Search Results (8)

This study aims to quantify the extent to which poor households receiving cash support from the Vision Umurenge Programme (VUP) allocate their income across major spending categories, mainly consumption, savings, household-level investment, and cash transfers for community participation. The analysis utilises a nationally representative panel dataset of 1642 respondents, collected between 2013 and 2017. A Maximum Likelihood Method (MLM) approach was employed to model four financial behaviours: (i) saving, (ii) consumption, (iii) investment, and (iv) social transfers as a proxy for community participation. The independent variables include the monetary benefits received by individuals over different periods, alongside demographic characteristics such as gender, age, education level, and area of residence (rural–urban), which were controlled in the analysis. The findings reveal a positive and statistically significant effect of the direct cash support provided by the VUP on increased consumption, and marginal effects on individual savings and investment behaviours. However, the data do not provide sufficient evidence to conclusively establish a relationship between participation in the VUP and cash transfers for community participation. The study recommends the intensification of efforts to engage in saving as way to build resilience, and further suggest a periodic increase in the VUP benefits’ size to cushion inflation effects. Full article

Somalia experienced its first wave of COVID-19 infections in March 2020 and has experienced fluctuating infection levels since. Longitudinal data on suspected cases of COVID-19, attitudes, and behaviours were collected by telephone interviews of cash-transfer programme beneficiaries from June 2020–April 2021. A multi-media Social and Behaviour Change Communication (SBCC) campaign was designed and implemented from February 2021 to May 2021. Between the end of the first wave and the onset of the second the perceived threat from COVID-19 increased, with the proportion of respondents viewing it as a major threat increasing from 46% to 70% (p = 0.021). Use of face coverings increased by 24% (p < 0.001) and hand shaking and hugging for social greeting decreased, with 17% and 23% more people abstaining from these practices (p = 0.001). A combined preventative behaviour score (PB-Score) increased by 1.3 points (p < 0.0001) with a higher score in female respondents (p < 0.0001). During wave 2, vaccine acceptance was reported by 69.9% (95% CI 64.9, 74.5), overall. Acceptance decreased with increasing age (p = 0.009) and was higher in males (75.5%) than females (67.0%) (p = 0.015). Awareness of the SBCC campaign was widespread with each of the 3 key campaign slogans having been heard by at least 67% of respondents. Awareness of 2 specific campaign slogans was independently associated with an increased use of face coverings (aOR 2.31; p < 0.0001) and vaccine acceptance (aOR 2.36; p < 0.0001). Respondents reported receiving information on the pandemic from a wide range of sources with mobile phones and radio the most common. Trust in different sources ranged widely. Full article

Payment apps and digital wallets are powerful tools used to exchange e-money via the internet. However, with the progressive disappearance of cash, there is a need for the digital equivalent of physical banknotes to guarantee the same level of anonymity of private payments. Few efforts to solve the double-spending problem exist in P2P payments (i.e., in avoiding the possibility of a payer retaining copies of digital coins in absence of a trusted third party (TTP)), and further research efforts are needed to explore options to preserve the privacy of payments, as per the mandates of numerous central bank digital currency (CBDC) exploratory initiatives, such as the digital euro. Moreover, generic programmability requirements and energetic impacts should be considered. In this paper, we present a sustainable offline P2P payment scheme to face the double-spending problem by means of a one-time program (OTP) approach. The approach consists of wiping the business logic out of a client’s app and allowing financial intermediaries to inject a certified payment code into the user’s device, which will execute (asynchronously and offline) at the time of payment. To do so, we wrap each coin in a program at the time of withdrawal. Then the program exploits the trusted execution environment (TEE) of modern smartphones to transfer itself from the payer to the payee via a direct IoT link. To confirm the validity of the approach, we performed qualitative and quantitative evaluations, specifically focusing on the energetic sustainability of the proposed scheme. Results show that our payment scheme is energetically sustainable as the current absorbed for sending one coin is, at most, ~1.8 mAh on an Apple smartphone. We advance the state-of-the-art because the scheme meets the programmability, anonymity, and sustainability requirements (at the same time). Full article

Background: Adolescents who are socially excluded are at increased risk of mental health problems such as depression and anxiety. Promoting social inclusion could be an effective strategy for preventing and treating adolescent depression and anxiety. Methods: We conducted a systematic review of intervention studies which aimed to prevent or treat adolescent depression and/or anxiety by promoting social inclusion. Throughout the review we engaged a youth advisory group of 13 young people (aged 21–24) from Uganda, Turkey, Syria, South Africa, and Egypt. Results: We identified 12 studies relevant to our review. The interventions tested use a range of different strategies to increase social inclusion and reduce depression and anxiety, including social skills training, psychoeducation, teaching life skills training, and cash transfers. Pooled standardised mean differences (SMDs) based on random-effects models showed medium-to-large benefits of interventions on improving depression and anxiety symptoms (n = 8; SMD = −0.62; 95% CI, −1.23 to −0.01, p < 0.05). Conclusion: Although there are not many studies, those which have been done show promising results that strongly suggest that social inclusion could be an important component of programmes to promote adolescent mental health. Full article

The effects of nutrition counselling (NC) and unconditional cash transfer (UCT) in improving growth in children under five and household food security are poorly understood in humanitarian settings. Therefore, this study aimed to evaluate the effects of NC and NC combined with unconditional cash transfer (NC + UCT) on children’s growth and food security in Somalia. The study was performed with a quasi-experimental design in two districts in the Banadir region of Somalia. Caregivers (n = 255) with mildly to moderately malnourished children aged 6 to 59 months old (n = 184) were randomized to the NC, NC + UCT and control groups. The interventions consisted of weekly NC for three months alone or in combination with UCT. The outcome variables were wasting, underweight, stunting, and food security. Difference-indifferences analysis was used to estimate the effect of the interventions. Our study did not find any significant impacts of NC or NC + UCT on child wasting, underweight, stunting, food security or household expenses. In conclusion, NC, alone or in combination with UCT, did not impact children’s growth or household food security. Thus, a culturally tailored NC programme over a longer period, supplemented with cash transfer, could be beneficial to consider when designing interventions to reduce malnutrition and food insecurity. Full article

Communities in major cities in developing countries may experience economic vulnerability, which has detrimental consequences for maternal and child health. This study investigated individual-, household-, and community-level factors associated with child growth and resilience of early-grade learners aged 6 to 8 years. Demographic characteristics, depression scale, child wellbeing, and anthropometric measurements were collected on a sample of 162 caregiver–child pairs (children 46% female) who receive the child support grant (cash transfer programme) from five low-income urban communities in the City of Johannesburg, South Africa. Height and weight were converted to z-scores using the WHO Anthroplus software. Multiple linear regression was used to assess factors associated with child health outcomes and multi-level regression to account for community-level factors. Higher income vulnerability was associated with lower weight- and height-for-age z-scores (WAZ and HAZ). Not completing secondary schooling and higher household size were associated with lower HAZ but higher BAZ. Child male sex and caregiver with depression were associated with lower child resilience. Caregiver’s level of schooling and household size remained independent predictors of child growth, while the caregiver’s mental health status independently predicted child resilience. Thus, notwithstanding systemic constraints, there may be modifiable drivers that can help in developing targeted intervention. Full article

This paper analyses data from a qualitative study undertaken with children and their families in two cash transfer programmes (CTPs) in Pakistan. Using a three-dimensional child well-being model that distinguishes material, relational and subjective dimensions, it argues that CTPs have helped extremely poor families sustain their basic dietary needs and marginally increase their health spending. Additional conditional payments have led to increased primary school enrolments, but CTPs have failed to address the distinctive vulnerabilities of children, including their nutritional needs, relational well-being and social status. A more holistic and child-sensitive approach to social protection would be the way forward to improve child well-being in line with the United Nations Charter on Rights of Children (UNCRC) to which Pakistan is a signatory. Full article

The analysis of massive databases is a key issue for most applications today and the use of parallel computing techniques is one of the suitable approaches for that. Apache Spark is a widely employed tool within this context, aiming at processing large amounts of data in a distributed way. For the Statistics community, R is one of the preferred tools. Despite its growth in the last years, it still has limitations for processing large volumes of data in single local machines. In general, the data analysis community has difficulty to handle a massive amount of data on local machines, often requiring high-performance computing servers. One way to perform statistical analyzes over massive databases is combining both tools (Spark and R) via the sparklyr package, which allows for an R application to use Spark. This paper presents an analysis of Brazilian public data from the Bolsa Família Programme (BFP—conditional cash transfer), comprising a large data set with 1.26 billion observations. Our goal was to understand how this social program acts in different cities, as well as to identify potentially important variables reflecting its utilization rate. Statistical modeling was performed using random forest to predict the utilization rated of BFP. Variable selection was performed through a recent method based on the importance and interpretation of variables in the random forest model. Among the 89 variables initially considered, the final model presented a high predictive performance capacity with 17 selected variables, as well as indicated high importance of some variables for the observed utilization rate in income, education, job informality, and inactive youth, namely: family income, education, occupation and density of people in the homes. In this work, using a local machine, we highlighted the potential of aggregating Spark and R for analysis of a large database of 111.6 GB. This can serve as proof of concept or reference for other similar works within the Statistics community, as well as our case study can provide important evidence for further analysis of this important social support programme. Full article