Literature DB >> 32396623

Social Media and the New World of Scientific Communication During the COVID-19 Pandemic.

Simon Pollett1, Caitlin Rivers2.   

Abstract

The human and social toll of the coronavirus disease 2019 (COVID-19) pandemic has already spurred several major public health "lessons learned," and the theme of effective and responsible scientific communication is among them. We propose that Twitter has played a fundamental-but often precarious-role in permitting real-time global communication between scientists during the COVID-19 epidemic, on a scale not seen before. Here, we discuss 3 key facets to Twitter-enabled scientific exchange during public health emergencies, including some major drawbacks. This discussion also serves as a succinct primer on some of the pivotal epidemiological analyses (and their communication) during the early phases of the COVID-19 outbreak, as seen through the lens of a Twitter feed.
© The Author(s) 2020. Published by Oxford University Press for the Infectious Diseases Society of America.

Entities:  

Keywords:  COVID-19; Twitter; scientific communication; social media

Mesh:

Year:  2020        PMID: 32396623      PMCID: PMC7239231          DOI: 10.1093/cid/ciaa553

Source DB:  PubMed          Journal:  Clin Infect Dis        ISSN: 1058-4838            Impact factor:   9.079


The coronavirus disease 2019 (COVID-19) pandemic, and our knowledge about the virus, has exponentially grown since media reports of a cluster of acute respiratory infections in Wuhan, Hubei Province, China, were first reported in December 2019 [1]. By 8 January 2020, the etiology of these cases was identified as a novel betacoronavirus, then named 2019-nCoV, and 41 cases had been reported [2]. Three months later, more than 1.3 million cases and 75 000 deaths had been reported across the world [3]. The human and social toll of this pandemic has already spurred several major public health “lessons learned,” and the theme of effective and responsible scientific communication is among them. The expansion of the outbreak has demanded a rapid response from public health authorities; fundamental epidemiological and scientific evidence has been acquired at breakneck speed to support those decisions. The demanding pace and large volume of COVID-19 science generated in the last 3 months, however, has made timely scientific communication through the conventional route of published biomedical journals at best challenging, and at worst obsolete. Twitter has an estimated global user network of 330 million monthly users, including an extensive network of scientists and epidemiologists who frequently use this media for scientific exchange [4, 5]. We propose that Twitter has played a fundamental—but often precarious—role in permitting real-time global communication between scientists during the COVID-19 epidemic, on a scale not seen before. Here, we discuss 3 key facets to Twitter-enabled scientific exchange during public health emergencies, including some major drawbacks. This discussion also serves as a succinct primer on some of the pivotal epidemiological analyses (and their communication) during the early phases of the COVID-19 outbreak, as seen through the lens of a Twitter feed. We do not cover the other major roles of Twitter and other social media during this epidemic, including transmission of rapid situational awareness reports, advisories, and public education from formal public health agencies and normative bodies [6, 7]. Similarly, concerns of malignant misinformation about COVID-19 deliberately spread through this medium are beyond the scope of this commentary [8].

OUTBREAK GENOMICS IN THE AGE OF TWITTER

Twitter accelerated the rapid, global dissemination of the first whole genome sequence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) from a consortium led by Fudan University, Shanghai, to the global science community approximately 10 days after the first alerts of the SARS-CoV-2 outbreak [9]. This sequence data permitted development of a polymerase chain reaction diagnostic assay, the protocol of which was disseminated mere days later through Twitter [10]. Between 11 and 18 January the first genomic analyses of viral genomes sequenced from Chinese cases, and then initial Thailand cases, were posted in real time to Twitter [11]. Aside from confirming that this novel zoonotic coronavirus was distinct from the previous 2003 SARS outbreak, these early results suggested the outbreak was seeded by a single or small number of zoonotic spillover events [12]. Subsequent genomic analyses—again circulated through Twitter—supplied further evidence of human-to-human transmission (rather than repeated zoonotic spillovers), have allowed estimates of the SARS-CoV-2 evolutionary rate, and provided the first evidence of weeks-long cryptic circulation in the United States (Washington State) [13, 14]. The latter, critical finding was principally communicated through Twitter with subsequent mainstream media coverage [15]. Aside from enabling dissemination and discussion of these important phylogenetic analyses across multiple scientific disciplines and other stakeholders, Twitter also amplified the sharing of bioinformatic freeware and protocols to optimize SARS-CoV-2 sequencing efficiency and quality [16-18].

OPEN-SOURCE EPIDEMIOLOGY: EARLY COVID-19 LINE LISTING AND EPIDEMIC PARAMETER ESTIMATION THROUGH SOCIAL MEDIA

As with other outbreaks, early estimation of epidemic parameters during the first month of the COVID-19 epidemic has been critical to predict the epidemic trajectory and inform decision making. Twitter played a key role in soliciting volunteers to crowd-source line-list case data from media reports and other open data sources. These constantly updated line-lists were shared by multiple independent groups, thereby enabling cross-comparisons for completeness [19-21]. Indeed, such open-source line-list data remain more comprehensive than what is currently published by some other countries now experiencing major COVID-19 epidemics. Early basic reproductive number (R0) estimates were shared on Twitter (including links to independent websites and preprint repositories) by independent groups of epidemiologists [22, 23]. This permitted side-by-side comparisons of this indicator of viral transmissibility, as recently summarized by Majumder et al [23]. Rapid commentary on Twitter by scientists provided careful interpretation and caveats around these published R0 estimates [24, 25, 26], and also emphasized the inherent limitations of extrapolating predictions of epidemic trajectories from R0 estimates [24, 27]. As further noted by Majumder et al, the uncertainty intervals of these open-source R0 estimates collectively overlapped with subsequently published formal R0 estimates [28, 29]. Accurate approximation and interpretation of the COVID-19 case-fatality ratio (CFR) has been critical for resource planning and risk messaging. Real-time discussions on Twitter have highlighted requirements and considerations for severity assessments, such as the importance of case follow-up and early outbreak sampling bias in inflating early CFR estimates, as well as making distinctions between the infection fatality ratio and the CFR [30-32]. These discussion points were vital to frame any early comparisons of COVID-19 morbidity and mortality with that of seasonal or pandemic influenza [33-35]. It is important to acknowledge, however, the continued importance of rigorously peer-reviewed journal publications of COVID-19 clinical and epidemiological characteristics, especially when accompanied by expert editorials, and particularly given the exponential rise of preprint publications, which may vary in quality [36]. This is particularly important to consider as there are recent data by Majumder et al that suggest public discourse of epidemiological phenomena have been driven more by preprints than formal subsequent peer-reviewed publications [23].

SNAKES AND LADDERS: THE OPPORTUNITIES AND CHALLENGES OF TWITTER IN SCIENTIFIC CONDUCT AND COMMUNICATION DURING PUBLIC HEALTH EMERGENCIES

As highlighted in an early 2020 Nature Microbiology editorial, global scientists openly reprimanded a group who published a genomic SARS-CoV-2 analysis through Twitter but failed to properly acknowledge the source of this molecular data [37]. Such open critique through this medium helps enable codes of conduct around epidemic sequence data sharing [38]. Real-time rebuttal, coupled with supporting preprint analyses, led to fast rejection of an invalid scientific conclusion that snakes were a probable animal reservoir for SARS-CoV-2, a claim that had led to widespread misinformation [39, 40]. Similarly, prompt corrections over journalist misinterpretations of supposed pangolin origins to the SARS-CoV-2 outbreak have been valuable. In this way, Twitter has facilitated vital counternarratives from the scientific community during these and other instances of controversial scientific communication, be they claims of the zoonotic origins of SARS-CoV-2, alarmist interpretation of upper-end R0 estimates, or confusion on whether particular public health policies were grounded on goals of “herd immunity.” Twitter has and continues to serve as a valuable medium to discuss the caveats and future directions in applying infectious disease models in COVID-19 decision making [41-44]. Still, Twitter remains the double-edged sword of rapid scientific communication during the ongoing COVID-19 pandemic. As advocated on Twitter itself, scientists will need to exercise great care in their communication using this and other social media to share their research as this outbreak unfolds throughout 2020 [45].
  5 in total

1.  Early Transmission Dynamics in Wuhan, China, of Novel Coronavirus-Infected Pneumonia.

Authors:  Qun Li; Xuhua Guan; Peng Wu; Xiaoye Wang; Lei Zhou; Yeqing Tong; Ruiqi Ren; Kathy S M Leung; Eric H Y Lau; Jessica Y Wong; Xuesen Xing; Nijuan Xiang; Yang Wu; Chao Li; Qi Chen; Dan Li; Tian Liu; Jing Zhao; Man Liu; Wenxiao Tu; Chuding Chen; Lianmei Jin; Rui Yang; Qi Wang; Suhua Zhou; Rui Wang; Hui Liu; Yinbo Luo; Yuan Liu; Ge Shao; Huan Li; Zhongfa Tao; Yang Yang; Zhiqiang Deng; Boxi Liu; Zhitao Ma; Yanping Zhang; Guoqing Shi; Tommy T Y Lam; Joseph T Wu; George F Gao; Benjamin J Cowling; Bo Yang; Gabriel M Leung; Zijian Feng
Journal:  N Engl J Med       Date:  2020-01-29       Impact factor: 176.079

2.  A novel coronavirus outbreak of global health concern.

Authors:  Chen Wang; Peter W Horby; Frederick G Hayden; George F Gao
Journal:  Lancet       Date:  2020-01-24       Impact factor: 79.321

3.  Rapid outbreak response requires trust.

Authors: 
Journal:  Nat Microbiol       Date:  2020-02       Impact factor: 17.745

4.  How to fight an infodemic.

Authors:  John Zarocostas
Journal:  Lancet       Date:  2020-02-29       Impact factor: 79.321

5.  Early in the epidemic: impact of preprints on global discourse about COVID-19 transmissibility.

Authors:  Maimuna S Majumder; Kenneth D Mandl
Journal:  Lancet Glob Health       Date:  2020-03-24       Impact factor: 26.763

  5 in total
  14 in total

1.  Gender inequities in the online dissemination of scholars' work.

Authors:  Orsolya Vásárhelyi; Igor Zakhlebin; Staša Milojević; Emőke-Ágnes Horvát
Journal:  Proc Natl Acad Sci U S A       Date:  2021-09-28       Impact factor: 11.205

2.  Influential factors for COVID-19 related distancing in daily life: a distinct focus on ego-gram.

Authors:  Kyu-Min Kim; Hyun-Sill Rhee
Journal:  BMC Public Health       Date:  2022-05-10       Impact factor: 4.135

Review 3.  COVID-19 vaccine hesitancy and acceptance: a comprehensive scoping review of global literature.

Authors:  Umair Majid; Mobeen Ahmad; Shahzadi Zain; Adebisi Akande; Fahham Ikhlaq
Journal:  Health Promot Int       Date:  2022-06-01       Impact factor: 3.734

4.  "Phytopathological strolls" in the dual context of COVID-19 lockdown and IYPH2020: Transforming constraints into an opportunity for public education about plant pathogens.

Authors:  Frédéric Suffert; Muriel Suffert
Journal:  Plant Pathol       Date:  2021-07-19       Impact factor: 2.772

5.  Reliance on scientists and experts during an epidemic: Evidence from the COVID-19 outbreak in Italy.

Authors:  Pietro Battiston; Ridhi Kashyap; Valentina Rotondi
Journal:  SSM Popul Health       Date:  2020-12-24

6.  A Nationwide Virtual Research Education Program for Medical Students in Pakistan: Methodological Framework, Feasibility Testing, and Outcomes.

Authors:  Ali Aahil Noorali; Maha Inam; Hamna Shahbaz; Hareem Rauf; Faiqa Binte Aamir; Farah Khalid; Saadia Abbas; Abdullah Saeed; Muhammad Daniyal Musharraf; Asma Altaf Hussain Merchant; Babar S Hasan; Muneera A Rasheed; Fyezah Jehan; Muhammad Tariq; Adil Hussain Haider
Journal:  Front Public Health       Date:  2022-01-10

7.  Long Haul COVID-19 Videos on YouTube: Implications for Health Communication.

Authors:  Erin T Jacques; Corey H Basch; Eunsun Park; Betty Kollia; Emma Barry
Journal:  J Community Health       Date:  2022-04-12

8.  Social Advertising Effectiveness in Driving Action: A Study of Positive, Negative and Coactive Appeals on Social Media.

Authors:  Murooj Yousef; Timo Dietrich; Sharyn Rundle-Thiele
Journal:  Int J Environ Res Public Health       Date:  2021-06-01       Impact factor: 4.614

9.  Post-publication promotion in rheumatology: a survey focusing on social media.

Authors:  Saloni Haldule; Samira Davalbhakta; Vishwesh Agarwal; Latika Gupta; Vikas Agarwal
Journal:  Rheumatol Int       Date:  2020-09-13       Impact factor: 2.631

10.  Introducing the Disease Outbreak Resilience Index (DORI) Using the Demographic and Health Surveys Data from sub-Saharan Africa.

Authors:  Isaac Koomson; Moses Okumu; David Ansong
Journal:  Soc Indic Res       Date:  2022-01-18
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