Accessibility Index Research Articles

Student access to technology at home and learning hours during COVID-19 in the U.S.

Studies have shown that the digital divide affects students' educational achievement across racial and ethnic groups. In light of this, the study investigates the effect of technology access at home on student learning hours during the COVID-19 pandemic and across racial and ethnic groups in the U.S. The Household Pulse Surveys (HPS), conducted by the United States Census Bureau and administered from August 19, 2020, to March 29, 2021, were used for the analysis. We compute a composite index of technology access using the principal component analysis (PCA). And for the empirical model, the study employed a Tobit regression model. The result shows that the estimated index of technology access based on PCA for the whole sample is about 0.92, indicating a higher level of access. However, the breakdown by race/ethnicity shows an average of about 0.93, 0.89, 0.90, 0.94, and 0.89 for students representing White, Black, Hispanic, Asia, and other races, respectively. This means the intensity at which households in the sample have access to technology is higher among the Asian and White students, followed by Hispanic, Black, and other races in that order. The estimated effect of technology access on the student learning hours during COVID-19 based on the Tobit regression model shows about a 3.1 unit points increase over the whole sample. And further analysis reveals variation at which access to the technology impacts learning hours across race and ethnicity groups. For example, we find that access to technology significantly increased learning hours by about 3.5, 1.6, 2.2, and 3.4 unit points among White, Black, Hispanic, and Asian students, respectively. The observed differing effect of access to technology on learning hours further highlights the racial disparities in American society's digital divide, which reveal how access to technology disproportionately impacts student learning hours during the COVID-19 pandemic across race and ethnicity.

Formulating a Railway Station Accessibility (RsAI) Model for Station Hierarchy Classification

The accessibility of railway stations plays a crucial role in assessing service quality, predicting travel patterns, and developing infrastructure in the surrounding areas. This paper proposes a railway station accessibility index (RsAI) (external) that incorporates various parameters, including network performance, into a weighted measure. We reviewed different methods for measuring accessibility levels for transit systems to identify the most suitable models for this study. The primary objective of this paper is to classify railway stations into different hierarchies based on their accessibility levels and to develop an external accessibility index to measure their performance. With increasing urbanization and congestion, accessing railway stations has become more challenging, impacting railway efficiency and leading to modal shifts to other transportation systems. This paper not only identifies critical parameters but also emphasizes the need to measure and improve last-mile network performance to enhance station accessibility, thereby benefiting both passengers and the railway industry.

The correlation between the city bus accessibility and transit ridership in Surabaya City, Indonesia

Suroboyo Bus and Trans Semanggi Suroboyo are public modes in Surabaya City, should be one way to serve city mobility in high number. However, the load factor of the city bus is below 50%. Therefore, it is necessary to evaluate the provision of public transportation, such as the city bus accessibility. This study uses the Public Transport Accessibility Levels (PTAL) method to analyze the city bus accessibility. The analysis result shows that most of the city bus accessibility levels are in the very poor category. This means that the city bus system could cover the city area at low level. Following that, the relationship between the accessibility level and the transit ridership is analyzed using correlation analysis. The results show that there are a significant correlation between the variable number of passengers and the bus stop accessibility index; frequency with the purpose of travel; accessibility index with the distance variable (distance of the departure stop from the origin location; distance of the destination stop to the destination location; distance traveled from the departure stop to the destination stop and total mileage); the frequency with the socioeconomic variables (age; average monthly income and driving license ownership). Based on these results, some recommendations are proposed to increase the accessibility level for influencing the demand of city bus.

Corporate Members and Index to Advertisers

Information DisplayVolume 39, Issue 3 p. 64-64 Corporate Members and Index to AdvertisersFree Access Corporate Members and Index to Advertisers First published: 17 May 2023 https://doi.org/10.1002/msid.1400AboutPDF ToolsExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL No abstract is available for this article. Volume39, Issue3May/June 2023Pages 64-64 RelatedInformation

Measuring the crop water demand and satisfied degree using remote sensing data and machine learning method in monsoon climatic region, India.

Supply of water is one of the most significant determinants of regional crop production and human food security. To promote sustainable management of agricultural water, the crop water requirement assessment (CropWRA) model was introduced as a tool for the assessment of satisfied degree of crop water requirements (CWR). Crop combination, water availability for agricultural production, water accessibility, and other indices were calculated considering the DEM, hydrological and climatic data, and crop properties for measuring the agricultural water requirement and satisfied degree in Bansloi River basin using the CropWRA model. Advanced machine learning model random forest was used to calculate the soil moisture considering the atmospheric variable, Landsat indices, and energy balance components for calculating the crop water satisfied degree and water requirement. The average crop water demand is 1.92m, and it ranges from 1.58 to 2.26m. The demand of crop water is more in the western part of the basin than the eastern part. The CropWSD (crop water satisfied degree) ranges from 17 to 116% due to variation in topography, river system, crop combination, land use, water uses, etc. The average crop water satisfied degree is 59%. About 71% of the total area is under 40% to 60% CropWSD level. CropWRA model can be applied for the sustainable water resource management, irrigation infrastructure development, and use of other modern technologies.

SPATIOTEMPORALLY IMPROVING THE RURAL ACCESS INDEX – A REMOTE SENSING BASED APPROACH

Abstract. Many countries, especially in the global south still lack the ability to effectively pursue basic policies, which can lead, in the worst case, to armed conflicts. Access to markets is a key factor for economic growth and an important component in reducing poverty. The SDG 9.1.1 addresses the proportion of the rural population who live within 2km of an all-season road, which can be mapped by the Rural Access Index (RAI), introduced by the World Bank in 2006. This requires the road network of so-called all-season roads, population distribution and rural areas. We developed a fully automated approach, using remote sensing and other open source data to calculate the RAI on an annual basis between 2013 and 2020 for the Lake Chad region. We achieved an overall accuracy between 97.0% and 97.5% in detecting all-season roads using a Random Forest classification. Our method shows similar results to those published by the World Bank. However, our approach provides a higher spatial and temporal resolution measuring the RAI compared to previous studies and is independent of field studies.

Spatial Inequalities in Access to Safe Drinking Water in an Upper-Middle-Income Country: A Multi-Scale Analysis of Brazil

Access to drinking water is recognized as a human right, meaning that it is necessary to guarantee its universal and equitable access. Since analyzing only the average access rates to drinking water may obscure inequalities, studies have adapted socioeconomic inequalities indices to assess disparities. This research evaluated the Safe Drinking Water Access Index (SDWA) and inequalities access in all Brazilian municipalities using microdata from the 2010 Demographic Census. The inequalities were analyzed adapting indices derived from the Lorenz curve (Gini index, concentration coefficient and dissimilarity index). The results showed that the lowest SDWA rates and the highest inequality index values occurred in the north and northeast regions. The municipalities with significant inequality indexes values were rural with reduced gross domestic product (GDP) per capita. It was possible to punctuate municipalities that do not fit these rules but still need attention to safe water access guarantee. The amplitude of inequality index results reveals significant inequalities in the same regions or SDWA ranges. The inequalities in safe drinking water access were made more evident by the adapted Gini Index. This research contributes to the literature with an unprecedented analysis of Brazil and could be adapted to other countries and replicated to assess inequalities in sanitation access.

Spatial heterogeneity of low-birthweight deliveries on the Kenyan coast

BackgroundUnderstanding spatial variations in health outcomes is a fundamental component in the design of effective, efficient public health strategies. Here we analyse the spatial heterogeneity of low birthweight (LBW) hospital deliveries from a demographic surveillance site on the Kenyan coast.MethodsA secondary data analysis on singleton livebirths that occurred between 2011 and 2021 within the rural areas of the Kilifi Health and demographic surveillance system (KHDSS) was undertaken. Individual-level data was aggregated at enumeration zone (EZ) and sub-location level to estimate the incidence of LBW adjusted for accessibility index using the Gravity model. Finally, spatial variations in LBW were assessed using Martin Kulldorf’s spatial scan statistic under Discrete Poisson distribution.ResultsAccess adjusted LBW incidence was estimated as 87 per 1,000 person years in the under 1 population (95% CI: 80, 97) at the sub-location level similar to EZ. The adjusted incidence ranged from 35 to 159 per 1,000 person years in the under 1 population at sub-location level. There were six significant clusters identified at sub-location level and 17 at EZ level using the spatial scan statistic.ConclusionsLBW is a significant health risk on the Kenya coast, possibly under-estimated from previous health information systems, and the risk of LBW is not homogenously distributed across areas served by the County hospital.

The Social Equity Of Public Green Open Space Accessibility: The Case Of South Tangerang, Indonesia

Public Green Open Space (PGOS) is widely known to provide many benefits for the well-being of urban community, especially the socially vulnerable. Achieving equitable PGOS access is crucial for the sustainability and livability of cities. This study aims to 1) observe the accessibility of PGOS and 2) investigate the social equity of PGOS access in South Tangerang, Indonesia. This study employed network-based accessibility analysis through GIS and constructed a green space access index at urban village level to observe the accessibility of PGOS for urban residents. Furthermore, statistical correlation tests were conducted to examine the social equity of PGOS access against socio-demographic variables. The spatiality of equity was explored by using Bivariate Moran’s I. The results found that in South Tangerang, PGOS access is unequal, showing 61.2% of residential areas being underserved. This study also found that PGOS access is higher in elite private neighborhoods. Furthermore, statistical tests showed that PGOS access is inequitable for the low-income group. As for the elderly and population density, PGOS access was found to be equitable. However, no correlation was found between children and PGOS access. Additionally, causes of inequality and inequity in PGOS access and its implications are further discussed. This study addresses several key policy implications for urban planners and specifically for the government of South Tangerang such as the need to reform PGOS planning & policy and developing alternative funding for PGOS.

View access index: The effects of geometric variables of window views on occupants’ satisfaction

One of the important aims of window design is to provide quality views that affect occupant health, well-being, and work performance. We assessed the effect of geometric variables (i.e., view angles, glazing area (Window-to-Wall Ratio, WWR), window distance, viewing direction and percentage of window view area in the visual field (PWV)) had on occupants’ satisfaction to view access. We conducted a human subject experiment with 40 participants using simulated images displayed in virtual reality headsets. Each participant rated 40 images with the geometric window view variables being presented in various combinations. The results showed that glazing area (WWR), window distance, and viewing direction were the three primary predictors for view access satisfaction. Based on the empirical results, we developed a view access index. This index found that satisfactory view access cannot be achieved with WWRs < ∼25%, and the level of satisfaction with view access did not increase substantially when WWRs > ∼65%. The proposed index is the first model that predicts occupant satisfaction to view access by considering the complex interplay of multiple geometric window view variables derived from an immersive environment. Given the impact of glazing area, window distance and viewing direction have on occupant satisfaction in the workplace, it is important to integrate them during the early stages of building design. For minimum view access requirements, we recommend WWRs and horizontal view angles that are greater than 25% and to 35°.

The Quest for Quality Healthcare Services – What we can learn from a settlement-based case study?

Adopting the case study approach present study attempts to unwrap the status of the healthcare accessibility of the Berhampur Community Development (CD) block of Murshidabad. A network-based method integrated with the gravity model is used to identify under-serviced areas that do not have access to essential healthcare services at the settlement level. The attempt is made to map the significant socio-economic and demographic factors affecting the accessibility of quality healthcare services that can suggest the best possible solution to considering the heterogeneous needs of the population concerning healthcare services. The healthcare accessibility index (Ai) to the population demand is mapped to delineate the underserviced area. The Joint Hansen’s Improved Gravity Model and Huff Model (probability model) is used with deprivation mapping. Following the human- rights approach of the good living standards, fourteen indicators were extracted from census data, and the indicators were standardized by applying a min-max normalization formula. The indices calculate to measure healthcare deprivation, and inaccessibility at the neighborhood scale indicate the sharp differences in the spatial context. The increasing coverage of healthcare facilities has yet to address the issue of accessibility as an interplay between facilities-connectivity matrix. The study used a connectivity matrix to analyze healthcare accessibility and found that network-based measurement of health accessibility is more suitable over straight-line distance. We found this work may help support policymaking and bridge the gap between the biased share of infrastructure coverage and health care disparity in the study area.

Evaluation and Analysis of Development Status of Yellow River Beach Area Based on Multi-Source Data and Coordination Degree Model

The Yellow River beach area is the basic component of the Yellow River Basin. Promoting the comprehensive improvement and high-quality development of the Yellow River beach area is an important guarantee of the long-term stability of the Yellow River and an important part of promoting the high-quality development and ecological protection of the Yellow River Basin. In this paper, four new indexes (flood risk intensity index, accessibility index, biological abundance index, and remote sensing ecological index) were extracted from geospatial data and remote sensing images, and a quantitative evaluation model (Ecology-Economy -Society-Flood, EESF) for the development of the Yellow River beach area were constructed based on social statistics, such as flood control and control in the beach area. The coordinated development level of the Yellow River beach area was evaluated by combining the “CRITIC–entropy weight method” and “‘single index quantification–multi-index synthesis–multi-criteria integration’ (SMI-P)—coordination degree model” methods. The spatial autocorrelation model was used to analyze the spatial distribution characteristics of the coordinated development level, and the global sensitivity and uncertainty analysis (GSUA) was carried out for the sensitivity and uncertainty of the parameters. Taking the Yellow River beach area in Shandong Province in 2009 and 2019 as the study object, the research results showed that during this period, the coordinated development level of the Yellow River beach area in Shandong Province showed a gradual upward trend, from 0.344 to 0.580, reaching a basic coordinated state; the overall coordinated development level of the beach area showed significant autocorrelation and small spatial heterogeneity. Grain production was the most sensitive parameter in the coordinated development model of the beach area. The beach area should rationally develop and utilize agricultural resources and promote the integration of ecological industries.

Effect of Moisture Content on Subgrade Soils Resilient Modulus for Predicting Pavement Rutting

The subgrade soil stiffness, which depends on the in-situ moisture content and soil index characteristics, is a key factor in pavement rutting. Due to variations in the compaction process used during construction and seasonal changes, the subgrade soil moisture content may deviate from the desired condition. The resilient modulus (MR), an important parameter of the Mechanistic-Empirical (M-E) pavement design process, is used to specify the subgrade soil stiffness. Repeated load triaxial tests, which can be challenging and time-consuming to execute, are often used to determine MR. As a result, correlations between MR and more accessible stiffness metrics and index qualities are frequently used. California bearing ratio (CBR) and repeated load triaxial tests were carried out in this investigation. Soil specimens were fabricated at moisture levels that were both above and below the optimum moisture content (wopt). The results of the two tests were correlated, and statistical models were created to correlate the parameters of the generalized constitutive resilient modulus model with the characteristics of the soil index. Additionally, utilizing the MR found for subgrade soils compacted at wopt and ±2%wopt, pavement rutting was analyzed for three base layer types. The results demonstrated that a laboratory-measured MR (MR(Lab)) decreases as the moisture content increases. Specimens compacted at −2%wopt showed higher MR(Lab) than specimens compacted at wopt. Specimens compacted at +2%wopt showed lower MR(Lab) than specimens compacted at wopt. Results also indicated that the MR(Lab) predicted higher pavement rutting compared to field measured MR (MR(Lab)). If a stabilized aggregate foundation layer was employed instead of an untreated granular base, subgrade soil moisture condition showed a significant impact on rutting.

Geographic accessibility and hospital competition for emergency blood transfusion services in Bungoma, Western Kenya

BackgroundEstimating accessibility gaps to essential health interventions helps to allocate and prioritize health resources. Access to blood transfusion represents an important emergency health requirement. Here, we develop geo-spatial models of accessibility and competition to blood transfusion services in Bungoma County, Western Kenya.MethodsHospitals providing blood transfusion services in Bungoma were identified from an up-dated geo-coded facility database. AccessMod was used to define care-seeker’s travel times to the nearest blood transfusion service. A spatial accessibility index for each enumeration area (EA) was defined using modelled travel time, population demand, and supply available at the hospital, assuming a uniform risk of emergency occurrence in the county. To identify populations marginalized from transfusion services, the number of people outside 1-h travel time and those residing in EAs with low accessibility indexes were computed at the sub-county level. Competition between the transfusing hospitals was estimated using a spatial competition index which provided a measure of the level of attractiveness of each hospital. To understand whether highly competitive facilities had better capacity for blood transfusion services, a correlation test between the computed competition metric and the blood units received and transfused at the hospital was done.Results15 hospitals in Bungoma county provide transfusion services, however these are unevenly distributed across the sub-counties. Average travel time to a blood transfusion centre in the county was 33 min and 5% of the population resided outside 1-h travel time. Based on the accessibility index, 38% of the EAs were classified to have low accessibility, representing 34% of the population, with one sub-county having the highest marginalized population. The computed competition index showed that hospitals in the urban areas had a spatial competitive advantage over those in rural areas.ConclusionThe modelled spatial accessibility has provided an improved understanding of health care gaps essential for health planning. Hospital competition has been illustrated to have some degree of influence in provision of health services hence should be considered as a significant external factor impacting the delivery, and re-design of available services.

High-level burnout in physicians and nurses working in adult ICUs: a systematic review and meta-analysis.

The prevalence of burnout in intensive care unit (ICU) professionals is difficult to establish due to the variety of survey instruments used, the heterogeneity of the targeted population, the design of the studies, and the differences among countries regarding ICU organization. We performed a systematic review and meta-analysis examining the prevalence of high-level burnout in physicians and nurses working in adult ICUs, including only studies that use the Maslach Burnout Inventory (MBI) as a tool to evaluate burnout and involving at least 3 different ICUs. Twenty-five studies with a combined population of 20,723 healthcare workers from adult ICUs satisfied the inclusion criteria. Combining 18 studies including 8187 ICU physicians, 3660 of them reported a high level of burnout (prevalence 0.41, range 0.15-0.71, 95% CI [0.33; 0.5], I2 97.6%, 95% CI [96.9%; 98.1%]). The heterogeneity can be at least in part explained by the definition of burnout used and the response rate as confirmed by the multivariable metaregression done. In contrast, there was no significant difference regarding other factors such as the study period (before or during the coronavirus disease 2019 (COVID-19) pandemic), the income of the countries, or the Healthcare Access and Quality (HAQ) index. Combining 20 studies including 12,536 ICU nurses, 6232 of nurses were reporting burnout (prevalence 0.44, range 0.14-0.74, [95% CI 0.34; 0.55], I2 98.6% 95% CI [98.4%; 98.9%]). The prevalence of high-level burnout in ICU nurses for studies performed during the COVID-19 pandemic was higher than that reported for studies performed before the COVID-19 pandemic (0.61 [95% CI, 0.46; 0.75] and 0.37 [95% CI, 0.26; 0.49] respectively, p = 0.003). As for physicians, the heterogeneity is at least in part explained by the definition used for burnout using the MBI but not by the number of participants. When compared, the prevalence of high-level burnout was not different between ICU physicians and ICU nurses. However, the proportion of ICU nurses with a high level of emotional exhaustion was higher than for ICU physicians (0.42 [95% CI, 0.37; 0.48] and 0.28 [0.2; 0.39], respectively, p = 0.022). According to this meta-analysis, the prevalence of high-level burnout is higher than 40% in all ICU professionals. However, there is a great heterogeneity in the results. To evaluate and to compare preventive and therapeutic strategies, there is the need to use a consensual definition of burnout when using the MBI instrument.

Global Diabetes Prevalence in COVID-19 Patients and Contribution to COVID-19- Related Severity and Mortality: A Systematic Review and Meta-analysis.

COVID-19 and diabetes both contribute to large global disease burdens. To quantify the prevalence of diabetes in various COVID-19 disease stages and calculate the population attributable fraction (PAF) of diabetes to COVID-19-related severity and mortality. Systematic review identified 729 studies with 29,874,938 COVID-19 patients. Studies detailed the prevalence of diabetes in subjects with known COVID-19 diagnosis and severity. Study information, COVID-19 disease stages, and diabetes prevalence were extracted. The pooled prevalence of diabetes in stratified COVID-19 groups was 14.7% (95% CI 12.5-16.9) among confirmed cases, 10.4% (7.6-13.6) among nonhospitalized cases, 21.4% (20.4-22.5) among hospitalized cases, 11.9% (10.2-13.7) among nonsevere cases, 28.9% (27.0-30.8) among severe cases, and 34.6% (32.8-36.5) among deceased individuals, respectively. Multivariate metaregression analysis explained 53-83% heterogeneity of the pooled prevalence. Based on a modified version of the comparative risk assessment model, we estimated that the overall PAF of diabetes was 9.5% (7.3-11.7) for the presence of severe disease in COVID-19-infected individuals and 16.8% (14.8-18.8) for COVID-19-related deaths. Subgroup analyses demonstrated that countries with high income levels, high health care access and quality index, and low diabetes disease burden had lower PAF of diabetes contributing to COVID-19 severity and death. Most studies had a high risk of bias. The prevalence of diabetes increases with COVID-19 severity, and diabetes accounts for 9.5% of severe COVID-19 cases and 16.8% of deaths, with disparities according to country income, health care access and quality index, and diabetes disease burden.

Assessing COVID-19 pandemic policies and behaviours and their economic and educational trade-offs across US states from Jan 1, 2020, to July 31, 2022: an observational analysis

The USA struggled in responding to the COVID-19 pandemic, but not all states struggled equally. Identifying the factors associated with cross-state variation in infection and mortality rates could help to improve responses to this and future pandemics. We sought to answer five key policy-relevant questions regarding the following: 1) what roles social, economic, and racial inequities had in interstate variation in COVID-19 outcomes; 2) whether states with greater health-care and public health capacity had better outcomes; 3) how politics influenced the results; 4) whether states that imposed more policy mandates and sustained them longer had better outcomes; and 5) whether there were trade-offs between a state having fewer cumulative SARS-CoV-2 infections and total COVID-19 deaths and its economic and educational outcomes. Data disaggregated by US state were extracted from public databases, including COVID-19 infection and mortality estimates from the Institute for Health Metrics and Evaluation's (IHME) COVID-19 database; Bureau of Economic Analysis data on state gross domestic product (GDP); Federal Reserve economic data on employment rates; National Center for Education Statistics data on student standardised test scores; and US Census Bureau data on race and ethnicity by state. We standardised infection rates for population density and death rates for age and the prevalence of major comorbidities to facilitate comparison of states' successes in mitigating the effects of COVID-19. We regressed these health outcomes on prepandemic state characteristics (such as educational attainment and health spending per capita), policies adopted by states during the pandemic (such as mask mandates and business closures), and population-level behavioural responses (such as vaccine coverage and mobility). We explored potential mechanisms connecting state-level factors to individual-level behaviours using linear regression. We quantified reductions in state GDP, employment, and student test scores during the pandemic to identify policy and behavioural responses associated with these outcomes and to assess trade-offs between these outcomes and COVID-19 outcomes. Significance was defined as p<0·05. Standardised cumulative COVID-19 death rates for the period from Jan 1, 2020, to July 31, 2022 varied across the USA (national rate 372 deaths per 100 000 population [95% uncertainty interval [UI] 364-379]), with the lowest standardised rates in Hawaii (147 deaths per 100 000 [127-196]) and New Hampshire (215 per 100 000 [183-271]) and the highest in Arizona (581 per 100 000 [509-672]) and Washington, DC (526 per 100 000 [425-631]). A lower poverty rate, higher mean number of years of education, and a greater proportion of people expressing interpersonal trust were statistically associated with lower infection and death rates, and states where larger percentages of the population identify as Black (non-Hispanic) or Hispanic were associated with higher cumulative death rates. Access to quality health care (measured by the IHME's Healthcare Access and Quality Index) was associated with fewer total COVID-19 deaths and SARS-CoV-2 infections, but higher public health spending and more public health personnel per capita were not, at the state level. The political affiliation of the state governor was not associated with lower SARS-CoV-2 infection or COVID-19 death rates, but worse COVID-19 outcomes were associated with the proportion of a state's voters who voted for the 2020 Republican presidential candidate. State governments' uses of protective mandates were associated with lower infection rates, as were mask use, lower mobility, and higher vaccination rate, while vaccination rates were associated with lower death rates. State GDP and student reading test scores were not associated with state COVD-19 policy responses, infection rates, or death rates. Employment, however, had a statistically significant relationship with restaurant closures and greater infections and deaths: on average, 1574 (95% UI 884-7107) additional infections per 10 000 population were associated in states with a one percentage point increase in employment rate. Several policy mandates and protective behaviours were associated with lower fourth-grade mathematics test scores, but our study results did not find a link to state-level estimates of school closures. COVID-19 magnified the polarisation and persistent social, economic, and racial inequities that already existed across US society, but the next pandemic threat need not do the same. US states that mitigated those structural inequalities, deployed science-based interventions such as vaccination and targeted vaccine mandates, and promoted their adoption across society were able to match the best-performing nations in minimising COVID-19 death rates. These findings could contribute to the design and targeting of clinical and policy interventions to facilitate better health outcomes in future crises. Bill & Melinda Gates Foundation, J Stanton, T Gillespie, J and E Nordstrom, and Bloomberg Philanthropies.

A composite index for assessing accessibility in urban areas: A case study in Central Athens, Greece

Effective transportation planning necessitates the consideration of all road network users and their needs. Towards this goal, the integration of accessibility in planning and the development of tools that enable the assessment and measurement of accessibility within urban areas becomes essential. This study aims to contribute to the accessibility assessment process of urban areas by developing two accessibility indices: the infrastructure and the opportunity accessibility index, which use an infrastructure-based and distance-based approach, respectively. Four types of users and their needs are considered: pedestrians, People with Disabilities (PWD), cyclists and public transport users. Data for modeling the accessibility indices are collected by: 1) an infrastructure audit, 2) a user survey, and 3) geographic information systems. The proposed method is applied in a district in central Athens, Greece, which is characterized by high population density and high level of activities. The Infrastructure Accessibility Index (IAI) measures accessibility for sidewalks, crosswalks, bikeways and public transport stops. The IAI results indicate moderate accessibility levels for pedestrians and PWD, for sidewalks and crosswalks. The Opportunity Accessibility Index (OAI) measures the share of different types of users that reach different opportunities within a time threshold. The accepted time threshold per user type is estimated based on the survey responds, for seven different opportunities: green spaces, recreational spaces, education buildings, health buildings, public service building, commercial uses and public transport stops. Compared to the IAI, the majority of users reach different opportunities within the estimated time threshold. The study concludes with recommendations to improve accessibility levels at local level.

Corporate Members and Index to Advertisers

Information DisplayVolume 39, Issue 2 p. 52-52 Corporate Members and Index to AdvertisersFree Access Corporate Members and Index to Advertisers First published: 20 March 2023 https://doi.org/10.1002/msid.1385AboutPDF ToolsExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL No abstract is available for this article. Volume39, Issue2March/April 2023Pages 52-52 RelatedInformation

Transportation Accessibility Mapping with Educational Facilities Analysis of Nashik City

Accessibility is usually mentioned as the essential principle in new urban planning and land use growth theories. Researchers have proposed a change in the usage of auto mobility planning toward the planning of accessibility. Cities are primarily governed by various purposes, such as work, education and shopping. The main aim of this research is to find out the accessibility of Educational Trips related to different modes of transportation. With the useful resource of case studies included in the literature, we have learned terms and concepts of accessibility in order to achieve this objective. For doing accessibility analysis, firstly Nashik City's secondary information is gathered and evaluated. After doing the secondary analysis, gaps are identified and a primary survey questionnaire is designed so that accessibility can be measured and evaluated in a better way for the city. With the help of a design questionnaire, a primary survey is conducted in Nashik to learn about the city's current travel patterns as well as issues encountered during the trip. Data collected from the primary analysis are used to calculate an accessibility index with graphical method for different modes of transportation and mapped for each zone. Gravity method and Accessibility Ratio for Public transportation method which was used in this study can be used for finding the accessibility to different services like workplaces, recreational places, commercial places and many more. Policymakers can also use accessibility ratio method to improve public transportation infrastructure within the city.