Skip to main content
Key Specialties
Cardiology Diabetology Endocrinology Gastroenterology Geriatrics and Gerontology Gynecology and Obstetrics Hematology Infectious Disease Internal Medicine Nephrology Neurology Oncology Pediatrics Respiratory Medicine Rheumatology Surgery
Congress Coverage
2024 ACC Congress 2023 ESMO Congress 2023 EASD Congress 2023 ERS Congress 2023 ESC Congress
Clinical Collections
Advances in Alzheimer’s

Keynote webinar | Spotlight on medication adherence

LIVE: Thursday 27th June 2024, 18:00-19:30 (CEST)
Join our expert panel to discover why you need to understand the drivers of non-adherence in your patients, and how you can optimize medication adherence in your clinics to drastically improve patient outcomes.
ADVANCED SEARCH
Log in
Top
BMC Medical Research Methodology
Published in: BMC Medical Research Methodology 1/2020

Open Access 01-12-2020 | Public Health | Research article

Coronavirus disease 2019 (COVID-19): an evidence map of medical literature

Authors: Nan Liu, Marcel Lucas Chee, Chenglin Niu, Pin Pin Pek, Fahad Javaid Siddiqui, John Pastor Ansah, David Bruce Matchar, Sean Shao Wei Lam, Hairil Rizal Abdullah, Angelique Chan, Rahul Malhotra, Nicholas Graves, Mariko Siyue Koh, Sungwon Yoon, Andrew Fu Wah Ho, Daniel Shu Wei Ting, Jenny Guek Hong Low, Marcus Eng Hock Ong

Published in: BMC Medical Research Methodology | Issue 1/2020

Login to get access

Abstract

Background

Since the beginning of the COVID-19 outbreak in December 2019, a substantial body of COVID-19 medical literature has been generated. As of June 2020, gaps and longitudinal trends in the COVID-19 medical literature remain unidentified, despite potential benefits for research prioritisation and policy setting in both the COVID-19 pandemic and future large-scale public health crises.

Methods

In this paper, we searched PubMed and Embase for medical literature on COVID-19 between 1 January and 24 March 2020. We characterised the growth of the early COVID-19 medical literature using evidence maps and bibliometric analyses to elicit cross-sectional and longitudinal trends and systematically identify gaps.

Results

The early COVID-19 medical literature originated primarily from Asia and focused mainly on clinical features and diagnosis of the disease. Many areas of potential research remain underexplored, such as mental health, the use of novel technologies and artificial intelligence, pathophysiology of COVID-19 within different body systems, and indirect effects of COVID-19 on the care of non-COVID-19 patients. Few articles involved research collaboration at the international level (24.7%). The median submission-to-publication duration was 8 days (interquartile range: 4–16).

Conclusions

Although in its early phase, COVID-19 research has generated a large volume of publications. However, there are still knowledge gaps yet to be filled and areas for improvement for the global research community. Our analysis of early COVID-19 research may be valuable in informing research prioritisation and policy planning both in the current COVID-19 pandemic and similar global health crises.
Literature
1.
2.
3.
Lu R, Zhao X, Li J, Niu P, Yang B, Wu H, Wang W, Song H, Huang B, Zhu N, et al. Genomic characterisation and epidemiology of 2019 novel coronavirus: implications for virus origins and receptor binding. Lancet. 2020;395(10224):565–74.CrossRef
4.
Ksiazek TG, Erdman D, Goldsmith CS, Zaki SR, Peret T, Emery S, Tong S, Urbani C, Comer JA, Lim W, et al. A novel coronavirus associated with severe acute respiratory syndrome. N Engl J Med. 2003;348(20):1953–66.CrossRef
5.
Zhong NS, Zheng BJ, Li YM, Poon XZH, Chan KH, Li PH, Tan SY, Chang Q, Xie JP, et al. Epidemiology and cause of severe acute respiratory syndrome (SARS) in Guangdong, People’s Republic of China, in February, 2003. Lancet. 2003;362(9393):1353–8.CrossRef
6.
Zaki AM, van Boheemen S, Bestebroer TM, Osterhaus ADME, Fouchier RAM. Isolation of a novel coronavirus from a man with pneumonia in Saudi Arabia. N Engl J Med. 2012;367(19):1814–20.CrossRef
7.
Park M, Cook AR, Lim JT, Sun Y, Dickens BL. A Systematic Review of COVID-19 Epidemiology Based on Current Evidence. J Clin Med. 2020;9(4).
8.
Cortegiani A, Ingoglia G, Ippolito M, Giarratano A, Einav S: A systematic review on the efficacy and safety of chloroquine for the treatment of COVID-19. J Crit Care 2020;57:279-83.
9.
Rodriguez-Morales AJ, Cardona-Ospina JA, Gutiérrez-Ocampo E, Villamizar-Peña R, Holguin-Rivera Y, Escalera-Antezana JP, Alvarado-Arnez LE, Bonilla-Aldana DK, Franco-Paredes C, Henao-Martinez AF et al: Clinical, laboratory and imaging features of COVID-19: a systematic review and meta-analysis. Travel Med Infect Dis 2020:101623–101623.
10.
Marx W, Schier H, Wanitschek M. Citation analysis using online databases: feasibilities and shortcomings. Scientometrics. 2001;52(1):59–82.CrossRef
11.
Lou J, Tian SJ, Niu SM, Kang XQ, Lian HX, Zhang LX, Zhang JJ. Coronavirus disease 2019: a bibliometric analysis and review. Eur Rev Med Pharmacol Sci. 2020;24(6):3411–21.PubMed
12.
Chahrour M, Assi S, Bejjani M, Nasrallah AA, Salhab H, Fares M, Khachfe HH. A Bibliometric analysis of COVID-19 research activity: a call for increased output. Cureus. 2020;12(3):e7357.PubMedPubMedCentral
13.
Boutron I, Chaimani A, Devane D, and JJM, Tovey D, Hróbjartsson A, Ravaud P: Interventions for preventing and treating COVID-19: protocol for a living mapping of research and a living systematic review. Zenodo 2020;3903347.
14.
Snilstveit B, Vojtkova M, Bhavsar A, Stevenson J, Gaarder M. Evidence & gap maps: a tool for promoting evidence informed policy and strategic research agendas. J Clin Epidemiol. 2016;79:120–9.CrossRef
15.
Saran A, White H. Evidence and gap maps: a comparison of different approaches. Campbell Syst Rev. 2018;14(1):1–38.CrossRef
16.
Katz DL, Williams AL, Girard C, Goodman J, Comerford B, Behrman A, Bracken MB. The evidence base for complementary and alternative medicine: methods of evidence mapping with application to CAM. Altern Ther Health Med. 2003;9(4):22–30.PubMed
17.
Hirsch JE. An index to quantify an individual's scientific research output. Proc Natl Acad Sci U S A. 2005;102(46):16569–72.CrossRef
18.
19.
He X, Lau EHY, Wu P, Deng X, Wang J, Hao X, Lau YC, Wong JY, Guan Y, Tan X et al: Temporal dynamics in viral shedding and transmissibility of COVID-19. Nat Med 2020;26:672–5.
20.
Chiu W-T, Huang J-S, Ho Y-S. Bibliometric analysis of severe acute respiratory syndrome-related research in the beginning stage. Scientometrics. 2004;61(1):69–77.CrossRef
21.
Zyoud SH. Global research trends of Middle East respiratory syndrome coronavirus: a bibliometric analysis. BMC Infect Dis. 2016;16(1).
22.
Huang C, Wang Y, Li X, Ren L, Zhao J, Hu Y, Zhang L, Fan G, Xu J, Gu X, et al. Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China. Lancet. 2020;395(10223):497–506.CrossRef
23.
Cao B, Wang Y, Wen D, Liu W, Wang J, Fan G, Ruan L, Song B, Cai Y, Wei M et al: A trial of Lopinavir–ritonavir in adults hospitalized with severe Covid-19. N Engl J Med 2020;382(19):1787–99.
24.
Ting DSW, Carin L, Dzau V, Wong TY. Digital technology and COVID-19. Nat Med. 2020;26(4):459–61.
25.
Wong ZSY, Zhou J, Zhang Q. Artificial intelligence for infectious disease big data analytics. Infect Dis Health. 2019;24(1):44–8.CrossRef
26.
27.
Li L, Qin L, Xu Z, Yin Y, Wang X, Kong B, Bai J, Lu Y, Fang Z, Song Q et al: Artificial Intelligence Distinguishes COVID-19 from Community Acquired Pneumonia on Chest CT. Radiology 2020;200905..
28.
Siettos CI, Russo L. Mathematical modeling of infectious disease dynamics. Virulence. 2013;4(4):295–306..CrossRef
29.
Wang H, Wang Z, Dong Y, Chang R, Xu C, Yu X, Zhang S, Tsamlag L, Shang M, Huang J, et al. Phase-adjusted estimation of the number of coronavirus disease 2019 cases in Wuhan, China. Cell Discov. 2020;6:10.CrossRef
30.
Kucharski AJ, Russell TW, Diamond C, Liu Y, Edmunds J, Funk S, Eggo RM: Early dynamics of transmission and control of COVID-19: a mathematical modelling study. Lancet Infect Dis 2020;20(5):553–8..
31.
Fang Y, Nie Y, Penny M. Transmission dynamics of the COVID-19 outbreak and effectiveness of government interventions: a data-driven analysis. J Med Virol. 2020;92(6):645–59.CrossRef
32.
Jewell NP, Lewnard JA, Jewell BL: Predictive mathematical models of the COVID-19 pandemic: underlying principles and value of projections. JAMA 2020;323(19):1893–4.
33.
Kissler SM, Tedijanto C, Goldstein E, Grad YH, Lipsitch M. Projecting the transmission dynamics of SARS-CoV-2 through the postpandemic period. Science (New York, NY). 2020:eabb5793.
34.
Shaban-Nejad A, Michalowski M, Buckeridge DL. Health intelligence: how artificial intelligence transforms population and personalized health. NPJ Digit Med. 2018;1:53.
35.
Wilder B, Suen S-C, Tambe M: Preventing infectious disease in dynamic populations under uncertainty. In: Thirty-Second AAAI Conference on Artificial Intelligence: 2018; 2018.
36.
Bent O, Remy SL, Roberts S, Walcott-Bryant A: Novel exploration techniques (NETs) for malaria policy interventions. In: Thirtieth AAAI Conference on Innovative Applications of Artificial Intelligence: 2018; 2018.
37.
Manogaran G, Mahroum N, Adawi M, Sharif K, Waknin R, Mahagna H, Bisharat B, Mahamid M, Abu-Much A, Amital H, et al. Public reaction to Chikungunya outbreaks in Italy—Insights from an extensive novel data streams-based structural equation modeling analysis. PLoS One. 2018;13(5).
38.
Olson DR, Bragazzi NL, Alicino C, Trucchi C, Paganino C, Barberis I, Martini M, Sticchi L, Trinka E, Brigo F, et al. Global reaction to the recent outbreaks of Zika virus: Insights from a Big Data analysis. PLoS One. 2017;12(9).
39.
Brooks SK, Webster RK, Smith LE, Woodland L, Wessely S, Greenberg N, Rubin GJ. The psychological impact of quarantine and how to reduce it: rapid review of the evidence. Lancet. 2020;395(10227):912–20.CrossRef
40.
Lai J, Ma S, Wang Y, Cai Z, Hu J, Wei N, Wu J, Du H, Chen T, Li R et al: Factors Associated With Mental Health Outcomes Among Health Care Workers Exposed to Coronavirus Disease 2019. JAMA Netw Open 2020, 3(3).
41.
Galea S, Merchant RM, Lurie N: The mental health consequences of COVID-19 and physical distancing: the need for prevention and early intervention. JAMA Intern Med 2020;180(6):817–8.
42.
Golberstein E, Wen H, Miller BF: Coronavirus disease 2019 (COVID-19) and mental health for children and adolescents. JAMA Pediatr 2020.
43.
Holmes EA, O'Connor RC, Perry VH, Tracey I, Wessely S, Arseneault L, Ballard C, Christensen H, Cohen Silver R, Everall I et al: Multidisciplinary research priorities for the COVID-19 pandemic: a call for action for mental health science. Lancet Psychiatry 2020;7(6):547–60.
44.
Tan BYQ, Chew NWS, Lee GKH, Jing M, Goh Y, Yeo LLL, Zhang K, Chin H-K, Ahmad A, Khan FA et al: Psychological impact of the COVID-19 pandemic on health Care Workers in Singapore. Ann Intern Med 2020;M20–1083.
45.
Mao L, Jin H, Wang M, Hu Y, Chen S, He Q, Chang J, Hong C, Zhou Y, Wang D et al: Neurologic manifestations of hospitalized patients with coronavirus disease 2019 in Wuhan, China. JAMA Neurol 2020;77(6):683–90.
46.
Wujtewicz M, Dylczyk-Sommer A, Aszkielowicz A, Zdanowski S, Piwowarczyk S, Owczuk R. COVID-19 - what should anaethesiologists and intensivists know about it? Anaesthesiol Intens Ther. 2020;52(1):34–41.CrossRef
47.
Liang W, Guan W, Chen R, Wang W, Li J, Xu K, Li C, Ai Q, Lu W, Liang H, et al. Cancer patients in SARS-CoV-2 infection: a nationwide analysis in China. Lancet Oncol. 2020;21(3):335–7.CrossRef
48.
Rosenbaum L: The untold toll - the Pandemic's effects on patients without Covid-19. N Engl J Med 2020;382:2368–71.
49.
Chotirmall SH, Martinez FJ, Schumacker PT, Cooke CR, Seam N, Brochard L, Tighe RM, Levy BD, Gern D, Wedzicha JA: Life at the editorial ‘COVID frontline’: the ATS journal family. Am J Respir Crit Care Med 2020;201(12):1457–9.
50.
Gautret P, Lagier J-C, Parola P, Hoang VT, Meddeb L, Mailhe M, Doudier B, Courjon J, Giordanengo V, Vieira VE et al: Hydroxychloroquine and azithromycin as a treatment of COVID-19: results of an open-label non-randomized clinical trial. Int J Antimicrob Agents 2020;105949.
51.
Liu J, Cao R, Xu M, Wang X, Zhang H, Hu H, Li Y, Hu Z, Zhong W, Wang M. Hydroxychloroquine, a less toxic derivative of chloroquine, is effective in inhibiting SARS-CoV-2 infection in vitro. Cell Discovery. 2020;6(1).
52.
Yao X, Ye F, Zhang M, Cui C, Huang B, Niu P, Liu X, Zhao L, Dong E, Song C et al: In vitro antiviral activity and projection of optimized dosing Design of Hydroxychloroquine for the treatment of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Clin Infect Dis 2020;ciaa237.
53.
Kim AHJ, Sparks JA, Liew JW, Putman MS, Berenbaum F, Duarte-García A, Graef ER, Korsten P, Sattui SE, Sirotich E et al: A rush to judgment? Rapid reporting and dissemination of results and its consequences regarding the use of Hydroxychloroquine for COVID-19. Ann Intern Med 2020;M20–1223.
54.
Yazdany J, Kim AHJ: Use of Hydroxychloroquine and Chloroquine during the COVID-19 pandemic: what every clinician should know. Ann Intern Med 2020;172(11):754–5.
55.
Taccone FS, Gorham J, Vincent J-L: Hydroxychloroquine in the management of critically ill patients with COVID-19: the need for an evidence base. Lancet Respir Med 2020;8(6):539–41.
56.
White NJ. Cardiotoxicity of antimalarial drugs. Lancet Infect Dis. 2007;7(8):549–58.CrossRef
57.
Liu M, Caputi TL, Dredze M, Kesselheim AS, Ayers JW: Internet searches for unproven COVID-19 therapies in the United States. JAMA Intern Med 2020;e201764.
58.
Wolkewitz M, Puljak L. Methodological challenges of analysing COVID-19 data during the pandemic. BMC Med Res Methodol. 2020;20(1):81.CrossRef
59.
Brat GA, Weber GM, Gehlenborg N, Avillach P, Palmer NP, Chiovato L, Cimino J, Waitman LR, Omenn GS, Malovini A et al: International Electronic Health Record-Derived COVID-19 Clinical Course Profile: The 4CE Consortium. medRxiv 2020;2020.04.13.20059691.
60.
Cowling BJ, Leung GM. Epidemiological research priorities for public health control of the ongoing global novel coronavirus (2019-nCoV) outbreak. Euro Surveill. 2020;25(6).
Metadata
Title
Coronavirus disease 2019 (COVID-19): an evidence map of medical literature
Authors
Nan Liu
Marcel Lucas Chee
Chenglin Niu
Pin Pin Pek
Fahad Javaid Siddiqui
John Pastor Ansah
David Bruce Matchar
Sean Shao Wei Lam
Hairil Rizal Abdullah
Angelique Chan
Rahul Malhotra
Nicholas Graves
Mariko Siyue Koh
Sungwon Yoon
Andrew Fu Wah Ho
Daniel Shu Wei Ting
Jenny Guek Hong Low
Marcus Eng Hock Ong
Publication date
01-12-2020
Publisher
BioMed Central
Published in
BMC Medical Research Methodology / Issue 1/2020
Electronic ISSN: 1471-2288
DOI
https://doi.org/10.1186/s12874-020-01059-y

Other articles of this Issue 1/2020

BMC Medical Research Methodology 1/2020 Go to the issue

Research article

Social media as a recruitment platform for a nationwide online survey of COVID-19 knowledge, beliefs, and practices in the United States: methodology and feasibility analysis

Research article

Modeling socio-demographic and clinical factors influencing psychiatric inpatient service use: a comparison of models for zero-Inflated and overdispersed count data

Research article

Database combinations to retrieve systematic reviews in overviews of reviews: a methodological study

Research article

Frequently repeated measurements -our experience of collecting data with SMS

Research article

Joint analysis of duration of ventilation, length of intensive care, and mortality of COVID-19 patients: a multistate approach

Research article

Effectiveness of SMS messaging for diarrhoea measurement: a factorial cross-over randomised controlled trial