Data Driven Vulnerability Outlook on Beirut’s Neighborhoods
Post blast Beirut leads to a long road into Reform, Recovery and Reconstruction. UNDP’s "Leave No One Behind" report released in September 2020 outlines 7 requirements to an inclusive and just recovery process. One key requirement being, that all efforts are people centered and data driven at the same time, rather than building centered and reconstruction based.
The below is an extract of the Accelerator Lab’s effort to build an interactive story page which uses spatial data analysis as a proxy to identify where the most vulnerable groups exist within the city’s neighborhoods. We also developed a multidimensional vulnerability index (MVI) to assess intersectional vulnerabilities at the household level, and then aggregate to the neighborhood level. The dataset used is mainly the socio-economic impact assessment (SEIA) that was conducted after the blast on the week of 17 August 2020*.
Socio Economic Impact Assessment (SEIA)
After the August 4th Explosion, UNDP Lebanon with support from UNDP surge Data Hub conducted a Socio-Economic Impact Assessment (SEIA) to assess the impact of the blast. The self-reported survey submissions were collected over a period of 6 days (week of 17 August 2020) using a combination of Facebook Ads, Google display ads, phone call surveys, and SMS. All channels targeted those located in or surrounding the geographic area of the blast and surrounding neighborhoods of Beirut.
To ensure a post-blast recovery process that is inclusive and just, it is essential to design a holistic response that addresses all different types of vulnerabilities, and incorporates social groups with the most intersecting vulnerabilities. These measures need to integrate the multiple timescales at which a recovery is designed, particularly an immediate –emergency- response and a long-term response.
As such, our work on SEIA was based on the need to collect disaggregated socio-economic and geo-referenced data that identifies people’s multiple indicators of vulnerability, namely: age, gender, nationality, race, location of residence and work, income, occupation, education, family status, physical and mental health status, tenure status, etc.
This data can help understand which people face multiple compounding disadvantages and identify the barriers to reducing their vulnerabilities. Through the examination of such people- driven data, deprived and marginalized social groups can be empowered through civic engagement, integrated and just policies, interventions and budgets can be voiced and enacted.
This rapid process resulted in 5,901 households surveyed / 3,680 businesses surveyed
*For surveys such as the SEIA, a sample of people are assessed instead of all inhabitants, which can only be achieved through a census. While censuses offer comprehensive and valuable information, they are relatively extremely costly and take years to plan for and to conduct. In disaster situations, a well-designed survey provides essential information within a short time frame to allow for rapid response. The SEIA dataset is self-reported and collected online, which means it cannot be comprehensively representative, in all data analysis, it is essential to understand the accuracy of the results. SEIA was collected within weeks of the blast, reaching approximately 6,000 people, which is a considerable sample size and allows for insights to be generated at the Beirut level.