Support For Policy Interventions Research Articles

Procedural inclusiveness can mitigate trust challenges in environmental policymaking

ABSTRACT Decreasing political trust poses severe challenges, particularly in policy domains where solutions to societal problems are urgently needed. The reason is that low trust decreases citizens' support for policy interventions. Since trust is difficult to increase in the short to medium term, this study explores how negative trust effects on policy support could be mitigated through policymaking procedures. We connect literature on policy design processes and trust to argue that involving broader actor coalitions when designing a policy is likely to mitigate the negative trust effect on public policy support. We test this argument with an empirical focus on environmental policy, based on data from a survey experiment in Switzerland (N = 6116). Our study design combines a choice experiment with treatment conditions for procedural inclusiveness and various levels of policy stringency with a novel approach to measuring trust. The main finding is that greater inclusiveness in terms of engaging a broader actor coalition in the policy design process reduces otherwise negative effects of low trust on policy support. The main policy implication is that political trust challenges are not a predicament for failure in addressing urgent societal problems but can be offset by including broad actor coalitions in policy design processes.

Leveraging Simulation Data to Understand Bias in Predictive Models of Infectious Disease Spread

The spread of infectious diseases is a highly complex spatiotemporal process, difficult to understand, predict, and effectively respond to. Machine learning and artificial intelligence (AI) have achieved impressive results in other learning and prediction tasks; however, while many AI solutions are developed for disease prediction, only a few of them are adopted by decision-makers to support policy interventions. Among several issues preventing their uptake, AI methods are known to amplify the bias in the data they are trained on. This is especially problematic for infectious disease models that typically leverage large, open, and inherently biased spatiotemporal data. These biases may propagate through the modeling pipeline to decision-making, resulting in inequitable policy interventions. Therefore, there is a need to gain an understanding of how the AI disease modeling pipeline can mitigate biased input data, in-processing models, and biased outputs. Specifically, our vision is to develop a large-scale micro-simulation of individuals from which human mobility, population, and disease ground-truth data can be obtained. From this complete dataset—which may not reflect the real world—we can sample and inject different types of bias. By using the sampled data in which bias is known (as it is given as the simulation parameter), we can explore how existing solutions for fairness in AI can mitigate and correct these biases and investigate novel AI fairness solutions. Achieving this vision would result in improved trust in such models for informing fair and equitable policy interventions.

Positive, negative or graded sustainability labelling? Which is most effective at promoting a shift towards more sustainable product choices?

AbstractSustainability labels convey information about different product attributes, such as its environmental impact, lifespan or ethical performance. The labelling can be either positive (only identifying the most sustainable products available on the market), negative (only identifying the least sustainable products available on the market) or graded (comparing the sustainable performance of a product with that of all other products on the market). We assess the relative performance of these three labelling approaches in terms of influencing product choices. A nationally representative sample of 1243 consumers from Germany, Spain and the Czech Republic participated in an incentive‐compatible online discrete choice experiment with random allocation to different labelling approaches. Compared with positive and negative labels, graded labels were most effective in guiding consumers towards more sustainable product choices. These findings support policy interventions that convey product sustainability with graded labels.

Ending groundwater overdraft without affecting food security

Groundwater development is key to accelerating agricultural growth and to achieving food security in a climate crisis. However, the rapid increase in groundwater exploitation over the past four decades has resulted in depletion and degradation, particularly in regions already facing acute water scarcity, with potential irreversible impacts for food security and economic prosperity. Using a climate–water–food systems modelling framework, we develop exploratory scenarios and find that halting groundwater depletion without complementary policy actions would adversely affect food production and trade, increase food prices and grow the number of people at risk of hunger by 26 million by 2050. Supportive policy interventions in food and water systems such as increasing the effective use of precipitation and investments in agricultural research and development could mitigate most negative effects of sustainable groundwater use on food security. In addition, changing preferences of high-income countries towards less-meat-based diets would marginally alleviate pressures on food price. To safeguard the ability of groundwater systems to realize water and food security objectives amidst climate challenges, comprehensive measures encompassing improved water management practices, advancements in seed technologies and appropriate institutions will be needed.

Technological Innovations in Agricultural Firms in Bulgaria: What is the Role of EU Funds?

Abstract The value chains that originate from agricultural production across the globe are of critical importance to achieving the Sustainable Development Goals. In the context of Bulgaria on the country level, the gross capital formation of agricutural firms has experienced an incredible increase of 95% because of buying machines and equioments during the years 2018 and 2022. Our research project focuses on analyzing the effects of governmental financial support on the growth and competitiveness of agricultural companies. For the study, data on firms that were financially aided to buy agricultural machinery between 2021 and 2023 was derived from the eufund.bg database. It was discovered that medium and large businesses are two to three times more likely to receive funding from the EU compared to the micro-enterprises. The study identified a significant North-South divide signaling a positive impact of funding to the less developed regions and in particular the Northwest region. Furthermore, the crucial role of the EU funding in enhancing the growth of the agricultural sector are emphasized by the study. The study identifies gaps in the efficacy of support programs and policy interventions in enhancing innovations in the agricultural sector. The study also offers insights on specific impacts on farm productivity, profitability, environmental sustainability, and socio-economic implications for the future studies.

Anxiety Disorders among Left-Behind Children in Rural China: A Comprehensive Literature Review

With rapid urbanization leading to mass adult migration from rural to urban areas in China, a consequential demographic group called left-behind children has emerged. Often left in the care of relatives or on their own, these children experience extended periods of parental absence associated with various mental health implications, notably anxiety disorders. This paper explores anxiety disorders of left-behind Children including depressive symptoms, the effect of COVID-19 and bullying victimization among left-behind children in rural China through literature review. Further, it examines potential interventions from the implementation of online mental health interventions, strengthening community support systems, and policy and financial interventions. Additionally, the paper points towards the potential efficacy of community-based interventions, emphasizing the importance of a multi-pronged approach. The analysis promotes a more thorough investigation into the viability and effectiveness of these interventions, opening the door to better mental health outcomes for underprivileged kids in rural China.

Determinants of risk factors for COVID-19 transmission in densely populated areas: Insights from the first wave of the pandemic

<b>Introduction:</b> COVID-19 spreads quickly, especially in densely populated countries like Indonesia. Understanding transmission factors can support in reducing transmission rates. The purpose of this study is to analyze the various factors that may contribute to the transmission of COVID-19 in Indonesia, especially in the first wave of pandemic.<br /> <b>Methods: </b>This was a cross sectional study design. The sample was selected from the new all record data or the database for recording COVID-19 cases at the health office at the research location by online system. The research was conducted in seven districts and cities across three provinces to obtain an overview of transmission in each regional characteristic. The number of samples was as high as 2,010, with confirmed cases and close contacts in Banda Aceh City, Aceh Besar District, Semarang City, Magelang District, Ternate City, South Halmahera District, and Tidore Islands City. Data analysis was done descriptively and were analyzed using Chi-square and logistic regression with SPSS software.<br /> <b>Results: </b>The multivariate analysis shows that five dominant factors the risk of COVID-19 transmission, there are, age, employment status, activities outside the home, medical history, and vaccination status. Age group of 20-39 years (odds ratio [OR]=1.6-1.7; 95% confidence interval [CI] 1.07-2.71), working of employment status (OR=1.51; 95% CI 1.10-2.07), have a comorbid in medical history (OR=2.39; 95% CI 1.67-3.4), have activities outside home (OR=1.82, 95% CI 1.39-2.39), and have not been vaccinated of COVID-19 (OR=3.03; 95% CI 3.37-3.87) were significantly related with an increased risk of COVID-19 transmission.<br /> <b>Conclusions: </b>productive age,<b> </b>work and activities outside the home, having comorbidities, and not having received COVID-19 vaccination are all risk factors for COVID-19 exposure. Eliminating all of these factors at the same time will undoubtedly be difficult. As a result, cross-sectoral collaboration is needed to control the spread of COVID-19 at the community and individual levels, as well as to support policy interventions to accelerate the elimination of COVID-19 cases.

Flooding in the urban fringes: Analysis of flood inundation and hazard levels within the informal settlement of Kibera in Nairobi, Kenya

Overlapping conditions of rapid urbanisation and climate change across developing countries are threatening the capacity of cities to manage climate risks, especially in the flood-exposed low-income peripheral areas. Limited studies have applied hydrodynamic flood models in ascertaining flooding conditions, supportive of risk-informed decisions in such urban fringes. Against this backdrop, we assessed plausible flooding and hazard conditions in the low-lying villages of Lindi and Silanga in Kibera informal settlement. The coupled one-dimensional and two-dimensional hydrodynamic model, customised from the Hydrological Engineering Centre's River Analysis System (HEC-RAS) was parameterised for flood simulation under different hydrological regimes and scenarios associated with flooding in Kibera. Volumetric flow estimates and a computed energy slope were used to define the upstream and downstream modelling boundary conditions respectively. Trial-and-error adjustment of the flow resistance coefficients from land-use features was applied in model calibration, and the results compared to the surveyed flood of 23rd April 2019. Results show that proximal areas to the Ngong River and Nairobi dam face high flood risks. A flood volume of 11.7×105m3 from a 2.5h, 50 mm rainfall could potentially inundate about 2.0% and 8.3% of areas in Lindi and Silanga respectively, while a volume of 48.9×105m3 from a 100-year storm of 172 mm could inundate about 10.6% of Lindi and 29.1% of Silanga. Upstream steeply sloping topographies of the villages increase flood velocities and risk of drowning, while the lower reaches at relatively flatter topographies, experience attenuated flow and rapid accumulation of flood waters, hence, higher flood depths. These results can support policy interventions for integrated flood risk management in Kibera, as a way of mainstreaming the underserved urban communities in climate risk management.

Employment Outcomes for People With Autism Spectrum Disorder: A Theory Mapping of the Evidence

Background:People with autism spectrum disorder (ASD) are three to four times less largely to be with employment compared to neurotypical others. Theory based studies may provide helpful indicators for the design and implementation of employment supports for people with ASD.Objective:This critical review examined the extent of the evidence for theory in studies on employment outcomes for people with ASD and taking into account social inequality. For the evidence, 35 studies were selected for review if they were published in the period 2000–2016 and assessed for the association between work participation with ASD applying descriptive survey or quasi-experimental design.Methods:Studies were examined for use of any theory, including four predetermined theory types: social liminality, psychosocial, behavioral, and structural-infrastructural. They were also content-analyzed to determine if they cited any evidence of social inequality influences on employment outcomes with ASD.Findings:Results indicated that none of the studies explicitly applied and tested a theory on work participation with ASD. Rather, the majority of the studies were implicitly framed on predominantly behavioral type theory with minor elements of workplace psychosocial support theory-oriented interventions. Regard of structural-infrastructural type theory addressing social inequality is incidentally addressed by a few of the studies (n= 3) that examined family income status influences.Conclusion:In conclusion, extant studies on the association between employment outcomes and ASD are seriously limited in their explanatory value by a lack of theoretical grounding. They also neglect influences of antecedent social inequality in employment outcomes with ASD. Future studies should apply specific theory to questions on employment outcomes with ASD to provide usable evidence to inform employment support policy instruments and interventions for people with ASD.

Illustrating nonlinear effects of built environment attributes on housing renters’ transit commuting

The empirical relationships between the built environment and transit use can support policy interventions for transit promotion. Limited studies have emphasized housing renters who are likely to be transit-dependent people and the nonlinear effects of built environment attributes on renters’ behavior. Using household travel data in Beijing, this study uses a decision-tree based gradient boosting machine to explore the nonlinear and threshold relationships between built environment attributes and commuting by transit. Renters are more sensitive to access to transit than owners. The collective contributions of bus stop density and distance to metro station are about 22% for renters and 14% for owners. Furthermore, most variables show non-linear effects on commuting by transit. The effects of bus stop density on renters’ commuting by transit rise sharply twice. One threshold is at a low-density level and the other is at a high-density level. Exploiting the threshold effects can produce cost-effective outcomes.

The Impact of Extremely Low Electric Rates on Energy Conservation, Planning and Resilience: A Case Study of Plattsburgh, New York

Electric rates in Plattsburgh, New York are among the least expensive in the United States. Plattsburgh’s rates are set by a preference power program that was enacted in 1957 to promote rural economic development. A survey distributed to customers of Plattsburgh’s municipally-owned electric utility inquired about familiarity with local electric rates and energy systems, conservation behaviors, and attitudes towards policy interventions intended to encourage conservation. Results indicate that energy consumers in Plattsburgh hold a moderate degree of familiarity with the community’s energy system and implement strong conservation actions. Support for policy interventions are mixed. Survey results reveal income inequality, as differences in conservation attitudes and behaviors are apparent among respondents that report varying degrees of financial vulnerability. Today, Plattsburgh is in need of a resilient energy system, yet inexpensive rates discourage investment in infrastructure. This research reveals the complex social, economic and policy forces interacting to determine Plattsburgh’s energy future.

Predicting housing deprivation from space in the slums of Dhaka

Cities in developing countries have been struggling to deal with the pressures of urbanization on infrastructure, basic services, land, and housing that often manifest as poor living conditions found in slums and informal settlements. One of the key challenges to effectively target policy interventions and meet Sustainable Development Goals (SDGs) for improving lives of people living in slums is the lack of data on their housing condition. Furthermore, the slum/non-slum dichotomy is inadequate in identifying specific deprivations that prevents effective policymaking and implementation. To this end, we propose a methodological framework to predict multidimensional housing deprivation with slums of Dhaka, Bangladesh as our case study. Our framework predicts multidimensional housing deprivation using geospatial and remote sensing variables. Several indicators, including distance to the central business district, arterial roads, major road junctions, railroads, average dwelling size, and street type within slums were related to increased risk of overall deprivation whereas proximity to heavy industry and shoreline, building density, informal street pattern, the low-level connectivity and proximity to social amenities were related to lower risk of housing deprivation. The results from the statistical models indicate their potential to predict the extent and type of housing deprivation, which could in turn support planning and policy interventions for achieving SDGs for the most vulnerable populations in slums of developing countries.

Impact of tourism development upon environmental sustainability: a suggested framework for sustainable ecotourism.

The empirical research investigated the relationship between tourism development and environmental suitability to propose a framework for sustainable ecotourism. The framework suggested a balance between business and environmental interests in maintaining an ecological system with the moderating help of government support and policy interventions. The study population encompasses tourism stakeholders, including tourists, representatives from local communities, members of civil administration, hoteliers, and tour operators serving the areas. A total of 650 questionnaires were distributed to respondents, along with a brief description of key study variables to develop a better understanding. After verifying the instrument’s reliability and validity, data analysis was conducted via hierarchical regression. The study findings revealed that a substantial number of people perceive socio-economic benefits, including employment and business openings, infrastructure development from tourism development, and growth. However, the state of the natural and environmental capital was found to be gradually degrading. Alongside the social environment, social vulnerability is reported due to the overutilization of land, intrusion from external cultures, and pollution in air and water due to traffic congestion, accumulation of solid waste, sewage, and carbon emissions. The study suggested a model framework for the development of sustained ecotourism, including supportive government policy interventions to ensure effective conservation of environmental and natural resources without compromising the economic viability and social well-beings of the locals. Furthermore, the variables and the constructs researched can be replicated to other destinations to seek valuable inputs for sustainable destination management elsewhere.

An investigation of the longitudinal relationship between neighbourhood income inequality and individual self-rated health in England.

There are mixed findings on whether neighbourhood income inequality leads to better self-rated health (SRH) or not. This study considers two hypotheses: individuals living in more unequal neighbourhoods have better SRH and the level of neighbourhood income inequality and its impact on SRH is moderated by household and neighbourhood level income related variables. Data from Waves 8-10 of the UK Household Longitudinal Study for respondents living in England at wave 8 were used. Neighbourhood income inequality was measured using Gini coefficients of household income from the Pay As You Earn and benefits systems for Lower Super Output Areas. Longitudinal ordinal multilevel models predicted self-rated health in 2016-18, 2017-19 and 2019-20 by income inequality and its interaction with household income, neighbourhood median income and neighbourhood deprivation, conditional on individual educational attainment, age, sex, ethnic group, years lived in current residence, region of residence and study wave. There were 24,889 respondents analysed over three waves. SRH was worse for those living in more income equal neighbourhoods. There was no indication that neighbourhood inequality was moderated by household income, neighbourhood median income or neighbourhood deprivation. These findings are in line with the balance of existing evidence and support policy interventions that aim to create mixed communities for the purpose of improving population health.

Universal Digital Twin – the impact of heat pumps on social inequality

• Estimated temporal and geospatial coefficients of performance of heat pumps. • Assessed CO 2 savings, and effect on fuel cost and fuel poverty. • Identified regional and geographical diversity of impact on inequality. • Enables possibility of forecasting fuel poverty to support policy interventions. • Analysis performed using knowledge-graph-based Universal Digital Twin. This paper investigates how using heat pumps for domestic heating would impact fuel poverty and social inequality. The analysis integrates a geospatial description of climate observations, gas and electricity infrastructure, energy consumption and fuel poverty from the base world of a Universal Digital Twin based on the World Avatar knowledge graph. Historic temperature data were used to estimate the temporal and geospatial variation of the performance of air source heat pumps in the UK. The corresponding change in gas and electricity consumption that could be achieved using heat pumps instead of gas for domestic heating was estimated. The geospatial impact of the heat pumps was assessed in terms of CO 2 savings, and their effect on fuel cost and fuel poverty. Whilst heat pumps would reduce emissions, it is predicted that they would increase fuel costs. It was shown that both local and regional areas of high fuel poverty would experience some of the largest increases in fuel cost. This illustrates the potential for the transition to sustainable heating to exacerbate social inequality. The analysis suggests that existing regional inequalities will increase, and that it comes down to a political choice between investments to support the most effective use of heat pumps, and delayed investments to counter social inequality. The ability of the World Avatar to integrate the models and data necessary to perform this type of holistic analysis provides a means to generate actionable information, for example, to enable local policy interventions to address the tension between social and environmental goals.

A Method for Measuring Coupled Individual and Social Vulnerability to Environmental Hazards

Although models of social vulnerability to environmental hazards are commonly developed to support policy interventions in emergencies and disasters, their utility is hindered by a lack of contextual information on individuals exposed to and affected by hazards. We develop a novel approach to model social vulnerability that couples individuals and their varying forms of protective capacity with the social fabric of the communities in which they reside. The backbone of our model is the Public-Use Microdata Sample (PUMS), a product of the U.S. Census Bureau that preserves a representative sample of completed responses to the American Community Survey (ACS). The PUMS enables us to understand the full range of individual protective capacities against a hazard in an exposed area, which we term individual vulnerability profiles (IVPs). In this case, we examine IVPs in the Coney Island–Brighton Beach section of New York City, which suffered severe impacts during Hurricane Sandy in 2012. To manage the large number of unique IVPs in Coney Island–Brighton Beach, we perform a segmentation analysis to generalize them into thematic cohort vulnerability profiles (CVPs) representing a typology of vulnerable people in Coney Island–Brighton Beach during Sandy. From synthetic populations of CVPs, we then estimate how individuals in varying housing types were coexposed to Sandy at the census tract level by classifying these areas into community social vulnerability profiles (SVPs). Our results provide a topology of social vulnerability that simultaneously links individual, community, and population-wide concerns, enabling a more holistic understanding of resources and interventions beneficial to human security during events like Sandy than is attainable with area-level metrics.

Food waste in Australian households: Role of shopping habits and personal motivations

AbstractThe intensity of household food waste is of concern throughout the world, especially, in developed countries like Australia where it accounts for 34% of all food wasted along the value chain. Due to these concerns, there has been an emergence of research over the last decade to support policy interventions. This study contributes to this body of knowledge by examining the influence of consumer shopping habits and motivational factors on the intensity of food wasted by Australian households. Based on data from an online survey of 5272 Australian households, results of this study reveal that most of the shopping habits examined (except buying food based on what is on special) have significant impacts on the intensity of food wasted. Furthermore, based on two‐step cluster analysis, it was found that consumers from different backgrounds possess similar types of shopping habits, however, they are different in terms of their levels of motivations aiming to reduce food being wasted. The insights provide guidance for practitioners and policymakers regarding what actions to be taken to reduce food waste in Australian households.

Effects of prophylactic and therapeutic antimicrobial uses in small-scale chicken flocks.

SummaryAntimicrobials are extensively used both prophylactically and therapeutically in poultry production. Despite this, there are little data on the effect of antimicrobial use (AMU) on disease incidence rate and per cent mortality. We investigated the relationships between AMU and disease and between AMU and mortality using data from a large (n = 322 flocks) cohort of small‐scale chicken flocks in the Mekong Delta, Vietnam, that were followed longitudinally from day old to slaughter (5,566 observation weeks). We developed a parameterized algorithm to emulate a randomized control trial from observational data by categorizing the observation weeks into ‘non‐AMU’, ‘prophylactic AMU’ and ‘therapeutic AMU’. To evaluate the prophylactic AMU effect, we compared the frequencies of clinical signs in ‘non‐AMU’ and ‘prophylactic AMU’ periods. To analyse therapeutic AMU, we compared weekly per cent mortality between the weeks of disease episodes before and after AMU. Analyses were stratified by clinical signs (4) and antimicrobial classes (13). Prophylactic AMU never reduced the probability of disease, and some antimicrobial classes such as lincosamides, amphenicols and penicillins increased the risk. The risk of diarrhoea consistently increased with prophylactic AMU. Therapeutic AMU often had an effect on mortality, but the pattern was inconsistent across the combinations of antimicrobial classes and clinical signs with 14/29 decreasing and 11/29 increasing the per cent weekly mortality. Lincosamides, methenamines and cephalosporins were the only three antimicrobial classes that always decreased the mortality when used therapeutically. Results were robust respective to the parameters values of the weeks categorization algorithm. This information should help support policy efforts and interventions aiming at reducing AMU in animal production.

Solidarities, Fairness, and Economic Governance in Advanced Capitalism: The Cases of COVID-19 Responses in Germany and the United States

This paper addresses the theoretical question of how competing models of social and economic solidarity shape patterns of economic governance in periods of economic crisis. Using the COVID-19 pandemic as a signal case, we seek to understand how changes in public opinion in response to similar social and economic shocks are informed by deeper ideational structures among citizens relating to their capacity for empathy, mutual support, and willingness to support and trust public policy interventions. Drawing on scholarly literatures related to moral economies and the social embeddedness of economic relationships, we undertake an empirical study of how the COVID-19 pandemic has shaped patterns of support for social and economic policies. We focus on Germany and the United States, countries with widely divergent modes of integration of capitalist markets and, therefore, potentially different levels of support for particular kinds of policy responses. We trace American and German policy responses since March 2020 across a number of domains, complemented by a systematic analysis of public opinion in the two countries, drawing from fifteen different sources of public-opinion data, in order to assess the pandemic’s effects on public support for individualized and collectively-oriented policy responses.

Perceptions About the Impact of Cigarette Filters on the Environment and Smoking-Related Behaviors

PurposeExamine adolescents’ and young adults’ (AYAs) knowledge and perceptions about the composition and environmental harms of cigarette filters and determine how perceptions are associated with support for policy interventions. MethodsCross-sectional, convenience sample from 10 California schools. AYAs (N = 429; 70% < 21 years) were surveyed about tobacco use, perceptions of cigarette filters, their impact on the environment, and cigarette sales bans. ResultsMost agreed that filters are harmful to the environment and not biodegradable (89%, n = 383 respectively); fewer knew filters are made of plastic (43%, n = 185). AYAs who agreed that filters are harmful to the environment were more supportive of cigarette sales bans (OR = 2.78 [95% CI: 1.18, 6.58]). ConclusionsKnowledge of the environmental harms of cigarettes among AYAs may strengthen support for tobacco control. More research is needed to further understand the knowledge and attitudes about the environmental impact of tobacco and to clarify how this might add support for tobacco-related policies.