Insurance against disasters plays a critical role in community recovery by providing policyholders with reliable and timely payments for repairing or reconstructing damaged houses. By allowing homeowners to transfer risk, insurance enables homeowners to address house without experiencing significant financial burdens. Although historical events have highlighted the importance of insurance, its quantitative impact on community recovery, particularly in tornado-impacted communities, is understudied. This study focuses on advancing our understanding of whether sufficiently insured houses can have a positive impact on the recovery of tornado-impacted communities (i.e., the main research question). This paper proposes a two-stage simulation framework to quantitatively evaluate the effects of insurance on community recovery. In the first stage of the framework, we developed statistical models to estimate homeowners' insurance decisions prior to a tornado event. In the second stage, we examined the effects of insurance on various aspects of community recovery. To develop empirical and statistical models regarding insurance decisions and their impacts on housing recovery, we collected data through online surveys targeting residents whose properties were damaged by the tornadoes that occurred in May 2019 in the United States. Finally, the proposed simulation framework was applied to the City of Dayton, Ohio following those May 2019 tornado events to address the main research question. The results of the simulation concluded that sufficiently insured houses can have a positive impact on community recovery and highlighted the need for effective policies and economic incentives to encourage individuals to purchase insurance.


Civil, Architectural and Environmental Engineering


Federal Emergency Management Agency, Grant 1635593

Keywords and Phrases

Community resilience; Housing recovery; Insurance; Quantitative analysis; Survey; Tornado

International Standard Serial Number (ISSN)

1573-0840; 0921-030X

Document Type

Article - Journal

Document Version


File Type





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Publication Date

01 Jan 2024