Infectious animal and zoonotic diseases are important and immediate global disease
threats which exhaust resources and place demands on both national and international
global animal and human health institutions and infrastructures. These diseases create
challenges for industry stakeholders and policy-makers because of their pandemic potential
and resultant widespread economic and social disruption. The current pandemic of the
coronavirus SARS-CoV-2 (disease name COVID-19), which was first detected in the wet
markets of Wuhan, Hubei Province, China, offers a contemporary example on which we
might reflect about the lessons learned from this Research Topic—in particular, the
importance of transparent data sharing and the development of risk-based evidence
for policy-making for zoonotic disease outbreak preparedness and control. COVID-19
has now been detected in 188 international locations despite the closure of the wet
markets and imposition of movement restrictions and other interventions to reduce
risks of onward transmission. Risk management decisions in different countries [such
as the imposition and subsequent release of social distance policies (1) and the introduction
of compulsory mask-wearing (2)] are not purely (public health) science-based. The
political, cultural, and societal dimensions of the pandemic have highlighted sharply
the need to “remedy… disciplinary silos” (3) through holistic interdisciplinary approaches
to understand the complex trade-offs and unintended consequences of disease control
policies.
In this Research Topic, we wanted to explore the development of a robust and fit-for-purpose
evidence base for animal (and public) health and the different mechanisms used to
ensure its effective delivery to policy-makers in order to better anticipate and respond
appropriately to existing and emerging animal and zoonotic disease risks. The response
to the call for papers yielded 17 accepted papers with 112 contributing authors and
the Research Topic has been accessed more than 25,000 times highlighting the importance
and timely nature of these contributions. In this editorial, we identify 5 key lessons
learned from these contributions and consider the future for risk-based policy-making
for animal and public health.
Improve Understanding and Communication of Concepts of Risk and Uncertainty To Different
Stakeholder Audiences
Policy and decision-making is not based on scientific evidence alone, but also influenced
by political will, existing governance structures, public opinion, and other exogenous
factors. Researchers need to engage with all of these facets in a holistic way, but
this is challenging to do in the context of traditional research environments. More
reflects on these difficulties and highlights the need for a commitment to integrate
“policy relevance to the research focus from the outset, to engage with policy-makers
and other stakeholders throughout, to use platforms to facilitate science-policy dialogue,
and to disseminate research findings appropriately.” He articulates the need and demand
for interdisciplinary approaches—and in particular, input from the social sciences,
which stems from the recognition that science, itself, is not value-free.
Assembling multi-disciplinary teams with appropriate expertise is fundamental to delivering
appropriate and effective risk assessment, communication, and management. Countries
have varying approaches to prioritizing disease risks for contingency planning which
reflect the economic, social, and cultural values of their communities. Two papers
in this series explore risk prioritization and perception, through different disciplinary
approaches. Bessell et al. use a semi-quantitative approach which uses a combination
of the rate of disease spread, disease mitigation factors, impacts on animal welfare
and production, the human health risks and the impacts on wider society to characterize
exotic disease priorities for Scotland. In contrast, Waldman et al., explore the role
of the social, economic, and cultural context in shaping the perceptions and practices
of actors who play significant roles in risk management. This paper illustrates the
importance of understanding “situated expertise” and particular forms of risk perception
and practice which both enhance and compromise risk reduction in different ways” (Waldman
et al.).
Anticipate Regulatory or Policy Barriers To Ensure Effective Implementation of Scientific
Evidence
The foundations of evidence-based decision-making begin with robust data collection,
access and sharing. Houe et al. acknowledge that although there may be a wealth of
data generated, many datasets have emerged from different organizations and have been
developed for other purposes, making it difficult to integrate them and use them to
their full potential. Appropriate regulations and policies need to be in place for
data access and sharing across organizational and legal boundaries. Sustaining the
value of these datasets to researchers and decision-makers depends almost entirely
on data accuracy and reliability; substantial changes in data architecture and structure,
which inevitably occur over time, need to be taken into account to ensure that risk
management decisions based on these data are justified and valid. Continued investment
into the maintenance and “upkeep” of these data is therefore critical for these data
to be useful to policy-makers.
Integrate Different Data Sources To Improve Disease Monitoring and Surveillance
Estimating the risk of incursion of disease depends on transparent data sharing, robust
animal health recording systems and fit-for-purpose veterinary public health infrastructure
which includes access to affordable diagnostic tests, laboratory facilities, and trained
technicians, veterinary professional, paraprofessionals, and researchers to interpret
and act on results. Georgaki et al. describe the advantages of the Bluetongue surveillance
programme in Northern Ireland, which has evolved to include the use of risk assessments
and simulation models to monitor the risk of incursion. Its design enables effective
mitigation measures to be identified to minimize disease risk and provides additional
assurances to protect NI's export markets in the European Union (EU) and third countries.
The authors also highlight the benefits of including both active and targeted surveillance
activities to enable early detection of disease. In Scotland, risk-based approaches
are also used to identify high risk areas for vector-borne diseases, such as Louping
ill virus (See Gilbert et al.). GIS-based data on environmental variables, when used
in combination with sero-prevalence data, become a powerful tool to identify risk
factors and improve opportunities for identification of alternative disease reservoirs.
Both of these are important for informing disease management policies and identifying
trade-offs between environmental and farming priorities and costs. These insights
are echoed in the contributions by Carneiro et al. and Semango et al. which remind
us of the value of traditional field-based epidemiology and recognize the importance
of a systems-based approach. As highlighted by the example of COVID-2019, a broad
and holistic understanding of the causal risk pathways is necessary to ensure that
critical disease reservoirs are also appropriately incorporated into strategies for
surveillance and risk mitigation.
Invest in Proactive Development of Risk Assessment Expertise and Generic, Flexible
Tools, and Frameworks Which are Ready-To-Use in Disease Emergencies
The majority of the contributions in this Research Topic identified the usefulness
of investing in proactive veterinary risk assessments which include risk pathways
that can be flexibly adapted and re-used in times of emergency to ensure business
continuity (see Auty et al.; de Vos et al.; Taylor et al.; Umber et al.; Walz, Middleton
et al.; Walz, Evanson et al.). For example, estimates of the risk of onward transmission
of disease associated with movements of carcasses from de-populated farms to other
areas for disposal inform risk management decisions about movements of vehicles, animals
and animal products out of disease control areas (Umber et al.; Walz, Evanson et al.).
While there is a lot of guidance available for animal-related product movements and
for a variety of carcass types, there may be country, disease or species-specific
gaps which are necessary to fill in order to “assist regulatory authorities in using
risk” to guide decision-making (for example to grant permitted movement or deny a
request to move for live animals or carcasses) (see Umber et al.). Proactively working
to elucidate these risks coupled with efforts to identify and address data and research
gaps can help countries minimize the risk of disease spread while also minimizing
the impact of the outbreak response on unaffected farms.
Incorporate Social Science and Humanities Expertise To Improve and Discriminate Between
Different Risk Management Decisions
Risk assessment is essential to target critical control points which are amenable
to risk reduction. Although technical solutions—such as improved diagnostic testing
regimens and disease control strategies—are available, their effectiveness depends
on the compliance and uptake of interventions by key stakeholders. Two papers explored
the likelihood of uptake of technological interventions, using distinct approaches.
Mohr et al., used economic game theory as a framework to evaluate farmers' strategic
decision-making in different contexts. The work explores the uptake of an effective
diagnostic test for sheep-scab—a disease which costs more than £8 million per year
to the UK industry. In theory, the benefits of control should outweigh the costs of
the test. However, this paper illustrates that the likelihood of uptake depends very
much on the farmer's perception of risk to the herd and whether they take a long-
or short-term view of profitability. Liu et al. explore this problem in a different
way. The authors construct different behavioral typologies of farmers which they refer
to as: “non-adopters,” “current adopters,” or “future adopters” with respect to different
technologies. Their paper suggests that in order to be successful, we need to better
understand our stakeholder populations so that policies, regulatory incentives, and
complementary training can be appropriately targeted to ensure effective uptake and
positive behavioral change.
A Forward Look: Create New Pathways To Improve Decision-Making
New technologies and methodologies in human and veterinary medicine, epidemiology,
agricultural production systems, and business tools and approaches have the capacity
to deliver large volumes of high-quality data and complex analyses to improve animal
and zoonotic disease surveillance and outbreak preparedness. However, scientific evidence
is usually only a small part of the evidence base for decision-makers. Incorporating
these advances into policy-making can be challenging, given the silos that exist between
human and animal health institutions, differences between research, policy and industry
timescales, and the need to consider multiple evidence bases and different stakeholder
groups. Without established effective and explicit communication channels between
scientists, policy, and industry audiences, researchers will struggle to respond to
policy needs with relevant research to inform decision-making in a timely and robust
manner. Models of science-policy delivery through innovative, multi-disciplinary partnerships
between academia, industry, and government (such as the Scottish Government Centers
of Expertise, described by Boden et al.), may offer a solution, particularly when
combined with purposeful communication and innovation aimed at these five lessons.
Author Contributions
LB was responsible for the concept and writing of this manuscript. All authors listed
have made a substantial, direct and intellectual contribution to the work, and approved
it for publication.
Conflict of Interest
The authors declare that the research was conducted in the absence of any commercial
or financial relationships that could be construed as a potential conflict of interest.