The NIH-funded KATRINA@10 Program consists of an interrelated set of three primary data collection projects that focus on specific sub-populations who were uniquely affected by Hurricane Katrina: households along Louisiana and Mississippi's Gulf Coast, low-income parents from New Orleans, and Vietnamese families living in New Orleans. In addition, the program contains two secondary analyses of data that are more broadly representative of the overall affected population, and three cores (Administrative, Data Collection, Data Management and Dissemination) to support the set of research projects. The following research questions represent the studies together as a whole: How well does the Socio-ecological model of Disaster Recovery developed by the research team (Abraham et al. 2010) predict recovery across the three cohort studies? How do trajectories of long-term recovery differ among and within these sub-populations? How do the trajectories of recovery compare to those of mainstream populations? How of the effects of pre-disposing factors (such as poverty) and degree-of-impact (such as flooding depth) vary among the three sub-populations? How do interpretations of the disaster, resilience, and recovery differ among respondents? What are the determinants of long-term recovery in domains such as mental and physical health, socio-economic status, and community and social roles? How are these domains related to each other across individuals and across sub-populations? This collection contains data from the Resilience in Survivors of Katrina (RISK) Project, which was a longitudinal study of low-income parents who lived in New Orleans at the time of Hurricane Katrina (August 2005). The initial study design was intended to increase educational attainment among college students, measuring economic status, social ties, and mental and physical health starting in 2003 (initial cohort n=1,019). However, with the aftermath of Hurricane Katrina, the research design evolved to study the consequences of a disaster for the lives of vulnerable individuals and their families. Follow-up surveys and in-depth qualitative interviews were conducted with participants at one year and five years post-Katrina, regardless of where participants lived. The data in this collection is from the most recent survey follow-up with RISK Project participants (n=716), conducted between 2016 and 2018. A public-use version (DS1) and restricted-use version (DS2) are available. Open-ended responses and continuous variables for respondent age and total household income have been masked in the public-use version; these items are available in the restricted-use version.

The purpose of this study, Proposed Locations for FEMA Trailers in Post-Katrina New Orleans, 2005-2006, is to understand the factors affecting decision makers who sought to place travel trailers in the New Orleans, LA area post-Hurricane Katrina. This data set captures the number of temporary trailers and temporary trailer sites per zip code that were proposed by the Federal Emergency Management Agency (FEMA) in conjunction with the New Orleans city government. Based on the TAC-RC-IA Priority Sites Report (Master Copy) dated 29 June 2006, this data set also p rovides demographic, socioeconomic, geographic, political, and civil society measures for 114 zip codes in and around metropolitan New Orleans, Louisiana where those trailers could have been placed. Demographic information includes population, voting age population, elderly population, and population density per zip code. Geographic measures include the area of the zip code in square miles along with three different measures for water damage and flooding per zip code. Socioecon omic indicators include median house prices, income, percentage of individuals attending college, percentage non-white, percentage of families below the poverty line, and percentage unemployed per zip code. Following Hamilton (1993), we measure civil society mobilization potential through voter turn out. Note that this data set does not capture the areas that, in the end, received trailers. Rather, it can be used to test the siting heuristics used by decision makers in the post- Katrina environment when many local communities in the area publicly expressed their opposition to have trailers and trailer parks put in their back yards. The list of proposed sites can be analyzed to understand which areas city and government planners believed would be most amenable to these controversial facilities in the post-Katrina environment.

The NIH-funded Katrina@10 Program consists of an interrelated set of three primary data collection projects that focus on specific sub-populations who were uniquely affected by Hurricane Katrina: households along Louisiana and Mississippi's Gulf Coast, low-income parents from New Orleans, and Vietnamese families living in New Orleans. In addition, the program contains two secondary analyses of data that are more broadly representative of the overall affected population, and three cores (Administrative, Data Collection, Data Management and Dissemination) to support the set of research projects. The following research questions represent the studies together as a whole: How well does the socio-ecological model of disaster recovery developed by the research team (Abramson et al. 2010) predict recovery across the three cohort studies? How do trajectories of long-term recovery differ among and within these sub-populations? How do the trajectories of recovery compare to those of mainstream populations? How do the effects of predisposing factors (such as poverty) and degree-of-impact (such as flooding depth) vary among the three sub-populations? How do interpretations of the disaster, resilience, and recovery differ among respondents? What are the determinants of long-term recovery in domains such as mental and physical health, socio-economic status, and community and social roles? How are these domains related to each other across individuals and across sub-populations? The Katrina Impacts on Vietnamese Americans in New Orleans (KATIVA NOLA) study was a longitudinal study interested in measuring the impact of Hurricane Katrina on Vietnamese-Americans living in New Orleans. The original sample was taken in summer 2005 and was followed by three rounds of short and medium-term data collection in the 5 years following Katrina. This study measured a variety of outcomes, including physical and mental health, economic stability, housing stability, and social ties, to examine the long-term recovery trajectories of participants. The data in this collection are from an additional, long-term follow-up survey conducted between 2017 and 2019. A public-use version (DS1) and restricted-use version (DS2) are available. Open-ended responses, continuous respondent age, continuous total household income, and a variable indicating exposure to specific flood events have been masked in the public-use version. These items are available in the restricted-use version.

Background characteristics of the African American and Vietnamese American participants in 2007 and 2018, applying bivariate analysis.

This dataset describes Airbnb homestay listing activity in New Orleans, Louisiana. Compiled on 7 November 2021, it is part of the Inside Airbnb initiative, which aims to quantify the impact of short-term rentals on housing and residential communities. The data includes listing details and reviews, with personally identifying information removed.

It offers insights into the New Orleans short-term rental market, a city significantly impacted by Hurricane Katrina and subsequent redevelopment efforts, which have raised concerns about gentrification and resident displacement. The dataset allows users to explore fundamental questions about Airbnb's presence, such as the number of listings in a neighbourhood, how many properties are rented to tourists versus long-term residents, host earnings, and the prevalence of hosts operating multiple listings. It can also inform discussions around city and state legislation concerning residential housing, short-term rentals, and zoning.

Columns

• id: Airbnb's unique identifier for each listing.
• name: The name given to the listing.
• description: A detailed account of the listing.
• neighborhood_overview: The host's description of the local area.
• host_id: Airbnb's unique identifier for the host or user.
• host_since: The date the host or user account was created. For hosts who also use Airbnb as guests, this may be their guest registration date.
• host_location: The self-reported location of the host.
• host_response_time: The average duration it takes for a host to reply to a message on the Airbnb platform.
• host_response_rate: The percentage of messages a host responds to on the Airbnb platform.
• host_acceptance_rate: The rate at which a host accepts booking requests.

Distribution

The dataset is provided in CSV format, including new_orleans_airbnb_listings.csv and reviews.csv. Specific total row or record counts are not available within the provided information.

However, details on value distribution for certain columns are present: * host_id: 5,752 unique values. * host_location: 5,487 unique values, with 68% reporting 'New Orleans, Louisiana, United States', 12% from 'US', and 20% from 'Other'. * host_response_time: 61% of hosts respond 'within an hour', with 26% being null. * host_response_rate: 58% of hosts have a '100%' response rate, with 26% being null. * host_acceptance_rate: 28% of hosts have a '100%' acceptance rate, with 24% being null. * host_since dates range from 13 December 2008 to 20 October 2021.

Usage

This dataset is ideal for: * Predicting short-term rental charges in New Orleans based on location and amenities. * Describing the 'vibe' of each neighbourhood using listing descriptions, suitable for Natural Language Processing (NLP) tasks. * Identifying the most common amenities offered in short-term rental listings. * Determining factors that contribute to popular or highly-rated listings. * Analysing differences in favourability among different New Orleans neighbourhoods. * Exploratory Data Analysis (EDA) and Regression modelling. * Researching the impact of short-term rentals on housing affordability and community dynamics.

Coverage

The dataset focuses on New Orleans, Louisiana, United States. It covers a time range for host activity from 13 December 2008 to 20 October 2021, with the data compilation date being 7 November 2021. While not directly demographic, the context addresses concerns about gentrification and the displacement of longtime residents in the city.

License

CC-BY

Who Can Use It

• Data Scientists and Analysts: For data science projects, statistical analysis, machine learning model building, and deriving insights from listing and review data.
• Urban Planners and Policy Makers: To understand the spread of short-term rentals, their impact on local housing markets, and to inform regulations and zoning decisions.
• Researchers and Activists: Studying the socio-economic effects of tourism and short-term rentals on urban communities, particularly concerning housing and gentrification.
• Real Estate Professionals: To gain market intelligence on short-term rental trends, pricing, and amenities in New Orleans.
• Hospitality Industry Stakeholders: To analyse competition and market demand in the New Orleans accommodation sector.

Dataset Name Suggestions

• New Orleans Airbnb Listings and Reviews
• New Orleans Airbnb Host and Listing Data
• NOLA Airbnb Activity Dataset
• Inside Airbnb New Orleans
• New Orleans Short-Term Rental Analysis Data

Attributes

Original Data Source: New Orleans Airbnb Listings and Reviews

Differences of post-disaster mental health between African American and Vietnamese American participants using a combined 2007 and 2018 dataset (N = 253), applying generalized estimating equations models.