|The NSF-funded study being done by Ole Miss on
Katrina’s impacts is testing a hypothesis that examines the effect of
involvement in social networks on a person’s response to the impact of
Katrina. However, in examining this hypothesis the study is generating
data in a three-step process that provide an empirical estimate of
housing and population effects in the Mississippi Gulf Coast area at
the epicenter of Katrina’s impact:
(1) We can compare our housing unit counts with those from Census 2000 on a block-by-block basis and account for any change between census 2000 and August 29th, 2005. This gives empirical numbers for the absolute and relative numbers of total houses that were destroyed and damaged by type of housing unit.
(2) From our survey data we can develop person per household (PPH) estimates by type of unit (e.g., permanent- single unit; permanent-multiple unit; temporary). We can apply the PPH estimates to the occupied housing stock we have counted to get population estimates for the entire study area and its sub-areas, which will yield estimated population changes after census 2000 that are due to Katrina.
(3) Also from our survey data, we then develop estimates of the composition (e.g., age-sex, and race) of the population in the study area and its sub-areas. We can compare these numbers to those from the 2000 census to examine changes in the composition of the population in the study area that are due to Katrina.
The preceding estimates can be combined with the results of our hypothesis test to assist in identifying the roles that social networks or the lack thereof play in how people respond to a large-scale natural disaster. These results can then be linked to current Census Bureau data such as provided by the American Community Survey to target populations that are likely to have poor responses to large scale natural disasters. For example, if we learn that elderly people who recently moved to the Mississippi Gulf Coast lack strong local social networks and that these same people did not fare as well as those with strong local social networks, then we can use Census Bureau data to identify areas where concentrations of elderly in-migrants live so that programs designed to provide them with access to social networks can be targeted in a cost-effective manner.