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Most outlets argue that before the United States can reopen safely, a new massive workforce needs to be in place to trace the contacts of people diagnosed with COVID-19, according to a report from the Johns Hopkins Center for Health Security.

Contact tracing is laborious, detailed and time-consuming detective work: Trained staff interview people who have been diagnosed with a contagious disease to figure out who they may have recently been in contact with. Then, they go tell those people they may have been exposed, sometimes encouraging them to quarantine themselves to prevent spreading the disease any further. Think of it as part public health work, and part investigation. The technique is a “cornerstone” of preventative medicine, says Dr. Laura Breeher, medical director of occupational health services at the Mayo Clinic. “Contact tracing, it’s having a moment of glory right now with COVID because of the crucial importance of identifying those individuals who have been exposed quickly and isolating or quarantining them,” she says.

A long-used public health tool, contact tracing aims to break the chain of transmission of a contagious disease by identifying and alerting those who may have been exposed to it. Traditionally, a trained contact tracer will interview an individual diagnosed with the disease to determine all of their recent contacts, then reach out to those contacts to provide further information—which may include a recommendation to self-quarantine. In the past, this meticulous strategy has been used to help control Ebola, SARS, sexually transmitted infections, and tuberculosis, among other communicable diseases.

With the global outbreak of COVID-19, public health experts believe contact tracing will be a critical step for containing the virus, alongside social distancing and widespread testing. Many countries have already deployed extensive contact tracing, including New Zealand, Iceland, Taiwan, Singapore, and South Korea.

The United States, too, is gradually ramping up efforts—including a new hiring surge funded by the CDC, a Google/Apple tech partnership, and statewide programs. In New York, Gov. Andrew Cuomo is working with Bloomberg Philanthropies to launch their contact tracing program that will include online training from the Johns Hopkins Bloomberg School of Public Health.

“In the absence of a vaccine, we think this is really the big public health tool we have to control transmission of COVID-19,” according to Crystal Watson, lead author of the report and Assistant Professor in the Bloomberg School. “We need to push hard for this.”

Is this true that “contact tracing” is essential and valuable or is it an academic exercise? Write your discussion based on your readings on the applications and challenges of contact tracing; address the pro’s and con’s of contact tracing since this pandemic is no longer in its early stages of spread, the vast majority of infected individuals are asymptomatic and in New York, for example more that 60% of new infected individuals were sequestered “at home”. Also take into consideration, privacy, costs, and issues with the timing and accuracy of current diagnostic tests. With all of your passion, argument for or against massive contact tracing for COVID-19.

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Intelligence and National Security

ISSN: 0268-4527 (Print) 1743-9019 (Online) Journal homepage: https://www.tandfonline.com/loi/fint20

Improving ‘Five Eyes’ health security intelligence
capabilities: leadership and governance challenges

Patrick F. Walsh

To cite this article: Patrick F. Walsh (2020): Improving ‘Five Eyes’ health security intelligence
capabilities: leadership and governance challenges, Intelligence and National Security, DOI:
10.1080/02684527.2020.1750156

To link to this article: https://doi.org/10.1080/02684527.2020.1750156

Published online: 22 Apr 2020.

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ARTICLE

Improving ‘Five Eyes’ health security intelligence capabilities:
leadership and governance challenges
Patrick F. Walsh

ABSTRACT
This article explores common organizational pressure points for ‘Five Eyes’
intelligence communities in their ability to understand, prevent and dis-
rupt potential emerging bio-threats and risks. The acceleration in the
development of synthetic biology and biotechnology for legitimate mar-
kets (e.g. pharmaceuticals, food production and energy) is moving faster
than current intelligence communities’ ability to identify and understand
potential bio-threats and risks.

The article surveys several political leadership and intelligence govern-
ance challenges responsible for the current sub-optimal development of
health security intelligence capabilities and identifies possible policy sug-
gestions to ameliorate challenges.

Introduction

For some practitioners across ‘Five Eyes’ Intelligence Communities (IC) the mention of ‘health
security’ and ‘intelligence’ together still seem a strange combination of words. For others in the IC
even if ‘health security threats and risks’ are seen as legitimate collection and analytical priorities akin
to others such as counter-terrorism and cyber–there is a reticence to invest in them. This somewhat
disengaged perspective is explainable partly because there is yet no clear trajectory for bio-threats
and risks. Disengagement is also arguably due–in part because historically ICs have not had a good
understanding of bio-threats and risks from the Cold War up to and after the Coalition invasion of
Iraq in 2003.

Based on recent research, this article investigates how ‘Five Eyes’ partner countries can improve
their health security intelligence capabilities to gain a deeper understanding of emerging bio-threats
and risks. It concludes that sustained and coordinated capability improvements are largely a function
of two aspects of intelligence governance: political leadership/external governance and internal IC
governance issues. The article explores the significance of both factors before assessing the future
outlook of health security intelligence capability over the next five years (2020-2025). Before
addressing the central question of how to improve health security intelligence capability, however,
it is important first to define how ‘health security intelligence’ is used in this article.

Health security intelligence

There are multiple interpretations on what constitutes ‘health security intelligence’ based largely on
the diverse disciplinary backgrounds of scholars who seek to define it. In particular, the literature
highlights this diversity between how public health specialists, clinicians, epidemiologists use the
term compared to intelligence and security specialists. Aldis provides a useful discussion on the lack

CONTACT Patrick F. Walsh pawalsh@csu.edu.au

INTELLIGENCE AND NATIONAL SECURITY
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of agreement and understanding, particularly between developed and developing countries, on the
concept of health security. He stated that the term ‘health security,’ like ‘biosecurity,’

‘sits at the intersection of several disciplines which do not share a commonmethodology (e.g., practitioners from
security studies, foreign policy, IR [international relations], development theory and practice of UN agencies).’1

As in biosecurity, inconsistencies arise in how health security is defined. Bernard has referred to
a ‘tribalism’ between the public health and security sectors, which has prevented both from under-
standing each other and perceiving common priorities.2 Historically, this has led to different
disciplines talking past each other and not seeing how their perspectives can provide potentially
a more accurate and inclusive definition of health security intelligence. As a former intelligence
analyst and intelligence studies scholar, my own perspectives of health security intelligence has
evolved over time. In my most recent work in this area – Intelligence, Biosecurity and Bioterrorism the
focus is largely on biosecurity and the intentional weaponising of biology.3 However, I concluded
that biosecurity should be seen as one aspect of a broader health security community–the other
being public health. The human security agenda, which emerged from the international relations
and security studies literature in the 1990s provides a unifying concept for understanding health
security intelligence. Human security scholars sought to broaden traditional notions of security–
beyond being solely about war and peace between states. Human security also emphasised the
security of individuals within and between states, and included security against pandemics, poverty,
access to education, and safe water amongst other basic human rights.4

In the context of a growing human security agenda, several scholars working in public health,
particularly clinicians and sociologists begun to argue increasingly the response to global pandemics
(HIV, SARs, H1N1, Zika and Ebola) as not just regional/global health emergencies, but also grave
health security events.5 Such events not only had the potential to make many sick, but their
implications globally – particularly for developing countries with fragile public sector infrastructure –
had security implications for states involved. The 2014–16 Ebola outbreak in Western Africa, which
killed 10,000 people illustrates how a major public health emergency not only has catastrophic
health outcomes, but can also destabilise the capacities of nation-states to respond to such crises.6

Similarly, since 2018 another Ebola outbreak has occurred in the Democratic Republic of Congo’s
North Kivu and Ituri provinces. Further at the time of writing, there has been an outbreak of corona
virus (COVID-19) first reported fromWuhan, China on 31 December 2019, which also underscores the
fragility of even economically wealthy states’ ability to respond to regional and global health security
crises.

In the case of the recent Ebola outbreak, there have been over 1900 deaths and although over
80,000 people have been immunized with a new Ebola vaccine, public health responders have been
attacked by rebel militia and prevented from tracing and treating population in surrounding areas.
This situation provides another example of the critical link between public health and security.7 In
summary, if naturally occurring public health incidents and security are linked then it follows that
intentional public health (biosecurity incidents involving bio-crimes and bio-terrorism) need to be
seen not only as intelligence and security priorities, but also clearly as public health incidents. For
example, the release of anthrax into a metropolitan transport hub, will require both intelligence and
public health personnel coming together to assess whether the threat/risk is primarily a biosecurity
or public health emergency. ‘Health security’ thus becomes a useful over-arching terminology to
capture both biosecurity and public health dimensions of health incidents in order to assess the
security implications of both. Clearly not all health security incidents as they unfold will rely on
a similar composition of public health, intelligence and security personnel. However, both dimen-
sions will remain co-dependent on each other as discussed in greater detail below.

With health security defined, the last aspect of ‘health security intelligence’ requiring clarification
is ‘intelligence.’ Again depending on the context (e.g. national security, policing, military, private
sector), there are many diverse perspectives on what ‘intelligence’ is and does. Leaving aside these
debates, and for the objectives of this article, I argue that intelligence has at least three unique

2 P. F. WALSH

defining attributes: secrecy, surveillance and the security environment.8 All these terms are relative in
the sense that in certain contexts (e.g. the Central Intelligence Agency, CIA) some intelligence
collected would be considered highly secret with profound impacts on a given nation’s interests if
it was shared widely – perhaps even in that nation’s intelligence community. Whereas a local policing
agency could possess material on file classified as ‘secret’ or ‘protected’ (or more accurately
privileged information), but the consequences of its release may be less deleterious. The point is
secrecy is a relative term, but in its broadest sense most intelligence practice regardless of context
cannot operate without a relative level of secrecy. The second term surveillance underscores another
primary objective of all intelligence practice regardless of context. Intelligence activities can include
an array of activities including research and information management. However, intelligence would
not be intelligence without an ability to warn decision-makers about impending risks and threats.
This requires active and sometimes passive surveillance of threat actors and risks in the security
environment, which is the third defining characteristic of intelligence. The security environment again
depending on the context in which intelligence is practiced is large, diverse and ever changing. It
includes an open-ended list of threats such as state based military threats, terrorism, cyber, failed
states and bio-threats and risks–the subject of this article.

With health security intelligence now defined, I now turn to a brief assessment of emerging bio-
threats and risk across ‘Five Eyes’ countries. Given limited space, the focus here is squarely on post 9/
11 emerging bio-threats and risks because it is the capability of ‘Five Eyes’ countries in managing
both contemporary and emerging threats and risks that is most germane to our discussion. This is not
to suggest that understanding the evolution of bio-threat and risk trajectories pre-9/11 is not
relevant to situating current or emerging threats. Indeed the rapid development of modern micro-
biology and the industrialisation of various biological weapons in state based programs (e.g. Soviet
Union, USA, UK and Canada) since 1945 – and the attempt by rogue states (particularly Iraq but also
Iran, North Korea and Syria) to do the same – provides a foundation upon which more recent bio-
threat and risk typologies can be understood. Additionally, the rapid development of synthetic
biology and biotechnology from the 1990s to the present and the potential weaponisation of
aspects of these technological advancements should also be examined against the broader historical
context of bio-threats and risk from 1945, throughout the Cold War and the immediate pre 9/
11 period. But these developments are chronicled in detail elsewhere for readers seeking this
background material.9

Discussion here of contemporary and emerging bio-threats and risks starts with the Amerithrax
incident of 2001. I argue Amerithrax represented a water shed moment in helping ICs and policy-
makers recalibrate their understanding about future bio-threats trajectories. In September and
October 2001, seven envelopes containing a dried powder form of anthrax spores were posted to
several media outlets and to the US Senate offices of Senators Thomas Daschle and Patrick Leahy.
The letters resulted in 22 cases of anthrax–five of which led to fatal inhalational anthrax. The anthrax
letters also resulted in the contamination and closure of several major US postal offices.10 The
Amerithrax attack came only a week after 9/11 so the United States was already unsettled about
the possibility of more terrorist attacks. The incident resulted in a 7 year long investigation, where the
US Department of Justice (DOJ) determined a single spore batch created by anthrax specialist
Dr Bruce E Ivins at the US Army Medical Research Institute of Infectious Diseases (USAMRID) was
the parent material for the letter spores. In July 2008 Ivins committed suicide before being indicted.
However, since the FBI officially closed the investigation in 2010 several biologists and chemists
disagree on whether the Bureau got the right perpetrator based on the presence of silicon and tin
coating on the anthrax spores. In the opinion of some experts this suggest a greater complexity of
manufacturing beyond the scope of what Ivins could do in his lab. Additionally, earlier in the
investigation another army research scientist Steven Hatfield was targeted, but later exonerated
with the DOJ paying a 4.6 million dollar legal settlement to the scientist.11 The DOJ has not changed
its position that Ivins was responsible and complex investigations such as Amerithrax underscore the
difficulties in attribution of individuals involved in bio-attacks.

INTELLIGENCE AND NATIONAL SECURITY 3

Amerithrax while not a major casualty attack was significant for a number of reasons. First it
influenced IC assessments about how easy it would be for non-state actors such as Al Qaeda to
produce and disseminate biological agents as weapons. Amerithrax showed the difficulties an
anthrax scientist had in producing the spores in ideal laboratory conditions. Al Qaeda and other
jihadist groups may have held an interest in developing bio-weapons, yet for the most part had
limited access to similar scientific expertise or a safe laboratory setting for their development. In
summary, the incident injected more subtlety and complexity into policy discussions given that
during the late 1990 s and early 2000 s a dominant strand in the political discourse was that it would
be relatively easily for terrorist groups to develop bio-weapons. Second, and more importantly,
Amerithrax demonstrated that the terrorist may be ‘an insider’ – for example a scientist going rogue.
Amerithrax therefore, ignited another arc of the debate about the most likely profile of bio-threat
actors that continues to the present.

Despite the lessons contained in Amerithrax, a comprehensive understanding of contemporary
bio-threats and risks remains unclear across the ‘Five Eyes’ countries and the broader scientific
community. However, there are two broad threat/risk typologies: stolen biological agents and dual
use research and synthetic biology, which illustrate where concerns exist for the potential malicious
use of biology into the future. I will focus more on the latter as this area is currently of greatest
concern by ICs and the scientific community.

Stolen biological agents
Stealing a controlled biological agent appears rare due to increased bio-safety regulations and
control of physical space (BSL 3 and 4 labs) that has developed since the Amerithrax incident in all
‘Five Eyes’ countries.12 Legislation and bio-safety regulations, which also include more stringent
security background checks for employees working with select biological agents (such as anthrax,
tularaemia, the plague) has provided greater protection. However, despite enhanced security
measures in the US and to some extent the UK, there have been a number of handling and
transportation safety episodes (particularly in the 2014 USD–2015), which demonstrate vulnerabil-
ities in safety practices remain. Such episodes involved the US Department of Defense and the
Centers for Disease Control and Prevention (CDC) and included safety protocols not being followed
fully in transporting select biological agents across the United States and internationally as well as
the shipping of bio-culture equipment from BSL 3 and 4 labs to lower safety rated labs without being
sufficiently decontaminated. In July 2019, safety concerns have again been highlighted when the US
Army Medical Research Institute of Infectious Diseases (USAMRID) – a key centre for the develop-
ment of biological countermeasures against bioterrorism suspended operations under the authority
of the Federal Select Agent Program for failing to meet federal biosafety requirements.13

Despite bio-safety lapses and given more stringent physical and personnel safety measures, it
seems that this bio threat/risk typology (stolen biological agents) is likely to remain very low across
‘Five Eyes’ countries. While it is unclear if there is a criminal market for the theft of controlled bio-
agents from secure labs, it would seem that organised criminal groups would have other compara-
tively less risky and more immediately profitable markets to pursue such as drug trafficking. In
particular, given the attribution of many controlled biological agents in BSL 3 to 4 labs can be
assessed forensically, criminal interest in stealing such substances is likely to be further dissuaded.14

The other main threat scenario of a terrorist group breaking in and stealing a controlled bio-agent
also seems less likely.

While 9/11 represented a sophisticated and impactful attack modality, most lethal attacks since
(at least in Western countries) have been simpler using readily available materials and weapons such
as improvised explosive devices, vehicles and knives. None of these require the same expertise as
stealing, handling or using controlled biological substances. Nonetheless, there are two areas of
potential concern in this bio-threat/risk typology (stolen biological agents), which ‘Five Eyes’ coun-
tries still need to collect and assess against: intellectual property theft by an ‘insider’ and the potential
for theft from some BSL 3 to 4 labs in fragile or vulnerable states.

4 P. F. WALSH

Given the exponential rise in synthetic biology, biotechnology research and commercialisation
both in the public and private sector – state and non-state sponsored theft of intellectual property
will likely increase. Such theft will be linked in many instances to broader cyber security and
information security threats that are currently impacting on ‘Five Eyes’ economies. Again, the IC’s
ability to manage the rising complexity in the broader cyber threat space remains a challenge. It is
likely then that ICs will continue to confront expertise and knowledge gaps in how the bio-economy
is being attacked and IP stolen by cyber-threat actors.15

The second area of concern (theft of controlled biological substances) in fragile or vulnerable
states, particularly those in the Middle East and Africa (e.g. Iraq, Syria, Pakistan) is also another area
where greater focus by ‘Five Eyes’ ICs is warranted. Such locations intersect hotspots for jihadist
inspired instability. It is possible that bio-safety lapses in research facilities near unstable locations or
radicalised individuals working within biological institutions could steal bio-agents for terrorist
attacks. Legitimate biological research facilities in vulnerable states require ongoing multi-lateral
global security efforts to promote bio-safety. ‘Five Eyes’ defence and foreign ministries have funded
bio-safety initiatives in vulnerable states in the past, but there is scope for a better coordinated
approach to bilateral and multilateral programs into the future.16

Dual use research and synthetic biology
Dual use research is defined here as research of dangerous biological agents that might be
weaponised, and the publication of that research, which theoretically could be disseminated to bio-
criminals or terrorists for their own nefarious objectives.17 There are a growing number of perspec-
tives of whether criminals and terrorists will exploit biotechnology and synthetic biology research
developed for legitimate purposes (e.g. health care, energy and food supply) for harm or profit.18 The
debates are complex and care should be exercised in not over-simplifying them, however it is
possible to discern two main intellectual strands from them. These are: technological (determinism)
and socio-technological perspectives. The technological determinists argue the upsurge in biotech-
nological advancements will make the access, use and exploitation of relevant knowledge and skills
easier and cheaper for those with malevolent intentions.19 Some of the consequences of the
industrialisation of biology adds weight to their arguments about easier access and use of biotech-
nology. For example, the entire human genome sequenced by 2013 took a team of scientists
13 years and 500 USD million to identify 20,500 genes. Today, the human genome can be sequenced
in a day using bench top equipment costing around 1000 USD. 20

In contrast, the socio-technologists while not discounting that criminals and terrorists may exploit
advances in synthetic biology and technology – argue that access to knowledge and skill is not the
same as being able to adeptly exploit these in order to produce a bio-weapon. Accessing, develop-
ing, manipulating or exploiting knowledge and skills still requires significant training – often in more
than one of the biological sciences (e.g. microbiology, molecular biology, genetics, and medicine).
Training requires not just being able to read and replicate the latest experiments but is also
dependent on applying skills intuitively in a social and collaborative sense frequently working with
a team of scientists. In summary, the ability of a threat actor to weaponise any dual use and synthetic
biology is dependent also on the inter-play of other social, economic and psychological variables.21

Both intellectual perspectives are not sterile academic debates. They matter because they inform
how policy makers, scientists and the intelligence community conceptualise how dual use research
and synthetic biology might be exploited by threat actors.

Shortly, the focus will turn to a brief summary of examples of bio-threats that may arise with the
exploitation of dual use research and synthetic biology. First however, in order to understand how bio-
threats may manifest, it is useful to distinguish between two broad threat trajectories for dual use
research and synthetic biology. The first (‘insiders’) refers to skilled scientists, researchers and techni-
cians, who use knowledge and skills to create dangerous bio-agents under the veil of legitimate
research. The second (‘outsiders’) refers to the exploitation of legitimate advances in biology, synthetic
biology and biotechnology for dangerous and criminal ends. In the second case, it could be one or

INTELLIGENCE AND NATIONAL SECURITY 5

more of the recent ‘gain of function’ (GOF) experiments, where genetic material has beenmanipulated
to encourage the development of dangerous pathogens thought to be rare, absent or dormant in the
general population (e.g. small pox, reconstruction of 1918 influenza virus) – or experiments that make
biological agents more virulent (e.g. mouse pox, horse pox, H5N1 avian influenza transmissible
between human surrogates such as ferrets).22 Such experiments are often promoted as benefiting
medicine by identifying vaccines or better ones against hard to treat viruses and bacteria. The
November 2018 announcement by Chinese scientist He Jiankui that he had allegedly created the
word’s first genetically edited babies that could be resistant to HIV is another recent example of many
scientific, ethical and security concerns raised about both GOF and gene editing experiments.23

Given both the insider and outsider threat trajectories, the critical question remains what types of
specific bio-threats are evolving? There is no satisfactory answer to this question, and debates
continue amongst scholars, scientists and to some extent within the ICs about where bio-threats
are likely to emerge within dual use research and synthetic biology. I argue in this article and
elsewhere that assessing bio-threats and risks will rely on a more strategic and comprehensive
assembling of scientific evidence on how developments in biotechnology and synthetic capabilities
could be exploited by threat actors. Additionally, identifying threats and risks will also rely on ICs
gaining a greater understanding of the intentions of particular actors to select capabilities as
weapons or for profit over other more conventional sources. Assessing intention and capability to
misuse dual use research and synthetic biology remains difficult because the science is moving
rapidly – which in turn makes it difficult to get a ‘fix’ on where vulnerabilities for malevolent
exploitation are located. Such difficulties are also a product of some of the ongoing capability issues
across ‘Five Eyes’ countries in adapting to technologically enabled threats more broadly (e.g. cyber).

Leaving aside the ongoing difficulties in assessing emerging bio-threats and risks, I summarise here
three threat cluster areas where ‘Five Eyes’ countries might consider developing better knowledge of
bio-threats and risks. These are: bio-unabombers, identify theft and bio-piracy. As noted earlier, biotech-
nology is big business particularly in the United States and other ‘Five Eyes’ countries.24 Given the
massive acceleration in biotechnology and synthetic biological sciences – probability alone suggests
that there will be more individuals (some mentally unstable) with a range of grievances (e.g. personal,
psychological, political and religious) working in the biological sciences and some may escalate these
to acts of violence. Disgruntled insiders (scientists), who can make a synthetic organism and sidestep
theft of natural organisms under lock and key in highly regulated high containment labs are uniquely
placed under the disguise of a bigger legitimate scientific project to become bio-unabombers. As
discussed earlier, the alleged involvement of scientist Bruce Ivins in the Amerithrax case is illustrative
here.25 Secondly, ‘identify theft’ – long an enabler of crime and terrorism in other contexts is also likely
to be a developing concern. The increase in DNA holdings in various government departments and the
private sector provide greater opportunities to steal or manipulate DNA. For example, it is possible that
individuals could assume someone’s identity by stealing their DNA, or leaving someone else’s blood
and saliva at a crime scene by genetic cloning to frustrate national security (terrorist) and law
enforcement investigations.26 Thirdly, bio-piracy could become a greater bio-threat and risk in ‘Five
Eyes’ countries. Recent developments in drugs, vaccines andmedicines can bemanipulated. Moreover,
in the last few years the development of gene editing techniques like CRISPR, Finger Nuclease and
Talen could be exploited criminally.27 Though currently there is an increasing ‘hype’ over the threat
significance of CRISPR–further fueled by a national assessment by the US IC during the Obama
Administration, which declared that it could be a national security threat.28 But it remains difficult to
know what if any threat actors, for example jihadists, ultra-nationalists, anarchists, bio-hackers, envir-
onmentally motivated individuals will exploit gene editing techniques like CRISPR.

Capability gaps

As noted earlier, there remain both gaps in scientific evidence and intelligence on what may
constitute emerging bio-threats and risks, particularly those arising from dual use research and

6 P. F. WALSH

synthetic biology. The acceleration of scientific discovery in biotechnology and synthetic biology
make assessing threats and risks in any comprehensive way difficult and this is unlikely to change in
the future. However, it is possible that some threats and risks might be ‘knowable’ – at least
sufficiently to provide decision-makers with warning. However, this will rely on each ‘Five Eyes’
country’s ability to reflect on current capabilities to assess bio-threats and risks in order to identify
capability gaps. With the above outline on potential bio-threat and risk trajectories in mind, this
section explores what are the principle capability gaps across the ‘Five Eyes’ countries. The final
section (outlook) will assess how, or indeed whether the gaps identified can be closed in the near
future.

Before describing the key capability gaps within and across ‘Five Eyes’ intelligence communities, it
is useful to clarify first how I will be using the term ‘capability.’ Based on previous research on
intelligence reform issues, I argue that capability is the sum of two inter-related factors. The first
I refer to as core intelligence processes and the second key enabling activities. Both factors are critical
to effective intelligence capabilities at the agency and community levels.29 In simple terms, core
intelligence processes include the key stages in the production process of intelligence products that
hopefully will influence and support decision-maker’s policy deliberations. These stages are: tasking
and coordination, collection, analysis, production and evaluation. The core intelligence processes
can be thought of as the functional aspects of intelligence production. In contrast, the key enabling
activities provide the structural foundation under which the core intelligence processes can operate
effectively. Intelligence product is not developed in a vacuum and it is the agency and community
key enabling activities (governance, ICT, human resources, legislation and research) that support the
‘intelligence production line.’30 In this section, I argue that health intelligence capability gaps include
a range of issues across core intelligence processes and key enabling activities. In the remaining
space, I will summarise some of the key capability gaps in both the core intelligence processes and
key enabling activities.

Core intelligence processes

There are capability gap issues in three core intelligence processes: tasking and coordination,
collection and analysis. The gaps in each area impact upon one another and as will be demonstrated
shortly also influence how capability gaps arise in the key enabling activities. Tasking and coordina-
tion include a range of activities by decision-makers and internally within ICs about how intelligence
assets particularly collection and analytical resources are to be applied against various threats and
risks. Given intelligence is a decision-maker’s support tool, priorities about the tasking and coordina-
tion of intelligence resources are formally determined at heads of government and cabinet level in
‘Five Eyes’ countries. The identification of other collection and assessment priorities not currently
tasked by senior cabinet ministers obviously are also made by ‘Five Eyes’ intelligence communities
on a regular basis. However, some recent (albeit tentative) research on tasking and coordination
against emerging bio-threats and risks suggest that both decision-makers and the intelligence
communities themselves remain relatively disengaged from these threats.31 This is not to suggest
some bio-threat and risk issues are not getting tasking and coordination attention both by govern-
ments and as part of the routine internal mechanisms of ‘Five Eyes’ communities. There still seems to
be some interest in state sponsored WMD (as it relates to bio) and bioterrorism, however this interest
is limited compared to earlier periods such as Amerithrax and the faulty WMD assessments that
preluded the coalition invasion of Iraq in 2003. There are any number of comparatively more ‘urgent’
threats and risks vying for the attention of ‘Five Eyes’ leaders such as conventional terrorism, cyber,
the resurgence of Russia, the rise of China and North Korea’s nuclear proliferation. In comparison,
emerging bio-threats and risks are akin to cyber threats – they are deeply technical, which com-
pounds the difficulty by IC and decision-makers understanding them. Many are also currently
assessed (rightly or wrongly) as low probability/high impact threats, which influences the amount
of tasking such issues receive by both political decision-makers and from within the ‘Five Eyes’

INTELLIGENCE AND NATIONAL SECURITY 7

intelligence machinery. Low levels of tasking have a knock on effect in the other two stages of the
core intelligence processes: collection and analysis.

From the perspective of collection, the first capability issue is that low or ad hoc levels of tasking
impact on ‘Five Eyes’ countries’ ability to develop better risk and threat methodologies that would
allow more accurate assessment of emerging bio-threats and risks. Poor ability to assess bio-threats
and risks circuitously results in even lower and ad hoc levels of tasking and therefore collection
against these issues by both decision-makers and within ICs. This latter point also raises a broader
question of whether current collection capabilities are suited ideally for gaining better calibration
against emerging bio-threats and risks. As noted earlier, emerging bio-threats and risks may well
arise from dual use research and synthetic biology, but given these areas are predominantly focused
on legitimate research and commercial development, will traditional and more covert IC collection
platforms (e.g. SIGINT, HUMINT and Geo-spatial intelligence) be best placed to ‘discover’ the illicit
weaponisation of biology in these sectors? The answer to this question is not clear. Clearly threat and
risk context will be important. Much will depend on the nature of the bio-threat and risk. Is it local,
national or transnational and is it at the planning, operational or attack stage? Given the emerging
nature of some bio-threats and risks, traditional collection platforms may be less helpful (at least
initially) compared to other open source intelligence such as scientific peer reviewed sources, social
media, epidemiology and microbial forensics in improving assessments of such threats and risks.32

However, current research suggests that while progress has been made in ‘Five Eyes’ countries to
link into and learn from these open sources, a more systematic and strategic approach needs to be
adopted to accessing bio-threat and risk related open source intelligence.33 Additionally, capability
improvements are needed in many open source intelligence areas derived from the scientific
community such as microbial forensics. Collection capabilities in the bio-threat and risk context
are also limited by other issues impacting on broader collection efforts across all ‘Five Eyes’ com-
munities. Of particular importance is the post Snowden impact of threat actors ‘going dark’ due to
them becoming aware of how to reduce their exposure to traditional IC collection platforms. The
increased encryption of communications via Apps and the use of the dark web present ongoing
collection capability challenges – not just in the bio-threat and risk area but across the entire security
environment.34

The third core intelligence process area where there are capability gaps is analysis. Similar to the
collection capability issues discussed some of the gaps in analysis on bio-threats and risks are not
unique to assessing these issues. They are symptomatic of broader concerns and debates across ‘Five
Eyes’ countries about how one improves analytical capabilities.35

The way ICs build analytical capability is influenced by external and internal factors. As noted
earlier in the discussion on tasking and coordination if political leaders do not demonstrate an
appetite for reading intelligence assessments on specialised or less ‘bread and butter’ issues then the
capability investment in these areas becomes depleted. While the exact headcount of analysts
working on bio-threat and risk issues across all ‘Five Eyes’ countries is unclear, discussions with
people with more intimate knowledge of the ICs work flows suggest that numbers within agencies
can be counted with the fingers on one or two hands.36 It seems that many analysts working on bio-
threat and risk issues are likely working on other accounts, including the broader suite of WMD issues
(e.g. chemical and nuclear). There are pockets of excellence and specialisation for example, in the
United States the FBI WMD Directorate Outreach program and in recent years within the Defense
Intelligence Agency (DIA). However, analytical expertise in emerging bio-threats and risks generally
remains shallow and fragmented within and across agencies. In summary, if decision-makers are not
calling for product on bio-threats and risks, then the internal leadership within ICs are less compelled
to increase the depth and breadth of analytical expertise in these areas. This in turn further reduces
both the skills and repository of knowledge in bio-threat and risk areas. This phenomenon of
intelligence leaders reducing the depth and breadth of analytical coverage in some areas has played
out in different agencies across ‘Five Eyes’ countries. For example, CIA agency leaders have in recent
years focused on getting more analysts to work flexibly across a range of areas to meet the ever

8 P. F. WALSH

increasing demand of current intelligence rather than necessarily cultivate subject matter
expertise.37 Flexibility has some merits, though it can prevent a deeper more sustained investment
in analysts with expertise in one specialised area, who arguably can write better current and strategic
products based on a deeper knowledge of the subject matter.38

Leadership decisions about where to invest in building analytical capability leads us to the main key
enabling activity related capability issue – governance. As discussed earlier, governance is only one of
five key enabling activities (governance, ICT, human resources, legislation and research). In recent
research, I found that there were also capability gaps in the other four key enabling activities, including
in human resources and legislation.39 However, given space limitations the focus here is on governance
issues as they are themost consequential for understanding capability gaps arising in other key enabling
activity areas. For example, poor governance can lead to poor human resource planning as well as
inadequate or not fit for purpose legislation in which to manage more effectively bio-threats and risks.

Governance

Intelligence governance is a term I have used in research on IC capability issues since 2011. From
research resulting in the book Intelligence and Intelligence Analysis, I developed an effective intelligence
framework. The framework showed that sound and adaptable IC capability relied on how well both
core intelligence processes and key enabling activities worked together to produce intelligence out-
comes decision-makers needed.40 In this research governance was defined as ‘attributes and rules
pertaining to strong sustainable leadership, doctrine design, evaluation, and effective coordination,
cooperation and integration of intelligence processes.’41 In simple terms, governance is about effective
leadership and it has an external dimension (‘the political leadership’) and an internal one (heads of IC
agencies and communities). It’s logical that sound governance (in both its external and internal
dimensions) should result in better intelligence capabilities. It is also follows that effective capabilities
allow the creation of a working environment where higher standard products inform decision-making.

Research into the governance capability issues as they relate to bio-threats and risks is ongoing so
the observations here are generalised, incomplete and require further validation across each ‘Five
Eyes’ country. However, based on discussions with some IC personnel and secondary literature there
is evidence that there are both external and internal governance capability issues. These have
a knock-on effect on how bio-threats and risks are coordinated and prioritised across each ‘Five
Eyes’ country. At this stage, the evidence is strongest in the US IC, where both public health
stakeholders and current and former members of IC and the broader security community have
been calling in recent years for better leadership both at the political and IC agency level over
managing bio-threats and risks. The United States Blue Ribbon Panel Report of 2015 is one example
of concerns raised about the lack of consistent leadership of broader health security issues including
the role of the IC.42 In the United States, several executive policy declarations on health security and
bioterrorism have been produced by successive administrations from George W Bush to the current
Trump administrations. However, what seems to bemissing is a clear articulation of how any national
health security strategy will be operationalised generally and how political and IC leadership will
coordinate effectively the limited resources to collect and assess against bio-threats and risks.
Additionally, and less clear, is how do ICs reach out more explicitly and strategically to important
stakeholders (e.g. scientists, public health specialists, clinicians) in order to improve the quality of
collection and analytical efforts? In the final section below, the paper revisits the capability gaps
discussed here to determine if they can be closed. It also provides an assessment of where ‘Five Eyes’
ICs capabilities might be on managing bio-threats and risks in five years’ time.

Outlook

Turning first to improving tasking and coordination processes, in the next five years this will continue to
be a difficult ad hoc process across ‘Five Eyes’ countries. Care needs to be exercised in generalising

INTELLIGENCE AND NATIONAL SECURITY 9

across each ‘Five Eyes’ country. Further detailed research is also required to assess how each ‘Five Eyes’
IC arranges tasking and coordination of bio-threats and risks. However, as noted earlier, research to
date suggest in all five countries while cross IC and broader government coordination has improved,
decisionmakers and therefore the IC leadership do not appear to routinely task on emerging bio-threat
and risk issues. The recent Trump Administrations’ national biodefense strategy and the UK’s Biological
Security Strategy both include rhetoric about the need of greater coordination of IC, public health and
other stakeholders.43 However in each case, there is little detail about how these strategic documents
will be operationalised. In the UK case, at the time of writing (August 2019) the Joint Committee on the
National Security Strategy has commenced an inquiry into the how the strategy is addressing
biosecurity and human health. The launch of the inquiry does suggest that further work is required
to fully implement it across the UK government. In particular, the US and UK policy documents, do not
identify a leadership position within the ICs, who could be responsible for ensuring there is regular
tasking and effective coordination of efforts in the collection and assessment of bio-threats and risks. As
discussed earlier, the core intelligence process of tasking and coordination is closely linked to the key
enabling activity of governance. Governance is crucially about effective political and internal leadership
of ICs. Hence tasking and coordination on bio-threats and risks is intricately linked to whether
improvements can be made in governance over the next five years.

On the other two core intelligence processes (collection and analysis) and leaving aside the
stultifying effect of a relatively low engagement in bio-threats and risks by the political leadership of
‘Five Eyes’ countries–there are opportunities to build on existing collection platforms in ways that
would improve information feeds on these issues. It may not be that ICs need to build additional
expensive collection platforms just for bio-threats and risks. In some cases, using existing covert and
open source intelligence that are already being applied against comparatively more conventional
threats and risks (terrorism and organised crime) will likely provide opportunities to collect inciden-
tally against bio-threats and risks.

Governance

Whether tasking and coordination can be improved depends first on whether a renewed interest in
bio-threats and risks can be garnered from the political leadership in ‘Five Eyes’ countries in the
absence of an actual bio-attack. In the United States, the Trump Administration has developed an
adversarial and mistrusting attitude to the US IC – making it difficult for IC leaders to discern which
intelligence priorities the President is interested on a day to day basis let alone emerging bio-threat
and risk issues. Additionally, effective tasking and coordination is further compounded by President
Trump’s focus mainly on border security and political matters including the US Congress impeach-
ment inquiry and earlier the Mueller special investigation into whether he and members of his
campaign team colluded with Russia in ways that influenced the outcome of the 2016 presidential
election. Combined these factors demonstrate a lack of a sustained political commitment and
interest in improving tasking and coordination, collection and assessments on emerging bio-
threats and risks.

Similarly in the UK, at the time of writing the government continues to be pre-occupied with
securing a Brexit deal from the EU, and it remains to be seen how cabinet ministers will focus on
implementing both the Biological Security Strategy and how the strategy might improve the way
the UK IC tasks, coordinates, collects and assesses emerging bio-threats and risks. Australia,
Canada and New Zealand all have the necessary IC and public health bureaucratic institutions
in place to theoretically respond to emerging bio-threats and risks. However, there is no evidence
that these governments have developed national health security strategic plans, which clearly
articulate how their ICs will improve their understanding of emerging bio-threats; or better
integrate their resources with important stakeholders such as scientists and the public health
sector.

10 P. F. WALSH

At the time of writing, there are major reform changes underway in the Australian Intelligence
Community (AIC) – including the establishment in 2018 of a new Office of National Intelligence to
better coordinate the Community. Other reforms include the establishment of a capability fund to
help the AIC identify where future investment needs to take place.44 Though given the amount of
other work ONI has to address across the Australian intelligence enterprise, it is unlikely the current
reform agenda in the near term will produce a national health security strategic plan that includes
reflection on how the AIC can play a role in understanding emerging bio-threats and risks.

Further, given the short electoral cycles in ‘Five Eyes’ countries and the perceived low probability
and high impact nature of bio-threats and risks by many policy makers – it seems unlikely political
leaders of each ‘Five Eyes’ country will address in any significant way current governance issues
relating to emerging bio-threats and risks. But the rapidly changing nature of all threats and risks
particularly those technologically enabled ones such as cyber, underscore the need for stronger
governance that can identify and remedy IC capability gaps in understanding bio-threats and risks.
As a start, better governance at the political level could be facilitated by formalised high-level
coordination. For example, the establishment of a Health Security Coordination Council led pre-
ferably by head of government (or the very least a senior cabinet minister) would provide a more
coherent ‘whole of government’ approach to tasking and coordination of bio-threats and risks as
well as identifying other capability gaps discussed in the paper. Current US and UK strategic plans
outlined earlier seem to place senior bureaucrats largely in charge of national level biosecurity,
biodefense committees. A senior cabinet minister (from either a health or security portfolio) is a more
appropriate choice to chair such a council. The council should also contain in addition to heads of IC,
other senior stakeholders including public and animal health specialists, and scientific advisors.
A broad and diverse council membership is critical to ensure national health security strategies
articulate a whole of government (including ICs) approach. The next ideal step in improving
governance arrangements would be for each stakeholder to develop operational plans to implement
government tasking priorities as well as ensuring effective coordination of resources.

For each ‘Five Eyes’ country a senior sub-cabinet level national health security intelligence officer
should also be established. This appointee would have authority to identify and implement tasking
and coordination, collection and analytical priorities across the entire IC. The national health security
intelligence officer would liaise with other important stakeholders that are part of the health security
coordination council; including public/animal health, scientists and their counter parts in other ‘Five
Eyes’ countries to gain a national and international understanding of emerging bio-threats and risk
as well as identifying IC capability gaps.

Closing collection capability gaps

A national health security intelligence officer sitting across the entire IC enterprise should be able to
implement coherent and coordinated national collection plans for bio-threats and risks that help
both collection and assessment agencies identify what role they can play in overall collection efforts.
A national health security intelligence officer can consider for example, how traditional collection
platforms (SIGINT, HUMINT, Geospatial Intelligence) are best applied to retrieve information about
both current and emerging bio-threats. Threat and risk evolution will also be an important con-
sideration in what collection capabilities need to be deployed. In other words, at what develop-
mental stage is the threat? Can it be prevented, disrupted or only treated after the event? It is quite
possible as noted earlier, that traditional collection platforms might be initially applied against more
‘here and now’ threats such as terrorism or organised crime – yet may also reveal in some
circumstances an interest by these threat actors or their associates in bio-threats and risks. This in
turn would allow a more focused application of other specialised, scientific collection tools such as
microbial forensics.

Arguably though with many bio-threats and risks, there are likely to be an even larger volume of
relevant information accessible to the IC from non-security stakeholders on the prevention,

INTELLIGENCE AND NATIONAL SECURITY 11

disruption and treatment of bio-threats and risks. While ‘Five Eyes’ ICs have in the past reached out to
some stakeholders, a more strategic and explicit approach to building trusted external expert
networks would improve collection efforts, particularly in areas such as dual use research of concern
and synthetic biology. The potential lists of relevant stakeholders is almost endless. They can be
found at the multi-lateral, bilateral, national, regional and local levels.45 At a multi-lateral level,
historically important security measures such as the Biological and Toxin Weapons Convention
(BTWC) will continue to provide ICs with information, albeit not always reliable about states’
adherence to the Convention. Other recent multilateral biosafety and biosecurity initiatives such
as the Global Health Security Agenda established by the Obama Administration could provide
opportunities for ‘Five Eyes’ ICs to increase awareness of potential bio-threats and risks in addition
of course to their public health capacity-building effects.46

In each ‘Five Eyes’ country, albeit some with more capacity (e.g. US and UK) defence departments
or their allied defence research divisions there are biodefence research capabilities which the ICs
could tap into more regularly. In the case of the United States, other government research bodies
such as the Intelligence Advanced Research Projects Activity (IARPA) also sponsor biodefense
research that is directly relevant to how ICs may participate in the future in the identification and
prevention of weaponised dual use research and synthetic biology. For example, in July 2017, IARPA
commissioned the Project Felix program to fund research that can detect signals of bio-engineering
including types of changes, location and possibly in the future where changes were made. Such work
could be used in cases where suspicious circumstances suggest the malicious exploitation of bio-
engineered material is occurring.47 Leaving aside what the defence, security and intelligence
research groups offer the IC in this area, it’s clear that the medical community (epidemiology and
public health) are also naturally indispensable partners for the ICs. Medical, public health and
epidemiological knowledge provides the ICs with a common understanding of how to identify
natural and intentional disease outbreaks and in some cases can inform attribution about what
threat actors may be responsible. Finally, first responders have critical knowledge about the physical
environment(s), where an attack occurs as well as forensic evidence, which can help inform tactical
and operational intelligence collection and analysis.

Analysis

In any intelligence agency, an effective operation of all core intelligence processes requires an almost
symbiotic relationship between collection and analysis. Uncoordinated and insufficient strategic and
operational collection planning will reduce the ability of analysts to improve the reliability and
validity of their products. There are no ‘off the shelf’ solutions to current analytical capability gaps
discussed earlier. Evaluating whether the analytical workforce is ‘fit for purpose’ as far as assessing
bio-threats and risks is really a sub-set of a bigger issue about whether ‘Five Eyes’ ICs have the right
mix of subject matter expert vs generalist analysts – against a whole range of current and emerging
threats. Significant investment has gone into training and education of analysts across ‘Five Eyes’
countries in the military, national security and to lesser degree the law enforcement community.48

But debates continue within ICs and amongst teachers and scholars what skills, knowledge and
competencies entry level analysts need to deal with the fast paced changes in the security environ-
ment. Less consideration is currently given to how to deploy subject matter experts in specialised
areas such as bio-threats and risks. Do ‘Five Eyes’ ICs try to develop specialised expertise in this
subject internally or should this work be out-sourced to trusted, security cleared outsiders who
might be scientists?

I argue that it shouldn’t be an either/or decision given that all ‘Five Eyes’ ICs need to maintain
corporate repositories of knowledge in specialised areas – yet at the same time it would be
impossible for those few individuals responsible for interpreting bio-threats and risks across the
entire IC to be experts in all bio-threat matters. Given resources are limited, another aspect of
workforce analytical training of staff on bio-threat and risk issues is that heads of agencies and ICs

12 P. F. WALSH

need to also think carefully about what role subject matter experts may play. Logically some
should be deployed in prevention roles that can provide strategic early warning of potential bio-
threat and risk trajectories. Others would need to focus on disruption of evolving bio-threats and
risk in operational settings; whilst others would be useful in assessing the treatment of threats and
risks.

Further evidence is required, but IC leaders currently do not appear to be planning in any
systematic way the future bio-threat and risk analytical workforce. As part of work force planning,
it is unclear whether IC leaders are considering in any strategic way what analytical capability gaps
are best met by external stakeholders (scientists, clinicians, and public health officials)–and how to
integrate more seamlessly this knowledge into the closed working environment within ICs. Finally,
with respect to sub-optimal analytical capabilities, further reflection by IC leaders needs to be given
on how potentially a diverse and voluminous amount of information collected across health security
sector (clinicians, epidemiologists, scientists, military, national security, law enforcement, animal and
agricultural health) can best be interrogated rapidly by analysts. Again the ability to quickly makes
sense of large data sets and intelligence is obviously a problem writ large for ICs not just an issue to
be resolved in the bio-threat and risk context.

In summary, this article argues it is unlikely that each ‘Five Eyes’ country will improve dramatically
their IC capabilities for managing bio-threats and risks in the next five years (2020–25). Barring
a catastrophic bio-attack by a terrorist group or other health security crisis resulting in high mortality
rates, bio-threats and risks will continue to be seen as low probability-high impact threats for political
decision-makers. This translates within the ICs as at best a watching brief of bio-threats and risks and
at worse them being largely ignored. At this time, bio-threats and risks only get ad-hoc attention by
the ‘Five Eyes’ ICs. For example, ICs may focus periodically on them as part of broader WMD threat
assessments ahead of hosting a major international event.

In addition to low levels of political tasking and coordination, systematic and proactive
approaches to managing bio-threats and risks at the IC level are not likely without stronger IC
governance by its leaders. This includes a national health security intelligence officer, who can
champion the threat and risk area and help agencies close capability gaps. In some ‘Five Eyes’
countries there has been some capability improvements since 9/11, however, based on available
evidence, I assess no substantial move towards a greater strategic approach to health security
intelligence across ‘the Five Eyes’ countries during the next five years. There is no available public
knowledge that there are any impending substantive bio-threats and risks, particularly emanating
from dual use research and synthetic biology. Nonetheless the rise in the cyber threat trajectory and
the struggle by ICs to understand it provides a good lesson that building capability takes time. It is
now time to invest in capability to better manage potential and emerging bio-threats and risks.
Hopefully the COVID-19 pandemic might provide a catalyst to build the kinds of capabilities in ICs
discussed throughout the article.

Notes

1. Aldis, “Health Security as a Public Health Concept,” 370.
2. Bernard, “Health and National Security,” 157.
3. Walsh, Intelligence Biosecurity and Bioterrorism.
4. The Human Security Centre, The Human Security Centre.
5. See for example, Elbe, “Pandemic Security,” 163–173.
6. Heymann, “Global Health Security: the Wider Lessons from the West WHO.” “Ebola Virus Disease in West Africa –

The First Nine Months of the Epidemic and Forward Projections,” 1481–1495; “Global Health Security: the Wider
Lessons from the West African Ebola Virus Disease Epidemic,” 1884–1901; Marston, “Ebola Response Impact on
Public Health Programs, West Africa 2014–2017”; WHO, “Ebola Virus Disease in West Africa – The First Nine
Months of the Epidemic and Forward Projections,” 1481–1495.

7. Soucheray, “With New Cases, Katwa Remains Epicenter of Ebola Outbreak.”
8. Walsh, Intelligence and Intelligence Analysis, 29–32.

INTELLIGENCE AND NATIONAL SECURITY 13

9. Alibek, Biohazard: The Chilling True Story of the Largest Covert Biological Weapons Program in the World; Balmer,
Britain and Biological Warfare. Expert Advice and Science Policy; Christopher, et al., “Biological Warfare: A Historical
Perspective,” 412–417; Geissler, & Ellis van Courtland Moon, (Eds.). Biological and Toxin Weapons: Research,
Development and Use from the Middle Ages to 1945; Koblentz, Living Weapons; and Walsh, Intelligence, Biosecurity
and Bioterrorism.

10. Walsh, Intelligence, Biosecurity and Bioterrorism, 30–31.
11. Broad and Shane, “Scientist’s Analysis Disputes FBI Closing of Anthrax Case.”
12. In BSL-3 to 4 rated labs, scientists work on pathogens that can cause serious or potentially lethal disease.

Generally, the most lethal agents, where there is no vaccine or an unknown risk of transmission are worked on in
BSL-4 labs.

13. Lizotte, “Research Halted at USAMRID Over Biosecurity Issues,” CDC, Report on the Potential Exposure to Anthrax;
CDC, 90 Day Internal Review of the Division of Select Agents and Toxins; Dennis Brady and Lena Sun, ‘FDA Found
More than Smallpox Vials in Storage Room.’ Washington Post. 16 July 2014, https://www.washingtonpost.com/
national/health-science/fda-found-more-than-smallpox-vials-in-storage-room/2014/07/16/850d4b12-0d22-
11e4-8341-b8072b1e7348_story.html?utm_term=.978241b9d1f8.

14. Walsh, “Managing Intelligence and Responding to Emerging Threats,” 837–57; Walsh, “Managing Emerging
Health Security Threats Since 9/11: The Role of Intelligence,” 341–67.

15. Koblentz and Mazanec, “Viral Warfare: The Security Implications of Cyber and Biological Weapons,” 418–34; and
Murch, “Emerging New Discipline to Help Safeguard the Bioeconomy.”

16. For a brief discussion on some of the bilateral and multi-lateral biosafety programs that ‘Five Eyes’ countries
have been active in see, Walsh, Intelligence, Biosecurity and Bioterrorism, 179–231.

17. Ibid., 179–231.
18. Tucker, Innovation, Dual Use and Security; Suk et al., “Dual Use Research and Technological Diffusion.

Reconsidering the Bioterrorism Threat Spectrum,” 1–3; Gerstein, Bioterror in the 21st Century: Emerging Threats
in a New Global Environment; National Academy of Sciences, Human Genome Editing. Science Ethics and
Governance; Arnason, “Synthetic Biology between Self-Regulation and Public Discourse,” 246–56.

19. Chyba, “Biotechnology and the Challenge to Arms Control,” 11–17; Carlson, “The Pace and Proliferation of
Biological Technologies,” 203–14; Petro and Carus, “Biological Threat Characterisation Research,” 295–308.

20. Walsh, Intelligence, Biosecurity and Bioterrorism, 44.
21. Kathleen Vogel’s work on the non-technical aspects of bio-threats provide a good background to all the non-

technical variables that should be considered in assessing bio-threats and risks. See, Vogel, “Biodefense,” 227–55;
“Intelligent Assessment: Putting Emerging Biotechnology Threats in Context,” 45–54; “Necessary Interventions.
Expertise and Experiments in Bioweapons Intelligence Assessments,” 61–88; and, Phantom Menace or Looming
Danger?.

22. Walsh, Intelligence, Biosecurity and Bioterrorism, 41–51.
23. Kolata, “Chinese Scientist Claims to Use Crispr to Make First Edited Babies”.
24. In the US, easily over 2 million people are employed with over 73,000 businesses working across range of

biosciences (medicine, agriculture, pharmaceuticals, research). Similarly in Australia, around 48,000 Australians
are employed in the biotechnology sector with the sector estimated to obtain a 4.4% annual growth reaching
8.67 billion AUD in revenues by 2021. See, Battelle. Battelle/Bio State Bioscience, Jobs, Investments and Innovation;
Ausbiotech, Australia’s Biotechnology Organisation (website), 2018. https://www.ausbiotech.org/biotechnol
ogy-industry/fast-facts.

25. Walsh, Intelligence, Biosecurity and Bioterrorism, 51.
26. Ibid., 41.
27. Willingham, “A Fresh Threat: Will CAS9 Lead to CRISPR Bioweapons?”; National Academy of Sciences. Human

Genome Editing. Science Ethics and Governance; Revill, “Could Gene Editing Tools Such as CRISPR be Used as
a Biological Weapon.”

28. Willingham, “A Fresh Threat”; Clapper, Statement for the Record. Worldwide Threat Assessment of the US
Intelligence Community.

29. A more detailed discussion of these factors and how they relate to theorising about effective intelligence
frameworks can be found in Walsh, Intelligence and Intelligence Analysis, 131–147; Walsh, “Building Better
Intelligence Frameworks Through Effective Governance,” 123–42.

30. Ibid.
31. Walsh, Intelligence, Biosecurity and Bioterrorism, 59–89.
32. Ibid., 89–121.
33. Ibid.
34. Walsh and “Rethinking “Five Eyes” Security Intelligence Collection Policies and Practice Post Snowden,” 345–68;

Chertoff, “A public policy perspective of the Dark Web,” 26–38; and Chen, Bioterrorism and Knowledge Mapping
Dark Web Exploring and Data Mining the Dark Side of the Web, 335–67.

35. Walsh, & Ratcliffe, “Strategic Criminal Intelligence Education: A Collaborative Approach,” 152–66. Walsh,
“Teaching intelligence in the twenty-first century: towards an evidence-based approach for curriculum design,”

14 P. F. WALSH

https://www.washingtonpost.com/national/health-science/fda-found-more-than-smallpox-vials-in-storage-room/2014/07/16/850d4b12-0d22-11e4-8341-b8072b1e7348_story.html?utm_term=.978241b9d1f8

https://www.ausbiotech.org/biotechnology-industry/fast-facts

1005–1021; Harrison, & Et al., “Tradecraft to Standards – Moving Criminal Intelligence Practice to a Profession
through the Development of Criminal Intelligence Training and Development Continuum,” 1–13.

36. Walsh, Intelligence, Biosecurity and Bioterrorism, 127–128.
37. Gentry and Gordon, Strategic Warning Intelligence, 223.
38. Ibid., 218.
39. Walsh, Intelligence, Biosecurity and Bioterrorism.
40. Walsh, Intelligence and Intelligence Analysis, 31–152.
41. Ibid., 149.
42. Blue Ribbon Study Panel, Blue Ribbon Study Panel on Biodefense. A National Blueprint for Biodefense: Leadership

and Major Reform Needed to Optimise Efforts; Blue Ribbon Study Panel, Biodefense Indicators One Year Later.
Events Outpacing Federal Efforts to Defend the Nation.

43. White House, National Biodefense Strategy; HMG. UK Biological Security Strategy.
44. For a discussion of the main aspects of the reform agenda currently underway in the AIC, see my ISA Paper:

“Transforming the Australian Intelligence Community: Mapping Change, Impact and Governance Challenges,”
paper given at the 60th International Studies Association Conference, 27 August 2019.

45. For a detailed discussion of what non-security stakeholders can bring to the IC see: Walsh, Intelligence, Biosecurity
and Bioterrorism, 179–231.

46. Ibid., 192–3.
47. Ibid., 183.
48. Walsh, “Teaching intelligence in the twenty-first century,” 1005–21.

Disclosure statement

No potential conflict of interest was reported by the author.

Notes on contributor

Patrick F. Walsh, PhD, is a former intelligence analyst, and has worked in Australia’s national security and law
enforcement environments. He is an associate professor in Intelligence and Security Studies, Charles Sturt University,
Australia. He is also a consultant to government agencies on intelligence reform and capability issues. His research
grants and publications focus on a range of areas related to intelligence capability; including but not limited to:
governance, leadership, intelligence and ethics, biosecurity and cyber. His last book, Intelligence, Biosecurity and
Bioterrorism (UK: Palgrave Macmillan, 2018), examined the challenges for ‘Five Eyes’ intelligence communities in
understanding and managing emerging bio-threats and risks.

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INTELLIGENCE AND NATIONAL SECURITY 17

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Abstract

Introduction
Health security intelligence
Stolen biological agents
Dual use research and synthetic biology

Capability gaps
Core intelligence processes
Governance
Outlook
Governance
Closing collection capability gaps
Analysis
Notes
Disclosure statement
Notes on contributor
Bibliography

royalsocietypublishing.org/journal/rstb

Review
Cite this article: Polonsky JA et al.

Outbreak analytics: a developing data science

for informing the response to emerging

pathogens. Phil. Trans. R. Soc. B

:
201

027

http://dx.doi.org/

.1098/rstb.2018.0276

Accepted: 4 December 2018

One contribution of 16 to a theme issue

‘Modelling infectious disease outbreaks in

humans, animals and plants: epidemic

forecasting and control’.

Subject Areas:
health and disease and epidemiology

Keywords:
epidemics, infectious, methods, tools,

pipeline, software

Author for correspondence:
Thibaut Jombart

e-mail: thibautjombart@gmail.com

†These authors contributed equally to the

study.

& 2019 The Authors. Published by the Royal Society under the terms of the Creative Commons Attribution
License http://creativecommons.org/licenses/by/4.0/, which permits unrestricted use, provided the original
author and source are credited.

Outbreak analytics: a developing data
science for informing the response
to emerging pathogens

Jonathan A. Polonsky1,3,†, Amrish Baidjoe4,†, Zhian N. Kamvar4, Anne Cori4,
Kara Durski2, W. John Edmunds

,6, Rosalind M. Eggo5,6, Sebastian Funk5,6,
Laurent Kaiser3, Patrick Keating5,8, Olivier le Polain de Waroux5,8,9,
Michael Marks7, Paula Moraga10, Oliver Morgan1, Pierre Nouvellet4,

,
Ruwan Ratnayake5,6, Chrissy H. Roberts7, Jimmy Whitworth5,8

and Thibaut Jombart4,5,8

1Department of Health Emergency Information and Risk Assessment, and 2Department of Infectious Hazard
Management, World Health Organization, Avenue Appia 20, 1211 Geneva, Switzerland
3Faculty of Medicine, University of Geneva, 1 rue Michel-Servet, 1211 Geneva, Switzerland
4Department of Infectious Disease Epidemiology, School of Public Health, MRC Centre for Global Infectious Disease
Analysis, Imperial College London, Medical School Building, St Mary’s Campus, Norfolk Place London W2 1PG, UK
5Department of Infectious Disease Epidemiology, 6Centre for Mathematical Modelling of Infectious Diseases, and
7Clinical Research Department, Faculty of Infectious and Tropical Diseases, London School of Hygiene and
Tropical Medicine, Keppel St, London WC1E 7HT, UK
8UK Public Health Rapid Support Team, London School of Hygiene and Tropical Medicine, Keppel St, London
WC1E 7HT, UK
9Public Health England, Wellington House, 133 – 155 Waterloo Road, London SE1 8UG, UK
10Centre for Health Informatics, Computing and Statistics (CHICAS), Lancaster Medical School,
Lancaster University, Lancaster LA1 4YW, UK
11School of Life Sciences, University of Sussex, Sussex House, Brighton BN1 9RH, UK

JAP, 0000-0002-8634-4255; AB, 0000-0001-5295-5085; ZNK, 0000-0003-1458-7108;
AC, 0000-0002-8443-9162; SF, 0000-0002-2842-3406; OM, 0000-0002-9543-3778;
PN, 0000-0002-6094-5722; TJ, 0000-0003-2226-8692

Despite continued efforts to improve health systems worldwide, emerging

pathogen epidemics remain a major public health concern. Effective response

to such outbreaks relies on timely intervention, ideally informed by all available

sources of data. The collection, visualization and analysis of outbreak data are

becoming increasingly complex, owing to the diversity in types of data, questions

and available methods to address them. Recent advances have led to the rise of

outbreak analytics, an emerging data science focused on the technological and
methodological aspects of the outbreak data pipeline, from collection to analysis,

modelling and reporting to inform outbreak response. In this article, we assess

the current state of the field. After laying out the context of outbreak response,

we critically review the most common analytics components, their inter-

dependencies, data requirements and the type of information they can provide

to inform operations in real time. We discuss some challenges and opportunities

and conclude on the potential role of outbreak analytics for improving our

understanding of, and response to outbreaks of emerging pathogens.

This article is part of the theme issue ‘Modelling infectious disease outbreaks

in humans, animals and plants: epidemic forecasting and control‘. This theme

issue is linked with the earlier issue ‘Modelling infectious disease outbreaks in

humans, animals and plants: approaches and important themes’.

1. Introduction
Emerging infectious diseases are a constant threat to public health worldwide.

In the past decade, several major outbreaks, such as the 2009 influenza pandemic [1],

http://crossmark.crossref.org/dialog/?doi=10.1098/rstb.2018.0276&domain=pdf&date_stamp=2019-05-20

http://dx.doi.org/10.1098/rstb/374/1776

mailto:thibautjombart@gmail.com

http://orcid.org/

http://orcid.org/0000-0002-8634-4255

http://orcid.org/0000-0001-5295-5085

http://orcid.org/0000-0003-1458-7108

http://orcid.org/0000-0002-8443-9162

http://orcid.org/0000-0002-2842-3406

http://orcid.org/0000-0002-9543-3778

http://orcid.org/0000-0002-6094-5722

http://orcid.org/0000-0003-2226-8692

http://creativecommons.org/licenses/by/4.0/

Figure 1. Successive phases of an outbreak response. The histogram along the top represents reported ( yellow) and unreported ( grey) incidence.

royalsocietypublishing.org/journal/rstb
Phil.Trans.R.Soc.B

374:20180276

the Middle-East Respiratory Syndrome coronavirus (MERS-

CoV) [2 – 4], the emergence of Zika [5,6] and the West African

Ebola virus disease (EVD) outbreak [7,8], have been potent

reminders of the need for robust surveillance systems and

timely responses to nascent epidemics [9]. The West African

EVD outbreak, by far the largest such epidemic in recorded his-

tory, in particular, had a strong impact on global health security

and public health policy and practice [7,8,10]. It highlighted the

difficulties of maintaining situational awareness in the absence

of standards for surveillance, data collection and analysis, as

well as the challenges of mounting and sustaining a large-scale

international response [7,8,11,12]. Despite the lessons learnt

[9,13,14], the recent (2018) EVD outbreaks in Democratic Repub-

lic of the Congo [15,16] are a stark reminder that a large number

of these challenges remain.

An important feature of the modern response to epidemics

is the increasing focus on exploiting all available data to inform

the response in real time and allow evidence-based decision

making [3,4,7,8,13,17]. Using data for improving situational

awareness is complex, involving a range of inter-connected

tasks and skills from point-of-care data collection to the gener-

ation of informative situational reports (sitreps). The science

underpinning these data pipelines involves a wide range of

approaches, including database design and mobile technology

[18,19], frequentist statistics and maximum-likelihood esti-

mation [7], interactive data visualization [20,21], geostatistics

[22 – 24], graph theory [20,25,26], Bayesian statistics [8,27,28],

mathematical modelling [29 – 31], genetic analyses [32 – 36]

and evidence synthesis approaches [37]. This accretion of

heterogeneous disciplines, which may be best summarized as

‘outbreak analytics’, forms an emerging domain of data

science: an ‘interdisciplinary field that uses scientific methods,

processes, algorithms and systems to extract knowledge and

insights from data in various forms’ [38], dedicated to inform-

ing outbreak response. Outbreak analytics sits at the crossroads
of public health planning, field epidemiology, methodological

development and information technologies, opening up excit-

ing opportunities for specialists in these fields to work together

to meet the needs for an epidemic response.

In this article, we outline this developing research field and

review the current state of outbreak analytics. In particular, we

focus on how different analysis components interact within

functional workflows, and how each component can be used

to inform different stages of an outbreak response. We discuss

key challenges and opportunities associated with the deploy-

ment of efficient, reliable and informative data analysis

pipelines and their potential impact.

2. The outbreak response context
(a) The different phases of an outbreak response
The focus of the public health response shifts during the

course of an epidemic or outbreak, and so do the analytics.

We identify four main stages (figure 1). The detection stage
starts with the first case and ends with the first intervention

activities (e.g. patient isolation, contact tracing, vaccination)

and involves surveillance systems and mostly qualitative

risk assessments. Next, the early response is the initial part
of the intervention during which the first simple analytics

can take place, essentially centred around estimating trans-

missibility. This blends into the intervention stage, where
more complex analytics may be involved to inform plann-

ing (e.g. vaccination strategies), which ends once the last

reported case has recovered or died. The post-intervention
stage is for lessons to be learned, for improving prepared-

ness for the next epidemic and for training and capacity

building [39].

(b) Questions during and after the intervention
During the early response, efforts are dedicated to estimating

the likely impact of the outbreak and anticipating the nature,

scale and timing of resources needed [7,13,15]. Theoretically,

different factors including not only the total number of cases

and fatalities but also the morbidity and overall impact on qual-

ity of life, as well as societal and economic impact, should

ideally be taken into account when attempting to predict

disease burden [40 – 43]. Generally, as the demographic and

morbidity data needed by composite measures of health-

adjusted life years [40] are lacking in outbreak response

contexts, efforts tend to focus on other proxies of impact: asses-

sing transmissibility, predicting future case incidence and

associated mortality and investigating risk factors [1,3,7,15].

Analytical needs to diversify as the intervention progresses.

While investigations of transmissibility, mortality and risk

factors remain key throughout [8], new questions may arise to

inform the implementation of control and mitigation measures.

These may focus on predicting the impact of potential measures

including testing (e.g. ‘Could a rapid test help reduce inci-

dence?’ [29]), vaccine development (e.g. ‘Could a candidate

vaccine be evaluated in this outbreak?’ [44,45]), vaccination

campaigns (e.g. ‘Which is the optimal vaccination strategy?’

[46,47]) or travel restrictions (e.g. ‘Should international travel

be restricted?’ [48]), or on estimating the impact of current

measures such as improvements in access to care (e.g. ‘Has the

royalsocietypublishing.org/journal/rstb
Phil.Trans.R.Soc.B
374:20180276
3
delay between symptom onset and hospitalization been
reduced?’ [14,15]). As case incidence reduces, statistical model-

ling can also be useful for assessing or predicting the end of an

outbreak [49 – 51]. At the field operational level, outbreak

response analytics may be best focused on informing and moni-

toring core surveillance activities and performance indicators,

such as contact tracing [11], through the use of tools for contact

data visualization [52], mapping [53,54] and on analysis pipe-

lines integrating mobile data collection tools [18,19,55,56]

with automated reporting systems [57 – 59]. Finally, the post-

intervention phase lends itself to retrospective studies, which

can assess further the impact of interventions [60], tease apart

finer processes driving the epidemic dynamics such as contact

patterns [12,61], study risk factors [54,62], identify avenues for

fortifying surveillance [13,36,63] and evaluate, improve and

develop modelling techniques [28,64,65].

(c) What are outbreak data?
The term ‘outbreak data’ encompasses different types of
information, of which we first distinguish ‘case data’ from ‘back-
ground data’. Case data include the description of reported cases
gathered in linelists, i.e. flat files where each row is a case and
each column a recorded variable (e.g. dates of onset and admis-

sion, gender, age, location), thereby fulfilling the definition of

‘tidy data’ in the data science community [66]. Case data also

include exposure and contact tracing data, either stored within

a linelist or in separate files, pathogen whole genome sequencing

(WGS) and data pertaining to outbreak investigations (e.g. case –

control and cohort study data). Background data document the
underlying characteristics of the affected populations. This

includes demographic information (e.g. maps of population den-

sities, age stratification, mixing patterns), movement data (e.g.

borders, traveller flows, migration), health infrastructure

(e.g. healthcare facilities, drug stockpiles) and epidemiological

data themselves (e.g. levels of pre-existing immunity). A final

type of data we consider here is ‘intervention data’, which refers
to information on decisions made and efforts deployed as part

of the intervention, such as vaccination coverage, the extent of

active case finding or potential changes in the epidemiologi-

cal case definition. An in-depth discussion of data needs in

outbreaks can be found in Cori et al. [13].

3. Outbreak analytics
(a) An overview of the outbreak analytics toolbox
We use the term ‘outbreak analytics’ to refer to the variety of
tools and methods used to collect, curate, visualize, analyse,

model and report on outbreak data. These tools and their

inter-dependencies are summarized in an exemplary workflow

represented in figure 2, derived from analyses pipelines used

during recent epidemics of pandemic influenza [1], MERS-

CoV [4] and EVD [7,8,17]. Note that workflows may vary

substantially in other epidemic contexts. For instance, analyses

of food-borne outbreaks may focus on traceback data [67 – 69],

while vector-borne disease analysis may focus heavily on

modelling the vector’s ecological niche [70,71].

(b) Tools for the collection of epidemiological data
Tools for data capture have become a focus of much discussion

in recent years as those involved in outbreak response seek

to make use of important technological advances including

mobile data collection, cloud computing and built-in automated

data analyses and reporting. In resource-limited settings, in par-

ticular, epidemiological data are still often collected with pen

and paper, the advantages of which are familiarity, simplicity,

low cost and reliability where access to Internet and power

sources may be limited. However, there are some downsides

to using paper as a data management tool, becoming increas-

ingly important with larger outbreaks, as any system for

the printing and distribution, collection and storage and digitiz-

ation of forms becomes overwhelmed. Additionally, two-stage

processes involving transcription of data from forms typically

introduces additional data entry errors [72 – 75] and substantial

delays from data capture to analysis [72].

Electronic data collection (EDC) is becoming increasingly

popular [18,19,55,56]. These tools make use of widely avail-

able, low-cost hardware (e.g. smartphones and tablets) [76]

that can, when appropriately configured, consume little

power and collect data offline, making them suitable for use

in resource-poor settings. Some of those may be part of existing

surveillance systems or be deployed instead for specific

enhanced surveillance and response activities during an out-

break. EDC platforms can also enhance data quality through

the use of restriction rules and logical checks, and enforce

reporting (even when there are zero cases) and entry of essen-

tial variables [72,76]. EDC can decrease the delay between data

collection, centralization and analysis, which is critical for

data-driven responses. Time can be saved through ‘form

logic’ (e.g. automatically skipping sections of a survey not

relevant to a participant), while real-time, automated centrali-

zation, data analysis and reporting can be directly built into

the platform. In addition, mobile-based EDC enables the collec-

tion of other types of data including GPS coordinates,

photographs, barcode (useful to link case data and clinical

specimens) and even aiding diagnostics by directly interfacing

with point-of-care diagnostic devices [77 – 79].

Maintaining confidentiality and privacy is a legitimate con-

cern whenever data concerning human subjects are collected.

While EDC systems provide opportunities for unauthorized

interception and access to such information, many systems

support end-to-end encryption during data transfer [80],

although few provide additional security through encryption

at the level of data entry.

data analysis is exploration, where visualization plays a

central role, completed with informative summary statistics

[81,82]. The first type of graphics needed for rapid assessment

of ongoing dynamics is the epidemic curve (epicurve), which

shows case incidence time series as a histogram of new onset

dates for a given time interval [83 – 85]. Cumulative case

counts, sometimes used in the absence of a raw linelist, are

best avoided in epicurves, as they tend to obscure ongoing

dynamics and create statistical dependencies in data points

that will result in biases and lead to under-estimating

uncertainty in downstream modelling [86].

Maps have been at the core of infectious disease epide-

miology from a very early stage [87]. Nowadays, they are

typically used to visualize the distribution of disease [88], for

representing the ‘ecological niche’ of infectious diseases at

large scales [23,24,89] and for assessing the spatial dynamics

of an outbreak and strategizing interventions [7,8]. Providers

of free and crowd-sourced [90] geographical data like the

Figure 2. Example of outbreak analytics workflow. This schematic represents eight general analyses that can be performed from outbreak data. Outputs containing
actionable information for the operations are represented as hexagons. Data needed for each analysis are represented as a different colour in the center, using plain
and light shading for mandatory and optional data, respectively. (Online version in colour.)

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374:20180276
4

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September 2018)), healthsites.io (see https://healthsites.io/

(accessed 26 September 2018)) and the Radiant Earth Foun-

dation (Radiant Earth Foundation – Earth imagery for

impact; see https://www.radiant.earth (accessed 18 November

2018)) provide layers of spatial data that include information on

the location of households and health facilities, among other

determinants. Several tools including SaTScan and ClusterSeer

are routinely applied to surveillance system data for automated

outbreak detection and the evaluation of clustering of disease

by time and space [91]. Other examples of freely available map-

ping tools that can help track the spread of infectious diseases

include the Spatial Epidemiology of Viral Haemorrhagic

Fevers (VHF) disease visualization (see http://www.health-

data.org/datavisualization/spatial-epidemiology-viralhemor-

rhagic-fevers; accessed 19 September 2018), which maps risks of

emergence and spread of VHF diseases, Nextstrain [92] and

Microreact [93], which focus on mapping pathogen evolution

and epidemic spread, and HealthMap [94], which provides

resources for the rapid detection of outbreaks. Geographical

locations of reported cases can also be useful for informing

more complex modelling approaches [95].

https://www.hotosm.org/

https://www.missingmaps.org/

https://healthsites.io/

https://www.radiant.earth

http://www.healthdata.org/datavisualization/spatial-epidemiology-viralhemorrhagic-fevers

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Phil.Trans.R.Soc.B
374:20180276
5
In epidemics driven by person-to-person transmission, a
last essential source of data is contact data [20], which includes

data on case exposure [12] as well as contact tracing, where
appropriate [11,63]. Exposure data document transmission

pairs, which can yield precious insights into ‘paired delays’

(figure 2) including the serial interval (time between onsets

of a case and their infector) or the generation time (time

between the dates of infections of a case and their infector)

[7,8], which are in turn useful for estimating transmissibility

[27,28,96,97]. Exposure data can also be used to investigate

the occurrence and determinants of super-spreading events

[12] and help identify introduction events in the case of zoono-

tic diseases [98]. Contact tracing, through the early detection of

new cases and their subsequent isolation and treatment, plays a

central role in reducing onward transmission and therefore

containing outbreaks [11,63,99], while additionally providing

potential information on risk factors [7,11].

Summary statistics are a useful complement to data visual-

ization in the exploratory phase of data analysis. Some metrics,

such as transmissibility, require the use of statistical or math-

ematical models in order to be estimated (see §3d below) and

are therefore not readily available as descriptive tools. Other

useful statistics can be readily computed from linelists, includ-

ing different demographic indicators of the reported cases

(e.g. gender, age, occupation [7,100,101]), case fatality ratios

(the proportion of cases who died of the infection) or case

delays such as the times to hospitalization, recovery or death,

reported as a whole [1,7,8] or stratified by groups [100,101].

The incubation period (time from infection to symptom onset)

is another important delay for informing the intervention (e.g.

to define the duration of contact tracing or declare the end of

an outbreak), but can be harder to derive as it requires data on

case exposure as well. Note that in the case of delays, these are

best analysed by characterising the full distribution (e.g. by fit-

ting to an appropriate probability distribution such as

discretized Gamma [7]) rather than reported as a single central

value [7,8,102,103].

(d) Quantifying transmissibility
The ‘transmissibility’ of a disease is here used to refer to the

rate at which new cases arise in the population, resulting

either in epidemic growth or decline [1,3,27,28]. Rather than

an intrinsic property of a specific disease, transmissibility

thus defined quantifies the propagation of a pathogen in a

given epidemic setting and is impacted by multiple factors

including population demographics, mixing and levels pre-

existing immunity. Importantly, estimates of transmissibility

reported in the literature will typically be biased towards

higher values, as subcritical outbreaks are by definition less

likely to be detected. Several metrics of transmissibility can

be used depending on the type of data available and can be

estimated using different approaches.

A first measure of transmissibility is the growth rate (r),
which is estimated from a simple model where case incidence

is either exponentially growing (r . 0) or declining (r , 0).
Typically, r is estimated directly from epicurves (figure 2)
using a log-linear model, where r is defined as the slope of a
linear regression on log-transformed incidence [104,105].

Besides its simplicity and its computational efficiency, this

approach has the benefits of being embedded in the linear

modelling framework, thereby allowing one to measure the

uncertainty associated with a given estimate of r, to test for

differences in growth rates, e.g. between different locations,

and to derive short-term incidence predictions. Moreover, the

growth rate can also be used to estimate the doubling and halv-

ing times of the epidemic, i.e. the time during which incidence

doubles (respectively is halved), as alternative metrics of trans-

missibility [103]. Unfortunately, the log-linear model can only

fit exponentially growing or decaying outbreaks, which may

not always be appropriate in the presence of complex spatial

or age structure, or owing to changes in reporting, transmissi-

bility or proportion of susceptible individuals over time.

Besides, it cannot readily accommodate time periods with no

cases, so that its applicability may in practice be restricted.

While r quantifies the speed at which a disease spreads, it does
not contain information on the level of the intervention that is
necessary to control a disease [106]. This is better characterized

by the reproduction number (here generically noted ‘R’), which
measures the average number of secondary cases caused by

each primary case. Researchers typically distinguish the basic

reproduction number (R0 [104]), which applies in a large, fully
susceptible population, without any control measures, from

the effective reproduction number (Reff ), which is the number
of secondary cases after accounting for behavioural changes,

interventions and declines in susceptibility [96]. The current

reproduction number determines the dynamics of the epidemic

in the near future, with values greater than 1 predicting an

increase in cases, and values less than 1 predicting control

[104]. The value of R can also be used to calculate the fraction
of the population that needs to be immunized (typically through

vaccination) in order to contain an outbreak [104].

Different methodological approaches have been developed

to estimate the reproduction number. R can be approximated
using estimates of the growth rate r combined with knowledge
of the generation time distribution [97]. R can also be derived
from compartmental models [104,107]. The formula will

depend on the type of model used, but such estimation

will usually require that different rates (e.g. rates of infection,

recovery, death) are either known or estimated by fitting the

model to data [104,107]. Real-world complexities can be incor-

porated into this approach; however, fitting such models can be

challenging and may require computationally intensive algor-

ithms such as data augmentation, approximate bayesian

computation, or particle filters [108]. Compartmental models

also require assumptions about the total population size and

the proportion of the population at risk, which may be difficult

to estimate in an outbreak. As an alternative, branching process

models can be used to estimate R directly from incidence data
[27,28,96,109]. This requires a pre-specified distribution of the

generation time, or of the serial interval, although recent devel-

opments suggest that in some cases, the generation time

distribution itself can also be simultaneously estimated [4].

Branching process models are usually much simpler to fit to

data than their compartmental counterparts, which facilitates

their use in real time [27].

Beyond the mere estimation of transmissibility, it is often

essential to forecast future incidence for advocacy and plan-

ning purposes, e.g. to compare different interventions and

epidemic scenarios [7,8,15,30]. A variety of mathematical and

statistical models, including those reviewed here for estimating

transmissibility, can also be used for short-term incidence fore-

casting [65]. Despite the growing body of research focusing on

predicting incidence during epidemics [65,110], there are cur-

rently no gold standards and the relative performances of

forecasting methods largely remain to be assessed. Methods

royalsocietypublishing.org/journal/rstb
Phil.Trans.R.Soc.

6
that have been developed and applied in other fields to rigor-
ously assess not just the accuracy of forecasts but also how

well models quantify the inherent uncertainty in making

predictions, are only rarely applied in infectious disease epide-

miology [111,112]. Whether it is to estimate R or predict future
incidence, the most appropriate method ultimately depends on

the particular epidemiological setting, existing knowledge of

the transmission dynamics and data availability. Branching

process models, for example, can be used for a quick estimate

of the current value of R from the recent trend in case numbers
and, by extrapolating this forward, of expected case numbers in

the near future [27,28,96]. Mechanistic or simulation models,

on the other hand, aim to include a more explicit representation

of the different factors that might influence transmission. They

can be a more natural choice for assessing the expected impact

of possible interventions, but they usually require careful para-

metrization and often intensive computation [29,30,45,113],

both of which can be challenging early in an outbreak when

data are scarce and rapid turnaround crucial.

B
374:20180276

(e) Analytical epidemiological techniques
Analytical epidemiological studies use data to better describe

outbreaks and populations at risk and inform real-time and

subsequent response efforts. Typically, these are conducted

during the intervention and post-intervention phases of an out-

break response (figure 1). They include observational designs

such as retrospective cohort and case – control studies to ident-

ify risk factors and quantify associations between potential

causes and their outcomes (typically, the disease in question),

and experimental designs, such as randomized-control studies

used to estimate the impact of interventions such as vaccination

and treatments [114]. These studies reside outside of the

normal scope of outbreak response activities, being inserted

ad hoc as functions that are not necessarily routine response
activities such as strengthening surveillance. In the case of

observational epidemiological studies, data on exposures and

outcomes are required, permitting estimations of the increased

risk of disease among people exposed to risk factors of interest

[54,62,115,116]. In the case of experimental epidemiology, data

on outcomes of interest are collected to permit estimations of

heterogeneity among groups (e.g. in the presence/absence of

intervention).

The usefulness of such studies in informing outbreak

response is highly context-dependent. Observational studies

may be undertaken early on in the intervention phase to

help identify ongoing infection sources of environmental,

food-borne or water-borne nature [117] and to stop the out-

break at its source. In longer-running outbreaks, they can

provide insights into opportunities for control [53,115,118]

and inform global policy decisions that relate to outbreak

response [119]. However, the time and expertise needed to

prepare and implement these studies may preclude their

application in the midst of an ongoing outbreak, so that the

cost and benefits of such an undertaking need to be carefully

weighed in emergency settings.

( f ) Genetic analyses
Whole genome sequencing of pathogens is increasingly afford-

able and reliable, and therefore more frequent in outbreak

investigations [1,120 – 126]. As technology is making real-time

sequencing in the field a developing standard in the coming

years [127,128], genetic analysis will likely carve out its own

space in the outbreak analytics toolkit.

Different methods can be used to extract information from

pathogen WGS. In bacterial genomics, molecular epidemiol-

ogy methods have been used extensively for defining strains

of related isolates [32,129], which can be used to infer various

features of the pathogens sampled such as their origins, antimi-

crobial resistance profiles, virulence or antigenic characteristics

[130 – 132]. These methods usually exploit only a fraction of the

information contained within pathogens’ genomes, as they rely

on genetic variation in a limited number of housekeeping

genes [32,129]. While these methods will likely remain useful

in years to come, substantially more information can be

extracted by using WGS to reconstruct phylogenetic trees,

which represent the evolutionary history of the sampled iso-

lates, assuming the absence of selection or horizontal gene

transfers [133]. Different types of phylogenetic reconstruction

methods can be used, including fast, scalable distance-based

methods [134] or more computer-intensive approaches using

a maximum-likelihood [135,136] or the Bayesian framework

[33,137]. Phylogenies can be used to assess the origins of a

set of pathogens [138], patterns of geographical spread [125],

host species jumps [139,140], past fluctuations in the pathogen

population sizes [141] and even, in some cases, the reproduc-

tion number [1]. Importantly, there is a growing tendency to

analyse phylogenetic trees in the broader context of other epi-

demiological data (mainly geographical locations until now),

which is facilitated by user-friendly Web applications [92,93].

A further step towards integrating WGS alongside epide-

miological data is the reconstruction of transmission trees

(who infects whom) using evidence synthesis approaches.

This methodological field has been growing fast over the past

decade [25,142 – 148], but most applications of these methods

remain within academia and their usefulness in the field in

an outbreak response context needs to be critically assessed.

A potential benefit of accurately reconstructing transmission

trees lies in the identification of multiple introductions, the

quantification of the proportion of unreported cases and the

detection of heterogeneities in individual transmissibility

[145]. Unfortunately, the reconstruction of transmission trees

is a difficult and computationally intensive problem. First,

most diseases do not accumulate sufficient genetic diversity

during the course of an outbreak to allow the accurate recon-

struction of transmission chains, so that multiple data sources

need to be used [35], making these methods more data-

demanding than most other approaches in outbreak analytics

(figure 2). In addition, the complex nature of the problem

requires the use of Bayesian methods for model fitting,

making these approaches difficult to interpret by non-experts

[145,146,148].

4. Discussion
In this article, we reviewed methodological and technological

resources forming the basis of outbreak analytics, an emerg-

ing data science for informing outbreak response. Outbreak

analytics is embedded within a broader public health infor-

mation context that starts with disease surveillance systems,

followed by risk assessment and management, the epidemiolo-

gical response itself, and finishes with the production of

actionable information for decision making. Part of the chal-

lenge that this new field will face in the coming years

royalsocietypublishing.org/journal/rstb
Phil.Trans.R.Soc.B
374:20180276
7
pertains to the seamless integration of data analytics pipelines
within existing workflows. As responders can allocate only

limited time to data analysis, analytics resources should

produce simple, interpretable results, highlighting the most

pressing issues that need addressing and monitoring all

relevant indicators to inform the response.

Outbreak analytics and resulting outputs are central to the

surveillance pillar of any outbreak response, yet resources and

capacities to ensure data availability and quality are often lim-

ited owing to operational constraints [16]. Priorities in terms of

data needs should be defined by what actionable information it

may give access to through the available analytics pipelines

[13]. In this respect, we foresee that typical linelist data such

as dates of events (e.g. onset, reporting, hospitalization, dis-

charge), age, gender, disease outcome, geographical locations

and exposure data will fulfil most needs, while other data

such as WGS may only be useful for specific diseases and con-

texts [34,35]. Intervention data are rarely collected but should

be given more consideration, as they are key to assessing the

impact and effectiveness of control measures, both during

and after the operations. Similarly, data on the fraction of

cases reported (and its variations through time), as well as be-

havioural changes (e.g. care-seeking behaviour) in the affected

populations, can be very important sources of information for

modelling [149].

Fortunately, what we called ‘background data’ in this

article can be gathered and shared outside of the epidemic con-

text. Besides maps, population census, sero-surveys or genetic

databanks, data on the natural histories of diseases derived

from past epidemics, such as key delay distributions and trans-

missibility, can form a useful substitute to real-time estimates,

especially in the early stages of outbreaks when such data may

be lacking. While crowd-sourced initiatives are promising and

have been used successfully in low resource settings [90], more

efforts are needed to collate and curate open data sources,

assess their quality and make them widely available to the

community. We argue that international public health agencies

and non-governmental agencies should play a central role in

orchestrating such background data preparedness.

Outbreak analytics is a developing field, and as such, there

remain many gaps in terms of data collection, analysis and

reporting tools. Some methodological challenges persist, such

as better characterising forecasting methods [28,64,65], includ-

ing spatial information and population flows into existing

transmission models [95], and improving the integration of

different types of data for reconstructing transmission trees

[35]. In order to ensure transparent methods and availability

to analysts in any setting, the implementation must be as

freely available, open-source software. Among other popular

programming languages, such as Python, Java, or Julia, the R

software [150] arguably offers the largest collection of free

tools for data analysis and reporting, and an increasing

number of packages for infectious disease epidemiology

[20,21,27,84,145] may form a solid starting point for the devel-

opment of a comprehensive, robust and transparent toolkit for

the analysis of epidemic data [151]. Importantly, the use of a

common platform for the development and use of outbreak

analytics tools will also likely contribute to standardizing

data practices, including collection, sharing and analysis.

A final point relates to the use and dissemination of these

new resources: how can outbreak analytics best help improve

public health? As noted by Bausch & Clougherty [39], health
science should not be an entity unto itself, but a means to an end.
Insofar as it can help field epidemiologists collect, visualize

and analyse data, and subsequently provide decision-makers

with actionable information, outbreak analytics will likely

occupy an increasing space in field epidemiology over the

years to come. We foresee that the dissemination of free train-

ing resources [152], the modernization of field epidemiology

training programmes and the deployment of applied data

scientists to the field with a sustained capacity building in

resource-poor and vulnerable countries will be instrumental

in shaping the future of this emerging field of health science.

Data accessibility. This article has no additional data.
Authors’ contributions. T.J. drafted the outline of the review and revised
the manuscript. J.A.P., A.B., T.J. wrote the first draft of the manu-
script. Z.N.K. produced the figures. A.C., W.J.E., R.M.E., S.F., L.K.,
P.K., M.M., P.M., P.N., O.P.W., R.R., J.W. contributed the content.

Competing interests. We declare we have no competing interests.
Funding. This paper was supported with funding from the Global Chal-
lenges Research Fund (GCRF) for the project ‘RECAP—research
capacity building and knowledge generation to support preparedness
and response to humanitarian crises and epidemics’ managed through
RCUK and ESRC (ES/P010873/1). P.K., O.L.P., J.W. and T.J. receive
support from the UK Public Health Rapid Support Team, which is
funded by the United Kingdom Department of Health and Social
Care. We acknowledge the National Institute for Health Research—
Health Protection Research Unit for Modelling Methodology (T.J.)
for funding. M.M., C.H.R., receive funding through the National Insti-
tute for Health Research (PR-OD-1017-20001). R.M.E. acknowledges
funding from an HDR UK Innovation Fellowship (grant no. MR/
S003975/1). A.C. thanks the Medical Research Council for funding.
S.F. was supported by the Wellcome Trust (210758/Z/18/Z). The
authors alone are responsible for the views expressed in this article
and they do not necessarily represent the views, decisions or policies
of the institutions with which they are affiliated.

Acknowledgements. We would like to thank Annick Lenglet and Isidro
Carrion-Martin, Epidemiologists at Medecins Sans Frontieres (MSF,
Operational Centre Amsterdam) for their additional reflections. The
views expressed in this publication are those of the authors and
not necessarily those of the National Health Service, the National
Institute for Health Research or the Department of Health and
Social Care. The authors alone are responsible for the views
expressed in this article and they do not necessarily represent the
views, decisions or policies of the institutions with which they are
affiliated.

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Outbreak analytics: a developing data science for informing the response to emerging pathogens

Introduction
The outbreak response context
The different phases of an outbreak response
Questions during and after the intervention
What are outbreak data?
Outbreak analytics
An overview of the outbreak analytics toolbox
Tools for the collection of epidemiological data
Descriptive analyses
Quantifying transmissibility
Analytical epidemiological techniques
Genetic analyses
Discussion
Data accessibility
Authors’ contributions
Competing interests
Funding
Acknowledgements
References

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