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Background: In the context of the COVID-19 infodemic, the global profusion of monikers and hashtags for COVID-19 have found their way into daily communication and contributed to a backlash against China and the Chinese people. Objective: This study examines public engagement in crisis communication about COVID-19 during the early epidemic stage and the practical strategy of social mobilization to mitigate the infodemic. Methods: We retrieved the unbiased values of the top-ranked search phrases between December 30, 2019, and July 15, 2020, which normalized the anonymized, categorized, and aggregated samples from Google Search data. This study illustrates the most-searched terms, including the official COVID-19 terms, the stigmatized terms, and other controls, to measure the collective behavioral propensities to stigmatized terms and to explore the global reaction to the COVID-19 epidemic in the real world. We calculated the ratio of the cumulative number of COVID-19 cases to the regional population as the cumulative rate (R) of a specific country or territory and calculated the Gini coefficient (G) to measure the collective heterogeneity of crowd behavior. Results: People around the world are using stigmatizing terms on Google Search, and these terms were used earlier than the official names. Many stigmatized monikers against China (eg, “Wuhan pneumonia,” G=0.73; “Wuhan coronavirus,” G=0.60; “China pneumonia,” G=0.59; “China coronavirus,” G=0.52; “Chinese coronavirus,” G=0.50) had high collective heterogeneity of crowd behavior between December 30, 2019, and July 15, 2020, while the official terms “COVID-19” (G=0.44) and “SARS-CoV-2” (G=0.42) have not become de facto standard usages. Moreover, the pattern of high consistent usage was observed in 13 territories with low cumulative rates (R) between January 16 and July 15, 2020, out of 58 countries and territories that have reported confirmed cases of COVID-19. In the scientific literature, multifarious naming practices may have provoked unintended negative impacts by stigmatizing Chinese people. The World Health Organization; the United Nations Educational, Scientific and Cultural Organization; and the media initiated campaigns for fighting back against the COVID-19 infodemic with the same mission but in diverse voices. Conclusions: Infodemiological analysis can articulate the collective propensities to stigmatized monikers across search behaviors, which may reflect the collective sentiment of backlash against China and Chinese people in the real world. The full-fledged official terms are expected to fight back against the resilience of negative perceptual bias amid the COVID-19 epidemic. Such official naming efforts against the infodemic should be met with a fair share of identification in scientific conventions and sociocultural paradigms. As an integral component of preparedness, appropriate nomenclatures should be duly assigned to the newly identified coronavirus, and social mobilization in a uniform voice is a priority for combating the next infodemic. (citation: Journal of Medical Internet Research 22(11):e22639, DOI: 10.2196/22639)
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Original Paper
The COVID-19 Infodemic:Infodemiology Study Analyzing
Stigmatizing Search Terms
Zhiwen Hu1*, PhD; Zhongliang Yang2*, PhD; Qi Li2*, BA; An Zhang3, PhD
1School of Computer and Information Engineering, Zhejiang Gongshang University, Hangzhou, China
2Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing, China
3State Key Laboratory of Resources and Environmental Information System, Institute of Geographical Sciences and Natural Resources Research,
Chinese Academy of Sciences, Beijing, China
*these authors contributed equally
Corresponding Author:
Zhiwen Hu, PhD
School of Computer and Information Engineering, Zhejiang Gongshang University
No 18 Xuezheng Street
Higher Education Zone
Hangzhou, 310018
China
Phone: 86 0571 28008316
Email: huzhiwen@zjgsu.edu.cn
Abstract
Background: In the context of the COVID-19 infodemic, the global profusion of monikers and hashtags for COVID-19 have
found their way into daily communication and contributed to a backlash against China and the Chinese people.
Objective: This study examines public engagement in crisis communication about COVID-19 during the early epidemic stage
and the practical strategy of social mobilization to mitigate the infodemic.
Methods: We retrieved the unbiased values of the top-ranked search phrases between December 30, 2019, and July 15, 2020,
which normalized the anonymized, categorized, and aggregated samples from Google Search data. This study illustrates the
most-searched terms, including the official COVID-19 terms, the stigmatized terms, and other controls, to measure the collective
behavioral propensities to stigmatized terms and to explore the global reaction to the COVID-19 epidemic in the real world. We
calculated the ratio of the cumulative number of COVID-19 cases to the regional population as the cumulative rate (R) of a specific
country or territory and calculated the Gini coefficient (G) to measure the collective heterogeneity of crowd behavior.
Results: People around the world are using stigmatizing terms on Google Search, and these terms were used earlier than the
official names. Many stigmatized monikers against China (eg, “Wuhan pneumonia,G=0.73; “Wuhan coronavirus,” G=0.60;
“China pneumonia,” G=0.59; “China coronavirus,G=0.52; “Chinese coronavirus,G=0.50) had high collective heterogeneity
of crowd behavior between December 30, 2019, and July 15, 2020, while the official terms “COVID-19” (G=0.44) and
“SARS-CoV-2” (G=0.42) have not become de facto standard usages. Moreover, the pattern of high consistent usage was observed
in 13 territories with low cumulative rates (R) between January 16 and July 15, 2020, out of 58 countries and territories that have
reported confirmed cases of COVID-19. In the scientific literature, multifarious naming practices may have provoked unintended
negative impacts by stigmatizing Chinese people. The World Health Organization; the United Nations Educational, Scientific
and Cultural Organization; and the media initiated campaigns for fighting back against the COVID-19 infodemic with the same
mission but in diverse voices.
Conclusions: Infodemiological analysis can articulate the collective propensities to stigmatized monikers across search behaviors,
which may reflect the collective sentiment of backlash against China and Chinese people in the real world. The full-fledged
official terms are expected to fight back against the resilience of negative perceptual bias amid the COVID-19 epidemic. Such
official naming efforts against the infodemic should be met with a fair share of identification in scientific conventions and
sociocultural paradigms. As an integral component of preparedness, appropriate nomenclatures should be duly assigned to the
newly identified coronavirus, and social mobilization in a uniform voice is a priority for combating the next infodemic.
(J Med Internet Res 2020;22(11):e22639) doi: 10.2196/22639
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KEYWORDS
infodemiology; COVID-19; infodemic; social contagion; collective perceptual biases; collective behavioral propensities; social
mobilization
Introduction
Background
The COVID-19 infodemic, associated with the COVID-19
outbreak, is getting some attention by researchers and policy
makers [1,2]. On December 31, 2019, the novel coronavirus
(2019-nCoV) disease was first reported from Wuhan City in
China. With the spread of COVID-19, a massive information
epidemic has undermined and disrupted global efforts to fight
against COVID-19. However, the infodemic challenge does not
receive enough attention in publications to fully understand it,
and its unique risks have only begun to be explored [3]. The
infodemic is partly characterized by a high information supply
of information of variable quality, and a demand for timely and
trustworthy information about 2019-nCoV [2,4-6].
On one hand, the global profusion of running headlines often
inscribe fear, prejudice, disgust, and hostility into hashtags and
monikers, branding discrimination and stoking panic [7-9].
Those monikers and morbid contents always combine with each
other in the epicenter of an infodemic, wherein one sheds light
on the social contagion of the other. The past few months have
witnessed a growth of stigmatized monikers, which have found
their way into daily communication and contributed to the
backlash against China, Chinese people, and Asians in general
[10-13]. Even worse, scientists frequently used similar monikers
in the pandemic paper tsunami and exacerbated the situation
[14,15].
On the other hand, individual perceptual bias could lead to
insufficient or excessive information seeking, which further
results in collective perceptual biases [16]. Pithy proper names
are expected to be powerful in the ongoing campaign against
the infodemic. As an integral component of preparedness,
appropriate nomenclatures should be duly assigned to the newly
identified coronavirus, which causes respiratory tract disease
in humans and has had an impact on public health. So far, there
are no universally accepted names, either for academic-industrial
usage or consistency with international virus taxonomy.
To address such issues, we used available metadata to unfold
the nature of the COVID-19 epidemic and the infodemic in this
study [17].
Study Objectives
An inappropriate official nomenclature might fuel the
infodemics unconsciously. In recent years, humans have
witnessed several outbreaks of infectious diseases caused by
viruses, with common names given by stakeholders. Each round
of naming practice is not always successful. As a case in point,
some strongly held, but flawed, names such as “Middle Eastern
Respiratory Syndrome” [18] and “Swine flu” were accused of
unintentional social and negative economic impacts by
stigmatizing certain industries or communities. “Swine flu,” an
influenza strain that is known to have originated in pigs, resulted
in financial damage to farmers, despite there being no evidence
that it could be spread via pork consumption [19,20]. Since
these incidents, in May 2015, the World Health Organization
(WHO) released some naming conventions for the naming of
new human diseases [21].
Infodemics long predate COVID-19 [22]. Unfortunately, with
the spread of the COVID-19 epidemic, another massive
infodemic has spread virally over the world with recurring
episodes [23,24]. Previous evidence suggests that the internet,
by its nature, could amplify and relay such infodemics swiftly
worldwide, cause exaggerated panic, and progressively worsen
stigmatization against people in the epicenter of an outbreak
[23-26]. In the ongoing infodemic, Corona beer is being affected
by the name’s similarity to the deadly coronavirus. In fact, the
Mexican brand originated back in 1925 before the first strain
of coronavirus was discovered and named. To address such
challenges, the WHO declared this infodemic as the
“2019-nCoV infodemic” on February 2, 2020 [4].
Based on a critical review, this study aims to take samples of
the trillions of Google searches in connection with COVID-19
from December 30, 2019, to July 15, 2020, to address the
following research issues:
Did public engagement in the crisis communication reflect
the collective sentiment of backlash against China and
Chinese people in the real world? What were the global
and geographical patterns of collective behavioral
propensities to stigmatized monikers and the official terms?
Were informed scientists well versed in the naming
conventions to minimize unintentional negative impacts?
What is the cohesive strategy of social mobilization to fight
back against the COVID-19 infodemic?
Methods
Infodemiology, a term coined by Eysenbach, is an emerging
transdisciplinary area of research studying the epidemiology of
information to address the pressing concerns of public health
and policy decisions [2, 17,27,28]. The transdisciplinary nature
of infodemiology can be found in Multimedia Appendix 1.
As of February 29, 2020, COVID-19 has spread to 60 countries
and territories. Of these, the WHO published the number of
cumulative cases in 54 member states on February 29, 2020, as
well as Hong Kong, Macao, and Taiwan. We retrieved the
cumulative cases of three nonmember states (Iceland,
Azerbaijan, and Monaco) from their official websites. The
corresponding total populations of 2019 come from the United
Nations [29]. The cumulative rate Rcan be viewed as a ratio of
the cumulative number of COVID-19 cases to the regional
population: R = i/p, where iis the number of confirmed
infections in a given country or territory and pis the national
or regional population.
In this study, we retrieved metadata from three information
sources: an electronic books corpus (Google Books Ngram
Corpus [GBNC]), journals (Web of Science [WoS] and
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PubMed), and the internet (Google Trends Index [GTI]), and
used them to facilitate subsequent analysis.
First, the GBNC provides a unique linguistic landscape that
benefits from centuries of rich grammatical and lexical resources
as well as cultural contexts [30]. Each taxonomic procedure
often begins with a search through tomes for comparative
morphologic variations to crystallize a pithy and appropriate
neologism. For example, the earliest usage of coronavirus and
coronaviruses could provide an insightful and compelling
argument for the historical story and help us understand the
essence of the name. The diachronic discourse of coronavirus,
coronaviruses, Coronaviridae, and Nidovirales promises to
articulate the unfolding chronological historical time scale from
when these terms were first used [31].
Second, WoS and PubMed are publication databases with rich
structural metadata. Scientometric analysis also promises to
articulate the unfolding chronological picture of infodemiology.
Under the umbrella of infodemiological scenarios, coupled with
GBNC, scientometric analysis on diachronic discourses of
pertinent keywords and phrases could reflect the historical
milestones and the status quo in the field of human
coronaviruses (HCoVs) research.
Third, the GTI part of this study commenced on December 30,
2019, and involved daily data collection worldwide until July
15, 2020, in 60 countries and territories that have reported
confirmed cases of COVID-19 as of February 29, 2020. In the
ongoing COVID-19 infodemic, stigmatized monikers against
controls are ideal indicators of negative bias, and the unbiased
and normalized GTIs were employed to determine their
populational usages across various regions over time to
characterize collective perceptual biases. GTI provides
knowledge dissemination metrics for query incidences of
relevant keywords and phrases, since about 63% of users on the
internet use Google to search for ubiquitous information [32].
Three prominent strengths of GTI reflect the global reactions
to major events in the real world: (1) vast data sets that include
trillions of random searches; (2) unbiased sampling from the
anonymized, categorized, and aggregated raw data; and (3)
normalized indexes reconciling the dynamic nature of search
volumes and the different population ratios in different regions.
Therefore, the dynamic spatiotemporal pattern of GTI provides
a unique lens into collective behavioral propensities of crowd
behavior and demographic perception of a social contagion.
Intensive information seeking or avoidance choices may
reinforce people’s cognition in both positive and negative ways,
which is proactively rewarded by the feedback of the targeted
information available [16]. In this study, a code scheme of
subjective searches in daily communication was designed to fit
three inclusion criteria: (1) top-ranked search interests, (2)
formal and with complete spelling, (3) consistent with the global
participants as much as possible. The collective behavioral
propensities to the stigmatized terms were measured and
compared with that of the control groups (the official terms and
their counterparts). Herein, collective behavioral propensities
to stigmatized terms directly represented the latent tendency to
gather and interpret health care information available, which
also reflected collective perceptual biases on preconceived
judgements and social contagion [16,33-35].
To demonstrate the collective behavioral propensities,
descriptive analysis and formal statistical analysis were carried
out. For the descriptive analysis, the daily indexes of the relative
search term volumes were separately mapped on a six-color
rendering scale from 0 to 100. The earliest day of each terms
debut was tracked and identified. Next, we introduced the Gini
coefficient to measure the collective heterogeneity of crowd
behavior. We denoted the search record of term Xin the Google
Trends data set as X= {x1, x2,...xn}, where xirepresents the
(normalized) search frequency of term Xat the i-th time step.
The mean value of Xis:
The Gini coefficient Gfor term Xcan then be calculated as
follows:
When the element values in Xare equal, the Gini coefficient G
takes the minimum value of 0, and when xi=0 for i= 1, ..., n–1
and xn=1, Gwill approach the maximum value of 1. The smaller
the Gis, the lower the collective heterogeneity of crowd
behavior is and the higher the homogeneity of individual
behaviors are. Conversely, it indicates that people are divided
in the consistency of individual behaviors.
Results
The Enigmatic Nature of HCoVs Puts People on Edge
It is necessary to take a glimpse into the hierarchical Linnaean
category of emerging coronaviruses [36,37]. As an international
authoritative body, the WHO is responsible for naming new
human infectious diseases. In 1966, the International Committee
on Nomenclature of Viruses (ICNV) was established with the
mission of introducing some degree of order and consistency
into the naming of viruses. In 1973, the ICNV became the
International Committee on Virus Taxonomy (ICTV), a global
authority on the designation and naming of viruses. There are
seven strains of HCoVs—HCoV-229E, HCoV-NL63,
HCoV-OC43, HCoV-HKU1, severe acute respiratory
syndrome–related coronavirus (SARS-CoV), Middle East
respiratory syndrome–related coronavirus (MERS-CoV), and
SARS-CoV-2—known to cause the common cold as well as
more severe respiratory disease. Of those, HCoV-229E,
HCoV-NL63, HCoV-OC43, and HCoV-HKU1 are routinely
responsible for mild respiratory illnesses like the common cold
but can cause severe infections in immunocompromised
individuals, while the others have caused more severe diseases
[38].
The diachronic discourse of coronavirus and coronaviruses in
the English corpus unveils that there was a mild increase in the
numbers of printed books dealing with HCoVs after the initial
description of coronaviruses in 1968 [39-41]. The discovery of
the novel strain had stimulated a new wave of research into
coronavirus and the diseases it causes. Furthermore,
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meta-analysis results from WoS and PubMed indicated that the
known knowledge remains off-limits in the field of combating
emerging HCoVs [42]. The WHO declared the 2019-nCoV
outbreak a Public Health Emergency of International Concern
(PHEIC) on January 30, 2020. This is the sixth time the WHO
has declared a PHEIC since the International Health Regulations
(IHR) came into force in 2005. Before COVID-19, there have
been five global health emergencies since such declaration was
formalized: swine flu (2009), polio (2014), Ebola (2014 and
2019), and Zika (2016). The detailed descriptions of diachronic
discourse analysis and scientometric analysis in this study can
be found in Multimedia Appendix 2.
SARS-CoV-2 is the seventh identified coronavirus that can
cause diseases of the respiratory tract via human-to-human
transmission. It caused a mysterious pneumonia outbreak that
is spreading far more quickly than the SARS-CoV and
MERS-CoV diseases [1,43,44], even though the epicenter of
the outbreak was locked down to curb the pandemic spread
[42,45]. Presently, its underlying mechanism of clinical severity
is yet to be determined, although many fatal cases have occurred
[46].
On the one hand, the outbreaks of SARS-CoV, HCoV-HKU1,
and SARS-CoV-2 were initially linked to China and lead people
into the deep-rooted impression of China as an unsanitary entity.
Chinese “wet markets” have been widely depicted as unsanitary
hot spots for the transmission of zoonotic diseases [15,47-56].
Moreover, China is inevitably vulnerable to be accused of lax
epidemiological control over HCoVs [57-63].
On the other hand, the enigmatic nature of HCoVs and the many
unknowns about these epidemics have put people on edge.
Information overload always follows closely behind the
epidemics caused by HCoVs, especially in the age of the internet
[64]. This enigmatic nature deepens people’s anxiety in a way
that makes them respond to provocative online posts, whether
intentional or not.
Collective Behavioral Propensities in the Public
We further examined what people were interested in and curious
about with COVID-19. Google Trends showed the
most-searched interest in the official terms (COVID-19,
2019-nCoV, SARS-CoV-2, and novel coronavirus pneumonia
[NCP]), the stigmatized terms (Wuhan coronavirus, China
coronavirus, Chinese coronavirus, Wuhan pneumonia, and China
pneumonia), and other counterparts (novel pneumonia and novel
coronavirus) from December 30, 2019, to July 15, 2020 (Figures
1and 2). Those dynamic searches are indicators of collective
behaviors across various regions over time. The detailed
descriptions of the code scheme of multifarious naming practices
can be found in Multimedia Appendix 3.
Figure 1. Calendar illustration on the relative search interest of the COVID-19 infodemic in the context of the COVID-19 epidemic (as of 15 July
2020; part 1).
People around the world are divided in their own opinions on
the internet and in daily communications. For the descriptive
analysis, a striking feature was that some stigmatized monikers
had comparatively high frequencies of collective usage. Being
echoed by daily responses, the negative and lasting
consequences pinpoint that those stigmatized names might have
contributed to the recent backlash against China and Chinese
people.
For the formal statistical analysis, first, the Gini coefficients of
the stigmatized terms (eg, “Wuhan pneumonia, G=0.73;
“Wuhan coronavirus,” G=0.60; “China pneumonia,” G=0.59;
“China coronavirus,G=0.52; “Chinese coronavirus,G=0.50)
are significantly higher than those of the official terms (eg,
“COVID-19, G=0.44; “SARS-CoV-2,” G=0.42; “Novel
Coronavirus Pneumonia,” G=0.46) and other controls (“novel
pneumonia,” G=0.45 and “novel coronavirus,” G=0.49). This
finding strongly indicates that the homogeneity of individual
propensities to stigmatized monikers are lower than the official
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terms and the neutral names. The vulnerable population are
highly susceptible to external negative sentiments. The 2019
novel coronavirus is thought to have originated in China, this
misunderstanding may have led to the high usage of “Wuhan
coronavirus, “China coronavirus, “Chinese coronavirus,
“Wuhan pneumonia,” “China pneumonia,” and other stigmatized
monikers, even after July 2020. Second, after January 15,
multifarious stigmatized monikers against Chinese people have
prevailed in the public. “COVID-19” (G=0.44) took over from
the premature name “2019-nCoV” (G=0.63), the latter finishing
around February 28. Third, a notable pattern was observed after
the announcements of the terms “COVID-19” and
“SARS-CoV-2” (the collective usage of “SARS-CoV-2” has
failed to match that of “COVID-19” in the public). The official
terms “COVID-19” and “SARS-CoV-2” have not become the
de facto standard usages. However, in the long run, the gradual
increase in official names would be beneficial to correct ethnic
stigmatization.
Figure 2. Calendar illustration on the relative search interest of the COVID-19 infodemic in the context of the COVID-19 epidemic (as of July 15,
2020; part 2).
To further examine the demographical perceptions of collective
behavioral propensities in the ongoing infodemic, we
characterized the relationship between the geographical interest
of stigmatized monikers and the cumulative rate of 58 countries
and territories in which confirmed cases of COVID-19 have
been reported. The results clearly unveil that people in Egypt,
Greece, New Zealand, the United Kingdom, the United States,
Canada, Finland, Russia, the Philippines, Denmark, Vietnam,
Nepal, and Mexico prefer to use stigmatized monikers against
Chinese people in comparison with other counterparts (Figure
3). As of February 29, 2020, up to 60 countries and territories
have reported confirmed cases of COVID-19, including Taiwan,
Iceland, Azerbaijan, and Monaco. There is no metadata available
for San Marino and Monaco in Google Trends, but the
geographical interest of stigmatized monikers against Chinese
people in the other 58 territories was normalized by median
volume to compare with each other. The cumulative rate is the
ratio of the confirmed cases to the total populations in the
countries or territories (Multimedia Appendix 4).
To characterize the patterns behind such collective perceptual
biases, we further scrutinized the geographical interest of
stigmatized monikers against China in 13 territories with low
cumulative rates over time (Figure 4). This illustration unveils
the geographical interest of stigmatized monikers in 13
territories (Egypt, Greece, New Zealand, the United Kingdom,
the United States, Canada, Finland, Russia, the Philippines,
Denmark, Vietnam, Nepal, and Mexico) between January 1,
2020, and February 29, 2020. The median volumes of the
corresponding search queries showed the trend of collective
behavioral propensities over time. Comparatively, some
stigmatized monikers against China saw high frequencies after
January 16. The substantial pattern of the high consistent curve
indicates that negative perceptual bias has been observed in the
perception of the natural origin of COVID-19 in the public.
As a co-occurrence perceptual phenomena, the illustration could
corroborate that people have used stigmatized monikers with
high frequencies in these territories after January 16, 2020.
People have a negative bias in their perception of COVID-19’s
natural origin in these regions. Moreover, people hold negative
perceptions of the authoritative responses in many countries
[37,42,65,66]. The prognostic significance of our findings is
that such approaches are expected to cause a psychological
typhoon eye effect—a paradoxical phenomenon that the
respondents closer to the epicenter of the pandemic appear to
be the least concerned by the imminent risks—in the near future.
People hold negative perceptual bias in their perception of
COVID-19’s natural origin in 58 countries and territories with
low cumulative rates (R; Figure 5). The substantial pattern was
observed on the geographical map of 58 countries and territories
with low cumulative rates and negative perceptual bias in the
perception of the natural origin of COVID-19 in the public. In
the sociocultural setting with a relatively complex context
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beyond the epidemiological dimension, this panoramic map
approach allowed us to better understand the prevalence and
severity of the COVID-19 infodemic throughout the regions,
comparatively. This finding reminds us that policy makers
should learn from best practices to reduce deliberate infodemic
risks, providing resources for knowledge and expertise in the
academic sphere as well as in the public.
Figure 3. Four-quadrant diagram of the relationship between the geographical interest of stigmatized monikers and cumulative rate.
Figure 4. The dynamic interest of stigmatized monikers against China in territories with low cumulative rates.
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Figure 5. Geographical map of the COVID-19 infodemic (February 29, 2020). WHO: World Health Organization.
What are the plausible reasons behind such collective perceptual
biases? Demographically, according to a Pew Research Center
survey [67], a median of 40% of the surveyed countries had a
positive view of China, compared with a median of 41% who
had an unfavorable opinion. However, recognizing that
COVID-19 has a potential public health impact, people are
asking existential questions, making them vulnerable to the
surfeit of information contagion from the outside world. When
emerging cases were reported in their country, infodemics about
the cause of the epidemic began, and nothing seemed certain
or obviously right. As a case in point, the Bill & Melinda Gates
Foundation, an American private foundation that has spent
billions on global health care, have been suspiciously accused
of manufacturing COVID-19 as biological warfare with the CIA
to “wage economic war on China.However, this was evidently
not plausible. Such an infodemic campaign reminds us that
authoritative organizations should work together with each other
and cultivate a well-trained team of professionals to mediate
infodemic risks.
From the beginning of the COVID-19 epidemic, people in most
Asia-Pacific countries, “where many more name China as a top
threat” [67], prioritized relations with China to jointly fight
COVID-19, rather than use malicious discrimination against
China. Regrettably, some individuals and media outlets have
been committed to showing a negative image of China by
promoting unfounded conspiracy theories such as a nonnatural
origin of COVID-19 [68], a coronavirus that was made in China
(even including desecration of the Chinese national flag), “China
is the real Sick Man of Asia” [69], and China’s Chernobyl
moment. Some instigators have made open apologies for
spreading these rumors [14], but others are intent on
whitewashing their words under the guise of freedom of speech.
Such voices do nothing but breed the pathogen of fear, panic,
prejudice, disgust, xenophobia, and racism [9,14,70,71].
Undoubtedly, they have been met overwhelmingly with harsh
criticism. On February 8, 2020, the Lancet published a statement
in solidarity with Chinese professionals in combating the novel
coronavirus outbreak and called for fighting against the
infodemics [68,72]. Later, more public health scientists have
endorsed this statement.
Collective Perceptual Biases in the Scientific
Community
Given that multifarious stigmatized monikers have become
dominant in the public, what is being used in the scientific
sphere? Admittedly, the plethora of papers on the pandemic
have somewhat aggravated the collective perceptual biases,
whether intentional or unintentional [73-75]. It is critical to have
individuals who are well versed in naming conventions
collaborate directly with researchers on a regular basis.
Unfortunately, before the antidotes for the infodemic (ie, proper
names) find their way into the public mind, debate on interim
solutions has been ongoing (Multimedia Appendix 3).
On January 12, 2020, the WHO provisionally named the 2019
novel coronavirus disease “2019-nCoV. China’s National
Health Commission (CNHC) decided to temporarily call the
disease “Novel Coronavirus Pneumonia” or “NCP” on February
7 (Figure 2). The CNHC’s official name has invoked intensive
arguments outside as well as inside the scientific community.
First, Chinese scientists are divided on that official name.
Supporters say the descriptive name follows typical
classification practices, whereas opponents claim that it could
be easily misunderstood and abused to sow the seeds for panic.
Second, the word novel is confusing because neither the disease
nor the host can be used to reliably determine the virus’s
novelty. Arguably, high mutation and gene recombination rates
make this type of virus ideal for pathogen evolution [76]. Once
viral mutation happens, it will no longer be novel.
Before that, the 2019 novel coronavirus was designated as
“WH-Human-1 coronavirus” (“Wuhan-Human-1 coronavirus”)
by a group of scientists in Nature on February 3, 2020 [77]. In
the same vein, on February 11, another name, “HARS-CoV”
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(Han acute respiratory syndrome coronavirus) with Han standing
for Wuhan in Chinese, was proposed in The Lancet (of note,
some of the coauthors are members of the WHO IHR
Emergency Committee) [15]. Obviously, such practices are
against the naming principles of the WHO—geographic
locations should be avoided in virus or disease names, and the
proper names should be short and easy to pronounce [78]. Such
names might provoke unintended negative impacts by
stigmatizing Wuhan citizens and Chinese people. Those flawed
notions take hold and should be duly corrected, as well as other
similar paradigms (Table 1).
Table 1. Chronological list of published articles with multifarious proposed names.
Proposed name
Articlea
Date (2020)
Wuhan coronavirus pneumoniaCheng et al [79]January 18
China coronavirusParry [80]January 20
Wuhan virusNature [81]January 21
China coronavirusCallaway and Cyranoski [82]January 22
Wuhan coronavirusLiu and Saif [83]January 22
China virusCallaway and Cyranoski [84]January 23
China coronavirusMahase [85]January 24
China coronavirusMahase [86]January 28
China coronavirusParry [87]January 29
China coronavirusCallaway [88]January 31
China coronavirusMahase [89]January 31
Novel Chinese coronavirusBassetti et al [90]January 31
Wuhan virusRalph et al [47]January 31
WH-Human-1 Coronavirusb
Wu et al [77]February 3
China coronavirusParry [91]February 4
PARS-CoVc
Jiang et al [92]February 5
China coronavirusCyranoski [93]February 7
HARS-CoVd
Wang et al [15]February 11
SARS-CoV-2Coronaviridae Study Group of the International Committee on Taxonomy of Viruses [38]February 11
Wuhan novel coronavirusZhou et al [94]February 12
TARS-CoVe
Jiang and Shi [95]February 14
HCoV-19f
Jiang et al [96]February 19
Wuhan-2019-nCoVGoh et al [97]February 19
NCIPg
Kooraki et al [98]February 19
NCPh
Xia et al [99]February 26
aThe metadata of the articles were retrieved from PubMed as of February 26, 2020.
bWH-Human-1 Coronavirus: Wuhan-Human-1 coronavirus.
cPARS-CoV: pneumonia acute respiratory syndrome coronavirus.
dHARS-CoV: Han acute respiratory syndrome coronavirus.
eTARS-CoV: transmissible acute respiratory syndrome coronavirus.
fHCoV-19: human coronavirus 2019.
gNCIP: novel coronavirus-infected pneumonia.
hNCP: novel coronavirus pneumonia.
In response to such concerns, on February 11, 2020, the WHO
officially renamed “2019-nCoV” as “COVID-19,with CO
meaning corona, VI for virus, Dfor disease, and 19 referring
to 2019. This generic descriptive reassignment offers an overdue
correction to those strongly held but flawed notions, with the
hope of minimizing stigma. Coinciding with the WHO’s latest
announcement, in a bioRxiv preprint [100], a new name “Severe
Acute Respiratory Syndrome coronavirus 2” or “SARS-CoV-2”
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was penned by the Coronavirus Study Group of the International
Committee on Taxonomy of Viruses (ICTV-CSG) on the same
day. ICTV-CSG explains that this designation highlights the
new strain’s similarity to SARS-CoV [38]. It is unclear whether
this proposal name will be approved by the next plenary meeting
of ICTV.
The WHO and some prominent virologists are far less skewed
toward SARS-CoV-2, the nomenclature endorsed by ICTV-CSG
[96,101]. Outside the academic-industrial sphere, people also
argued against this proposed name. Although it seems natural
for ICTV-CSG to add a numeral 2behind “SARS-CoV” to
signify their relation, many prominent scientists have scrambled
to refute this claim. To the untrained eye, the hasty designation
may mislead the public to perceive a more severe virus strain
as a direct descendant of SARS-CoV, rather than just a close
affinity for the causative agent of another major viral outbreak
in China in 2002 and 2003. Before that, on February 5, 2020,
Jiang and colleagues [92] proposed another name, “Pneumonia
Acute Respiratory Syndrome Coronavirus” (“PARS-CoV”) in
Cellular & Molecular Immunology. By the same token, this
assignment also intends to retain equivalent terminology to
SARS-CoV. Nonetheless, only 2 weeks later, without mention
of their earlier similar formulations [92,95], they reintroduced
the third name “HCoV-19” (“Human coronavirus 2019”) in The
Lancet [96], objecting to the usage of SARS-CoV-2.
The looming worry is that the public are susceptible to
SARS-CoV [25], which evokes the memory of the higher case
fatality ratio. On February 9, 2020, Chen Huan-chun, a Chinese
academician and virologist, made a public apology for
mistakenly saying 2019-nCoV is SARS-CoV, which had struck
a nerve and aroused great consternation in the Chinese public.
Mitigating infodemic risks by making informed and judicious
choices is a catch-22 for authoritative organizations. It is
necessary to punctuate heuristic cautions and continuous
introspection of previous multifarious names [18,25,78,101],
which is a requisite bedrock of such scientific efforts. Recently,
global profusion of candidates has been discussed inside the
scientific community, as well as on social media (eg,
transmissible acute respiratory syndrome coronavirus
[TARS-CoV] [95] and contagious acute respiratory syndrome
coronavirus [CARS-CoV]). Whatever merits and demerits each
term has, some of them should be fairly recognized with
plausible reasons. Authorities should have an open mind to the
modest introspections and rededications of such collective
efforts. On February 22, 2020, CNHC officially renamed the
temporary English name “NCP” as “COVID-19,with the hope
of standing with the WHO and further discouraging the use of
stigmatized titles [102].
Combating the COVID-19 Infodemic: Same Mission,
Diverse Voices
As the COVID-19 epidemic spreads, so does the information
epidemic. The COVID-19 infodemic has introduced a new round
of challenges for crisis communication, just as Dr Tedros
Adhanom Ghebreyesus, the Director-General of the WHO,
remarked at the Munich Security Conference on February 15,
2020: “We’re not just fighting an epidemic; we’re fighting an
infodemic.” Infoveillance is an effective strategy against
infodemics [34,35,103]. Unfortunately, with the same mission
of corroborating reliable information and keeping people
informed, different practitioners are upholding diverse voices
in the campaigns against the ongoing information epidemic. As
can be seen from Figure 6, Google Trends showed that the
interest of the portmanteau words “infodemic,” “disinfodemic,
and “misinfodemic” from January 1, 2020, to July 15, 2020.
The discourse system to address the present challenge is divided
into three camps: the infodemic campaign endorsed by the WHO
partnered with internet giants worldwide, the disinfodemic
campaign backed by organizations led by the United Nations
Educational, Scientific and Cultural Organization (UNESCO),
and the misinfodemic campaign supported by other practitioners.
Although the infodemic campaign is dominating the fray, most
people are currently more interested in what is going on in the
real world but are curious about what an infodemic is. The
detailed descriptions of the code scheme of combating the
COVID-19 infodemic in this study can be found in Multimedia
Appendix 3.
In 2002, Eysenbach [27, 103] coined the portmanteau
“infodemiology” (a novel transdisciplinary science to unravel
the complex propagation patterns of misinformation and public
health relevant information) along with the portmanteau
“infoveillance” (a type of syndromic surveillance that uses
online content). On February 2, 2020, the WHO adopted the
term “infodemic” as an “overabundance of information – some
accurate and some not that makes it hard for people to find
trustworthy sources and reliable guidance when they need it”
[1]. In the aftermath of the online technical consultation on the
COVID-19 infodemic [1], the WHO crystallized an
evidence-based framework to underpin infodemic management
interventions [1, 2, 104]. In the disinfodemic campaign, Posetti
and Bontcheva [105] proposed the neologism “disinfodemic”
(a blend of dis-, information, and epidemic) in the
research-based policy briefs of UNESCO, considering its
opposite of information [106]. A minority of researchers favor
the term “misinfodemic” (a blend of mis-, information, and
epidemic) in line with misinformation [107]. In contrast,
“infodemic” is a more efficient portmanteau than “disinfodemic”
or “misinfodemic” for communicative efficiency determined
by shorter orthographic and phonetic length, according to Zipf’s
[108,109] principle of least effort governing human lexicons.
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Figure 6. Illustration on the relative search interest of information contagion from around the world. EPI-WIN: Information Network for Epidemics;
WHO: World Health Organization.
On the other hand, it is critical to engage individuals to fully
realize the damaging effect of infodemics and participate in the
initiative of disproving COVID-19 myths. With social network
giants worldwide, the WHO has been committed to curb the
infodemics. For example, as part of the coordinated action,
Facebook flagged around 50 million pieces of
COVID-19–related content in April 2020. However, according
to a Pew Research Center’s American News Pathways survey,
about three in ten Americans still believe the viral conspiracy
theories (COVID-19 was created in a lab and the COVID-19
outbreak was intentionally planned by people in power) [110].
Therefore, drawing on the lessons learned from the
contextualized pollution of the media ecosystem, each one of
us should contribute to the fight against both societal COVID-19
and information contagion in the most effective way.
Discussion
Principal Findings
With an emphasis on infodemiological analysis and
meta-analysis on the COVID-19 epidemic and infodemic, we
scrutinized the collective communication behaviors on the
internet and pertinent usages in publications in sociocultural
paradigms to uncover collective behavioral propensities and
consequences.
First, psychologists often make claims about the relatedness
between epidemics and panic based on qualitative evidence.
The quantitative results reveal that people are invariably
vulnerable to panic attacks during episodes of epidemics with
an enigmatic nature. People around the world are divided in
their favor of stigmatized monikers because of perceptual bias
in the public and scientific communities. People in 13 (22%)
out of 58 territories with low cumulative rates had negative
behavioral propensities to stigmatized monikers in their daily
communications. Perceptual bias in the perception of the natural
origin of COVID-19 is part of the reason for specific regions,
rather than the degree of infection in their territories.
Second, infodemics follow closely on the heels of every
pathogen [5,6,23,24,37], branding discrimination and stoking
panic. Official names would duly discourage the spread of
regional stigmatization and racial discrimination, and reverse
negative perceptual biases and collective behavioral propensities
in public engagement.
Third, the coordinated campaign of fighting against the
COVID-19 infodemic has called for an approachable uniform
voice in line with the same mission, keeping lay audiences
informed.
Conclusion
With the benefit of hindsight provided by the Gini coefficient
(G), the contextualized results indicate that many stigmatized
monikers against China had a higher collective heterogeneity
of crowd behavior than the official terms between December
30, 2019, and July 15, 2020. The prognostic significance of
information seeking and avoidance is that infodemiological
analysis could provide a hallmark reference to reframe
extensible discussions on the COVID-19 epidemic and
infodemic, as well as substantial patterns of the next infodemic.
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At this critical moment, an epoch-making name is expected to
be scientifically pithy and socially acceptable, with minimal
unintentional negative impacts on nations, economies, and
people. This is a positivist doctrine, not merely for naming a
virus but for the vitality of science and the promotion of social
progress. Obviously, some naming practices went awry,
intentionally or not [14]. A learning lesson from the infodemic
is the necessity of coming up with guidelines for the adoption
of practical principles intended to enhance the possibility for
the lessening of stigmatization and discrimination.
Technically, we now see collaborative efforts as a potential way
to help strengthen and standardize ongoing international
initiatives of the WHO and the ICTV [5,6]. Admittedly,
understanding the way naming rules strengthen the integrity
and quality of naming practices with the original mission
remains nominal rather than substantial [18,25,78,101]. A
Nature editorial remarked, “As well as naming the illness, the
WHO was implicitly sending a reminder to those who had
erroneously been associating the virus with Wuhan and with
China in their news coverage — including Nature. That we did
so was an error on our part, for which we take responsibility
and apologize” [14]. As another precaution, the word novel was
recommended by the WHO for “indicating a new pathogen of
a previously known type, recognizing that this term will become
obsolete if other new pathogens of that type are identified” [21].
However, stakeholders frequently reserve novel for indicating
new types of viruses, lest this word fundamentally lose its impact
without regular amendments.
Acknowledgments
We express indebtedness to anonymous reviewers for their valuable and constructive comments. ZH thanks Dr Kenneth McIntosh
and Dr Elliot Lefkowitz for their personal communications. This study was supported in part by the National Natural Science
Foundation of China under Grant U1936208 and Zhejiang Provincial Natural Science Foundation of China under Grant
LZ21F020004.
Authors' Contributions
ZH was involved in the conceptual design of the study. ZH, ZY, QL, and AZ performed the metadata analyses. All authors wrote
and approved the final manuscript.
Conflicts of Interest
None declared.
Multimedia Appendix 1
The transdisciplinary nature of infodemiology.
[DOCX File , 408 KB-Multimedia Appendix 1]
Multimedia Appendix 2
Diachronic discourse analysis and scientometric analysis.
[DOCX File , 146 KB-Multimedia Appendix 2]
Multimedia Appendix 3
Code schemes.
[DOCX File , 73 KB-Multimedia Appendix 3]
Multimedia Appendix 4
Cumulative rates.
[XLSX File (Microsoft Excel File), 14 KB-Multimedia Appendix 4]
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Abbreviations
CARS-CoV: contagious acute respiratory syndrome coronavirus
CNHC: China's National Health Commission
GBNC: Google Books Ngram Corpus
GTI: Google Trends Index
HARS-CoV: Han acute respiratory syndrome coronavirus
HCoV: human coronavirus
HCoV-19: human coronavirus 2019
ICNV: International Committee on Nomenclature of Viruses
ICTV: International Committee on Virus Taxonomy
ICTV-CSG: Coronavirus Study Group of the International Committee on Taxonomy of Viruses
IHR: International Health Regulations
MERS-CoV: Middle East respiratory syndrome–related coronavirus
NCP: novel coronavirus pneumonia
PARS-CoV: pneumonia acute respiratory syndrome coronavirus
PHEIC: Public Health Emergency of International Concern
SARS-CoV: severe acute respiratory syndrome–related coronavirus
TARS-CoV: transmissible acute respiratory syndrome coronavirus
UNESCO: United Nations Educational, Scientific and Cultural Organization
WH-Human-1 coronavirus: Wuhan-Human-1 coronavirus
WHO: World Health Organization
WoS: Web of Science
2019-nCoV: novel coronavirus
Edited by G Eysenbach, R Kukafka; submitted 18.07.20; peer-reviewed by P Rzymski, A Chang; comments to author 02.08.20; revised
version received 19.08.20; accepted 03.11.20; published 16.11.20
Please cite as:
Hu Z, Yang Z, Li Q, Zhang A
The COVID-19 Infodemic: Infodemiology Study Analyzing Stigmatizing Search Terms
J Med Internet Res 2020;22(11):e22639
URL: http://www.jmir.org/2020/11/e22639/
doi: 10.2196/22639
PMID:
©Zhiwen Hu, Zhongliang Yang, Qi Li, An Zhang. Originally published in the Journal of Medical Internet Research
(http://www.jmir.org), 16.11.2020. This is an open-access article distributed under the terms of the Creative Commons Attribution
License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any
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bibliographic information, a link to the original publication on http://www.jmir.org/, as well as this copyright and license information
must be included.
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... The first report of a case was in Wuhan in China, a city home to 11 million people. That eventually resulted in an ongoing pandemic (Hu et al., 2020). This pandemic is thought to have developed from bats as the original host and was subsequently transmitted to humans via another animal host, possibly at a wet market for live animal trading (Guo et al., 2020). ...
... The coronavirus is transferrable and causes respiratory tract disease in humans, which has a potential public health impact (Hu et al., 2020). It was first identified in December 2019 in Wuhan, Hubei province in China, and has resulted in an ongoing pandemic. ...
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Background/objective: The understanding and practice of public health crisis communication are improved through the study of responses to past crises, but require retooling for present challenges. The ‘Addressing Ebola and other outbreaks’ checklist contains guiding principles built upon maxims developed from a World Health Organization consultation in response to the mad cow (bovine spongiform encephalopathy) crisis that were later adopted for Ebola. The purpose of this article is to adapt the checklist for the health communication challenges and public health practices that have emerged during the coronavirus disease 2019 (COVID-19) pandemic. The communication challenges of promoting vaccine acceptance are used to illustrate a key area that requires strengthened communication. Type of program or service: Effective communication principles for application during the COVID-19 pandemic. Results: The COVID-19 pandemic has introduced unique challenges for public health practitioners and health communicators that warrant an expansion of existing health communication principles to take into consideration: the new infodemic (or mis/disinfodemic) challenge – particularly as treatments and vaccines are being developed; communication of risk and uncertainty; health-information behaviours and the instantaneous nature of social media, and the relationship between media literacy and health literacy; the effects of the pandemic on other health issues; and the need for a flexible communication strategy that adapts to the different stages of the pandemic. Lessons learnt: Principles discussed in this article will help build preparedness capacity and offer communication strategies for moving from the acute phase to the ‘next normal’ with likely prevention (e.g. herd immunity achieved through vaccination) and societal COVID-19 resilience.
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Background: An infodemic is an overabundance of information - some accurate and some not - that occurs during an epidemic. In a similar manner to an epidemic, it spreads between humans via digital and physical information systems. It makes it hard for people to find trustworthy sources and reliable guidance when they need it. Objective: A WHO technical consultation on responding to the infodemic related to the COVID-19 pandemic was held, entirely online, to crowdsource suggested actions for a framework for infodemic management. Methods: A group of policymakers, public health professionals, researchers, students and other concerned stakeholders was joined by representatives of the media, social media platforms, various private sector organizations and civil society to suggest and discuss actions for all parts of society, and multiple related professional and scientific disciplines, methods and technologies. 594 ideas for actions were crowdsourced online during the discussions and consolidated into suggestions for an infodemic management framework. Results: The analysis team distilled the suggestins into a set of 50 proposed actions for a framework for managing infodemics in health emergencies. The consultation revealed six policy implications to consider. First, interventions and messages must be based on science and evidence, and must reach citizens and enable them to make informed decisions on how to protect themselves and their communities in a health emergency. Second, knowledge should be translated into actionable behaviour-change messages, presented in ways that are understood by and accessible to all individuals in all parts of all societies. Third, governments should reach out to key communities to ensure their concerns and information needs are understood, tailoring advice and messages to address the audiences they represent. Fourth, to strengthen the analysis and amplification of information impact, strategic partnerships should be formed across all sectors, including but not limited to the social media and technology sectors, academia, and civil society. Fifth, health authorities should ensure that the above actions are informed by reliable information that helps them understand the circulating narratives and changes in the flow of information, questions and misinformation in communities. Sixth, following experiences to date in responding to the COVID-19 infodemic and the lessons from other disease outbreaks, infodemic management approaches should be further developed to support preparedness and response and to inform risk mitigation, and enhanced through data science and socio-behavioural and other research. Conclusions: The first version of this framework proposes five action areas in which WHO Member States and actors within society can apply, according to their mandate, an infodemic management approach adapted to national contexts and practices. Responses to the COVID-19 pandemic and the related infodemic require swift, regular, systematic and coordinated action from multiple sectors of society and government. It remains crucial that we promote trusted information and fight misinformation, thereby helping save lives.
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In this ongoing SARS-CoV2 Corona virus pandemic, we are witnessing an uninhibited spread of mis-information on various social media platforms. This spread of mis-information or “mis-infodemic” is playing a negative role in our fight against the virus with far reaching consequences. International organizations like the WHO and other governmental organizations have geared up to the occasion to limit the spread of these and bring clarity in this context. In this time of crisis, risk communication is vital in the communication between organizations/government and the people. But apart from the organizations, the onus is on the people and media to realise the importance and verify the authenticity of information being circulated. It is imperative that information, being a double edged sword, is handled with caution and effective communication strategies are devised for the dissemination of accurate and scientific health related information. Social media can be used in a constructive way in mitigating the effects of this pandemic for the betterment of the society.
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Unstructured: In this issue of the Journal of Medical Internet Research, the World Health Organization (WHO) is presenting a framework for managing the coronavirus disease (COVID-19) infodemic. Infodemiology is now acknowledged by public health organizations and the WHO as an important emerging scientific field and critical area of practice during a pandemic. From the perspective of being the first "infodemiolgist" who originally coined the term almost two decades ago, I am positing four pillars of infodemic management: (1) information monitoring (infoveillance); (2) building eHealth Literacy and science literacy capacity; (3) encouraging knowledge refinement and quality improvement processes such as fact checking and peer-review; and (4) accurate and timely knowledge translation, minimizing distorting factors such as political or commercial influences. In the current COVID-19 pandemic, the United Nations has advocated that facts and science should be promoted and that these constitute the antidote to the current infodemic. This is in stark contrast to the realities of infodemic mismanagement and misguided upstream filtering, where social media platforms such as Twitter have advertising policies that sideline science organizations and science publishers, treating peer-reviewed science as "inappropriate content."