Paolo F. Ricci

Causal regulations vs. political will: why human zoonotic infections increase despite precautionary bans on animal antibiotics.

Using precautionary principles when facing incomplete facts and causal conjectures raises the possibility of a Faustian bargain. This paper applies systems dynamics based on previously unavailable data to show how well intended precautionary policies for promoting food safety may backfire unless they are informed by quantitative cause-and-effect models of how animal antibiotics affect animal and human health. We focus on European Union and United States formulations of regulatory precaution and then analyze zoonotic infections in terms of the consequences of relying on political will to justify precautionary bans. We do not attempt a political analysis of these issues; rather, we conduct a regulatory analysis of precautionary legal requirements and use Quantitative Risk Assessment (QRA) to assess a set of policy outcomes. Thirty-seven years ago, the Joint Committee on the Use of Antibiotics in Animal Husbandry and Veterinary Medicine (the Swann Report) warned that uncontrolled use of similar antibiotics in humans and food animals could promote the emergence of resistant strains of foodborne bacteria that could endanger human health. Since then, many countries have either banned or restricted antibiotics as feed additives for promoting animal growth. Others, including the United States, have relied on prudent use guidelines and programs that reduce total microbial loads, rather than focusing exclusively on antibiotic-resistant bacteria. In retrospect, the regulatory strategy of banning or restricting animal antibiotic uses has had limited success: it has been followed in many cases by deteriorating animal health and increases in human illnesses and resistance rates. Conversely, a combination of continued prudent use of antibiotics to prevent and control animal infections, together with HACCP and other improvements, has been followed by large improvements in the microbial safety of chickens and other food animals in the United States, leaving both animals and people better off now than they were decades ago. A quantitative risk assessment model of microbiological risks (Campylobacter because of data availability) suggests that these outcomes may be more than coincidental: prudent use of animal antibiotics may actually improve human health, while bans on animal antibiotics, intended to be precautionary, inadvertently may harm human health.

Modeling Dose-response at Low Dose: A Systems Biology Approach for Ionization Radiation

For ionization radiation (IR) induced cancer, a linear non-threshold (LNT) model at very low doses is the default used by a number of national and international organizations and in regulatory law. This default denies any positive benefit from any level of exposure. However, experimental observations and theoretical biology have found that both linear and J-shaped IR dose-response curves can exist at those very low doses. We develop low dose J-shaped dose-response, based on systems biology, and thus justify its use regarding exposure to IR. This approach incorporates detailed, molecular and cellular descriptions of biological/toxicological mechanisms to develop a dose-response model through a set of nonlinear, differential equations describing the signaling pathways and biochemical mechanisms of cell cycle checkpoint, apoptosis, and tumor incidence due to IR. This approach yields a J-shaped dose response curve while showing where LNT behaviors are likely to occur. The results confirm the hypothesis of the J-shaped dose response curve: the main reason is that, at low-doses of IR, cells stimulate protective systems through a longer cell arrest time per unit of IR dose. We suggest that the policy implications of this approach are an increasingly correct way to deal with precautionary measures in public health.

Regulatory-Science: Biphasic Cancer Models or the LNT-Not Just a Matter of Biology!

There is no doubt that prudence and risk aversion must guide public decisions when the associated adverse outcomes are either serious or irreversible. With any carcinogen, the levels of risk and needed protection before and after an event occurs, are determined by dose-response models. Regulatory law should not crowd out the actual beneficial effects from low dose exposures—when demonstrable—that are inevitably lost when it adopts the linear non-threshold (LNT) as its causal model. Because regulating exposures requires planning and developing protective measures for future acute and chronic exposures, public management decisions should be based on minimizing costs and harmful exposures. We address the direct and indirect effects of causation when the danger consists of exposure to very low levels of carcinogens and toxicants. The societal consequences of a policy can be deleterious when that policy is based on a risk assumed by the LNT, in cases where low exposures are actually beneficial. Our work develops the science and the law of causal risk modeling: both are interwoven. We suggest how their relevant characteristics differ, but do not attempt to keep them separated; as we demonstrate, this union, however unsatisfactory, cannot be severed.

The Role of Linear and Non-Linear Dose-Response Models in Public Decision-Making (What to do When Uncertainty Affects Environmental Health Choices)

This Special Issue contains several articles that use theoretical and empirical findings about causation at low doses in an attempt to provide useful methodological insights to those concerned with making choices about the tolerable level of danger posed by carcinogens and toxic agents at very low exposures. The reason for our concern with the soundness of choices dealing with those exposures has been most vividly and tragically shown by the two natural events — earthquake and resulting tsunami — that caused the catastrophes that so greatly affect Japan. The nuclear power plans suffered failures that have had an almost immediate impact on the future of energy production and policies of countries that depend or consider on nuclear energy. Once again, the development and safety of nuclear power is questioned, in part because of the belief that very low exposure to the radionuclides emitted in those accidents causes cancers, regardless of dose. The question then is: Is there evidence—rather than either dogma or assumption or both—that low levels of exposure cause detriment to human health? Clearly, there is no argument that much larger exposures do cause cancer or can kill in very short order. In regulatory risk analysis, causation, through dose-response models, is part of the legal basis for justifying the reduction of exposures to hazardous agents likely to cause cancer. When a sufficiently large population is exposed to a very low (near-background) dose, even nearly infinitesimal excess individual risks can in principle cause a substantial number of additional cancer cases. In the aggregate, the overall expected number of cancer cases, while large, may still be generally undetectable, given the large background number of cancers in a population. To set environmental and occupational standards, the law couples legal causation and the “best science” about cause and effect to regulatory policy-making. The potential

CHANGING THE RISK PARADIGMS CAN BE GOOD FOR OUR HEALTH: J-SHAPED, LINEAR AND THRESHOLD DOSE-RESPONSE MODELS

Both the linear (at low doses)-no-threshold (LNT) and the threshold models (S-shapes) dose-response lead to no benefit from low exposure. We propose three new models that allow and include, but do not require – unlike LNT and S-shaped models — this strong assumption. We also provide the means to calculate benefits associated with bi-phasic biological behaviors, when they occur and propose: Three hormetic (phasic) models: the J-shaped, inverse J-shaped, the min-max, and Method for calculating the direct benefits associated with the J and inverse J-shaped models. The J-shaped and min-max models for mutagens and carcinogenic agents include an experimentally justified repair stage for toxic and carcinogenic damage. We link these to stochastic transition models for cancer and show how abrupt transitions in cancer hazard rates, as functions of exposure concentrations and durations, can emerge naturally in large cell populations even when the rates of cell-level events increase smoothly (e.g., proportionally) with concentration. In this very general family of models, J-shaped dose-response curves emerge. These results are universal, i.e., independent of specific biological details represented by the stochastic transition networks. Thus, using them suggests a more complete and realistic way to assess risks at low doses or dose-rates.

Water quality and non-point sources of risk: the Jiulong River Watershed, P. R. of China

Retrospective water quality assessment plays an essential role in identifying trends and causal associations between exposures and risks, thus it can be a guide for water resources management. We have developed empirical relationships between several time-varying social and economic factors of economic development, water quality variables such as nitrate-nitrogen, COD(Mn), BOD(5), and DO, in the Jiulong River Watershed and its main tributary, the West River. Our analyses used alternative statistical methods to reduce the dimensionality of the analysis first and then strengthen the studys causal associations. The statistical methods included: factor analysis (FA), trend analysis, Monte Carlo/bootstrap simulations, robust regressions and a coupled equations model, integrated into a framework that allows an investigation and resolution of the issues that may affect the estimated results. After resolving these, we found that the concentrations of nitrogen compounds increased over time in the West River region, and that fertilizer used in agricultural fruit crops was the main risk with regard to nitrogen pollution. The relationships we developed can identify hazards and explain the impact of sources of different types of pollution, such as urbanization, and agriculture.

Probabilistic Risk Assessment for Coastal Engineering Planning: A Case Study of Xiamen Bay, P. R. China

Coastal engineering planning (CEP) must deal with routine and non-routine hazardous conditions, particularly from cumulative hazards or from events with low probability but large consequences. We develop and exemplify a risk-based assessment to support coastal engineering planning, which is consistent with the precautionary principle, and provides scientific support for decision-making processes. Our approach, based on probabilistic risk assessment, PRA, methods, assesses the probable viability of nine engineering projects considered around Xiamen Bay, a major coastal city in Fujian province, PRC. We focus on these projects to exemplify the method and its results, and base our conclusions on the minimization of the hazardous conditions in Xiamen Bay.

Conflicts, Choices, and Solutions: Informing Risky Choices†

This article deals with key aspects of informing decision making of what may be the optimal choice, given a set of potential choices, unpredictable events, the value of the consequences (positive or negative) associated with each choice, and criteria for making the choice. This article introduces some of those criteria, methods and measures that can be used to inform policy maker relative to the set of options included in the analysis, and provides examples. n n nKeywords: n ndecision analysis; nrisk; ncriteria for choice; nequilibria