective, number of patients included, patient demographics, SARS COV-2 related outcome, and validity assessment of the publication), and operational definitions (definition of the source population, risk or preventive factor definition, clinical characteristics of patients, outcomes reported). Analysis is performed by calculating pooled odds ratios with 95% confidence interval. Weighted average of likelihood ratios are computed using the inverse variance methods to pool both binary or continuous data [Egger et al 2001]. Data analysis is performed using PHP scripting language and MySQL database management system.


Discussion

This platform provides an up-to-date evidence map and synthesis of available primary research estimates on the factors associated with SARS-CoV-2 infection and related outcomes.


References
  • Bragge P, Clavisi O, Turner T, Tavender E, Collie A, Gruen RL. (2011) The global evidence mapping initiative: scoping research in broad topic areas. BMC Med Res Methodol;11:92.
  • CSSE (2020) Coronavirus COVID-19 Global Cases by the Center for Systems Science and Engineering (CSSE) at Johns Hopkins University. Available: https://gisanddata.maps.arcgis.com/ (accessed 02-04-2020).
  • Egger M, Altman D, Smith G, and Altman D (2001) Systematic Reviews in Health Care(2nd Edition) Meta-Analysis in Context Hardcover, 506 Pages, Published 2001 by Bmj Books ISBN-13: 978-0-7279-1488-0
  • Livescience (2020) 1st known case of coronavirus traced back to November in China Available: https://www.livescience.com/first-case-coronavirus-found.html (accessed 02-04-2020).
  • Pubmed (2020) US National Library of Medicine National Institutes of Health. Available: https://www.ncbi.nlm.nih.gov/pubmed/?term=covid+19 (accessed 02-04-2020).
  • Ouzzani M, Hammady H, Fedorowicz Z, and Elmagarmid A (2016) Rayyan - a web and mobile app for systematic reviews. Systematic Reviews 5:210, https://doi.org/10.1186/s13643-016-0384-4.
  • Xu L, Yyaqian M, Chen G (2020) Risk factors for severe corona virus disease 2019 (COVID-19) patients : a systematic review and meta analysis. (preprint article) Available: https://doi.org/10.1101/2020.03.30.20047415 (accessed 02-04-2020).