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      Coronavirus disease (COVID-19) prevention and treatment methods and effective parameters: A systematic literature review

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          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Highlights

          • •

            Proposing a taxonomy tree to investigate the COVID-19 confronting methods and effects.

          • •

            Providing a systematic literature review based on the proposed taxonomy tree.

          • •

            Indicating the impact of medical and social methods for facing the COVID-19 outbreak.

          Abstract

          Background and objective

          The coronavirus disease 2019 (COVID-19) outbreak was first identified in Wuhan in December 2019, which was declared a pandemic virus by the world health organization on March 11 in 2020. COVID-19 is an infectious disease and almost leads to acute respiratory distress syndrome. Therefore, the virus epidemic is a big problem for humanity healthy and can lead die in special people with background diseases such as chronic obstructive pulmonary diseases, chronic heart failure, diabetes mellitus, and kidney failure. Different medical, social, and engineering methods have been proposed to face the disease include treatment, detection, prevention, and prediction approaches.

          Methods

          We propose a taxonomy tree to investigate the disease confronting methods and their negative and positive effects. Our work consists of a case study and systematic literature review (SLR) to evaluate the proposed methods against the virus outbreak and disease epidemic.

          Results

          Our experimental results and observations demonstrate the impact of the proposed medical, prevention, detection, prediction, and social methods for facing the spread of COVID-19 from December 2019 to July 2020.

          Conclusion

          Our case study can help people have more information about the disease and its impact on humanity healthy and illustrate effective self-caring methods and therapies.

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          Most cited references57

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          Towards a Methodology for Developing Evidence-Informed Management Knowledge by Means of Systematic Review

          David Tranfield, David Denyer, Palminder Smart (2003)
          Article 0 comments Cited 1890 times – based on 0 reviews     Review now
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            Is Open Access

            Effective treatment of severe COVID-19 patients with tocilizumab

            Xiaoling Xu, Mingfeng Han, Tiantian Li … (2020)
            Significance In patients with coronavirus disease 2019, a large number of T lymphocytes and mononuclear macrophages are activated, producing cytokines such as interleukin-6 (IL-6), which bind to the IL-6 receptor on the target cells, causing the cytokine storm and severe inflammatory responses in lungs and other tissues and organs. Tocilizumab, as a recombinant humanized anti-human IL-6 receptor monoclonal antibody, can bind to the IL-6 receptor with high affinity, thus preventing IL-6 itself from binding to its receptor, rendering it incapable of immune damage to target cells, and alleviating the inflammatory responses.
            Article 0 comments Cited 1309 times – based on 0 reviews     Review now
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              Clinical, laboratory and imaging features of COVID-19: A systematic review and meta-analysis

              Alfonso J. Rodríguez-Morales, Jaime A. Cardona-Ospina, Estefanía Gutiérrez-Ocampo … (2020)
              Introduction An epidemic of Coronavirus Disease 2019 (COVID-19) began in December 2019 in China leading to a Public Health Emergency of International Concern (PHEIC). Clinical, laboratory, and imaging features have been partially characterized in some observational studies. No systematic reviews on COVID-19 have been published to date. Methods We performed a systematic literature review with meta-analysis, using three databases to assess clinical, laboratory, imaging features, and outcomes of COVID-19 confirmed cases. Observational studies and also case reports, were included, and analyzed separately. We performed a random-effects model meta-analysis to calculate pooled prevalences and 95% confidence intervals (95%CI). Results 660 articles were retrieved for the time frame (1/1/2020-2/23/2020). After screening, 27 articles were selected for full-text assessment, 19 being finally included for qualitative and quantitative analyses. Additionally, 39 case report articles were included and analyzed separately. For 656 patients, fever (88.7%, 95%CI 84.5–92.9%), cough (57.6%, 95%CI 40.8–74.4%) and dyspnea (45.6%, 95%CI 10.9–80.4%) were the most prevalent manifestations. Among the patients, 20.3% (95%CI 10.0–30.6%) required intensive care unit (ICU), 32.8% presented with acute respiratory distress syndrome (ARDS) (95%CI 13.7–51.8), 6.2% (95%CI 3.1–9.3) with shock. Some 13.9% (95%CI 6.2–21.5%) of hospitalized patients had fatal outcomes (case fatality rate, CFR). Conclusion COVID-19 brings a huge burden to healthcare facilities, especially in patients with comorbidities. ICU was required for approximately 20% of polymorbid, COVID-19 infected patients and hospitalization was associated with a CFR of >13%. As this virus spreads globally, countries need to urgently prepare human resources, infrastructure and facilities to treat severe COVID-19.
              Article 0 comments Cited 1068 times – based on 0 reviews     Review now
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                Author and article information

                Journal
                Journal ID (nlm-ta): Sustain Cities Soc
                Journal ID (iso-abbrev): Sustain Cities Soc
                Title: Sustainable Cities and Society
                Publisher: Published by Elsevier Ltd.
                ISSN (Print): 2210-6707
                ISSN (Electronic): 2210-6715
                Publication date PMC-release: 22 October 2020
                Publication date (Electronic): 22 October 2020
                Electronic Location Identifier: 102568
                Affiliations
                [a ]Institute of Research and Development, Duy Tan University, Da Nang, 550000, Viet Nam
                [b ]Faculty of Information Technology, Duy Tan University, Da Nang, 550000, Viet Nam
                [c ]Department of Computer Science, Khazar University, Baku, Azerbaijan
                [d ]Department of Computer Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran
                Author notes
                [* ]Corresponding author at: Institute of Research and Development, Duy Tan University, Da Nang, 550000, Viet Nam.
                Article
                Publisher Item ID: S2210-6707(20)30786-1 Publisher ID: 102568
                DOI: 10.1016/j.scs.2020.102568
                PMC ID: 7578778
                PubMed ID: 33110743
                SO-VID: ff29093c-792e-4885-8092-07936fced65f
                Copyright © © 2020 Published by Elsevier Ltd.
                License:

                Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active.

                History
                Date received : 10 July 2020
                Date revision received : 14 October 2020
                Date accepted : 15 October 2020
                Categories
                Subject: Article

                Keywords: covid-19,systematic literature review (slr),treatment,prevention,detection
                Data availability:
                Keywords: covid-19, systematic literature review (slr), treatment, prevention, detection

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