Courses in Catastrophe Modeling and Resilience at Lehigh University

Example Courses

CAT 401: Catastrophe Modeling and Resilience

The course introduces students from a diverse set of backgrounds (engineering, natural sciences, computer science, math, economics) to the fundamental concepts, terminology, methods, tools, and general framework of this growing field. Students learn how to model hazard, fragility, vulnerability, disaster recovery, and losses in a probabilistic way. They also learn how to present and communicate their results in a way that is useful for decision making, to have a direct impact on policies, prioritize investments, plan mitigation actions, and implement adaptation and preparedness strategies. Throughout the course, students learn how to use catastrophe risk and resilience modeling software and databases. The course provides training also on general topics like research methods and scientific communication. Special lectures address complementary topics, such as the effect of climate change, as well as societal impact and ethical concerns raised by catastrophe insurance and resilience enhancement. Guest lectures offered by experts from the public sector and private sector provide insight on how the concepts and tools learned in class are applied every day in various contexts and inspire the students on potential career options. A term project replaces the final exam and completes the course, offering the student the opportunity to showcase what they learned during the semester.

Advanced analyses of various applications of catastrophe models, such as natural disasters or health-related threats to inform management and policies. Course activities include 

1. Reading recent publications on catastrophe model development, application and limitations 

2. Practical exercises, in-class and as homework, about deterministic and stochastic model construction 

3. Result visualization of disaster impacts via geographic information systems. 

Theory and context-dependent practical problems on catastrophe model parameterization are covered. 

Introduces tools from financial mathematics necessary for insurance applications. It presents the basic mathematics of interest rates and investments, such as present value, annuity calculations, and bond valuation. An introduction to modeling claims with Markov chains and Poisson processes will be presented. In a second part, the course will also introduce some of the standard models used in risk modeling, such as no-arbitrage pricing for derivatives and the Black-Scholes model. Fixed-income markets models are also discussed briefly. The course will focus on the interpretation of the models, and some practical numerical aspects. 

Students work individually or in teams, integrating knowledge and skills acquired in their prior course work, to develop catastrophe models or perform resilience assessment for realistic scenarios and applications. Projects will be inspired by and possibly conducted in collaboration with partners from private sector, public sector, or academia. The students will produce written reports and/or oral presentations, as appropriate for the project.

A study of selected topics in catastrophe modeling and resilience, applied to any field of interest to the student. The research may include methodological advancements, new findings, or extensions to the scope of application of known techniques.

The computational analysis of data to extract knowledge and insight. Exploration and manipulation of data. Introduction to data collection and cleaning, reproducibility, code and data management, statistical inference, modeling, ethics, and visualization. Not available to undergraduate students.