Socio-economic Status, Food Security Status and its Coping Strategies among 'The Lost Food Project' (TLFP) Recipients in Klang Valley during COVID-19 Pandemic

Introduction: The Lost Food Project (TLFP) is a non-profit organization who continuously working on their strategic plan in combating the food insecurity problem by distributing food surplus to low income households within Klang Valley. This cross-sectional study aims to determine the socioeconomic status, food security status and its coping strategies among TLFP recipients in Klang Valley during COVID-19 pandemic. Methods: This study was conducted from April to June 2021. There were 88 respondents recruited through convenience sampling. A set of questionnaires regarding food assistance, nutrition knowledge, food security and its coping strategies was prepared, and the respondents were interviewed either by phone, face-to-face or self-administered questionnaire. Results: The prevalence of food insecurity among households in this study was 59.1%. Most of them have moderate (37.5%) to good (27.5%) nutrition knowledge. The coping strategy that most of the respondents applied was 'using less expensive food' (58.3%) with at least once per week within the past one month. Food insecure households tend to adopt more coping strategies compared to those food secure households (p<0.001). Moreover, households who rent their house (p<0.01), low household income (p<0.05) and high monthly food and drinks expenditure (p<0.01) were associated with the food insecurity among TLFP recipients. Conclusion: The study concluded that lower household income, higher food and drinks expenditure and those who rent the house have negative impacts on household's food security status. Thus, the situation forced them to apply more food-related coping strategies in their daily life. Further research should be conducted on the effectiveness of TLFP in helping them to improve Malaysian's food security status. © 2023 Authors. All rights reserved.

Socio-economic Status, Food Security Status and its Coping Strategies among 'The Lost Food Project' (TLFP) Recipients in Klang Valley during COVID-19 Pandemic

Introduction: The Lost Food Project (TLFP) is a non-profit organization who continuously working on their strategic plan in combating the food insecurity problem by distributing food surplus to low income households within Klang Valley. This cross-sectional study aims to determine the socioeconomic status, food security status and its coping strategies among TLFP recipients in Klang Valley during COVID-19 pandemic. Methods: This study was conducted from April to June 2021. There were 88 respondents recruited through convenience sampling. A set of questionnaires regarding food assistance, nutrition knowledge, food security and its coping strategies was prepared, and the respondents were interviewed either by phone, face-to-face or self-administered questionnaire. Results: The prevalence of food insecurity among households in this study was 59.1%. Most of them have moderate (37.5%) to good (27.5%) nutrition knowledge. The coping strategy that most of the respondents applied was 'using less expensive food' (58.3%) with at least once per week within the past one month. Food insecure households tend to adopt more coping strategies compared to those food secure households (p<0.001). Moreover, households who rent their house (p<0.01), low household income (p<0.05) and high monthly food and drinks expenditure (p<0.01) were associated with the food insecurity among TLFP recipients. Conclusion: The study concluded that lower household income, higher food and drinks expenditure and those who rent the house have negative impacts on household's food security status. Thus, the situation forced them to apply more food-related coping strategies in their daily life. Further research should be conducted on the effectiveness of TLFP in helping them to improve Malaysian's food security status. [ FROM AUTHOR]

The persistence of household energy insecurity during the COVID-19 pandemic

This study analyzes household energy insecurity in the United States during the first year of the COVID-19 pandemic. Previous research is limited by mostly cross-sectional research designs that do not allow scholars to study the persistency of this specific type of material hardship. We fill this gap by analyzing data from an original, nationally-representative, panel survey of low-income households. We find high levels of energy insecurity during the first year of the COVID-19 pandemic, especially during the initial months when the economic dislocation was at its height, and that many low-income households experienced it on multiple occasions during this period. We also identify disparities: households with people of color, very low-income, children aged five years and younger, with someone who relies on an electronic medical device, and those living in deficient housing conditions were more likely to experience energy insecurity. Households with these characteristics were also more likely to suffer from energy insecurity on a persistent basis through the first year of the pandemic.

Socio-Demographic Factors Affecting Food Security for Low-Income Household During the COVID-19 Pandemic in the Special Region of Yogyakarta

The COVID-19 pandemic has affected household food security, especially those with low incomes. This study aims to: (1) analyze the influence of socio-demographic factors (gender, age, mother’s education, marital status, occupation, dependents, income, and social assistance) on food security. (2) Measuring the level of food security of low-income families in the Special Region of Yogyakarta seen from the share of food expenditure, using a cross-sectional design and a quantitative approach and involved a sample of 250 low-income households, determined randomly by purposive sampling technique. We collected data through questionnaires, and the data were analyzed using descriptive statistical methods and multiple linear regression models using SPSS software. Three socio-demographic variables affect food security: employment, income, and the number of dependents. Simultaneously, these factors significantly affect the respondents’ food consumption expenditure. This study found that only 42.4% of respondents had food security. It shows that the current COVID-19 pandemic has exacerbated the poverty experienced by respondents. As for recommendations: (1) The government needs to provide social protection to help low-income households through food assistance programs. (2) Social protection programs need to be combined with household-based socio-economic empowerment programs to improve the food security of low-income households sustainably.

A Cyber-Physical-Social Perspective on Future Smart Distribution Systems

An increasing number of distributed energy resources (DERs), such as rooftop photovoltaic (PV), electric vehicles (EVs), and distributed energy storage, are being integrated into the distribution systems. The rise of DERs has come hand-in-hand with large amounts of data generated and explosive growth in data collection, communication, and control devices. In addition, a massive number of consumers are involved in the interaction with the power grid to provide flexibility. Electricity consumers, power networks, and communication networks are three main parts of the distribution systems, which are deeply coupled. In this sense, smart distribution systems can be essentially viewed as cyber-physical-social systems. So far, extensive works have been conducted on the intersection of cyber, physical, and social aspects in distribution systems. These works involve two or three of the cyber, physical, and social aspects. Having a better understanding of how the three aspects are coupled can help to better model, monitor, control, and operate future smart distribution systems. In this regard, this article provides a comprehensive review of the coupling relationships among the cyber, physical, and social aspects of distribution systems. Remarkably, several emerging topics that challenge future cyber-physical-social distribution systems, including applications of 5G communication, the impact of COVID-19, and data privacy issues, are discussed. This article also envisions several future research directions or challenges regarding cyber-physical-social distribution systems.

Machine Learning Models for Predicting Financially Vigilant Low-Income Households

The COVID-19 pandemic has adversely affected households’lives in terms of social and economic factors across the world. The Malaysian government has devised a number of stimulus packages to combat the pandemic’s effects. Stimulus packages would be insufficient to alleviate household financial burdens if they did not target those most affected by lockdowns. As a result, assessing household financial vigilance in the case of crisis like the COVID-19 pandemic is crucial. This study aimed to develop machine learning models for predicting and profiling financially vigilant households. The Special Survey on the Economic Effects of Covid-19 and Individual Round 1 provided secondary data for this study. As a research methodology, a cross-industry standard process for data mining is followed. Five machine learning algorithms were used to build predictive models. Among all, Gradient Boosted Tree was identified as the best predictive model based on F-score measure. The findings showed machine learning approach can provide a robust model to predict households’financial vigilances, and this information might be used to build appropriate and effective economic stimulus packages in the future. Researchers, academics and policymakers in the field of household finance can use these recommendations to help them leverage machine learning. Author

Exploring the use of mobile phones by children with intellectual disabilities: experiences from Haryana, India.

PURPOSE: Covid-induced lockdowns have increased the importance of technology in education. Though access to technology as well as availability of the internet remain a major concern for a lot of children in the global south, children with intellectual disabilities are disadvantaged even more as most of the e-content is developed keeping in mind the average learner. MATERIALS AND METHODS: Unstructured interviews were conducted with children with intellectual disabilities studying in government schools in Haryana as well as their teachers and parents. Thematic analysis of the interviews was conducted to understand the use-patterns of mobile phones by children with intellectual disabilities. RESULTS: Findings suggest that these children are learning to use mobile phones on their own or with some support and are able to navigate the complexities of these smartphones quite well. They use these devices mostly for their entertainment. This paper then reflects on the need and strategies to develop these technologies in ways that they can be used as effective tools for teaching children with intellectual disabilities, especially in the inclusive education system in developing countries. CONCLUSION: The paper reflects on the need to develop technology and tools using flexible and exploratory designs to enhance the learning processes for children with intellectual disabilities from the lower income strata.IMPLICATIONS FOR REHABILITATIONThis study highlights the importance of being able to use mobile phones by children with intellectual disabilities belonging to low income families.Following this, the article argues for designing of mobile phones suitable for use by children with intellectual disabilities using playfulness and explorations, andBuilding e-content keeping the elements of playfulness and exploration which can enhance the learnings of this group of students which is often ignored.

Quantifying the prevalence of energy poverty across Canada: Estimating domestic energy burden using an expenditures approach

Energy poverty is gaining public attention in Canada. Based on statistical analysis of Statistics Canada's 2016 Survey of Household Spending, we estimate that 7-9% of households spent more than 10% of their income on energy expenditures. Households in the Atlantic provinces faced the most energy poverty and highest energy expenditures. Low income, geography, and dwelling conditions were the main predictors of energy poverty. Households in energy poverty also spent approximately five times more on energy expenditures as a proportion of their total expenditures compared to households not in energy poverty. Our study fills a key research gap as a limited number of studies exist on the extent and drivers of energy poverty in Canada. Further, our study's robust quantitative estimates allow benchmarking and comparative research. These estimates lay the groundwork for evidence-based solutions-and our findings highlight the need to reconsider current policies. Considering the challenge of the ratio of energy costs to income is vital, especially in the aftermath of events such as COVID-19 or the 2021 heatwave in western Canada, which result in different energy behaviours and needs. More broadly, in the regular day-to-day, energy services should be seen as necessary and decision makers ought to consider the energy burden of Canadians.

Using Content Analysis and Machine Learning to Identify COVID-19 Information Relevant to Low-income Households on Social Media

COVID-19 pandemic has caused great distress in the lives of many populations. Low-income households are among the most severely impacted groups in the United States and across the globe. Using social media, this paper aims to identify and organize the information about the impact of the pandemic on low-income households. We use content analysis to derive an annotation protocol and manually annotate a tweet dataset using this protocol. Furthermore, we use machine learning to learn models from the annotated dataset. We also employ a human-in-the-loop data augmentation procedure to improve the model's performance for the underrepresented classes. Our results show that using carefully annotated data, automated machine learning models can be trained and employed to identify information relevant to low income households, potentially in real time. © 2021 IEEE.

SNAP participation among low-income US households stays stagnant while food insecurity escalates in the months following the COVID-19 pandemic.

The COVID-19 pandemic led to increased food-insecurity rates, particularly among low-income households. Participation in the Supplemental Nutrition Assistance Program (SNAP) was expected to rise in response. We surveyed 931 US residents from households with annual incomes below $50,000 to collect information on food security and food assistance program participation in the year prior to the pandemic and in the first four months of the pandemic, along with household and individual-level demographics. Food insecurity increased from 31% prior to the pandemic to 39% in the first four months of the pandemic, while self-reported SNAP participation stagnated. Even more alarmingly, among low-income households that were also food-insecure, 47% reported participating in SNAP prior to the pandemic but only 39% did so in the first four months following the pandemic's onset. In particular, Black households, households with children, and those in the lowest income category experienced the largest declines in SNAP participation. Food assistance programs designed to alleviate hunger should facilitate participation among the most vulnerable, especially when these groups are faced with multiple challenges, like during the COVID-19 pandemic.