A probabilistic epidemiological model for infectious diseases: The case of COVID-19 at global-level

This study has developed a probabilistic epidemiological model a few weeks after the World Health Organization declared COVID-19 a pandemic (based on the little data available at that time). The aim was to assess relative risks for future scenarios and evaluate the effectiveness of different management actions for 1 year ahead. We quantified, categorized, and ranked the risks for scenarios such as business as usual, and moderate and strong mitigation. We estimated that, in the absence of interventions, COVID-19 would have a 100% risk of explosion (i.e., more than 25% infections in the world population) and 34% (2.6 billion) of the world population would have been infected until the end of simulation. We analyzed the suitability of model scenarios by comparing actual values against estimated values for the first 6 weeks of the simulation period. The results proved to be more suitable with a business-as-usual scenario in Asia and moderate mitigation in the other continents. If everything went on like this, we would have 55% risk of explosion and 22% (1.7 billion) of the world population would have been infected. Strong mitigation actions in all continents could reduce these numbers to, 7% and 3% (223 million), respectively. Although the results were based on the data available in March 2020, both the model and probabilistic approach proved to be practicable and could be a basis for risk assessment in future pandemic episodes with unknown virus, especially in the early stages, when data and literature are scarce.     

Assessment of ductile dike behavior as a novel flood risk reduction measure

Dikes are an effective flood risk reduction measure in deltaic areas. Present risk analyses consist often of decoupled calculations of probabilities of dike failure and calculation of consequences of flooding given dike failure. However, the flood defense design determines not only the probability of failure, but influences the consequences of flooding as well. Especially when the dike has a ductile failure and breach growth behavior, due to a structural robust design, the consequences of flooding reduce. In this article, we present a novel assessment of risks and investments, valuing structural robustness of a construction type, represented by its ductile behavior during high loads. Therefore, the consecutive occurrence of initial dike failure mechanisms, failure path development, breach growth, and consequences is modeled integral and time-dependent. The investments consist of the costs to reinforce or reconstruct the flood defense to behave relatively ductile. This integral assessment enables to compare flood impacts of different construction types and different dimensions of designs. We applied it on a case in a riverine area in the Netherlands. The results show that the total societal costs and the individual risks on victims are very dependent on the construction type. The risk profile of a polder protected by a brittle or a ductile dike differs significantly. The brittle sand dike in the case requires larger dimensions than the more ductile dike with a clay core.     

Preference for Flexibility in a Savage Framework

We study preferences over Savage acts that map states to opportunity sets and satisfy the Savage axioms. Preferences over opportunity sets may exhibit a preference for flexibility due to an implicit uncertainty about future preferences reflecting anticipated unforeseen contingencies. The main result of this paper characterizes maximization of the expected indirect utility in terms of an ‘Indirect Stochastic Dominance’ axiom that expresses a preference for ‘more opportunities in expectation.’ The key technical tool of the paper, a version of Möbius inversion, has been imported from the theory of nonadditive belief functions; it allows an alternative representation using Choquet integration, and yields a simple proof of Kreps' (1979) classic result.