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Advanced biological information such as computational biology, in vitro transformation assays, genome pathway analysis, genotoxicity assays, proteomics, gene expression, cell signaling disruption and hormone receptors offer the poten- tial for significant improvements in the ability of regulatory agencies to consider the risks of the thousands of compounds—and mixtures of compounds—currently unexamined. While the science for performing the assays underlying such information is developing rapidly, there is significantly less understanding of the rationality of using these data in specific decision problems. This paper explores these issues of rationality, identifying the issues of rationality that remain to be developed for applications in regulatory risk assessment, and providing a draft decision framework for these applications. The conclusion is that these rapid, high throughput methods hold the potential to significantly improve the protection of public health through better understanding of risks from compounds and mixtures, but incorporating them into existing risk assessment methodologies requires improvements in understanding the reliability and rates of Type I and Type II errors for specific applications.
A variant of the Adaptive Regional Input-Output model (ARIO) has been developed to explore the sensitivity of the London economy to loss of production capacity in sectors affected by climate change related damage. The model is designed for linking to an Event Accounting Matrix (EAM) produced by climate and engineering teams, and then follow this damage through direct and indirect losses in the economy during a recovery process that is either demand-led (in which recovery of production capacity takes place only as demand recovers) or investment-led (where recovery of production capacity can precede demand). Outputs from the model are used to assess the relative vulnerability of London’s economy to production capacity (Capital stock) loss in each of the 42 economic sectors, for purposes of identifying where to most effectively allocate resources to climate change adaptation strategies or to recovery operations when used in conjunction with an EAM. Measures of impact related to GDP loss, recovery time and the ratio of indirect to direct losses are developed for these scenarios. Results show that indirect losses are a significant component of total losses, with a multiplier of between 1.3 and 2 depending on the scale of initial damage.