SHELscape is a spatially-explicit agent-based model for understanding short-run post-natural disasters non-linear adjustment processes in a multi-market framework.


SHELscape is a complex systems framework developed to understand patterns of post-natural disaster labor and goods movements and their impact on income and consumption distributions. The motivation for this research comes from a lack of baseline data in low-income regions where natural disasters usually affect a large population, and, with limited resources, policy response becomes a key challenge.

The model uses a bottom-up approach to define interactions at the micro agent-agent Level. The economy is programmed as primarily a rural agrarian society with multiple villages and cities. Each location reaches its own stable equilibrium in the goods and the labor markets which determines price and wages, that in turn determine income and consumption distributions. Locations interact with each other through migration and regional export of goods resulting in meso-level stable trends at the regional level.

The system can be shocked through various channels including disruption of food production, loss of human life, disruption of road networks, and productivity loss. Agents adapt to the changing environment, which allows regional-level patterns of population displacement, and income and consumption distributions to be tracked and clusters of vulnerability to be identified.


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Naqvi, A., Gaupp, F., & Hochrainer-Stigler, S. (2020).The risk and consequences of multiple breadbasket failures: an integrated copula and multilayer agent-based modeling approach. OR Spectrum, 42: 727–754.

Naqvi, A. (2017). Deep Impact: Geo-Simulations as a Policy Toolkit for Natural Disasters. World Development, 99: 395-418.

Naqvi, A., & Rehm, M. (2014). A multi-agent model of a low income economy: simulating the distributional effects of natural disasters. Journal of Economic Interaction and Coordination, 9: 275–309.

Naqvi, A., & Rehm, M. (2014). Simulating natural disasters - A complex systems framework. 2014 IEEE Conference on Computational Intelligence for Financial Engineering & Economics (CIFEr), London, England.

Naqvi, A., & Sobiech, C. (2010). Simulating Humanitarian Crisis and Socio-Economic Vulnerability: Applications of Agent Based Models. Published in collection “Tipping Points in Humanitarian Crisis: From Hot Spots to Hot Systems”. United Nations University – Institute for Environment and Human Security (UNU-EHS) SOURCE 13.