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The COVID-19 pandemic has posed many challenges in almost all sectors around the globe. Because of the pandemic, government entities responsible for managing health-care resources face challenges in managing and distributing their limited and valuable health resources. In addition, severe outbreaks may occur in a small or large geographical area. Therefore, county-level preparation is crucial for officials and organizations who manage such disease outbreaks. However, most COVID-19-related research projects have focused on either state- or country-level. Only a few studies have considered county-level preparations, such as identifying high-risk counties of a particular state to fight against the COVID-19 pandemic. Therefore, the purpose of this research is to prioritize counties in a state based on their COVID-19-related risks to manage the COVID outbreak effectively.

In this research, the authors use a systematic hybrid approach that uses a clustering technique to group counties that share similar COVID conditions and use a multi-criteria decision-making approach – the analytic hierarchy process – to rank clusters with respect to the severity of the pandemic. The clustering was performed using two methods, k-means and fuzzy c-means, but only one of them was used at a time during the experiment.

The results of this study indicate that the proposed approach can effectively identify and rank the most vulnerable counties in a particular state. Hence, state health resources managing entities can identify counties in desperate need of more attention before they allocate their resources and better prepare those counties before another surge.

To the best of the authors’ knowledge, this study is the first to use both an unsupervised learning approach and the analytic hierarchy process to identify and rank state counties in accordance with the severity of COVID-19.

This study contributes to a growing body of literature on the Paycheck Protection Program (PPP) by examining how lender incentives affected prioritization of large borrowers. In addition, this study separately examines incentives for commercial banks and credit unions during the program.

Using 2020 PPP loan data, the authors create a proxy for lender loan prioritization by comparing the skewness statistics of large and small loan distributions. A regression model is used to examine lender reporting incentives and loan prioritization.

Results show that larger borrowers were prioritized in receiving PPP loans earlier. Lenders with financial reporting concerns and commercial banks favored large borrowers to a greater extent.

This study may inform social planners and regulators about the benefits and costs of delegating emergency funding loan decisions to financial institutions.

The authors believe this paper is the first to examine financial institution reporting incentives in relationship to PPP lending practices. It adds novelty by examining lender incentives, while prior research has focused heavily on the economic consequences of the program and how borrower–lender relationships affected loan practices during the program.

The purpose of this study is to evaluate the impact of food access and other vulnerability measures on the COVID-19 progression to inform the public health decision-makers while setting priority rules for vaccine schedules.

In this paper, the authors used the Supplemental Nutrition Assistance Program (SNAP) data combined with the Centers for Disease Control and Prevention (CDC)’s social vulnerability score variables and diabetes and obesity prevalence in a set of models to assess the associations with the COVID-19 prevalence and case-fatality rates in the United States (US) counties. Using the case prevalence estimates provided by these models, the authors developed a COVID-19 vulnerability score. The COVID-19 vulnerability score prioritization is then compared with the pro-rata approach commonly used for vaccine distribution.

The study found that the population proportion residing in a food desert is positively correlated with the COVID-19 prevalence. Similarly, the population proportion registered to SNAP is positively correlated with the COVID-19 prevalence. The findings demonstrate that commonly used pro-rata vaccine allocation can overlook vulnerable communities, which can eventually create disease hot-spots.

The proposed methodology provides a rapid and effective vaccine prioritization scoring. However, this scoring can also be considered for other humanitarian programs such as food aid and rapid test distribution in response to the current and future pandemics.

Humanitarian logistics domain predominantly relies on equity measures, where each jurisdiction receives resources proportional to their population. This study provides a tool to rapidly identify and prioritize vulnerable communities while determining vaccination schedules.

This paper discusses a multifaceted approach to developing specific and general climate resilience in a state transportation system that focuses on organizations and physical infrastructure. The paper focuses on resilience building to the dynamically evolving climate-related threats and extreme events in a transportation agency. This paper aims to enable agencies to understand better how their systems are exposed to different hazards and provide the information necessary for prioritizing their assets and systems for resilience improvement.

This paper leverages long-term climate hazard databases, spatial and statistical analyses and nonprobabilistic approaches for specific and general climate resilience improvement. Spatial and temporal variability assessments were conducted on granular historical records of exposure obtained from Spatial Hazards Events and Losses Database for the United States data set to identify emerging hot spots of exposure. These were then assessed in combination with various asset specific vulnerability parameters, presented with examples of pavements and bridges. Specific metrics were obtained for the various aspects of vulnerability in the context of a given asset to estimate the overall vulnerability. A criticality-vulnerability matrix was then developed to provide a prioritization model for transportation systems.

This paper provides insights into the evolving nature of exposure, vulnerability and risk assessments and an approach to systematically account for climate change and the uncertainties associated with it in resilience planning. The Multi-Hazards Exposure, Vulnerability and Risk Assessment tool presented in this paper conducts climate hazard exposure, vulnerability and risk analysis on pavements, bridges and culverts and can be applied by any transportation agency.

This study does not address operational aspects of the transportation system nor include future climate scenario data, but uses the historical records available at hand for resilience planning. With better climate projection data available in the future, the approach should be enhanced by leveraging scenario-based planning.

This paper is of potential value to practitioners and researchers interested in developing resilience building capabilities to manage the effects of climate-related hazards and extreme events as well as unknown threats on infrastructure and organizational performance.

This paper bridges an important gap in infrastructure resilience approaches by systematically accounting for the dynamic nature of climate change and the system level context of vulnerability beyond the physical condition of assets.

This chapter addresses the growing need to analyze the relationship between COVID-19 vulnerability and disability status at the national scale in the US. It presents a quantitative study that seeks to determine whether US counties more vulnerable to the COVID-19 pandemic contain significantly higher percentages of people with disabilities (PwDs), in general, and socially disadvantaged PwDs (based on their ethnicity/race, biological sex, age poverty, and employment status), in particular.

Vulnerability to COVID-19 is measured using the COVID-19 Pandemic Vulnerability Index (PVI) model developed by the National Institute of Environmental Health Sciences, which integrates multiple variables into relevant indicators that are weighted and combined to formulate a county-level PVI score. These scores are linked to a wide range of disability-related variables from the 2019 American Community Survey five-year estimates. Statistical analyses are based on multivariable generalized estimating equations that extend the generalized linear model to account for spatial clustering.

US counties more vulnerable to the COVID-19 pandemic are characterized by significantly higher percentages of PwDs, when vaccination is considered in estimating the PVI. These counties also contain significantly higher percentages of ethnic/racial minority, female, below poverty, and unemployed PwDs, in multiple timeframes of the pandemic.

The findings provide important insights and new knowledge on the relationship between COVID-19 vulnerability and socially disadvantaged PwDs in the US. The county-level associations highlight the need for additional data and more detailed analysis to examine the differential impacts of this pandemic on PwDs, as well as formulate appropriate intervention strategies.

Purpose – State and national environmental justice (EJ) programs have expanded in recent years to address new risks and challenges. Several programs including the Environmental Protection Agency's (EPA) Environmental Justice Small Grants (EJSG) program have helped to facilitate this growth. Since 1994, more than 1,000 small grants have been awarded through the EJSG to support communities in developing solutions to local environmental and public health problems. This chapter evaluates the collective impact of these investments.

Design/methodology/approach – Using Geographic Information Systems (GIS) to map the locations of EJSG funds relative to data from the Toxics Release Inventory (TRI), this chapter addresses two main questions. First, are grants being awarded to the types of communities (low-income, minority areas facing major environmental hazards) intended to be served by the program? Second, have there been any significant environmental changes in EJSG areas since the start of the program?

Findings – Results of county-level spatial analysis reveal that EJ grants are only in part being awarded to minority or low-income counties facing higher than the national average TRI releases and that average toxic releases have increased significantly in EJSG counties in some EPA regions relative to non-EJSG counties.

Originality/value – These results and the novel application of mapping methods to tracking small grants allocations highlight the need for systematic EJ program evaluation and coordination.

Unprecedented levels of investment in transit and transit-oriented development in Los Angeles County have not resulted in gains for transit-dependent populations or overall higher ridership for that matter. They have instead saddled them with inordinate cost burdens and displacement pressures. Yet racialised, low-income communities that rely on transit are far from passive victims. Rather, they are participating in advocacy campaigns that penetrate decision-making venues and procedures and co-create institutional practices, policy priorities, and public and private investments that serve their interests and build a Los Angeles that is more widely accessible and affordable. This chapter presents a case study of the Alliance for Community Transit-Los Angeles (ACT-LA), a regional coalition of over 40 community-based organisations at the helm of direct-action policy campaigns and participatory planning initiatives to advance transit justice and equitable transit-oriented communities (TOC). After examining ACT-LA's origins in the LA-based movement for community benefits agreements, the analysis focuses on how ACT-LA has combined political mobilisation for ballot-box measures with participatory policy-making and planning processes to advance just, equitable, sustainable transit systems, and TOC. The concluding discussion considers the implications of the ACT-LA case for reformulating participatory policy-making and planning around transportation and land use to further equity and climate goals.

The purpose of this paper is to analyse ethical competence related to healthcare governance and management tasks at the county/regional level in Sweden. The paper also discusses conditions that support or constrain the development and application of such competence.

The study is based on original qualitative data from 13 interviews and 6 meeting observations. Three key groups of actors were included: politicians, civil servants and CEOs in publicly financed health-provider organizations. An abductive analysis was carried out by a stepwise method guided by thematic research questions.

The informants viewed themselves as having a high degree of ethical responsibility for healthcare practice. However, they did not integrate ethical reflection and dialogue into their work decisions (e.g. regarding budgets, reforms and care agreements). The current organization, control systems and underlying business principles, along with the individuals’ understanding of their own and others’ roles, tended to constrain the development and use of ethical competence.

Qualities of an appropriate ethical competence related to healthcare governance and management, and conditions to develop and use such competence, are suggested.

Hardly any empirical research has examined ethical competence related to healthcare governance and management tasks. The paper integrates ethics and theories on learning in organizations and contributes knowledge about ethical competence and the conditions necessary to develop and practise ethical competence in an organizational and inter-organizational context.

An important part of the Northwest Forest Plan was 1.2 billion dollars of community development assistance made available to northern California, Oregon, and Washington through the Northwest Economic Adjustment Initiative (NEAI). The NEAI developed a complex institutional structure to eliminate regional administrative gridlock and enable workers and families, businesses, communities, and tribes that depended on forest product-based economies to regain or improve their economic and social well-being. As part of an evaluation of NEAI that included 31 community case studies, institutional analysis gauged how the initiativeʼs institutional and organizational structure affected program implementation. This paper examines how the institutional analysis complemented the community case studies, the use of Schneider and Ingramʼs policy design framework as a tool for describing and assessing the initiativeʼs institutional design, and the lessons learned from the overall evaluation.

Scholars and practitioners have come to understand the important role of local governments in the causes and effects of climate change. The literature has examined both the substantive and symbolic determinants of urban sustainability policies in addition to the implementation issues associated with those policies. At the heart of these policies is the idea that local governments have the desire and ability to engage in socially and environmentally responsible practices to mitigate climate change. While important, these studies are missing a key component in the investigation of local government involvement in sustainability policies: government purchasing power. This study examines the effect of administrative professionalism and interest group presence on the determinants of green procurement in the understudied context of counties in the United States.