Commentary: Barriers and Opportunities to Changing the Research Agenda to Support Precaution and Primary Prevention

Conceptual research to define the Precautionary Principle and its rôle in science, science policy, and public health is making substantial progress. In September 2001, participants at the International Summit on Science and the Precautionary Principle developed a vision for science to address the complexity of contemporary health risks in a way that could lead to more precautionary, preventive decisions under uncertainty. Its components include: (1) a more effective linkage between research on hazards and research on primary prevention; (2) increased use of interdisciplinary approaches including better integration of qualitative and quantitative data; (3) innovative methods for analyzing cumulative and interactive effects, populations and systems and vulnerable sub-populations; (4) systems for continuous monitoring to avoid unintended consequences of actions and to identify early warnings of risks; (5) more comprehensive techniques for analyzing and communicating hazards and uncertainties; and (6) a more dynamic interface between science and policy. This article addresses barriers and opportunities to the practical application of this vision for science. Scientists in many fields have recognized the need for innovative approaches and tools to address increasingly complex, uncertain risks of a global scale. While opportunities to apply precautionary concepts in the research agenda exist, public health scientists must be cognizant of current and emerging barriers in the research agenda that balance the research focus on characterizing proximate causal mechanisms of disease, to the detriment of research and policy to support primary prevention.     

Implications of the Precautionary Principle: Is it a Threat to Science?

Scientific research is of proven value to protecting public health and the environment from current and future problems. We explore the extent to which the Precautionary Principle is a threat to this rôle for science and technology. Not surprisingly for a relatively simple yet still incompletely defined concept, supporters of the Precautionary Principle come from different viewpoints, including a viewpoint that is at least uneasy with the rôle of science, and particularly its use in risk assessment. There are also aspects of the Precautionary Principle that inherently restrict obtaining and using science. The Hazardous Air Pollutant (HAP) provisions in the US Clean Air Act Amendments are an example of the Precautionary Principle, which both shifted the burden of proof so that the onus is now on showing a listed compound is harmless, and required maximum available control technology (MACT) instead of a primarily risk-based approach to pollution control. Since its passage in 1990 there has been a decrease in research funding for studies of HAPs. Other potential problems include that once MACT regulations are established, it may be difficult to develop new technological approaches that will further improve air pollution control; that by treating all regulated HAPs similarly, no distinction is made between those that provide a higher or lower risk; and that there is a perverse incentive to use less well studied agents that are not on the existing list. As acting on the Precautionary Principle inherently imposes significant costs for what is a potentially erroneous action, additional scientific study should be required to determine if the precautionary action was successful. If we are to maximize the value of the Precautionary Principle to public health and the environment, it is crucial that its impact not adversely affect the potent preventive rôle of science and technology.     

Commentary: The Rôle of Toxicology in Prevention and Precaution

Advocates of the Precautionary Principle have recently called for a “new science” to support the goals of precaution-based environmental and occupational health policy. While much attention has been given to epidemiology, the evidentiary science most relevant to precaution, or prevention, is toxicology. Opportunities for enhancing the rôle of toxicology in public policy must consider current biases in the field. Thus, rather than a “new science,” advocates for change should focus upon ensuring that current scientific methods are appropriate and that interpretations of scientific data are accurate.     

On Being Careful What We Wish for: Some Difficulties with Operationalizing the Precautionary Principle

An important part of the Precautionary Principle is that taking action is justified for protecting public health even when there is some scientific uncertainty. We examine here the two components of this central feature of the precautionary principle, scientific uncertainty and decision making. In order to operationalize the principle we should examine the consequences of its decision rules and how they perform under various conditions. The performance of decision rules in disease screening is measured by the sensitivity and specificity of the rule, but the consequences for the patient are given by the positive and negative predictive values, determined not only by the performance of the rule by the prevalence of the disease in the population. We look at positive and negative predictive value of the Precautionary Principle from the standopoint of the costs to one or other parts of society, show that the usual rule which tends to maximize sensitivity in favor of specificity may have unexpected consequences, and demonstrate that it is sometimes possible to trade sensitivity and specificity off against each other in a way the improves both positive and negative predictive value, or worse, degrades both.We conclude by asking if certain strategies are better for one or the other kinds of uncertainty.     

The Precautionary Principle in the Information Society

The Precautionary Principle aims to anticipate and minimize potentially serious or irreversible risks under conditions of uncertainty. Thus it preserves the potential for future developments. It has been incorporated into many international treaties and pieces of national legislation for environmental protection and sustainable development. However the Precautionary Principle has not yet been applied systematically to novel Information and Communication Technologies (ICTs) and their potential environmental, social, and health effects. In this article we argue that precaution is necessary in this field and show how the general principle of precaution can be put in concrete terms in the context of the information society. We advocate precautionary measures directed towards pervasive applications of ICT (Pervasive Computing) because of their inestimable potential impacts on society.     

Multidisciplinary Research: Strategies for Assessing Chemical Mixtures to Reduce Risk of Exposure and Disease

The Precautionary Principle is founded on the use of comprehensive, coordinated research to protect human health in the face of uncertain risks. Research directed at key data gaps may significantly reduce the uncertainty underlying the complexities of assessing risk to mixtures. The National Institute of Environmental Health Sciences (NIEHS) has taken a leadership rôle in building the scientific infrastructure to address these uncertainties. The challenge is to incorporate the objectives as defined by the Precautionary Principle with the knowledge gained in understanding the multifactorial nature of gene-environment interactions. Through efforts such as the National Center for Toxicogenomics, the National Toxicology Program, and the Superfund Basic Research Program, NIEHS is translating research findings into public health prevention strategies using a 3-pronged approach: (1) identify/evaluate key deviations from additivity for mixtures; (2) develop/apply/link advanced technologies and bioinformatics to quantitative tools for an integrated science-based approach to chemical mixtures; (3) translate/disseminate these technologies into useable, practical means to reduce exposure and the risk of disease. Preventing adverse health effects from environmental exposures requires translation of research findings to affected communities and must include a high level of public involvement. Integrating these approaches are necessary to advance understanding of the health relevance of exposure to mixtures.     

The Precautionary Principle: Implications for Risk Management Strategies

The European Commission has published a Communication on the Precautionary Principle and a White Book on Governance. These provide us (as research civil servants of the Commission) an institutional framework for handling scientific information that is often incomplete, uncertain, and contested. But, although the Precautionary Principle is intuitively straightforward to understand, there is no agreed way of applying it to real decision-making. To meet this perceived need, researchers have proposed a vast number of taxonomies. These include ignorance auditing, type one-two-three errors, a combination of uncertainty and decision stakes through post-normal science and the plotting of ignorance of probabilities against ignorance of consequences. Any of these could be used to define a precautionary principle region inside a multidimensional space and to position an issue within that region. The rôle of anticipatory research is clearly critical but scientific input is only part of the picture. It is difficult to imagine an issue where the application of the Precautionary Principle would be non-contentious. From genetically-modified food to electro-smog, from climate change to hormone growth in meat, it is clear that: 1) risk and cost-benefit are only part of the picture; 2) there are ethical issues involved; 3) there is a plurality of interests and perspectives that are often in conflict; 4) there will be losers and winners whatever decision is made. Operationalisation of the Precautionary Principle must preserve transparency. Only in this way will the incommensurable costs and benefits associated with different stakeholders be registered. A typical decision will include the following sorts of considerations: 1) the commercial interests of companies and the communities that depend on them; 2) the worldviews of those who might want a greener, less consumerist society and/or who believe in the sanctity of human or animal life; 3) potential benefits such as enabling the world's poor to improve farming; 4) risks such as pollution, gene-flow, or the effects of climate change. In this paper we will discuss the use of a combination of methods on which we have worked and that we consider useful to frame the debate and facilitate the dialogue among stakeholders on where and how to apply the Precautionary Principle.     

Incorporating Science,Technology, Fairness,and Accountability in Environmental,Health, and Safety Decisions

The Precautionary Principle is in sharp political focus today because (1) the nature of scientific uncertainty is changing and (2) there is increasing pressure to base governmental action on more “rational” schemes, such as cost-benefit analysis and quantitative risk assessment, the former being an embodiment of ‘rational choice theory’ promoted by the Chicago school of law and economics. The Precautionary Principle has been criticized as being both too vague and too arbitrary to form a basis for rational decision making. The assumption underlying this criticism is that any scheme not based on cost-benefit analysis and risk assessment is both irrational and without secure foundation in either science or economics. This paper contests that view and makes explicit the rational tenets of the Precautionary Principle within an analytical framework as rigorous as uncertainties permit, and one that mirrors democratic values embodied in regulatory, compensatory, and common law. Unlike other formulations that reject risk assessment, this paper argues that risk assessment can be used within the formalism of tradeoff analysis—a more appropriate alternative to traditional cost-benefit analysis and one that satisfies the need for well-grounded public policy decision making. This paper will argue that the precautionary approach is the most appropriate basis for policy, even when large uncertainties do not exist, especially where the fairness of the distributions of costs and benefits of hazardous activities and products are a concern. Furthermore, it will offer an approach to making decisions within an analytic framework, based on equity and justice, to replace the economic paradigm of utilitarian cost-benefit analysis.     

Dimensions of the Precautionary Principle

This essay attempts to provide an analytical apparatus which may be used for finding an authoritative formulation¹ of the Precautionary Principle. Several formulations of the Precautionary Principle are examined. Four dimensions of the principle are identified: (1) the threat dimension, (2) the uncertainty dimension, (3) the action dimension, and (4) the command dimension. It is argued that the Precautionary Principle can be recast into the following if-clause, containing these four dimensions: “If there is (1) a threat, which is (2) uncertain, then (3) some kind of action (4) is mandatory.” The phrases expressing these dimensions may vary in (a) precision and (b) strength. It is shown that it is the dimension containing the weakest phrase that determines the strength of the entire principle. It is suggested that the four-dimensional if-clause be used as an analytical apparatus in negotiations of the Precautionary Principle.     

The Precautionary Principle,Epidemiology and the Ethics of Delay

Ethics tells us: do good and do no harm and invokes the norms of justice, equity and respect for autonomy in protecting and promoting health and well-being. The Precautionary Principle, a contemporary re-definition of Bradford Hill's case for action, gives us a common sense rule for doing good by preventing harm to public health from delay: when in doubt about the presence of a hazard, there should be no doubt about its prevention or removal. It shifts the burden of proof from showing presence of risk to showing absence of risk, aims to do good by preventing harm, and subsumes the upstream strategies of the DPSEEA (Driving Forces Pressure Stress Exposure Effect Action) model and downstream strategies from molecular epidemiology for detection and prevention of risk. The Precautionary Principle has emerged because of the ethical import of delays in detection of risks to human health and the environment. Ethical principles, the Precautionary Principle, the DPSEEA model and molecular epidemiology all imply re-emphasizing epidemiology's classic rôle for early detection and prevention. Delays in recognizing risks from past exposures and acting on the findings (e.g., cigarette smoking and lung cancer, asbestos, organochlorines and endocrine disruption, radiofrequency, raised travel speeds) were examples of failures that were not only scientific, but ethical, since they resulted in preventable harm to exposed populations. These may delay results from, among other things, external and internal determinants of epidemiologic investigations of hazard and risk, including misuse of tests of statistical significance. Furthermore, applying the Precautionary Principle to ensure justice, equity, and respect for autonomy raises questions concerning the short-term costs of implementation to achieve long-term goals and the principles that guide compensation.     

Finding Common Ground for Environmental Decisions: Public Health Principles as a Foundation for Better Choices

The history of environmental decision-making in the United States is primarily one of antagonism, conflict, and litigation. Four sectors of American society are typically at odds over why and how to solve environmental problems—government regulators, businesses proponents, environmental advocates, and members of affected communities. Dissimilar worldviews are at the heart of most environmental disputes, and people in the four sectors tend to have diverse perspectives and philosophies that affect how they interpret and respond to environmental issues. To promote integrated, cost-effective decisions, the public health paradigm (prevention first, intervention second, treatment third), as embodied in the Precautionary Principle and the concept of Sustainable Development, should be mutually adopted as a joint framework for prioritizing solutions to pressing environmental problems. The core public health principle of prevention first is a simple yet powerful tenet that can help foster better environmental choices that are more effective, efficient, and equitable.     

Assessing the Human,Social, and Environmental Risks of Pervasive Computing

The vision of Pervasive Computing is built on the assumption that computers will become part of everyday objects, augmenting them with information services and enhanced functionality. This article reports on the approach we have used to assess potential side effects of this development on human health and the environment, and the major risks we identified. Social risks such as the risk of conflicts between users and non-users of the technology were also included because of their potential indirect adverse health effects. Assessing a technological vision before it has materialized makes it necessary to deal with two types of uncertainty: first, the uncertainty of how fast and to what extent the technology will be taken up and how it will be used; second, the uncertainty of causal models connecting technology-related causes with potential health or environmental effects. Due to these uncertainties, quantitative methods to evaluate expected risks are inadequate. Instead, we developed a “risk filter” that makes it possible to rank risks according to a set of qualitative criteria based on the Precautionary Principle. As the overall result, it turned out that Pervasive Computing bears potential risks to health, society, and/or the environment in the following fields: Non-ionizing radiation, stress imposed on the user, restriction of consumers' and patients' freedom of choice, threats to ecological sustainability, and dissipation of responsibility in computer-controlled environments.     

The Importance of Type II Error and Falsifiability

Aim. Before intergovernmental consensus under the Rio Declaration in 1992, ignorance of type I errors had been disfavoured in science. However, the Precautionary Principle (PP) counsels the avoidance of type II errors, rather than of type I errors. We need a new academic code for the PP. Material and methods. The risk of extinction has usually been evaluated based on conservative estimates of the present population size. I define the weight of evidence as the extinction risk of Japanese vascular plants based on unbiased estimates. Catch quotas in the fisheries are usually decided by precautionary approach. I calculate the long-term yield and risk of stock collapse under a simple stock dynamics model. Results. The weight of evidence depends on the frequency of grids with size unknown. In a few plant species, rankings based on conservative estimates have differed from rankings based on unbiased estimates. In fishery management, a catch quota based on a precautionary approach proved neither sufficient nor necessary to avoid stock collapse. The precautionary approach is one of the reasons that prevent us from maximizing a sustainable yield. Conclusions. We need to clarify the endpoint of risks, and check whether it is necessary to adopt a PP. We can obtain the weight of evidence that is measured under unbiased estimates, while the risk based on a PP is measured under conservative estimates.     

Causal Characteristics for Ecoepidemiology

We suggest that there are six fundamental characteristics of causation: time order, co-occurrence, preceding causation, sufficiency, interaction, and alteration. The cause precedes the effect (time order). The cause co-occurs with the unaffected entity in space and time (co-occurrence). Causes and their effects are the result of a web of causation (preceding causation). The intensity, frequency, and duration of the cause are adequate and the susceptible entity can exhibit the type and magnitude of the effect (sufficiency). The cause effectively interacts with the entity in a way that induces the effect (interaction). And, the entity is changed by the interactions with the cause (alteration). In contrast to Hill's criteria, the causal characteristics are distinct from the: (1) evidence that is used to document causal characteristics, (2) sources of information used to develop the evidence, and (3) qualities used to evaluate evidence of causal characteristics and body of evidence for the causal relationship. Evidence of causal characteristics can form the basis for assessments of epidemiological studies and can structure an explanatory narrative that is causally relevant and substantive. Six core characteristics may be easier to organize, evaluate, communicate, and for decision-makers to assimilate, remember, and inspire action.     

Research Implications of Science-Informed,Value-Based Decision Making

In ‘Hard’ science, scientists correctly operate as the ‘guardians of certainty,’ using hypothesis testing formulations and value judgements about error rates and time discounting that make classical inferential methods appropriate. But these methods can neither generate most of the inputs needed by decision makers in their time frame, nor generate them in a form that allows them to be integrated into the decision in an analytically coherent and transparent way. The need for transparent accountability in public decision making under uncertainty and value conflict means the analytical coherence provided by the stochastic Bayesian decision analytic approach, drawing on the outputs of Bayesian science, is needed. If scientific researchers are to play the rôle they should be playing in informing value-based decision making, they need to see themselves also as ‘guardians of uncertainty,’ ensuring that the best possible current posterior distributions on relevant parameters are made available for decision making, irrespective of the state of the certainty-seeking research. The paper distinguishes the actors employing different technologies in terms of the focus of the technology (knowledge, values, choice); the ‘home base’ mode of their activity on the cognitive continuum of varying analysis-to-intuition ratios; and the underlying value judgements of the activity (especially error loss functions and time discount rates). Those who propose any principle of decision making other than the banal ‘Best Principle,’ including the ‘Precautionary Principle,’ are properly interpreted as advocates seeking to have their own value judgements and preferences regarding mode location apply. The task for accountable decision makers, and their supporting technologists, is to determine the best course of action under the universal conditions of uncertainty and value difference/conflict.     

The Precautionary Principle,Science and Human Health Protection

As technology advances rapidly, so do applications with potential adverse implications on human health. The possible threats include risks that can be substantial, far-reaching and irreversible, and currently available methods of investigation, designed to deal with direct exposure-disease associations, are not always suitable. Growing interest is being paid to health effects that may be the consequence of distal, “upstream” determinants. Considering the complex chain of events that links such determinants with health can be extremely difficult, and exposes severe limitations in science. Thus, there is often a mismatch between what is known and what would be required to inform rational, evidence-based decision making, which is increasingly called for. It has become apparent how production and use of scientific evidence in decision making must be accompanied by precaution, especially in those circumstances, more and more common in recent times, where there is an uncertain possibility that serious health consequences might take place. Several cautionary approaches have been proposed, but the Precautionary Principle (PP) has been the object of especially intense debate in recent years. Developed in the field of environmental health, the PP has been clarified, and has been applied or called for in several instances in public health. Although a unique definition is not available, the principle has been characterised, and criteria for its application have been proposed. However, many questions remain open on general as well as specific issues. In this paper, we address some of the questions that are relevant for the PP to support rational decision making in environment and health and more in general to strengthen its contribution towards human health protection.     

Making Causal Claims about Environmentally Induced Adverse Effects

Causal inferences are a vital and intrinsic part of assessing the risk of adverse effects on human populations and ecological resources from biological, chemical, physical, and psychosocial stressors. While it is well known that a statistical association does not necessarily imply a causal association, the central role of causal theory in health and ecological risk assessment is often overlooked. In this article, we present a succinct account of causal theory in the health sciences, emphasize the importance of differentiating between formal and informal approaches to causal inference, describe the weight-of-evidence process that is currently the predominant means of inferring causality in the context of science-based regulatory decisions, and discuss the effects of causal theory on the current and future practice of risk assessment. Our aim is to highlight the significance of decisions about causation and causal inference, and to suggest that explicit, well-considered choices will serve to strengthen the scientific underpinnings of regulatory decision-making.     

In silico model‐based inference: A contemporary approach for hypothesis testing in network biology

Inductive inference plays a central role in the study of biological systems where one aims to increase their understanding of the system by reasoning backwards from uncertain observations to identify causal relationships among components of the system. These causal relationships are postulated from prior knowledge as a hypothesis or simply a model. Experiments are designed to test the model. Inferential statistics are used to establish a level of confidence in how well our postulated model explains the acquired data. This iterative process, commonly referred to as the scientific method, either improves our confidence in a model or suggests that we revisit our prior knowledge to develop a new model. Advances in technology impact how we use prior knowledge and data to formulate models of biological networks and how we observe cellular behavior. However, the approach for model‐based inference has remained largely unchanged since Fisher, Neyman and Pearson developed the ideas in the early 1900s that gave rise to what is now known as classical statistical hypothesis (model) testing. Here, I will summarize conventional methods for model‐based inference and suggest a contemporary approach to aid in our quest to discover how cells dynamically interpret and transmit information for therapeutic aims that integrates ideas drawn from high performance computing, Bayesian statistics, and chemical kinetics. © 2014 American Institute of Chemical Engineers Biotechnol. Prog., 30:1247–1261, 2014