This study analyzed the content of Twitter data collected during Hurricane Harvey to identify the data of the highest relevance for assessing the impacts on infrastructure through automatically grouping the tweets by topics of discussion.
Respondents with the greatest economic and mental health impacts from Hurricane Harvey were respectively four times more likely to experience income loss during the pandemic and five times more likely to suffer severe anxiety because of the pandemic.
Researchers discovered that, on average, 75% of the chemicals detected in two measurements were found in higher concentrations immediately after the hurricane. People’s baseline exposure, however, was already high.
The research team ran an large-area surveys of firms affected by Superstorm Sandy and Hurricane Harvey and found that for every dollar spent on resilience, firms avoided an average of $4.57 in business interruption losses.
Using the 2017 Hurricane Harvey flood event as a test case, this study set up a series of sensitivity analyses to highlight three challenges associated with large‐scale flood inundation modeling, including (a) model parameterization, (b) errors in digital
This paper examines the link between property damage, flood insurance, and mortgage credit risk using a unique, loan-level database that combines post-disaster home inspection data, flood zone designations, and loan performance measures in the area
This paper proposes and tests a multilayer framework for simulating the network dynamics of inter-organizational coordination among interdependent infrastructure systems (IISs) in resilience planning. Inter-organizational coordination among IISs (such