Abstract
Background: This study explores how the Roma in Romania, the EU's most concentrated population, are faring in terms of a number of quality of life indicators, including poverty levels, healthcare, education, water, sanitation, and hygiene. It further explores the role of synthetic populations and modelling in identifying at-risk populations and delivering targeted aid. Methods: 135 surveys were conducted across five geographically diverse Romanian communities. Household participants were selected through a comprehensive random walk method. Analyses were conducted on all data using Pandas for Python. Combining land scan data, time-use survey analyses, interview data, and ArcGIS, the resulting synthetic population was analysed via classification and regression tree (CART) analysis to identify hot-spots of need, both ethnically and geographically. Results: These data indicate that the Roma in Romania face significant disparities in education, with Roma students less likely to progress beyond 8 th grade. In addition, the Roma population remains significantly disadvantaged with regard to safe and secure housing, poverty, and healthcare status, particularly in connection to diarrheal disease. In contrast, however, both Roma and non-Roma in rural areas face difficulties regarding full-time employment, sanitation, and water, sanitation, and hygiene infrastructure. In addition, the use of a synthetic population can generate information about 'hot spots' of need, based on geography, ethnicity, and type of aid required. Conclusions: These data demonstrate the challenges that remain to the Roma population in Romania, and also point to the myriad of ways in which all rural Romanians, regardless of ethnicity, are encountering hardship. This study highlights an approach that combines traditional survey data with more wide-reaching geographically based data and CART analysis to determine 'hot spot' areas of need in a given population. With the appropriate inputs, this tool can be extrapolated to any population in any country.
Highlights
In the years that followed independence and the democratic election of 1990, the southeastern European country of Romania received significant aid from the International Monetary Fund (IMF), World Bank (WB), European Bank for Reconstruction and Development (EBRD), European Investment Bank (EIB), the US Agency for International Development (USAID), and other donors[1]
International aid agencies and non-governmental organizations often employ assessment surveys and interviews to determine the type and level of need in a particular area or for a disadvantaged population[14]. While such methods are useful for specific communities ‘of interest’ and can provide statistical support for straightforward claims or goals, they are of little use in identifying new areas and populations in need or addressing multi-faceted and complex issues. This proofof-concept study explores the possibility of using a synthetic representation of Romania to predict currently unrecognized areas of need based on key variables from an assessment survey and a classification and regression tree (CART) analysis
Regional survey We developed our survey by combining questions adapted from a validated WASH survey previously used for multiple use service strategy research and the WHO core questions on drinking-water and sanitation[15] with questions related to demographics, socio-economic status, and healthcare access and history, we conducted 135 surveys each consisting of 56 total questions across five geographically diverse communities throughout Romania
Summary
In the years that followed independence and the democratic election of 1990, the southeastern European country of Romania received significant aid from the International Monetary Fund (IMF), World Bank (WB), European Bank for Reconstruction and Development (EBRD), European Investment Bank (EIB), the US Agency for International Development (USAID), and other donors[1]. In the 1990’s and early 2000’s, vaccination rates, for measles, improved to around 98 per cent, up from less than 70 per cent at the time of independence; HIV/AIDS cases have decreased and life expectancy for those living with HIV has increased dramatically; and there has been a significant decrease in domestic violence[2] For such assessments, international aid agencies and non-governmental organizations often employ assessment surveys and interviews to determine the type and level of need in a particular area or for a disadvantaged population[14]. International aid agencies and non-governmental organizations often employ assessment surveys and interviews to determine the type and level of need in a particular area or for a disadvantaged population[14] While such methods are useful for specific communities ‘of interest’ and can provide statistical support for straightforward claims or goals, they are of little use in identifying new areas and populations in need or addressing multi-faceted and complex issues.
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