Available via license: CC BY
Content may be subject to copyright.
hp://www.td-sa.net Open Access
The Journal for Transdisciplinary Research in Southern Africa
ISSN: (Online) 2415-2005, (Print) 1817-4434
Page 1 of 13 Review Arcle
Read online:
Scan this QR
code with your
smart phone or
mobile device
to read online.
Authors:
Travis M. Noakes1
David Bell2
Timothy D. Noakes3
Aliaons:
1Department of Applied
Design, Faculty of Informacs
and Design, Cape Peninsula
University of Technology,
Cape Town, South Africa
2Independent consultant,
Lake Jackson, Taxes, United
States
3Department of Wellness
Sciences, Faculty of Health
and Wellness Sciences, Cape
Peninsula University of
Technology, Cape Town,
South Africa
Corresponding author:
Travis Noakes,
travis@thenoakesfoundaon.
org
Dates:
Received: 01 July 2022
Accepted: 17 Aug. 2022
Published: 21 Dec. 2022
How to cite this arcle:
Noakes TS, Bell D, Noakes,
TD. Who is watching the
World Health Organisaon?
‘Post-truth’ moments beyond
infodemic research.
J transdiscipl res S Afr.
2022;18(1), a1263.
hps://doi.org/10.4102/
td.v18i1.1263
Copyright:
© 2022. The Authors.
Licensee: AOSIS. This work
is licensed under the
Creave Commons
Aribuon License.
Introducon
What counts as rumours, disinformation, misinformation and malinformation in health
communications has emerged as an important global concern, especially during acute public
health crises. Already in February 2020, even before the coronavirus disease 2019 (COVID-19)
pandemic had taken hold, the World Health Organization (WHO) Director-General Tedros
Adhanom Ghebreyesus raised concerns that the COVID-19 outbreak was already accompanied
by an infodemic.1 He warned that an overflow of information of varying quality might surge
during any public health event that begins suddenly and unexpectedly. He argued that this could
pose a new health risk by interfering with the public’s ability to find high-quality health
information with which they could better protect themselves, their families and their communities
from harm. Experiences with health misinformation during the Ebola, human immunodeficiency
virus (HIV), polio and Zika epidemics have been claimed to reveal costs to public health and to
health systems when rumours and misinformation are amplified.2 It is also necessary to flag that
poor public health communication responses can further aggravate such negative outcomes, as
can the misuse of public health. An example of the latter being the hepatitis B vaccine program’s
use for identifying the children of Osama Bin Laden’s household.3
To improve public understanding by anticipating, identifying and responding to such
communication risks, the WHO recently established a public research agenda for managing
infodemics.4 An infodemic is defined as an:
[O]verflow of information of varying quality that surges across digital and physical environments during
an acute public health event. It leads to confusion, risk-taking, and behaviors that can harm health and
lead to erosion of trust in health authorities and public health responses. Owing to the global scale and
The World Health Organization (WHO) has established a public research agenda to address
infodemics. In these, ‘an overflow of information of varying quality surges across digital and
physical environments’. The WHO’s expert panel has raised concerns that this can result in
negative health behaviours and erosion of trust in health authorities and public health
responses. In sponsoring this agenda, the WHO positioned itself as a custodian that can flag
illegitimate narratives (misinformation), the spread of which can potentially result in societal
harm. Such ‘post-truth’ moments are rife with the coronavirus disease 2019 (COVID-19) public
health emergency. It provides an opportunity for researchers to analyse divisions in knowledge
labour, which can help explain when ‘post-truth’ moments arrive. The first COVID-19 example
for this division foregrounds the development of knowledge in an academic context. Added to
this is the infodemic or disinfodemic research agenda and personal health responsibility,
whose academic contributors are similar. In contrast, the division of labour for messenger
ribonucleic acid (mRNA) vaccine research foregrounds the role of vaccine manufacturing
pharmaceutical companies in driving and promoting related knowledge production.
Transdiciplinary Contribution: This analysis focuses on intergroup contradictions between
the interests of agencies and their contrasting goals and across different types of knowledge
division. Many intergroup contradictions exist, and a few intergroup examples are also
described. An overarching contradiction was identified where rushed guidance based on
weak evidence from international health organisations may well perpetuate negative health
and other societal outcomes rather than ameliorate them.
Keywords: COVID-19; divisions in knowledge labour; intergroup contradictions; international
health organisation; mRNA vaccines; pandemic.
Who is watching the World Health Organisaon?
‘Post-truth’ moments beyond
infodemic research
Read online:
Scan this QR
code with your
smart phone or
mobile device
to read online.
Page 2 of 13 Review Arcle
hp://www.td-sa.net Open Access
high stakes of the health emergency, responding to the infodemic
related to the pandemic is particularly urgent. Building on
diverse research disciplines and expanding the discipline of
infodemiology, more evidence-based interventions are needed to
design infodemic management interventions and tools and
implement them by health emergency responders.4 (p. 2)
This agenda posits that addressing infodemics on digital
platforms is of central importance to any pandemic response.
To coordinate research on these risks in an emergent
discipline, from June to October 2020, the WHO convened
online consultations with more than 100 experts from 20
disciplines across more than 30 countries. It developed,
shortlisted and prioritised research questions for the
infodemic public research agenda as a novel discipline. Five
focus areas or ‘streams’ were identified for immediate action.
These streams span: (1) the evaluation of infodemic impacts,
(2) how to study them, (3) what drives them, (4) identifying
approaches to better manage them and (5) considerations for
developing new tools for infodemic management.4 This
agenda is intended to serve as a reference point for the WHO,
partners, research agencies and academia to build a global
capacity that can better manage contemporary and future
global health threats.
Analysing divisions of knowledge
labour in researching COVID-19
‘post-truths’
The ‘COVID-19 pandemic’ is a shared discourse, a way in
which people talk about a global health topic as part of a
shared concern. Their conversation can draw on varied
discourses, semiotic ways of construing aspects of the world
(physical, social or mental) that can generally be identified
with different positions or perspectives of various groups of
social actors.5 Specific discourses (such as statistical models
for pandemics) are often developed by professional experts.
They work in a complex division of knowledge labour to
produce different forms of ‘educational knowledge’. Bernstein
defined such knowledge as ‘uncommonsense’ knowledge:
[I]t is knowledge freed from the particular, the local, through the
various languages of the sciences or forms of reflexiveness of the
arts which make possible either the creation or the discovery of
new realities’.6 (p. 770)
Bernstein pointed to the ‘pedagogic device’ as the social
mechanism underpinning knowledge production.7 This
device comprises three levels for analysis, either ‘distributive’,
‘recontextualising’ or ‘evaluative’: a set of distributive rules
orders the regulation and distribution of a society’s
worthwhile knowledge store. This knowledge store is
transformed into pedagogic discourse for educational
transmission through recontextualising rules. Such pedagogic
discourse becomes ordered by evaluative rules into a set of
criterial standards to be attained.
Kwok et al.’s Table 18 shows how the divisions of knowledge
labour for COVID-19 are delineated. Emile Durkheim’s theory
for Division of labour proposes that this division encompasses
the separation and specialisation of work among varied
personnel with different expertise.9 Separation entails that
various tasks in a work process become separated into
various component and cofunctioning processes, which
agents do. Bernstein described how knowledge work is done
by a network of individual human agents and socialising
agencies. Such agencies may comprise families, peers, groups,
schools or colleagues at work.7
Each transformation of knowledge takes place in a particular
field (see Table 1), within which different expert agents work.
This field of knowledge production may be marked by a
hierarchical knowledge structure, such as in the health sciences,
whose very general propositions and theories integrate
knowledge at lower levels. Alternately, the structure may be
horizontal, such as in the humanities. It contains a series of
specialised languages and expert modes of interrogation, plus
criteria for the design and sharing of texts.10
The three rules and their associated fields comprise a
pedagogic device that is an arena of conflict and struggle.
Social groups attempt to dominate the development of
educational knowledge. Rival groups attempt to appropriate
the device to impose their own rules via constructing
particular code modalities. Code refers to a ‘set of organizing
principles behind the language employed by members of a
social group’.11 Code modality is a principle of hierarchisation.
Hence, the device or apparatus becomes the focus of
challenge, resistance and conflict.7
Kwok et al. describe how the global health crisis of COVID-19
presents a fertile ground for exploring the complex division
of knowledge labour in a ‘post-truth’ era.8 Much has been
written about ‘post-truth’, producing multiple definitions.
Generally, ‘post-truth’ is considered an information disorder
in which rumour and disinformation blight digital platforms
and other communication channels. Fake news and
alternative facts are spread as misinformation, which can
result in negative outcomes linked to malinformation. Post-
truth’s advent is also marked by multiple forms of expertise
and fact-checking, dog-whistle politics appealing to emotion,
denial of science and consequently the return of fascism.12,13,14
In contrast to this broad conceptualisation of post-truth,
knowledge production is a narrow concept useful for
exploring the social conditions of knowledge. Researchers
TABLE 1: Division of knowledge labour in COVID-19.
Rules Discourse acvity by eld Agents in the pandemic
Distribuve rules Producon of discourse
in Higher Educaon
Epidemiologists, immunologists,
microbiologists, pathologists,
virologists
Recontextualising
rules
Recontextualisaon
of discourse on Media
Plaorms
News media, health ocials in
the government, policians,
‘fake’ news spreaders, anyone on
social media plaorms
Evaluave rules Reproducon of discourse
in Government
The most senior government
ocials who evaluate the
scienc discourse and transform
the assessment into policies and
pracces
Source: Adapted from Kwok H, Singh P, Heimans S. The regime of ‘post-truth’: COVID-19 and
the polics of knowledge. Disc Stud the Cult Polit Edu. 2021;1–15. hps://doi.org/10.1080/
01596306.2021.1965544, (p. 6).8
COVID-19, coronavirus disease 2019.
Page 3 of 13 Review Arcle
hp://www.td-sa.net Open Access
can analyse divisions in knowledge labour for explaining
where ‘post-truth’ moments arrive.
Division of knowledge labour in
COVID-19: An example
Kwok et al.’s Table 1 was designed to support an analysis of
the division of knowledge labour in relation to COVID-19. It
features the higher education (HE), media and government
fields. According to this framing, the distributive rules for
COVID-19 discourse development are driven by university
experts. Distributive rules govern the fields where the
production of new knowledge takes place. For example, an
epidemiological scholar at a university is an agent who
produces a statistical model that predicts COVID-19’s
potential mortality and morbidity.
Recontextualisation can be seen as the appropriation of
external discourses, where discourses are incorporated into
strategies pursued by groups of social agents within the
recontextualising field.15 Recontextualising rules regulate the
translation of knowledge and comprise the prevalent
discourse to which lay people are exposed. A news journalist
would recontextualise the epidemiologist’s calculations
in a lead article edited for that newspaper’s audience.
Kwok et al.8 argue that the era of post-truth is marked by
the intense and visible pressures that arise from such
pedagogisation of medical knowledge. Pedagogisation16
refers to the process by which specialist knowledge that is
inaccessible to the public becomes translated into novel
forms that nonspecialist audiences can access and
understand more readily. There are many digital platforms
that support such forms of recontextualisation, which can
range from movie-length videos to pithy tweets. In response
to this information, Internet audiences can add their own
comments.
Key opinion leaders from outside the medical field can
readily access social media to recontextualise the health
narrative. New recontextualisation organisations are formed
in response to nonexperts’ attempts to wield power over
medical discourse. These range from collaborations between
public media organisations and research institutions to
‘fact-checkers’ reliant on algorithms and fast data for
cross-checking relevant information.
The vast increase in communication through recontextualised
sources has led to the mystery and incoherence of medical
knowledge becoming more obvious and more visible in the
post-truth era.8 This increases the challenge to universities and
commercial medical enterprises wanting to retain public trust
in the scientific and medical knowledge that they have
developed and the resulting public interventions.
What counts as ‘valid’ knowledge and practice in the
division of knowledge labour is determined by evaluative
rules – according to Bernstein.7 Whoever can evaluate such
validity is the most influential and powerful person or group
in that division. As the COVID-19 pandemic was predicted
to cause an unprecedented number of deaths across the
globe, the initial step of government health officials was to
consult with selected epidemiologists who had produced
predictive models of how many deaths would happen in the
pandemic. Only senior political officials had the power to
transform the predictions of those epidemiologists into
policy actions that impacted entire populations around the
globe. Consequently, political leaders in the upper echelons
of government hold the greatest evaluative power according
to this analysis of how the division of knowledge labour
impacts knowledge transfer to the public.
This analysis clarifies that researchers need to explore the
relations between and within each division’s fields.
This analysis can reveal areas of contradiction and conflict. For
example, political leaders may be driven by very different
concerns in the political field than epidemiologists
working in academia. Scholars across a variety of
disciplines may disagree on the efficacy of measures taken
by governments to protect citizens’ safety. As national
statistics for confirmed infections and COVID-19 deaths
are released, epidemiologists will critique each other’s
statistical models, focusing particularly on the assumptions
inherent in their different models and their resulting
predictions.
Aim
Exposing contradicons within and between key
COVID-19 divisions of knowledge labour
Kwok et al.’s division of knowledge labour in COVID-19
foregrounds the university as the pre-eminent producer of
COVID-19 knowledge.8 By contrast, this article proposes
that relationships with other influential knowledge
development fields must be considered, for example,
pharmaceutical companies that manufacture experimental
therapies and direct research to determine whether these
products are ‘safe and effective’. Such areas of knowledge
development are vitally important to analyse regarding
their potential contributions to the COVID-19 discourse. It
is also important to consider how stakeholders may have
similar aims that purport to serve public health, but in
reality they prioritise agendas of expanding markets or
securing new sponsorship. Powerful agents can collaborate
across divisions of knowledge labour for establishing an
institutional oligarchy. Its hegemonic collaboration can
supress alternative viewpoints that contest and query
powerful agents’ interests.
This reflects our disagreement with the view that distributive
rules in HE can escape the external influence of powerful
agents, such as industry and government. In contrast, we
believe that it is necessary to study the silent type of
collaboration that can exist between powerful agents who
pursue their own, and collective, ambitions at the expense of
public health and academic knowledge.
Page 4 of 13 Review Arcle
hp://www.td-sa.net Open Access
As we discuss subsequently, this is glaringly evident in the
narrow options that the public are presented for managing
COVID-19.
Elaborating the earlier example for epidemiologists can
illustrate the influence of key agents outside the university:
Statistical modelers are paid by specific interests, and
modelers are aware of the preferences of funders’ interests.
Experts whose knowledge claims achieve the highest
visibility may be consulted because they are at specific
institutions that benefit from funding streams whose sources
are highly instrumental in politics. Media have their own
criteria for selecting ‘valid’ sources; models that predicted
minimal change would seem ill-suited for scary headlines
and selling newspapers. Well-established modelers with
better predictions have consequently been ignored. As a
result, the pandemic models discussed at universities
can strongly reflect the influence of other fields – entities
in fields are not isolated while setting distributive,
recontextualising and evaluative rules. In public health, this
reflects the reality of clear funding streams operating to
push vested interests that can be beneficial but may also be
harmful. Companies can exert a significant influence on
what is acceptable for universities to research via funding
grants provided by these firms. Exploring contradictions
between fields, such as commercial and academic ones, is
useful to highlight major concerns with how the evidence
about COVID-19 is presented to the public. In particular,
the ‘post-truth’ moments that scholars researching the
infodemic may be unaware of should be spotlighted for
investigation.
Method
In this opinion piece, we elaborate on where ‘post-truth’
moments may arrive in three types of division of knowledge
labour: the first is the infodemic research agenda (see Table 2),
the second is research into mRNA vaccines (see Table 3)
and the third concerns research into individual health
responsibility to protect against fatal COVID-19 outcomes
(see Table 4) and the risk of onward viral transmission. For
this public health crisis, we are concerned with the
relationships between health communication, public health
policy and recommended medical interventions. The second
and third types of knowledge division were chosen as the
guidance vetted by the WHO will and has had major social
consequences for people’s health, especially the poor and
working class in Southern Africa.8
Following Gerrard17 and Malcolm’s14 call, we focus on
the underlying principles that govern knowledge, its
transformation and transmission via fields and organisations.
Special attention is given to the intergroup contradictions
that are present between agencies. Such ‘contradictions’ exist
within and between the categories. Contradictions occur
between agents and agencies with different interests, which
are directed by and reflected in their divergent goals. An
analysis of these contradictions is helpful for broadening our
understanding of where ‘post-truth’ moments lie and what
disinformation the WHO’s infodemic research agenda might
miss or neglect.
Division of knowledge labour in the
infodemic research agenda
The distributive and recontextualising rules in the division of
knowledge labour for the infodemic research agenda (see
Table 2) are close to that of COVID-19 (Table 1). However,
the infodemic research agenda contains different evaluators,
specifically international health organisations responsible for
global health. One such organisation is the WHO, a United
Nations agency whose goal is to connect ‘nations, partners
and people to promote health, keep the world safe and serve
the vulnerable – so everyone, everywhere can attain the
highest level of health’ (WHO, 2022).
As a global health organisation, the WHO leads the
infodemic research agenda. In this role, WHO positions
itself as a custodian of evaluative rules for the infodemic.
As a custodian, it flags narratives that it considers illegitimate
TABLE 2: Division of knowledge labour in the infodemic research agenda.
Rules Discourse acvity by eld Agents in the COVID-19
infodemic
Distribuve rules Producon of infodemic
research discourse in
Higher Educaon
Researchers in computer
science and informacs,
health science, informacs,
media and communicaons,
polics, psychology, and
other salient disciplines
Recontextualising rules Recontextualisaon of
infodemic research
discourse on Media
Plaorms
Journal editors and
publishers, journalists,
public relaons experts on
digital plaorms, dissident
scholars
Evaluave rules Evaluaon of which
discourses constute
rumour, disinformaon,
misinformaon and
malinformaon by
Internaonal Health
Organisaons
Leaders in the: WHO,
Centres for Disease Control,
United Naons Educaonal
Scienc and Cultural
Organizaon, Organisaon
for Economic Cooperaon
and Development
WHO, World Health Organisaon.
TABLE 3: Division of knowledge labour on mRNA vaccines.
Rules Discourse acvity by eld Agents in the pandemic
Distribuve rules Producon of
‘vaccinaon’ discourse by
Vaccine Manufacturing
Pharmaceucal Companies
Pharmaceucal company
leadership, Company
researchers
Recontextualising rules Recontextualisaon of
discourse on Media
Plaorms
Public relaons and news
media experts, health
ocials in the government,
policians, vaccinaon
scholars, ‘an-vaxxers’ on
digital plaorms
Evaluave rules Evaluaon of the
vaccinaon discourse
by the Centre for Disease
Control
The most senior government
health ocials who evaluate
the mRNA vaccines research
and approve their rollout for
inoculaons
mRNA, messenger RNA, ribonucleic acid.
TABLE 4: Survival rates for dierent ages infected with COVID-19.
Age of paent (years) Probability of survival (%)
0–19 99.997
20–49 99.98
50–69 99.5
70+ 94.6
COVID-19, coronavirus disease 2019.
Page 5 of 13 Review Arcle
hp://www.td-sa.net Open Access
(misinformation), whose spread as disinformation can
potentially result in societal harm, as malinformation. This
approach on the COVID-19 ‘misinfodemic’ is shared by
another two evaluators, both popular health organisations:18
the United Nations Educational Scientific and Cultural
Organisation has developed two policy guides for tackling
the COVID-19 ‘disinfodemic’ (2020, 2022). The Organisation
for Economic Cooperation and Development (OECD) has
also provided guidance regarding OECD policy responses
to ‘COVID-19 misinformation’ (2020).
The evaluative rules in the infodemic research agenda follow
international health organisations’ guidance regarding what
constitutes false and misleading discourses. Researchers are
urged to study such discourse as dangerous threats that
undermine these health authorities’ guidance to the public.
The grand narrative that the WHO infodemic research
agenda claims is that it exists solely for the public health
benefit in building knowledge and taking actions that might
prevent excess deaths and other harms in viral pandemics.
The WHO positions itself and its partners (such as Centres
for Disease Control and Prevention and public health
agencies) as scientific authorities that arbitrate what
constitutes medical truth or, alternatively, disinformation.
Accordingly, the WHO adopts the status of the ultimate truth
provider, an organisation whose verdicts can be accepted
without question.
This has the potential to create an intragroup contradiction
when infodemic scholars at universities research the WHO’s
decisions but learn that these and related guidance have
shifted dramatically, sometimes with no clear justification.
For example, Table 5 lists the key guidelines provided by the
WHO for ‘mitigating the risk and impact of epidemic and
pandemic influenza’. However, a cursory glance shows that
the public health measures applied in 2019 would be radically
altered just months later. This was from the very beginning of
the COVID-19 pandemic, so clearly before new research
could have established that these previously accepted, wide-
ranging guidelines would be ineffective against the spread of
COVID-19.
Scholars who are dependent on research funding from the
WHO or those whose funding sustains the WHO (including
the Bill and Melinda Gates Foundation) might choose not to
criticise such sudden and unexplained shifts in guidance. A
linked concern is that it is unclear who the original funders of
the infodemic research agenda were. There does not seem to be
a line item for it in the WHO’s programme budget for the 2020–
2021 period. Scholars in the recontextualisation field whose
dissent flags the weak, or nonexistent, evidence base for such
shifts in the WHO’s guidance will also find themselves in
contradiction with both the distributive and evaluative fields.
The WHO may also face contradictions if its role as a
custodian and evaluator of measures against COVID-19
conflicts with those of its existing funders. The WHO has
increased its dependence on external funders, including
pharmaceutical companies and investors, particularly the
Bill and Melinda Gates Foundation. Organisations such as
the Global Alliance for Vaccines and Immunization (GAVI),
the Vaccine Alliance and the Coalition for Epidemic
Preparedness Innovations (CEPI, focused on epidemics)
have arisen alongside the WHO and have private investors
and corporate entities represented directly on their boards.
These entities channel further funding into the WHO. Most
privately sourced WHO funding is ‘directed’, meaning it is
for specified programs and outcomes, for which the WHO
staff funded by this source must therefore work. Such an
undue influence on the evaluation of COVID-19 discourse
may explain the WHO’s changed guidance on mRNA
vaccines. The pandemic provided an opportunity for the
expedited approval of mRNA vaccines as ‘trusted vaccines’
despite incomplete phase III trials of unusually small size.19,20
This also required the definition of a ‘vaccine’21 to be altered
so that the mRNA products could be classified as ‘vaccines’
in contrast to the traditional definition accepted for decades,
if not centuries.
TABLE 5: World Health Organizaon recommendaons for non-pharmaceucal public health measures versus epidemic and pandemic inuenza.
Number Recommendaon in ‘Non-pharmaceucal Public Health Measures for Migang the Risk and Impact of Epidemic and Pandemic Inuenza
World Health Organisaon’ (2019)
Page
1 ‘Acve contact tracing is not recommended in general, because there is no obvious raonale for it in most Member States’. 38
2‘Home quaranne of exposed individuals to reduce transmission is not recommended because there is no obvious raonale for this measure,
and there would be considerable dicules in implemenng it’.
47
3.1 ‘The eect of reacve school closure in reducing inuenza transmission varied but was generally limited’. 50
3.2 ‘In such cases, the adverse eects on the community should be fully considered (e.g. family burden and economic consideraons), and the
ming and duraon should be limited to a period that is judged to be opmal.’
52
4 ‘ The strength of evidence on workplace closure is very low because the idened studies are all simulaon studies’. 54
5 ‘ The eect of measures to avoid crowding alone in reducing transmission is uncertain’. ‘Timely and sustained applicaon of measures to avoid
crowding may reduce inuenza transmission, although the quality of evidence of its eecveness is very low.’
57
6 ‘No scienc evidence was idened for the eecveness of travel advice against pandemic inuenza; however, providing informaon to
travellers is simple, feasible and acceptable’.
61
7.1 ‘Entry and exit screening for infecon in travellers is not recommended, because of the lack of sensivity of these measures in idenfying
infected but asymptomac (i.e. pre-symptomac) travellers’.
63
7.2 Entry and exit screening are ‘Not recommended due to the overall ineecveness in reducing the introducon of infecon and delaying local
transmission’. ‘Involuntary screening may have ethical or legal implicaons’.
64
8 ‘Overall, border closure is not recommended unless required by naonal law or in extraordinary circumstances during a severe pandemic, and
countries should nofy WHO as required by IHR. This is due to the very low quality of evidence, economic consequences, resource implicaons
and ethical implicaons.’
69
Note: Table based on the original design by Abir Ballan, shared via her personal Telegram account in May 2021. hps://t.me/abirballan1/377
WHO, World Health Organizaon; IHR, Internaonal Health Regulaons.
Page 6 of 13 Review Arcle
hp://www.td-sa.net Open Access
The division of knowledge labour
for messenger RNA vaccine
development
Conventional division of knowledge labour diagrams (see
Table 1 and Table 5) places the HE or tertiary academic field
as the leader of discourse production. By contrast, the
division for mRNA vaccine research (see Table 3) highlights
how companies manufacturing vaccines drive contemporary
research and the distributive rules in knowledge labour.
Academic institutions are not the most important contributor
to mRNA vaccine innovation, as only wealthy pharmaceutical
companies have the financial and other resources to drive
this research, especially at the ‘lightning speed’ that became
their stated, indeed over-arching, goal. This required that
within just a few months, a complex combination of resources
be deployed across a myriad of clinical trial sites spread
across the globe.
An example of this is Pfizer’s clinical trials of its BioNTech
Comirnaty mRNA vaccines; within just 4 months, it scaled
this trial to include 46 000 participants at 150 sites in six
countries.22 Pfizer’s clinical development team used
predictive models for COVID-19 incidence at the local level
to select potential sites and optimise their site selection.
Artificial intelligence and machine learning were used by
Pfizer’s scientists to ‘perform quality checks and analyse vast
amounts of trial data in near real time. Participants’ data
could be refreshed every 4 h’. The use of supercomputing
reduces ‘the computation time for complex calculations and
scientific simulations by 80% – 90%’, resulting in a reduction
in labour-intensive research outcomes from years to months
and weeks.
The production of vaccination discourse by manufacturers
features very different contradictions between and within
agencies than does the production of COVID-19 or infodemic
knowledge. In the first place, the role that pharmaceutical
companies have in producing vaccination discourse is
massively conflicted. Conflict of interest arises in pursuing
such costly research on novel mRNA vaccines, because
whether the company producing these therapies will
ultimately benefit financially from the future sales of these
therapies depends entirely on the published efficacy and
safety results from their own research.
Well-documented failures in the Pfizer trial of their COVID-19
vaccine highlight the dangers of these contradictions. The
original trial was scheduled to last for two years; however,
after three months, the study’s patients were ‘unblinded’.23
The control group had been offered the mRNA vaccines,
which effectively prevented a long-term study of the
treatment’s safety.24 Other major flaws in the study included
falsified data, the employment of inadequately trained
vaccinators and slow follow-up on adverse events reported
in Pfizer’s pivotal phase III trial.25 Staff who conducted
quality control checks were overwhelmed by the volume of
problems they were finding. That study also found that all-
cause mortality was higher in the ‘vaccinated’ than in the
control group26 (Table S4, p. 78) which should have been
recognised as a safety signal. Pfizer only acknowledged one
excess death (16 vs. 15) in the vaccinated group in its six
month safety report. It was:
[S]o damning that it should have closed the case against this
vaccine but captured FDA officials nevertheless gave Pfizer their
approval; the broken VAERS system and the mainstream and
social media all conspired to conceal the evidence of the crime
when vaccinated Americans began dying in droves, and CDC
implemented its own retinue of enshrouding machinations to
cloak real-life carnage.26 (p. 79)
Pfizer responded by attempting to have all the relevant
information from the trial sealed from public scrutiny for
75 years, contrary to the stated priority of providing facts
to counter ‘misinformation’. Following a Freedom of
Information Act request, this decision was rescinded by a
Federal Court in the northern district of Texas that ordered
that the relevant data be released at a rate of 55 000 pages per
month. This lack of transparency has been strongly criticised
in the British Medical Journal (BMJ):27 ‘Pfizer’s pivotal covid
[sic] vaccine trial was funded by the company and designed,
run, analysed and authored by Pfizer employees’. The
company and contract research organisations that carried out
the trial hold all the data. Unfortunately, there is ‘inadequate
availability of COVID-19 vaccine trial documents and data;
individual participant data will not be available for months,
perhaps years, for most vaccines’.28 The widespread ‘use of
interventions without full data transparency’ raises ‘concerns
over the rational use of COVID-19 vaccines’.
Indeed, original concerns about the proprietary of the Pfizer
COVID-19 trial were raised by an employee of a large clinical
research company contracted to conduct that trial.25
Predictably, the whistle-blower, Brook Jackson, immediately
lost employment. Agents inside vaccine manufacturers
confront an intragroup contradiction if their research
produces negative findings for their employer’s products. A
recent evaluation of serious adverse events of special interest
observed in phase III randomised trials of Pfizer and
Moderna’s mRNA COVID-19 vaccines has recommended
the need for formal harm–benefit analyses, particularly those
that are stratified according to risk of serious COVID-19
outcomes such as hospitalisation or death.29 This was based
on the finding that the excess risk of serious adverse events of
special interest surpassed the risk reduction for COVID-19
hospitalisation relative to the placebo group in both trials.
A major intergroup contradiction exists in evaluators, such as
the CDC and European Medicines agency, receiving large
proportions of their budget from the industry they are
supposed to regulate.30 Another potential conflict of interest
exists in these evaluators being entirely dependent on vaccine-
producing companies for the accurate (and honest) reporting
of results from their vaccine trials. The Pfizer experimental
product was initially promoted to stop the spread of
COVID-19, thereby allowing a ‘return to normality’ according
to Pfizer’s CEO, Albert Bourla.31 However, unlike previously
Page 7 of 13 Review Arcle
hp://www.td-sa.net Open Access
well-tested vaccines, the mRNA vaccines proved ineffective
at halting transmission of the supposed infectious agent.32
Moreover, the waning effectiveness of even third doses of
‘vaccinations’ soon became apparent.33,34,35 As a result, natural
infection provides superior long-term protection.36
Vaccine-manufacturing pharmaceutical companies need to
protect their intellectual property – vaccine ingredients are
proprietary. This may present a challenge to regulators’ third-
party evaluations of these firms’ research. It also presents a
contradiction in the recontextualisation field where sceptics
can claim that mRNA vaccines contain harmful substances.
In stark contrast to the challenges in the recontextualisation
field that an absence of information creates, releasing too
much information also creates its own challenges. For
example, Pfizer shared 80 000 pages of information on its
research trial in a ‘Pfizer dump’. Critics had a huge amount
of information that they could recontextualise, such as in
viral tweets that falsely claimed the dump to reveal vaccine
efficacy as only 12%, not the 95% that Pfizer claimed.37 Critics
of the WHO’s COVID-19 response have flagged how its
funders’ economic and ideological interests have shaped
research funding into preventive or alternative treatments.
The director of the National Institute of Allergy and Infectious
Diseases, Dr Anthony Fauci and NIH receive substantial
amounts from their patents, while the CDC sells vaccines.26
A lack of correspondence between the claims from
experimental clinical trials and those in the real world led to
the public’s first-hand experience of this failure. It would
have been expected that international health authorities
would have modified their guidelines, especially as they
relate to mandatory vaccine policies. However, this was not
the case. Instead, the WHO remained silent, as they have
been failing to address issues of vaccine safety.38 For example,
the response to the finding that more deaths have occurred in
the first year of the vaccine rollout than all the other vaccines
over the past 30 years met with the excuse that ‘we had to
overlook the safety measures because this was a deadly
pandemic’.39
Another contradiction exists between the deliberation and
recontextualisation fields, where vaccine-manufacturing
pharmaceutical companies can use their large online
advertising budgets to influence content on digital platforms
and fact-checking. With the contemporary Internet facilitating
control by large technology companies, a related concern is
tied to their financial investments in vaccine manufacturers.
Large advertising payments and investments may result in
hidden algorithmic influence on Big Tech platforms, where
algorithmic amplification shapes the margins of ‘acceptable
opinion’: mRNA vaccines may be foregrounded in top search
results that only feature positive stories. In contrast,
algorithmic censorship can be applied to negative news on
mRNA technologies, and unfavourable reports are fact-
checked. An example is the ‘fact-checking’ messaging from
Facebook which flagged the sharing of a legitimate BMJ
investigation. It described a Pfizer contractor who may have
falsified data and skewed findings in its original jab studies.25
This article’s Facebook shares were accompanied by a
‘missing context’ warning claiming the article might ‘mislead
people’. This was linked to Lead Stories, Facebook’s fact-
checker’s website.
It is also pertinent to note that the division of knowledge
labour for mRNA vaccine development should not be
considered separately from that for COVID-19 or the infodemic
research agenda. Strong contradictions may emerge from
the relationships between multinational pharmaceutical
companies and agencies in the two distributive and evaluation
fields. Multinational pharmaceutical companies are referred
to as ‘Big Pharma’ because of their large size and large profits
resulting in their acquisition of significant political influence.40
Less well known is how these same companies direct the
research agenda in academia and medical research discourse
through the lucrative grants that they distribute liberally. For
example, each dean of a prestigious university’s medical
faculty must attract funders to help cover the high running
costs compounded by budgetary shortfalls resulting from
shrinking government subsidies. Cost recovery is achieved by
placing research levies on all grants to faculty researchers.
Such levies can range from 20% at a typical South African
university to 70% at leading medical research universities in
the United States. This money helps sustain the faculty’s
staffing and infrastructure. Large grants from wealthy
institutions are highly valued because they generate large
research levies. In South Africa, the three most prized funders
are the National Institute of Health, the Bill and Melinda Gates
Foundation and the Wellcome Trust. The latter two provide
much of the funding for local vaccine-related research and
their investment is large, running to hundreds of millions of
South African rands, even for individual trials run by single
South African universities.41
Another important contradiction exists between the
decolonial agenda of African governments versus the high
costs of purchasing mRNA vaccines manufactured overseas.
Localisation of vaccine manufacturing capacity by lower- and
middle-income countries necessitates that most of the
equipment, personnel and consumables be imported for
years, further limiting benefits to the local economy.13
Notwithstanding the huge advertising budgets of Big Pharma
companies, there may be a rejection of mRNA vaccine
technologies within local markets. For example, Africa’s first
COVID-19 vaccine plant led by Aspen pharmacare risked
closure because of not receiving orders for Aspenovax.42
In exploring COVID-19 post-truths, researchers should
consider the discourses related to grant making and
sponsorship rules (see Table 6). While not constituting a
pedagogical device, both are important in shaping the
direction of the research that will either be encouraged or
discouraged. Research organisations dependent on external
funding to cover their annual budget shortfalls will be more
susceptible to the influence of those funders on their research
Page 8 of 13 Review Arcle
hp://www.td-sa.net Open Access
programs. External funders have their own criteria for
evaluating what constitutes an attractive research project,
and the primary consideration will be to generate future
revenues for their company as required by United States (US)
law – the concern of ‘shareholder primacy’ established by the
1919 Dodge vs. Ford Motor Co. case.
As a result, in the projects they support, there will always be
the inevitable tension between the funder’s desire for an
industry-favourable outcome on which future product sales
are wholly reliant versus the potentially devastating effects
of the finding that their product is either ineffective or
harmful. Or even worse, that it is both harmful and ineffective.
This raises questions about Pfizer’s apparent disinterest in
full transparency.25,27,28
There is also a contradiction in funding research that might
support the development or marketing of rival products or
lead to an existing product to fail. The most egregious
examples of this have been the suppression of out-of-hospital
treatments shown to be potentially effective if used early in
COVID-19 infections, especially ivermectin.43 In part, this
reluctance to pursue alternative, out-of-hospital treatments is
explained by the need for vaccine manufacturers to have an
Experimental Use Application (EUA) applied to their
vaccines. An EUA cannot be granted if alternative, effective
treatments are already available.
South Africa provides an excellent example of the
complexity of these conflicts of interest. All internationally
competitive medical faculties in South Africa receive very
substantial funds from the three linked international
organisations already mentioned that support vaccine
research – the Bill and Melinda Gates Foundation, the
National Institute for Health and the Wellcome Trust.
Indeed, one might argue that there is a direct relationship
– perhaps not causal – between the international standing
of the different South African medical faculties and the
magnitude of the funding each receives for research into
vaccines, mRNA vaccines and their development. A
natural consequence is that three of the most influential
members of the South African President’s Coronavirus
Command Council are heavily funded by these
organisations. The Bill and Melinda Gates funding for
vaccine research in Africa is granted to just two South
African medical faculties, who have reportedly received
upwards of $154 million over the years.
In addition to influencing university research, large
pharmaceutical companies also have the budgets to influence
academic publishers and health councils, as discussed by
Blaylock.39 In South Africa, concerns have been raised about
the independence of the South African Health Products
Regulatory Authority (SAHPRA), which receives or has
received funding from the Bill and Melinda Gates Foundation.
Recently, SAHPRA terminated the ‘Compassionate Use
Access Programme’ for ivermectin in South Africa.
Another potential site of contradiction exists where flawed
interventions and policies may be coerced through global
health organisations and via local government by more
powerful international organisations. The WHO’s policy
may reflect the interests of more powerful organisations,
such as the World Economic Forum, and the influence of
donors, such as the Bill and Melinda Gates Foundation.44
World Health Organizaon ignores
personal health behaviours that can
reduce the risks of fatal COVID-19
outcomes
The WHO document states that:
[A]n infodemic can lead to confusion, misunderstanding of health
information, risk-taking and behaviours that can harm health
under the public health response, and lead to mistrust in health
authorities. Therefore, people need timely, accurate, and accessible
information in the right format and amount during epidemics to
adopt health-promoting behaviours to protect themselves, their
families, and their communities against the infection.4 (n.p.)
Clearly the focus of this document is ostensibly to protect the
‘people’ – presumably the public – from harm by providing
correct information that will assist them to adopt health-
promoting behaviours, the goal of which is to protect
everyone from infection. Having stated that this is their goal,
it is reasonable to expect that the WHO can establish clarity
for the most appropriate actions for achieving these goals.
This raised the question whether the WHO provided
information that would assist individuals to alter their
personal health behaviours – as opposed to the measures of
hard lockdowns and border closures enforced on all.
As described previously,45 very early in the ‘pandemic’ it was
found that not everyone is at equal risk for a fatal COVID-19
infection. This information should have been crucial in
developing an appropriate global response to the ‘pandemic’
and in advising individuals of their probability of developing
the disease. With this information, those at greatest risk could
have prepared themselves more effectively. Such COVID-19
discourse seems largely been ignored in HE. It was never
stated that the gradient of risk for a fatal COVID-19 outcome
differs by more than 400-fold between the young, who are
essentially at zero risk, and the elderly, especially those who
live in nursing homes and in whom close to 40% of all
COVID-19 deaths were reported, for example, in England
and Wales. By contrast, the CDC suggested that this is over
8000-fold. An early study found that people above age 65
account for 91% – 95% of all COVID-19 deaths in eight
TABLE 6: Grant-making and sponsorship discourse acvity and agents.
Rules Discourse acvity by eld Agents in the pandemic
Grant-making rules Producon of discourse for
evaluang research raonales
by Corporate Funders
Pharmaceucal company,
research foundaons and
other grant makers,
Sponsorship rules Producon of discourse for
potenal COVID-19 research
funders by Research
Organisaons
Leadership in HE and at other
research organisaons,
academic journals
HE, higher educaon; COVID-19, coronavirus disease 2019.
Page 9 of 13 Review Arcle
hp://www.td-sa.net Open Access
European epicenters for the outbreak. People younger than
65 years had a 34–73-fold lower risk than those older than 65
years. The absolute risk for COVID-19 death ranged from 1.7
per million people for those younger than 65 years living in
Germany to 79 per million in those residing in New York
City. After age 80, the risk of death rose steeply to 1 in 6000 in
Germany and 1 in 420 in Spain.
Already in September 2020, the US Centers for Disease
Control and Prevention in Atlanta, Georgia, released survival
rates for different ages in the United States that suggested the
risk was very low at young ages. Similarly, the South African
data shows exponentially increasing risk from age 49 for fatal
COVID-19 outcomes (see Figure 1).
The second important risk factor also identified very early in
the ‘pandemic’ was the presence of underlying medical
conditions (comorbidities). In the Netherlands, Italy and
New York City, respectively, 99.7%, 99.3% and 98.2% of all
deaths occurred in those with one or more underlying
comorbidities. The most important comorbidity is underlying
poor metabolic health, characterised by the medical condition
of insulin resistance, often presenting as the metabolic
syndrome, visceral obesity, hypertension and Type 2 diabetes
mellitus (T2DM).
In one of the very earliest studies of 5700 persons hospitalised
in New York City for COVID-19 infection, these comorbidities
were present in the following proportions: (1) hypertension,
56%; (2) obesity, 42% and (3) T2DM, 34%. In September 2020,
a large Western Cape (South Africa) study of 501 fatal cases of
COVID-19 reported that just two factors – age and T2DM –
massively increased the risk of a fatal outcome (Figure 1). Age
above 50 years increased the risk between 8- and 17-fold.
People with T2DM and elevated hemoglobin A1C values,
indicating poor diabetic control, were at 5–12 times greater
risk for a fatal outcome than were those without T2DM. In
contrast, a history of tuberculosis increased the risk 2.7-fold,
and human immunodeficiency virus (HIV) just two-fold.
Other studies found other markers of abnormal metabolic
control including visceral obesity (2.5–11-fold increase risk).46,47
From left: sex, age, type 2 diabetes mellitus (T2DM), other
chronic diseases, tuberculosis, HIV. Note that an HbA1c
value in excess of 7% is diagnostic of T2DM; higher values
indicate more advanced disease. Reproduced from data in
Table 5.3,48
Physicians treating T2DM patients with COVID-19 infections
should also have been informed that any patient with an
elevated blood glucose concentration on hospital admission
was at a four-fold greater risk of a fatal outcome.49 Patients
with T2DM whose blood glucose levels exceeded 10 mmol/L
20
18
16
14
12
Hazard rao
10
8
6
4
21.00
Profile
Age14 Diabetes Others Tuberculosis HIV
Male
20–39
40–49
50–59
60–69
> 70 years
None
HbA1c < 7%
HbA1c > 9%
No HbA1c
Hypertension
Chronic kidney disease
Chronic lung disease
Never
Previous
Current
Negave
Posive
HbA1c 7–8.9%
1.45 1.00
2.83
7.78
11.54
16.79
1.00
5.37
8.53
12.07
2.91
1.31 1.86
0.93 1.00 1.51
2.70
1.00
2.14
0
Female
Source: Adapted from Boulle A, Davies M-A, Hussey H, et al. Risk factors for COVID-19 deaths in a populaon cohort study from the Western Cape Province, South Africa. Clin Infect Dis. 2021 Oct
5;73(7):e2005–e2015. hps://doi.org/10.1093/cid/ciaa1198
HIV, human immunodeciency virus.
FIGURE 1: Hazard raos for risk of fatal outcome in COVID-19 infecons in the Western Cape.66
TABLE 7: Division of knowledge labour on personal health responsibility in a
pandemic.
Rules Discourse acvity by eld Agents in the pandemic
Distribuve rules Producon of discourse in
Higher Educaon
Epidemiologists, immunologists,
microbiologists, pathologists,
virologists
Recontextualising rules Recontextualisaon of
discourse on Media
Plaorms
News media, health ocials in
the government, policians,
‘fake’ news spreaders, anyone
on social media plaorms
Evaluave rules Reproducon of discourse
by Internaonal Health
Organisaons.
Leaders in the: WHO, Centres
for Disease Control, United
Naons Educaonal Scienc
and Cultural Organisaon,
Organisaon for Economic
Cooperaon and Development
WHO, World Health Organisaon.
Page 10 of 13 Review Arcle
hp://www.td-sa.net Open Access
during COVID-19 infection had a significantly worse survival
rate (98.9% versus 89.0%) than those with better glucose
control. Similarly, mortality measured at 60 days in patients
with T2DM was 80% versus 92% in those without T2DM.
Elevated blood glucose concentrations in COVID-19 patients
with T2DM are harmful because: (1) they increase the ability
of the COVID-19 virus to replicate, and (2) they amplify the
inflammatory response in the lungs and adipose tissue,50
among other effects.51
Evidence also accumulated early in the ‘pandemic’ showing
that vitamin D deficiency may be a key determinant of
more severe COVID-19 outcome.52,53,54 Thus, some proposed
early on that patients with COVID-19 infections should
receive supplemental magnesium, vitamin D and zinc55 and
that these supplements should be taken for prophylaxis.
Subsequently, selenium deficiency was added as another
potential nutritional deficiency that could worsen COVID-19
outcomes.56 Interestingly, an analysis of self-reported data
found that a cohort of 18 497 persons who chose not to be
vaccinated, comprising 6% of 297 618 such persons, were less
likely to suffer severe COVID-19 outcomes than those who
chose to be vaccinated.57 In part, this might be because those
who chose to be unvaccinated were more likely to adopt
nutritional and other interventions known to be beneficial
in preventing more serious COVID-19 infections. Given such
overwhelming evidence for the importance of personal
responsibility, what contradictions might explain why its
discourses seem largely ignored in the COVID-19 discourse
from HE and government?
In the first place, personal responsibility is not a commercial
site for generating large profits, some of which may be
donated in supporting HE research. Research into effective,
low-cost interventions seems to be at odds with the
economic interests of both grant recipients and Big Pharma
donors. Replacing costly treatments with low-cost
alternatives would not only greatly diminish the
profitability of existing funders but also reduce the pool of
new ones, as well as the size of future donations from all
such donors.
Another contradiction exists in the exclusion of primary
healthcare workers from the distributive rules for personal
health responsibility during the pandemic. In particular,
dissident health professionals and academic scholars who
promote personal responsibility have faced censorship on
campus and by medical authorities.58 Lacking an opportunity
to share their knowledge in public created a contradiction
whereby marginalised experts have turned to the
recontextualisation field for working around public health
authoritarianism.
A further contradiction exists in the scientific enterprise in HE
lending itself to being an arena for misinformation.59 In science,
the old information of an outdated theorem’s paradigm and its
axioms is an obstacle to a better understanding. Such outdated
understanding may be ‘low-quality’ information. However,
from the perspective of orthodoxy, views that support new
paradigms are unverified knowledge and potentially
‘misinformation’. Any international health organisation that
wishes to be an evaluator must have the scientific expertise for
managing this ongoing paradox or irresolvable contradiction.
Organisations such as the WHO may theoretically be able to
convene such knowledge, but their dependence on funding
from conflicted parties would normally render them ineligible
to perform such a task.
How different modalities of knowledge become presented to
the public is crucial for understanding ‘post-truth’ dimensions
in a pandemic.8 This article alerts researchers to a broad range
of ‘post-truth’ moments and flags the danger of relying on
global health authorities to be the sole custodians of who is
allowed to define what comprises an information disorder.
In each case, challenges to such scientific propaganda should
not automatically be (mis-) characterised as low-quality or
harmful information. Rather, the digital voices of responsible
dissenters can be valuable in protecting scientific integrity
and public health.
Review ndings
The need to watch the World Health
Organizaon and other health ‘custodians’
The WHO describes its main goal as leading and championing
‘global efforts to give everyone, everywhere an equal chance
to live a healthy life’ (2022). However, very early in the
COVID-19 epidemic, it was clear that this was not the case.
For example, it has been claimed that of the 800 000 persons
in the United States who died with a diagnosis of COVID-19
infections, as many as 640 000 could have been saved
had proven early out-of-hospital treatments such as
hydroxychloroquine and ivermectin been mandated.39,60,61
Instead, ‘these knowledgeable doctors were prevented from
employing otherwise safe drugs with the intention of saving
COVID-19-infected people’.33
Thus:
[N]either Anthony Fauci, the CDC, WHO nor any medical
governmental establishment has ever offered any early treatment
other than Tylenol, hydration and call an ambulance once you
have difficulty breathing. This is unprecedented in the entire
history of medical care as early treatment of infections is critical in
saving lives and preventing severe complications. Not only have
these medical organizations and federal lapdogs not even
suggested early treatment, they attacked anyone who attempted
to initiate such treatment with all the weapons at their disposal –
loss of license, removal of hospital privileges, shaming,
destruction of reputations and even worse.62 (p. 2)
The WHO is complicit in all COVID-19 deaths that could
have been prevented by the initiation of early effective
treatment. A probable explanation for why early treatment
was not encouraged in the United States lies in the windfall
that the COVID-19 ‘pandemic’ brought to the US hospital
companies. The Federal Care Act provided a disincentive
for out-of-hospital care of COVID-19 infections by offering
$12 000 for each patient admitted to intensive care units
Page 11 of 13 Review Arcle
hp://www.td-sa.net Open Access
(ICU) and $39 000 for each patient in the ICU placed on a
respirator.33 Early on, it was found that 60% of patients
placed on ventilators were more likely to have a fatal
outcome.63 This mortality rate was reduced with time as
care providers became more skilled in the use of this form of
treatment. Or alternatively, they realised that this form of
treatment was more likely to produce a fatal outcome than
was its avoidance. Blaylock39 makes the point that billions
in federal COVID-19 aid are now being used by the hospital
‘giants’ to purchase financially endangered hospitals – an
unintended consequence of the failure to promote out-of-
hospital treatment with proven effective repurposed
medications.
With regard to vaccine harms, the mantra of ‘safe and
effective’ from the WHO and other public health institutions
is called into question through orthodox methods of review
of the vaccine data provided by the vaccine companies
themselves.29 The gigantic profits for investors in COVID-19
vaccines have bankrolled mandatory vaccine policies that
have led to significant individual harms while returning
ascribed ‘benefits’ that have continually diminished in
scope.
Conclusion
It seems that the WHO’s advice was not evidence
based, leaving plenty of scope for speculation in the
recontextualisation field. We have described this and many
other intergroup contradictions that exist within, and
between, divisions of knowledge labour in the COVID-19
pandemic. The changed nature of vaccine knowledge
production is spotlighted, and its accelerated division of
labour is driven by the dominating financial interests of
those companies that manufacture the experimental
therapies. Manufacturers of these novel therapies dominate
the division of knowledge labour in mRNA vaccine
production. These companies also exert undue influence on
academic institutions and health organisations that are
expected to be independent of external influences in their
search for truth.
The division of knowledge labour in the COVID-19 pandemic
regarding the promotion of vaccine uptake, and safety has
influenced the WHO’s reluctance in tracking vaccine injuries.
The WHO did not promote a range of relatively simply
health-promoting behaviours known to improve personal
resistance to infection, especially of those who are the most at
risk of a fatal COVID-19 outcome.
We argue that the contradictions in the development of
mRNA vaccine production knowledge strongly influence
outcomes related to personal health knowledge. Most
notably, the WHO’s failures in its acceptance of the need for
vaccinating all the world’s people even before proper clinical
trials establishing that these novel experimental therapies
were both ‘safe and effective’. The WHO also failed to address
the issue of personal responsibility in optimising personal
health choices and behaviours.
Given such massive failures, to be credible, the WHO
infodemic research agenda should open earnest discussion
on whether its own choices and guidelines have
contributed to ‘misinformation’, ‘disinformation’ and even
‘malinformation’. It should also address the other COVID-19
myths, which officials continue to promote (PANDATA,
2021).64 Without such epistemic humility, this research
agenda can be criticised, as the agenda’s actual goal may be
to direct attention away from the multiple failures of
government and health authorities in fighting a pandemic
with inappropriate measures. In particular, given that
prioritising vaccines over other measures has had huge
social costs for Africa’s poor.65
The CDC, NIH and WHO’s endorsement of multinational
pharmaceutical companies’ products is particularly troubling.
It marks a ‘new normal’ of institutional capture by industry-
sponsoring regulators who become their ‘lobbyists’. This
contrasts to the silo efforts of external influence in the past, for
example by lobbyists working for Big Tobacco or Big Food.63
They spun embedded scientific research touting the ‘benefits’
of smoking and processed foods. At the same time, evidence
of harm was attacked as ‘junk science’. At least with cigarettes
and ultra-processed foods, many individuals have the choice
to buy or avoid paying. In stark contrast, tax-paying publics
have no such option in avoiding the steep costs of mRNA
vaccines. Public taxes pay for these treatments, while
less expensive and potentially more effective interventions
are ignored. Paying for vaccines takes funding away from
interventions that would address wider and more pressing
global health needs, in particular, poverty, malaria,
tuberculosis and T2DM.
As outsiders and dissidents from the COVID-19 consensus,
we have raised several constructive criticisms of the
infodemic research agenda. Such concerns seem apposite to
the ideology of the pro-vaccine, Great Reset agenda of the
WHO and its economic stakeholders. We suspect that our
unrequested advice and unwanted criticism will simply be
ignored, so we welcome your feedback.
Acknowledgements
The publication developed from a collaboration between the
Noakes Foundation’s Academic Free Speech and Digital
Voices research theme and Pandemics Data Analytics
(PANDA).
Compeng interests
The authors have declared that no competing interests exists.
Authors’ contribuons
T.M.N., the senior author, conceptualised the manuscript’s
direction and focus; wrote the first draft and was responsible
for all visualisations. T.M.N. provided the major input to all
subsequent revisions. D.B. contributed to the investigation’s
Page 12 of 13 Review Arcle
hp://www.td-sa.net Open Access
formal analysis, providing specialist health sociology input
and reviewing and editing the final draft. T.D.N. edited all
drafts; provided critical comments on the flow, meaning and
content of the manuscript and assisted the investigation with
specialist medical input.
Ethical consideraons
This article followed all ethical standards for research
without direct contact with human or animal subjects.
Funding informaon
This research received no specific grant from any funding
agency in the public, commercial or not-for-profit sectors.
Data availability
The authors confirm that the data supporting the findings
of this study are available within the article.
Disclaimer
The views and opinions expressed in this article are those of
the authors and do not necessarily reflect the official policy or
position of any affiliated agency of the authors.
References
1. Ghebreyesus TA. Munich security [homepage on the Internet]. World Health
Organisaon; 2020. Available from: hps://www.who.int/director-general/
speeches/detail/munich-security-conference
2. Calleja N, AbdAllah A, Abad N, et al. A public health research agenda
for managing infodemics: Methods and results of the rst WHO infodemiology
conference. JMIR Infodemiology. 2021;1(1):e30979. hps://doi.org/ 10.2196/
30979
3. Scienc_American. The spies who sabotaged global health. Sci Am.
2013;308(5):12–13. hps://doi.org/10.1038/sciencamerican0513-12
4. Mahajan A, Czerniak C, Lamichhane J, et al. WHO public health research agenda
for managing infodemics. Eur J Public Health. 2021;31(suppl_3):ckab164.030.
hps://doi.org/10.1093/eurpub/ckab164.030
5. Fairclough N. A dialeccal-relaonal approach to crical discourse analysis in
social research. Methods of crical discourse analysis. Thousand Oaks, CA: Sage,
2009; p. 162–186.
6. Arnot M. & Reay D. The framing of performance pedagogies: pupil perspecves
on the control of school knowledge and its acquision, In: Lauder H, Brown P,
Dillabough J.-A. & Halsey A, editors. Educaon, globalizaon and social change.
Oxford: Oxford University Press, 2006; p. 766–778.
7. Bernstein B. Pedagogy, symbolic control, and identy: Theory, research, crique.
Lanham, MD: Rowman & Lileeld; 2000.
8. Kwok H, Singh P, Heimans S. The regime of ‘post-truth’: COVID-19 and the polics
of knowledge. Disc Stud the Cult Polit Edu. 2021;1–15. hps://doi.org/10.1080/0
1596306.2021.1965544
9. Durkheim E. The division of labor in society. Social stracaon. New York, NY:
Routledge, 2019; p. 178–183.
10. Bernstein B, Solomon J. ‘Pedagogy, identy and the construcon of a theory of
symbolic control’: Basil Bernstein quesoned by Joseph Solomon. Br J Sociol Educ.
1999;20(2):265–279. hps://doi.org/10.1080/01425699995443
11. Lilejohn SW, Foss KA. Theories of human communicaon. Long Grove, IL:
Waveland Press; 2010.
12. Fuller S. Post-truth: Knowledge as a power game. London: Anthem Press; 2018.
13. Plotkin S, Robinson JM, Cunningham G, Iqbal R, Larsen S. The complexity and cost
of vaccine manufacturing – An overview. Vaccine. 2017;35(33):4064–4071.
hps://doi.org/10.1016/j.vaccine.2017.06.003
14. Malcolm D. Post-truth society? An Eliasian sociological analysis of knowledge
in the 21st century. Sociology. 2021;55(6):1063–1079. hps://doi.org/
10.1177/0038038521994039
15. Chouliaraki L, Fairclough N. Discourse in late modernity. Discourse in late
modernity. Edinburgh: Edinburgh University Press; 2022.
16. Stavrou S. Pedagogising the university: On higher educaon policy implementaon
and its eects on social relaons. J Educ Policy. 2016;31(6):789–804. hps://doi.
org/10.1080/02680939.2016.1188216
17. Gerrard J. The uneducated and the polics of knowing in ‘post truth’ mes:
Ranciere, populism and in/equality. Disc Stud Cult Poli Educ. 2021;42(2):155–169.
hps://doi.org/10.1080/01596306.2019.1595528
18. Redeker D, Bernardes M, Davidian G, et al. Mapping policy responses to the
COVID-19 misinfodemic. IPW working paper. Bremen: University of Bremen; 2022.
19. Food and Drug Administraon. Emergency use authorizaon (EUA) for an
unapproved product review memorandum [homepage on the Internet]. Food and
Drug Administraon; 2020 [cited n.d.]. Available from: hps://www.fda.gov/
media/144416/download
20. Frenck RW, Klein NP, Kitchin N, et al. Safety, immunogenicity, and ecacy of the
BNT162b2 COVID-19 vaccine in adolescents. N Engl J Med. 2021;385(3):239–250.
hps://doi.org/10.1056/NEJMoa2107456
21. Loe M. Yes, the CDC changed its denion of vaccine to be ‘more transparent’
[homepage on the Internet]. VERIFY; 2022 [cited n.d.]. Available from: hps://www.
verifythis.com/article/news/verify/coronavirus-verify/cdc-changed-vaccine-
denion-more-transparent/536-03ce7891-2604-4090-b548-b1618d286834
22. Chadha S. How digital helps a life sciences leader move at light speed [homepage
on the Internet]. McKinsey; 2022 [cited n.d.]. Available from: hps://www.
mckinsey.com/industries/life-sciences/our-insights/how-digital-helps-a-life-
sciences-leader-move-at-light-speed
23. Alliance CCC. The Pzer inoculaons for COVID-19: More harm than good
[homepage on the Internet]. Canadian Covid Care Alliance; 2021 [cited 2021 Dec
16]. Available from: hps://www.canadiancovidcarealliance.org/
24. Doshi P. COVID-19 vaccines: In the rush for regulatory approval, do we need more
data? BMJ. 2021;373:n1244. hps://doi.org/10.1136/bmj.n1244
25. Thacker PD. COVID-19: Researcher blows the whistle on data integrity issues in
Pzer’s vaccine trial. BMJ. 2021;375:n2635. hps://doi.org/10.1136/bmj.n2635
26. Kennedy RF. The Real Anthony Fauci: Bill Gates, Big Pharma, and the global war on
democracy and public health. Skyhorse Publishing; 2021.
27. Doshi P, Godlee F, Abbasi K. COVID-19 vaccines and treatments: We must have raw
data, now. BMJ. 2022;376:o102. hps://doi.org/10.1136/bmj.o102
28. Tanveer S, Rowhani-Farid A, Hong K, Jeerson T, Doshi P. Transparency of
COVID-19 vaccine trials: Decisions without data. BMJ Evid Based Med.
2021;27(4):199–205. hps://doi.org/10.1136/bmjebm-2021-111735
29. Fraiman J, Ervi J. Jones M, et al. Serious adverse events of special interest
following mRNA vaccinaon in randomized Trials [homepage on the Internet].
2022 [cited 2022 Jun 29]. Available from: hps://papers.ssrn.com/sol3/papers.
cfm?abstract_id=4125239
30. Demasi M. From FDA to MHRA: Are drug regulators for hire? BMJ. 2022;377:o1538.
hps://doi.org/10.1136/bmj.o1538
31. Fourcade M. Pzer CEO sees return to normal life ‘soon’ [homepage on the
Internet]. Bloomberg; 2022 [cited n.d.]. Available from: hps://www.bloomberg.
com/news/articles/2022-01-17/pfizer-s-bourla-sees-return-to-normal-life-in-
garo-interview
32. Singanayagam A, Hakki S, Dunning J, et al. Community transmission and viral load
kinecs of the SARS-CoV-2 delta (B.1.617.2) variant in vaccinated and unvaccinated
individuals in the UK: A prospecve, longitudinal, cohort study. Lancet Infect Dis.
2022;22(2):183–195. hps://doi.org/10.1016/S1473-3099(21)00648-4
33. Levine-Tiefenbrun M, Yelin I, Alapi H, et al. Waning of SARS-CoV-2 booster viral-
load reducon eecveness. Nat Commun. 2022;13(1):1237. hps://doi.
org/10.1038/s41467-022-28936-y
34. Levin EG, Lusg Y, Cohen C, et al. Waning immune humoral response to BNT162b2
COVID-19 vaccine over 6 months. N Engl J Med. 2021;385(24):e84. hps://doi.
org/10.1056/NEJMoa2114583
35. Goldberg Y, Mandel M, Bar-On YM, et al. Waning immunity aer the BNT162b2 vaccine
in Israel. N Engl J Med. 2021;385(24):e85. hps://doi.org/10.1056/NEJMoa2114228
36. Goldberg Y, Mandel M, Bar-On YM, et al. Protecon and waning of natural and
hybrid immunity to SARS-CoV-2. N Engl J Med. 2022;386(23):2201–2212. hps://
doi.org/10.1056/NEJMoa2118946
37. Morris J. Do the recent 80k pages of Pzer documents released really show vaccine
ecacy was only 12%? [homepage on the Internet]. Jerey Morris; 2022 [cited
n.d.]. Available from: hps://www.covid-datascience.com/post/do-the-recent-80k-
pages-of-pzer-documents-released-really-show-vaccine-ecacy-was-only-12
38. Acevedo-Whitehouse K, Bruno R, McCullough P, et al. SARS-CoV-2 mass
vaccinaon: Urgent quesons on vaccine safety that demand answers from
internaonal health agencies, regulatory authories, governments and vaccine
developers. Hoboken, NJ: Authorea Preprints; 2021.
39. Blaylock RL. COVID UPDATE: What is the truth? Surg Neurol Int. 2022;13:167.
hps://doi.org/10.25259/SNI_150_2022
40. Gøtzsche PC. Deadly medicines and organised crime: How big pharma has
corrupted healthcare. Boca Raton, FL: CRC press; 2019.
41. Matendawafa A. Limited community engagement on COVID-19 response – A
piall in SA’s response to COVID-19 [homepage on the Internet]. African Alliance;
2020 [cited n.d.]. Available from: hps://africanalliance.org.za/shabir-madhi-
principal-invesgator-sa-ox1_ncov-vida-vaccine-trial/.
42. Cocks T. South Africa’s aspen COVID-19 vaccine plant risks closure aer no orders,
execuve says [newspaper online]. 2022 [cited 2022 May 02]. Available from: Reuters.
43. Bryant A, Lawrie TA, Dowswell T, et al. Ivermecn for prevenon and treatment of
COVID-19 infecon: A systemac review, meta-analysis, and trial sequenal
analysis to inform clinical guidelines. Am J Ther. 2021;28(4):e434. hps://doi.
org/10.1097/MJT.0000000000001402
44. Kyrie V, Broudy D. Hiding in plain sight: Technocrac tyranny behind a medical mask.
Propoganda in Focus [homepage on the Internet]. 2022. [cited n.d.]. Available from:
hps://propagandainfocus.com/hiding-in-plain-sight-technocrac-tyranny-behind-
a-medical-mask/
Page 13 of 13 Review Arcle
hp://www.td-sa.net Open Access
45. Noakes T, Sboros M. The COVID-19 revoluon – The best long-term protecon is
improved metabolic health. The eat right revoluon: Your guide to living a longer,
healthier life. Cape Town: Penguin Random House, 2021; p. 142–148.
46. Petersen A, Bressem K, Albrecht J, et al. Obesity and COVID-19: The role of visceral
adipose ssue. medRxiv. 2020. hps://doi.org/10.1101/ 2020.05. 14.20101998
47. Yang Y, Ding L, Zou X, et al. Visceral adiposity and high intramuscular fat deposion
independently predict crical illness in paents with SARS-CoV-2. Obesity.
2020;28(11):2040–2048. hps://doi.org/10.1002/oby.22971
48. Western Cape Department of Health in collaboraon with the Naonal Instute
for Communicable Diseases SA. Risk factors for coronavirus disease 2019
(COVID-19) death in a populaon cohort study from the Western Cape Province,
South Africa. Clin Infect Dis. 2020;73(7):e2005–e15.
49. Wang S, Ma P, Zhang S, et al. Fasng blood glucose at admission is an independent
predictor for 28-day mortality in paents with COVID-19 without previous diagnosis
of diabetes: A mul-centre retrospecve study. Diabetologia. 2020;63(10):
2102–2111. hps://doi.org/10.1007/s00125-020-05209-1
50. Mauvais-Jarvis F. Aging, male sex, obesity, and metabolic inammaon create the
perfect storm for COVID-19. Diabetes. 2020;69(9):1857–1863. hps://doi.
org/10.2337/dbi19-0023
51. Apicella M, Campopiano MC, Mantuano M, Mazoni L, Coppelli A, Del Prato S.
COVID-19 in people with diabetes: Understanding the reasons for worse outcomes.
Lancet Diabetes Endocrinol. 2020;8(9):782–792. hps://doi.org/10.1016/S2213-
8587(20)30238-2
52. Maghbooli Z, Sahraian MA, Ebrahimi M, et al. Vitamin D suciency, a serum
25-hydroxyvitamin D at least 30 ng/mL reduced risk for adverse clinical outcomes
in paents with COVID-19 infecon. PLoS One. 2020;15(9):e0239799. hps://doi.
org/10.1371/journal.pone.0239799
53. Rhodes JM, Subramanian S, Laird E, Grin G, Kenny RA. Perspecve: Vitamin D
deciency and COVID-19 severity – Plausibly linked by latude, ethnicity, impacts
on cytokines, ACE2 and thrombosis. J Intern Med. 2021;289(1):97–115. hps://
doi.org/10.1111/joim.13149
54. Lau FH, Majumder R, Torabi R, et al. Vitamin D insuciency is prevalent in severe
COVID-19. medRxiv. 2020. hps://doi.org/10.1101/2020.04.24.20075838
55. Cooper ID, Cros CAP, DiNicolantonio JJ, et al. Relaonships between
hyperinsulinaemia, magnesium, vitamin D, thrombosis and COVID-19: Raonale for
clinical management. Open Heart. 2020;7(2):e001356. hps://doi.org/10.1136/
openhrt-2020-001356
56. Fakhrolmobasheri M, Mazaheri-Tehrani S, Kieliszek M, et al. COVID-19 and
selenium deciency: A systemac review. Biol Trace Elem Res. 2021;
200:3945–3956. hps://doi.org/10.1007/s12011-021-02997-4
57. Robert V, Do CP, Kathrada N, Lindley K. Self-reported outcomes, choices and
discriminaon among a global COVID-19 unvaccinated cohort. Hoboken, NJ:
Authorea; 2022.
58. Simon A. These are the courageous doctors who fought the COVID farce and paid
the price [homepage on the Internet]. Issues&Insights; 2022 [cited n.d.]. Available
from: hps://issuesinsights.com/2022/02/25/these-are-the-courageous-doctors-
who-fought-the-covid-farce-and-paid-the-price/.
59. Renstrom J. How science helps fuel a culture of misinformaon. NiemanLab
[homepage on the Internet]. 2022 [cited n.d.]. Available from: hps://www.
niemanlab.org/2022/06/how-science-helps-fuel-a-culture-of-misinformaon/
60. Marik PE, Kory P, Varon J, Iglesias J, Meduri GU. MATH+ protocol for the treatment
of SARS-CoV-2 infecon: The scienc raonale. Expert Rev An Infect Ther.
2021;19(2):129–135. hps://doi.org/10.1080/14787210.2020.1808462
61. McCullough PA, Kelly RJ, Ruocco G, et al. Pathophysiological basis and raonale
for early outpaent treatment of SARS-CoV-2 (COVID-19) infecon. Am J Med.
2021;134(1):16–22. hps://doi.org/10.1016/j.amjmed.2020.07.003
62. Albright L. Medical nonconformity and its persecuon [homepage on the Internet].
Brownstone Instute; 2021 [updated 2021 Oct 13]. [cited n.d.]. Available from:
hps://brownstone.org/arcles/medical-nonconformity-and-its-persecuon/
63. Brownell KD, Warner KE. The perils of ignoring history: Big tobacco played dirty
and millions died. How similar is big food? Milbank Q. 2009;87(1):259–294.
hps://doi.org/10.1111/j.1468-0009.2009.00555.x
64. Pandemics Data and Analycs [PANDA]. (2021). 20 Lies. Retrieved 2022/10/02
[homepage on the Internet]. 2021 [cited 2022 Oct 02]. Available from: hps://
www.pandata.org/20-lies/
65. Shaw C. The COVID-19 pandemic: Destroying human bonds and health as central
to a larger agenda. Propaganda in Focus [homepage on the Internet]. 2022 [cited
n.d.]. Available from: hps://propagandainfocus.com/the-covid-19-pandemic-
destroying-human-bonds-and-health-as-central-to-a-larger-agenda/
66. Boulle A, Davies M-A, Hussey H, et al. Risk factors for COVID-19 deaths in a
populaon cohort study from the Western Cape Province, South Africa. Clin Infect
Dis. 2021 Oct 5;73(7):e2005–e2015. hps://doi.org/10.1093/cid/ciaa1198
