Estimating Downtime in Loss Modeling

Abstract

Downtime includes the time necessary to plan, finance, and complete repairs on facilities damaged in earthquakes or other disasters. It is an essential component of loss modeling, because it is one measure of operational failure in lifelines and business interruption in buildings. Data from building repairs after the Loma Prieta and Northridge earthquakes, together with institutional risk management projections are used to define the rational and irrational components of downtime for buildings. Rational components include construction costs and time. Irrational situation-specific components take into account the time needed to mobilize for repairs and include financing, relocation of functions, workforce availability, regulatory changes, and economic uncertainty. To quantify these factors, the pace of recovery can be linked to the scale of damage in a stock of buildings in the affected region.

Downtime Estimation for Resilience Assessment Accounting External Factors

“…The repair time is equal to the estimated construction time, whereas the extensive damage state also includes the time for activities such as finance, design, and permits [4]. Such activities have been acknowledged by Comerio [5] as "irrational" components, which include four issues dominating the preconstruction period: (1) the need to secure financing, (2) the ability to relocate building functions, (3) the availability of labor, and (4) economic and regulatory uncertainties. According to Comerio, total downtime is the aggregation of rational and irrational components.…”

Post-Earthquake Recovery of a Community and Its Electrical Power Supply System

“…Different values can be assigned to the parameters depending on the damage state of the components. This allows taking into consideration that heavily damaged components need a longer time to repair than slightly damaged ones [7]. If new information becomes available, all parameters can easily be updated and different recovery speeds can be simulated by simply adapting the parameters of the recovery functions.…”

“…The recovery of the EPSS and the community it supplies to are modeled using different settings ( The mean and standard deviation of the different lognormal component recovery functions of Setting 1 (the 'reference scenario') are estimated for each damage state of each component using existing data for recovery rates from natural hazards [3,7,20]. To account for the longer reconstruction time and uncertainties for severely damaged components, it is assumed that the mean and standard deviation for recovery functions from DS3 back to DS1 are considerably higher as those from DS2 back to DS1 [7].…”

“…To account for the longer reconstruction time and uncertainties for severely damaged components, it is assumed that the mean and standard deviation for recovery functions from DS3 back to DS1 are considerably higher as those from DS2 back to DS1 [7].…”

Organisational resilience following the Darfield earthquake of 2010

“…Indirect losses related to disasters emerge throughout the recovery period. Comerio (2006), for instance, states that organisational downtime required to plan, finance, and complete repairs, temporary relocation costs, and the need for additional human resources to facilitate recovery work are a real and quantifiable cost of earthquakes. Several studies have also documented the major financial ramifications of critical service infrastructure (lifelines) disruptions, which cause businesses to shut down or operate less efficiently (Kroll et al, 1991;Alesch et al, 1993;Tierney and Nigg, 1995;Webb, Tierney, and Dahlhamer, 1999).…”