{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,5,14]],"date-time":"2025-05-14T03:42:48Z","timestamp":1747194168612,"version":"3.40.5"},"reference-count":29,"publisher":"MIT Press","issue":"4","content-domain":{"domain":["www.mitpressjournals.org"],"crossmark-restriction":true},"short-container-title":["Quantitative Science Studies"],"published-print":{"date-parts":[[2020,12]]},"abstract":"<jats:p> The speed with which biomedical specialists were able to identify and characterize COVID-19 was partly due to prior research with other coronaviruses. Early epidemiological comparisons with Severe Acute Respiratory Syndrome (SARS) and Middle East Respiratory Syndrome (MERS), also made it easier to predict COVID-19\u2019s likely spread and lethality. This article assesses whether academic interest in prior coronavirus research has translated into interest in the primary source material, using Mendeley reader counts for early academic impact evidence. The results confirm that SARS and MERS research in 2008\u20132017 experienced anomalously high increases in Mendeley readers in April\u2013May 2020. Nevertheless, studies learning COVID-19 lessons from SARS and MERS or using them as a benchmark for COVID-19 have generated much more academic interest than primary studies of SARS or MERS. Thus, research that interprets prior relevant research for new diseases when they are discovered seems to be particularly important to help researchers to understand its implications in the new context. <\/jats:p>","DOI":"10.1162\/qss_a_00083","type":"journal-article","created":{"date-parts":[[2020,8,17]],"date-time":"2020-08-17T12:32:51Z","timestamp":1597667571000},"page":"1381-1395","update-policy":"https:\/\/doi.org\/10.1162\/mitpressjournals.corrections.policy","source":"Crossref","is-referenced-by-count":7,"title":["Coronavirus research before 2020 is more relevant than ever, especially when interpreted for COVID-19"],"prefix":"10.1162","volume":"1","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-6065-205X","authenticated-orcid":true,"given":"Mike","family":"Thelwall","sequence":"first","affiliation":[{"name":"Statistical Cybermetrics Research Group, University of Wolverhampton, UK"}]}],"member":"281","reference":[{"issue":"3","key":"bib1","doi-asserted-by":"crossref","first-page":"567","DOI":"10.1007\/s11192-005-0228-9","volume":"63","author":"Adams J.","year":"2005","journal-title":"Scientometrics"},{"issue":"3","key":"bib2","volume":"12","author":"Chahrour M.","year":"2020","journal-title":"Cureus"},{"journal-title":"BioRxiv","year":"2020","author":"Colavizza G.","key":"bib3"},{"issue":"1","key":"bib4","doi-asserted-by":"crossref","first-page":"1","DOI":"10.30699\/ijmm.14.1.1","volume":"14","author":"Danesh F.","year":"2020","journal-title":"Iranian Journal of Medical Microbiology"},{"issue":"1","key":"bib5","first-page":"354","volume":"34","author":"Dehghanbanadaki H.","year":"2020","journal-title":"Medical Journal of The Islamic Republic of Iran (MJIRI)"},{"issue":"5","key":"bib6","doi-asserted-by":"crossref","first-page":"1","DOI":"10.7324\/JAPS.2020.10501","volume":"10","author":"G\u00f3mez-R\u00edos D.","year":"2020","journal-title":"Journal of Applied Pharmaceutical Science"},{"key":"bib7","doi-asserted-by":"crossref","first-page":"104806","DOI":"10.1016\/j.ssci.2020.104806","author":"Haghani M.","year":"2020","journal-title":"Safety Science"},{"issue":"2","key":"bib8","doi-asserted-by":"crossref","first-page":"34","DOI":"10.26554\/sti.2020.5.2.34-40","volume":"5","author":"Hamidah I.","year":"2020","journal-title":"Indonesian Journal of Science and Technology"},{"key":"bib9","doi-asserted-by":"crossref","first-page":"374","DOI":"10.12688\/f1000research.23690.1","volume":"9","author":"Hossain M. 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