Assessment Of Drivers Research Articles

Are we promoting green cities in Latin America and the Caribbean? Exploring the patterns and drivers of change for urban vegetation

As cities opt for green policies to address urban socio-ecological challenges it becomes important to evaluate how the urban landscape responds to them, and if these responses are strengthening the benefits of nature for all. The Latin American and Caribbean (LAC) region is one of the most biodiverse and urbanized regions of the world, which makes it imperative to understand how greening policies have impacted the distribution, accessibility, and quantity of vegetated areas in cities through time. Using a landscape ecology approach, we explored the effects of local urban dynamics on the pathways of urban vegetation in ten LAC capital cities in the last 20 years. Our results showed a great fluctuation of vegetation cover change for the region, with Santiago (Chile) losing more than 10% of its urban vegetation to Brasilia gaining 19%, while fragmentation and inequities in the distribution of vegetation increased in all cities. Cities followed four pathways of vegetation change, displaying different patterns of change in fragmentation, size of the vegetated patches and their clustering. This discloses that the greening policies and actions adopted in LAC cities led to increased vegetation cover, or avoided its loss, but did not assure a better distribution of the green and its benefits. Vegetation in LAC cities are still fragmented, where vegetation is not connected and is not equitably distributed, showing that policies in place have not addressed distributional injustice yet. This is corroborated by the assessment of drivers of change where we found social factors were the most important determinants of urban vegetation dynamics. Results from our study provide evidence for developing policies towards urban greening and connectivity, not only to prevent further biodiversity loss but also for creating more resilient communities and cities that address environmental inequities.

Small scale agriculture continues to drive deforestation and degradation in fragmented forests in the Congo Basin (2015–2020)

The Central African region hosts the largest continuous tract of forest in Africa, regulating global climate while providing essential resources and livelihoods for millions of people and harbouring extensive biodiversity. Extractive industries, infrastructure development and industrial agriculture have often been cited as major threats to these forests and are expected to increase. A regional collaborative effort has produced the first systematically validated remote sensing assessment of deforestation and degradation drivers in six central African countries for the 2015–2020 time period. Multiple, overlapping drivers are assessed through visual interpretation and show that the rural complex, a combination of small-scale agriculture, villages, and roads contributes to the majority of observed deforestation and degradation. Industrial drivers such as mining and forestry are less common, although their impacts on carbon and biodiversity could be more permanent and significant than informal activities. Artisanal forestry is the only driver that is observed to be consistently increasing over the study period. Our assessment produces information relevant for climate change mitigation and land use planning which requires detailed information on multiple direct drivers to target specific activities and investments.

Water security threats and solutions in the Grande River basin – One of the Brazilian agricultural frontiers

This paper evaluates the effectiveness of sustainable agricultural management solutions at a farm level to mitigate water security threats in one of Brazil's agricultural frontiers – the Grande River basin. The paper addresses future challenges to water security in the river basin and explores how effective solutions are at a farm level to mitigate current and future water security threats at a basin scale. Based on the assessment of multiple drivers, higher future water security threats in the region are predicted in 2040 due to climate change, land use modification and corresponding changes in water use. The paper finds that the Formosa do Rio Preto region, which is not currently water-insecure, may turn into a water security hotspot area by 2040. The effective response index for water security (ERI-WS), based on the qualitative assessment of the impact at the farm scale, is used to evaluate the effectiveness of current sustainable management practices in addressing water security challenges. The water security dimensions approach of the ERI-WS shows that >50 % of the sites have technologies that can have positive impacts on the “Drinking water and human well-being”, “Economic activities and development”, “Ecosystem” and the “Resilience” dimensions. The paper finds that 66 % of the farms have efficient soil, land, and water management solutions (ERI-WS > 0.5) to address current and future water security issues. These solutions range from sustainable grazing land management to integrated plant nutrition management to enhanced soil productivity. However, 15 % of the farms located in vulnerable areas of the municipalities of São Desidério, Barreiras and Catolândia have lower effectiveness. Results also indicate that 36 % of the sites, distributed in 8 municipalities, employ nature-based solutions to mitigate water security threats, mainly those related to water quality conditions in downstream areas, indicating the relevance of these practices in the region.

Vibration comfort assessment of tractor drivers based on sEMG and vibration signals

In order to comprehensively evaluate the driver’s vibration comfort under different vibration conditions, eighteen subjects were required to drive a tractor at different speeds on field and asphalt roads respectively in the real vehicle experiment. The sEMG signals and vibration acceleration signals of the subjects were recorded. And the time-frequency domain analysis of sEMG signals and acceleration signals were used to determine the relationship among the characteristic indexes, tractor speed and road surfaces. The relevance analysis showed that there was a significant correlation between the integral electromyography (iEMG) and median frequency (MF) of the middle scalene muscle, erector spinae muscle and gastrocnemius muscle, the RMS of weighted acceleration (aw) of the neck, waist and legs, and the subjective comfort feelings. It was proven that the tractor speed had a significant impact on human body vibration based on the ANOVA result (p < 0.05). With the increase of running speed, the time domain indexes of sEMG signals including iEMG, RMS and the vibration acceleration signals of the testing body parts increased significantly, while the amplitudes of frequency domain indexes decreased. Therefore, a quantitative regression evaluation model for the comfort of the neck, waist and legs integrating the sEMG and vibration signals was established, and its relative errors were 5.05, 4.38 and 6.12% respectively. This proposed assessment model can combine characteristics of the partial and overall vibration response of human body effectively, predict the tractor driver’s vibration comfort accurately, provide a theoretical basis for the evaluation of tractor cab vibration comfort.

Assessment of meteorological and air quality drivers of elevated ambient ozone in Beijing via machine learning approach.

Over the past few years, surface ozone (O3) pollution has dominated China's air pollution as particulate matter has decreased. In Beijing, the annual average concentrations of ground-level O3 from 2015 to 2020 regularly increased from 57.32 to 62.72μg/m3, showing a change of almost 9.4%, with a 1.6% per year increase. The meteorological factors are the primary influencer of elevated O3 levels; however, their importance and heterogeneity of variables remain rarely understood. In this study, we used 13 meteorological factors and 6 air quality (AQ) parameters to estimate their influencing score using the random forest (RF) algorithm to explain and predict ambient O3. Among the meteorological variables and overall, both land surface temperature and temperature at 2m from the surface emerged as the most influential factors, while NO2 stood out as the highest influencing factor from the AQ parameters. Indeed, it is crucial and imperative to reduce the temperature caused by climate change in order to effectively control ambient O3 levels in Beijing. Overall, meteorological factors alone exhibited a higher coefficient of determination (R2) value of 0.80, compared with AQ variables of 0.58, for the post-lockdown period. In addition, we calculated the number of days O3 concentration levels exceeded the WHO standard and newly proposed peak-season maximum daily 8-h average (MDA8) O3 guideline for Beijing. The exceedance number of days from the WHO standard of MDA8 ambient O3 was observed to be the highest in June, and each studied year crossed peak season guidelines by almost 2 times margin. This study demonstrates the contributions of meteorological variables and AQ parameters in surging ambient O3 and highlights the importance of future research toward devising an optimum strategy to combat growing O3 pollution in urban areas.

Analysis of factors influencing Circular-Lean-Six Sigma 4.0 implementation considering sustainability implications: an exploratory study

ABSTRACT In this study, we develop a new paradigm, Circular Lean Six Sigma 4.0 (CLSS4.0) to promote manufacturing sustainability. This paper aims to provide a practical and holistic view of the drivers and barriers that can help companies design an integrated CLSS4.0 model. The paper is based on a qualitative exploratory study using multiple case studies within 12 Moroccan manufacturing firms conducted through semi-structured interviews with top executive managers. The results show that the drivers are related to expected operational and environmental performance, increasing customer requirements, gaining competitive advantage and market growth while barriers are related to insufficient tangible (finance, human and equipment) and intangible (skills and techniques) resources, data privacy, technical issues and management support. The proposed framework identifies the assessment of drivers and barriers and their attributes as a starting point for managers to lead the CLSS4.0 transformation, thereby contributing to its successful implementation. To the best of our knowledge, this study is among the very first studies to discuss the CLSS4.0 drivers and barriers. It could be useful to managers as a diagnostic tool to assess their ability to implement CLSS4.0 before investing in the initiative.

Microhabitat conditions drive uncertainty of risk and shape neophobic responses in Trinidadian guppies, Poecilia reticulata.

In response to uncertain risks, prey may rely on neophobic phenotypes to reduce the costs associated with the lack of information regarding local conditions. Neophobia has been shown to be driven by information reliability, ambient risk and predator diversity, all of which shape uncertainty of risk. We similarly expect environmental conditions to shape uncertainty by interfering with information availability. In order to test how environmental variables might shape neophobic responses in Trinidadian guppies (Poecilia reticulata), we conducted an in situ field experiment of two high-predation risk guppy populations designed to determine how the 'average' and 'variance' of several environmental factors might influence the neophobic response to novel predator models and/or novel foraging patches. Our results suggest neophobia is shaped by water velocity, microhabitat complexity, pool width and depth, as well as substrate diversity and heterogeneity. Moreover, we found differential effects of the 'average' and 'variance' environmental variables on food- and predator-related neophobia. Our study highlights that assessment of neophobic drivers should consider predation risk, various microhabitat conditions and neophobia being tested. Neophobic phenotypes are expected to increase the probability of prey survival and reproductive success (i.e. fitness), and are therefore likely linked to population health and species survival. Understanding the drivers and consequences of uncertainty of risk is an increasingly pressing issue, as ecological uncertainty increases with the combined effects of climate change, anthropogenic disturbances and invasive species.

Impact assessment of professional drivers’ speed compliance and speed adaptation with posted speed limits in different driving environments and driving conditions

ABSTRACT This study analyzed the impact of driving environments (real-world and simulated world) and driving conditions (no time pressure and time pressure) on speed compliance and speed adaptation. Professional car drivers were recruited, and the data was collected in real-world and simulated world under no time pressure and time pressure driving conditions. The comparison results using Wilcoxon-signed rank test showed that speed compliance and speed adaptation were not consistently significant and were not in the same direction highlighting the influence of various factors like road features and driver characteristics. The generalized linear mixed model results showed that speed compliance was relatively better in simulated world (by 3.98 kmph) than real-world. Further, speed adaptation under time pressure was about 5.86 kmph lower during real-world as compared to simulated world. The findings from this study can provide new insights on road safety strategies and policy implications for limiting speeding-related crash risks.

Container terminal automation: assessment of drivers and benefits

ABSTRACT This study identifies and analyzes the relative importance of the multi-faceted factors that drive the decision to automate container terminals and the realized benefits, thus establishing how accurately terminal operators predicted the benefits of automation. The empirical analysis relies on a survey-based approach and the input of senior representatives of terminal operating entities in charge of the fully and semi-automated container terminals. The analysis of the findings, using statistical tools (i.e., descriptive statistics, Pearson correlations, ANOVA, Kruskal-Wallis), reveals that most of the benefits assumed by an individual terminal operator materialized once the automated terminal was in operation. It also concludes that expectations often exceed benefits and vice versa. A stepwise regression analysis enables the search of causal relationships between drivers and realized benefits with key characteristics of automated container terminals, such as their organizational features, technical dimensions, and the maritime and urban markets they serve. This article is a revised and expanded version of a paper Container Terminal Automation: Assessment of Drivers and Benefits presented at the International Association of Maritime Economists Annual Conference, Busan, Korea, 2022.

Assessment of drivers and barriers in the adoption of Mobility as a Service (MaaS): a case study of Noida, India

ABSTRACT Mobility as a Service (MaaS) has emerged as a transformative concept in urban transportation, integrating multiple modes of transportation through digital platforms to provide seamless travel experiences. By utilizing smartphone applications, MaaS simplifies trip planning, real-time information access, and consolidated payment systems, offering convenience to users. However, MaaS research has primarily focused on developed countries with well-established transport systems, making it crucial to explore its potential and challenges in developing cities of the global south, such as Noida in India. In this study, Noida, a satellite town of NCT Delhi, was chosen as only case study to gather data on user behaviour and preferences regarding app-based mobility services. A comprehensive survey collected information on socio-economic factors, personal vehicle ownership, commuting patterns, public transport usage, and attitudes towards digital ecosystems and app-based mobility services. Principal Component Analysis and K-means Clustering techniques were applied to identify distinct user types and categories, providing insights into user preferences and expectations. The analysis of the collected data revealed user clusters and their respective characteristics. The sustainability aspects of on-demand mobility services were evaluated, comparing user perceptions with private vehicle usage. The study also examined the impact of app-based mobility services on public transport and identified barriers and constraints specific to different user clusters, contributing to a better understanding of the feasibility of implementing MaaS. The findings will provide valuable insights for policymakers and transportation authorities, enabling the development of strategies and interventions to enhance urban mobility and foster MaaS adoption. By addressing the specific needs and preferences of users, MaaS can play a significant role in improving the efficiency and sustainability of transportation in complex urban environment cities like Noida in India.

High blood pressure prevalence, awareness, treatment, and blood pressure control among Ugandans with rheumatic and musculoskeletal disorders.

Rheumatic and musculoskeletal disorders (RMDs) are associated with cardiovascular diseases (CVDs), with hypertension being the most common. We aimed to determine the prevalence of high blood pressure (HBP), awareness, treatment, and blood pressure control among patients with RMDs seen in a Rheumatology clinic in Uganda. We conducted a cross-sectional study at the Rheumatology Clinic of Mulago National Referral Hospital (MNRH), Kampala, Uganda. Socio-demographic, clinical characteristics and anthropometric data were collected. Multivariable logistic regression was performed using STATA 16 to determine factors associated with HBP in patients with RMDs. A total of 100 participants were enrolled. Of these, majority were female (84%, n = 84) with mean age of 52.1 (standard deviation: 13.8) years and median body mass index of 28 kg/m2 (interquartile range (IQR): 24.8 kg/m2-32.9 kg/m2). The prevalence of HBP was 61% (n = 61, 95% CI: 51.5-70.5), with the majority (77%, n = 47, 95% CI: 66.5-87.6) being aware they had HTN. The prevalence of HTN was 47% (n = 47, 37.2-56.8), and none had it under control. Factors independently associated with HBP were age 46-55years (adjusted prevalence ratio (aPR): 2.5, 95% confidence interval (CI): 1.06-5.95), 56-65 years (aPR: 2.6, 95% CI: 1.09-6.15), >65 years (aPR: 2.5, 95% CI: 1.02-6.00), obesity (aPR: 3.7, 95% CI: 1.79-7.52), overweight (aPR: 2.7, 95% CI: 1.29-5.77). There was a high burden of HBP among people with RMDs in Uganda with poor blood pressure control, associated with high BMI and increasing age. There is a need for further assessment of the RMD specific drivers of HBP and meticulous follow up of patients with RMDs.

Assessment of Driver's Stress using Multimodal Biosignals and Regularized Deep Kernel Learning.

In this work, we classify the stress state of car drivers using multimodal physiological signals and regularized deep kernel learning. Using a driving simulator in a controlled environment, we acquire electrocardiography (ECG), electrodermal activity (EDA), photoplethysmography (PPG), and respiration rate (RESP) from N = 10 healthy drivers in experiments of 25min duration with different stress states (5min resting, 10min driving, 10min driving + answering cognitive questions). We manually remove unusable segments and approximately 4h of data remain. Multimodal time and frequency features are extracted and employed to regularized deep kernel machine learning based on a fusion framework. Task-specific representations of different physiological signals are combined using intermediate fusion. Subsequently, the fused multimodal features are fed a support vector machine (SVM) and a random forest (RF) for stress classification. The experimental results show that the proposed approach can discriminate between stress states. The combination of PPG and ECG using RF as classifier yields the highest F1-score of 0.97 in the test set. PPG only and RF yield a maximum F1-score of 0.90. Furthermore, subject-specific cross-validation improves performance. ECG and PPG signals are reliable in classifying the stress state of a car driver. In summary, the proposed framework could be extended to real-time stress state assessment in driving conditions.

Driving style identification and its association with risky driving behaviors among truck drivers based on GPS, load condition, and in-vehicle monitoring data

This study provides an approach to identify driving style of truck drivers by using GPS, load condition, and in-vehicle monitoring data and investigates the association of driving styles with risky driving behaviors from macro and micro perspectives. The naturalistic driving data used in this study were collected from 4,357 trucks in Hangzhou, China over three months in 2021. Six driving volatility parameters and six warning parameters were used to characterize the driving styles. Then, three driving styles under the two load conditions were identified using k-means clustering methods and principal component analysis. Finally, one-way MANOVA and ANOVA were used to analyze the relationship between driving styles and driving risk. It was found that truck drivers have different thresholds for aggressive and cautious driving style under different load conditions. Truck drivers who exhibited aggressive driving under both load conditions exhibited high driving risk. Although most truck drivers exhibited safe or normal driving under both conditions, the few who exhibited aggressive driving contribute to a disproportionate driving risk. These results can help distinguish differences in truck drivers’ driving styles under different load conditions, thus providing a more comprehensive safety assessment of truck drivers’ performance for monitoring purposes.

Growth drivers in emerging capitalist economies: building blocks for a post-Keynesian analysis and an empirical exploration of the years before and after the Global Financial Crisis

This paper contributes to the growth models debate by expanding the concept of growth drivers to emerging capitalist economies (ECEs). Conceptually, the paper synthesizes growth drivers with a growth model operationalization based on GDP growth contributions and financial sector balances. Drawing on post-Keynesian and structuralist economics, as well as, empirical studies, seven growth drivers for ECEs are reviewed: income distribution, price and non-price competitiveness, commodity prices, private debt, foreign direct investment (FDI) and fiscal policy. Descriptive data for these drivers are presented for 19 regionally grouped ECEs between 2000 and 2019. On average, Asian ECEs exhibit higher growth rates, stable real exchange rates, high and increasing non-price competitiveness and high private debt levels. Latin American countries show comparatively lower growth rates, high but decreasing income inequality, unstable exchange rates and relatively expansionary fiscal policy after the Global Financial Crisis (GFC). Central and Eastern European countries generally display medium to high growth rates, lower income inequality, high non-price competitiveness, a substantial FDI stock and, after the GFC, real depreciations and contractionary fiscal policy. The assessment of cross-country growth drivers via bivariate coefficients reveals limited robust results, except for non-price competitiveness, which emerges as a significant driver. Additionally, we find indications that private debt and expansionary fiscal policy became more important for growth in ECEs after the GFC. This is in line with the emergence of domestic demand- and private debt-led growth models in ECEs following the GFC in the course of private deleveraging and austerity policies in developed capitalist economies.

Examining policy−institution−program (PIP) responses against the drivers of ecosystem dynamics. A chronological review (1960–2020) from Nepal

Ecosystems are dynamic forms of nature, intuitively affected by natural processes and human interventions, depending on various drivers of changes and management responses. Understanding the ecosystem dynamics (ED) from the perspective of both the drivers of changes and the effectiveness of policy−institution−program (PIP) responses is crucial for nature sustainability. PIP response to a management problem, as a sectoral intervention, has been analysed in the past; however, national-level assessment of drivers of ecosystem dynamics and its PIP responses has not been done so far. This paper is aimed at cyclical assessment and chronological analysis (1960–2020) of the appropriateness and effectiveness of the PIP responses to the drivers of ED, taking the case of Nepal. Using a driver-pressure-state-impact-response (DPSIR) framework, we have assessed 38 drivers of ED on a decadal basis and analysed > 30 policy instruments as well as 15 periodic development plans (i.e., five-year plans and three-year plans) that have been developed yet. Moreover, we have carried out 300 household surveys to understand local people’s demand for ecosystem management. Based on various qualitative and quantitative analyses, we have portrayed pressure, state, and impact of various economic, demographic, technological, governance, globalization, and other drivers, including PIP response to address the drivers of changes. We found that the drivers of ED are non-linear and multifaceted, but the PIP responses are sectoral and incremental (i.e., piecemeal gradation to the previous efforts). Instead of characterization of drivers of ED and public demand, domestic PIP responses are largely influenced by global environmental discourse. Our findings are critical in understanding dynamic drivers of ecosystems and pathways of PIP responses, which might support policymakers and scholars in Nepal and other developing countries in the Himalayas to recalibrate PIP measures for sustainable resource management by suitably addressing the drivers of ED.

3-Domains screening toolkit for medical assessment of older drivers: Feasibility study in Australian general practice

Some general practitioners (GPs) find the older driver medical assessment challenging, citing clinical uncertainty and concerns about communicating the need for further testing or driving cessation while maintaining a trusting therapeutic relationship. A screening toolkit could help support GP decision making and communication about fitness to drive. The aim of this study was to investigate the feasibility, acceptability and utility of the 3-Domains screening toolkit for the medical assessment of older drivers in Australian general practice.A prospective mixed-methods study was conducted in nine general practices in south-east Queensland. Participants were older drivers (age ≥75 years) attending annual driving licence medical assessment, GPs and practice nurses. The 3-Domains toolkit comprises three screening tests (Snellen chart visual acuity, functional reach, road signs recognition). We evaluated the feasibility, acceptability and utility of the toolkit.Practices used the toolkit in 43 older driver medical assessments (age 75-93 years; combined predictive score 13-96%). Twenty-two semistructured interviews were conducted. Older drivers felt reassured by the thorough assessment. GPs said the toolkit fitted into practice workflows, informed clinical judgement and supported conversations about fitness to drive while preserving therapeutic relationships.The 3-Domains screening toolkit is feasible, acceptable and useful for the medical assessment of older drivers in Australian general practice.

U.S. Strategic Interest in the Moon: An Assessment of Economic, National Security, and Geopolitical Drivers

Since the 1980s, U.S. leaders have repeatedly directed the United States to return to the Moon, yet in each case, efforts were canceled within a few years of being announced. However, with the Artemis Program, for the first time in 30 years, a plan to return to the Moon has been endorsed by two successive presidential administrations. Today, interest in the Moon extends beyond the traditional scientific and inspirational motivations associated with the National Aeronautics and Space Administration’s exploration plans, with military, commercial, and international entities articulating corresponding, and sometimes independent, lunar goals. Some government leaders have argued that the return to the Moon has become a strategic interest for the United States. This paper investigates this claim, examining the economic, national security, and geopolitical drivers underlying U.S. lunar ambitions. We find that while rhetoric on the economic and national security importance of cislunar exploration and development is often overstated, there are some legitimate reasons for interest within these sectors. There are also strong geopolitical drivers for cislunar exploration and development.

Integrated assessment and optimization of dual environment and production drivers in grinding

Integrated assessment and optimization of dual environment and production drivers in grinding

A quantitative assessment of key drivers for environmental economic practices adoption for sustainable development

AbstractThe purpose of this paper is to present the results of an assessment aimed at evaluating potential drivers for the adoption of environmental economic practices in the construction industry, with a view to enhancing sustainability of construction projects, using the Nigerian construction industry as a case study. This study utilized a post‐positivist philosophical approach and a quantitative research design to collect data from construction professionals in the Nigerian construction industry through a well‐structured questionnaire. The collected data was analyzed using various statistical tests, including the Kruskal–Wallis H test, Kendall's coefficient of concordance (W), Chi‐square (χ2), and exploratory factor analysis. Five major clusters of drivers for the adoption of environmental economic practices were derived in this study. These are (1) operational drivers, (2) stakeholder drivers, (3) market and financial drivers, (4) regulatory and policy drivers, and (5) technological drivers. The findings of this study offer valuable insights into the potential drivers for the adoption of environmental economic practices in the construction industry, particularly from the perspective of a developing country such as Nigeria. Overall, this study contributes to the promotion of environmental sustainability in the construction industry, particularly in developing countries, which can have significant implications for global sustainability efforts.

Communication Interventions and Assessment of Drivers for Hendra Virus Vaccination Uptake.

Hendra virus disease (HeVD) is an emerging zoonosis in Australia, resulting from the transmission of Hendra virus (HeV) to horses from Pteropus bats. Vaccine uptake for horses is low despite the high case fatality rate of HeVD in both horses and people. We reviewed evidence-based communication interventions to promote and improve HeV vaccine uptake for horses by horse owners and conducted a preliminary evaluation of potential drivers for HeV vaccine uptake using the Behavioural and Social Drivers of Vaccination (BeSD) framework developed by the World Health Organization. Six records were eligible for review following a comprehensive search and review strategy of peer-reviewed literature, but evidence-based communication interventions to promote and improve HeV vaccine uptake for horses were lacking. An evaluation of potential drivers for HeV vaccine uptake using the BeSD framework indicated that horse owners' perceptions, beliefs, social processes, and practical issues are similar to those experienced by parents making decisions about childhood vaccines, although the overall motivation to vaccinate is lower amongst horse owners. Some aspects of HeV vaccine uptake are not accounted for in the BeSD framework (for example, alternative mitigation strategies such as covered feeding stations or the zoonotic risk of HeV). Overall, problems associated with HeV vaccine uptake appear well-documented. We, therefore, propose to move from a problems-focused to a solutions-focused approach to reduce the risk of HeV for humans and horses. Following our findings, we suggest that the BeSD framework could be modified and used to develop and evaluate communication interventions to promote and improve HeV vaccine uptake by horse owners, which could have a global application to promote vaccine uptake for other zoonotic diseases in animals, such as rabies.