Array
(
    [0] => stdClass Object
        (
            [journal] => stdClass Object
                (
                    [id_jnl] => 87
                )

        )

    [1] => stdClass Object
        (
            [section] => stdClass Object
                (
                    [section] => 281
                )

        )

    [2] => stdClass Object
        (
            [title] => Array
                (
                    [0] => The multidisciplinary nature of COVID-19 research@en
                )

        )

    [3] => stdClass Object
        (
            [abstract] => Array
                (
                    [0] => Objective. We analyzed the scientific output after COVID-19 and contrasted it with studies published in the aftermath of seven epidemics/pandemics: Severe Acute Respiratory Syndrome (SARS), Influenza A virus H5N1 and Influenza A virus H1N1 human infections, Middle East Respiratory Syndrome (MERS), Ebola virus disease, Zika virus disease, and Dengue.
Design/Methodology/Approach. We examined bibliometric measures for COVID-19 and the rest of the studied epidemics/pandemics. Data were extracted from Web of Science, using its journal classification scheme as a proxy to quantify the multidisciplinary coverage of scientific output. We proposed a novel Thematic Dispersion Index (TDI) for the analysis of pandemic early stages. 
Results/Discussion. The literature on the seven epidemics/pandemics before COVID-19 has shown explosive growth of the scientific production and continuous impact during the first three years following each emergence or re-emergence of the specific infectious disease. A subsequent decline was observed with the progressive control of each health emergency. We observed an unprecedented growth in COVID-19 scientific production. TDI measured for COVID-19 (29,4) in just six months, was higher than TDI of the rest (7,5 to 21) during the first three years after epidemic initiation.
Conclusions. COVID-19 literature showed the broadest subject coverage, which is clearly a consequence of its social, economic, and political impact. The proposed indicator (TDI), allowed the study of multidisciplinarity, differentiating the thematic complexity of COVID-19 from the previous seven epidemics/pandemics.
Originality/Value. The multidisciplinary nature and thematic complexity of COVID-19 research were successfully analyzed through a scientometric perspective.@en
                )

        )

    [4] => stdClass Object
        (
            [author] => Array
                (
                    [0] => Ricardo Arencibia-Jorge
                    [1] => Lourdes García-García
                    [2] => Ernesto Galban-Rodriguez
                    [3] => Humberto Carrillo-Calvet
                )

        )

    [5] => stdClass Object
        (
            [subject] => Array
                (
                    [0] => Covid-19@en
                    [1] => Multidisciplinarity@en
                    [2] => Pandemic diseases@en
                    [3] => Scientometrics@en
                    [4] => Bibliometric indicators@en
                    [5] => Scientific production@en
                    [6] => Citation analysis@en
                    [7] => Thematic dispersion index@en
                )

        )

    [6] => stdClass Object
        (
            [source] => stdClass Object
                (
                    [vol] => 1
                    [nr] => no.
                    [year] => 2021
                    [theme] => 
                )

        )

    [7] => stdClass Object
        (
            [datePub] => Array
                (
                    [0] => 2020-12-22
                )

        )

    [8] => stdClass Object
        (
            [DOI] => Array
                (
                    [0] => stdClass Object
                        (
                            [type] => DOI
                            [value] => Array
                                (
                                    [0] => 10.47909/ijsmc.13
                                )

                        )

                )

        )

    [9] => stdClass Object
        (
            [http] => Array
                (
                    [0] => stdClass Object
                        (
                            [type] => HTTP
                            [value] => Array
                                (
                                    [0] => https://ijsmc.pro-metrics.org/index.php/i/article/view/29
                                )

                        )

                    [1] => stdClass Object
                        (
                            [type] => HTTP
                            [value] => Array
                                (
                                    [0] => https://ijsmc.pro-metrics.org/index.php/i/article/view/29/33
                                )

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                )

        )

    [10] => stdClass Object
        (
            [language] => Array
                (
                    [0] => en
                )

        )

    [11] => stdClass Object
        (
            [license] => Array
                (
                    [0] => Copr
                    [1] => by-nc/4.0
                )

        )

)