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Attempts to decrease socioeconomic health disparities face various challenges, which include ethical questions about prioritization and value-conflicts. To deal with these questions in a way that takes equal standing as a central value, this paper explores the potential of a relational egalitarian capability approach to local health equity policies. Especially for local health equity policies, a relational egalitarian capability approach seems promising as it offers more perspectives for action and evaluation additional to considerations of distributive justice. To scrutinize if this approach can offer an adequate normative basis for health equity policies and be a helpful ethical guide in practice, five desiderata are identified that a relational egalitarian capability approach to local health equity should fulfil. These desiderata stem from a consideration of political-ethical pluralism and scarcity of time and resources as non-ideal conditions characterizing public policy practice, as well as of three questions that any capability approach should answer to be applicable in practice. For each of the five desiderata, a brief outline is given of what relational egalitarian theories and the capability approach offer in response to the questions implied by these desiderata. Ultimately, these questions need to be answered in relation to specific policies in particular contexts.

Despite renewed policy priorities to universalise health coverage, unmet need for healthcare is long-standing concern in India. The recent data suggests the unmet healthcare need amounts to a notable share of twelve per cent. While studies have examined inequalities in healthcare utilisation in single axes of social power, there was no consensus on the role of the intersectionality between class, caste and gender in shaping the unmet health need. Utilising data from National Sample survey 75th round (2017–18), this paper identifies the factors contributing to such unmet need and investigate the intersectionality of class with caste and gender in determining unmet need. The contribution of socioeconomic factors was assessed by the decomposition method & multivariate logistic regression was used to measure inter and intra-class differentials in unmet need. The analysis informs that class inequality is fundamental to having unmet need with limited role of gender and caste. Economic class however, interacting with caste and gender unfolds wider gaps in access to healthcare. While inter-class differences in unmet need are observed across caste as well as gender, intra-class differences intensify more by caste inequalities. The findings indicate the significance of the intersectional approach in identifying the sources of health inequity and special recognition to the income-poor and socially marginalised in policy agenda. Eliminating the barriers to health care access therefore needs a multidimensional construct of identifying combination of attributes to be focused towards realization of universal health coverage. These observations should aid in formulation and restructuring of the existing healthcare interventions to achieve equity in healthcare provision.

Intersectionality is a widely adopted theoretical orientation in the field of women and gender studies. Intersectionality comes from the work of black feminist scholars and activists. Intersectionality argues identities such as gender, race, sexuality, and other markers of difference intersect and reflect large social structures of oppression and privilege, such as sexism, racism, and heteronormativity. The reach of intersectionality now extends to the fields of public health and knowledge translation. Knowledge translation (KT) is a field of study and practice that aims to synthesize and evaluate research into an evidence base and move that evidence into health care practice. There have been increasing calls to bring gender and other social issues into the field of KT. Yet, as scholars outline, there are few guidelines for incorporating the principles of intersectionality into empirical research. An interdisciplinary, team-based, national health research project in Canada aimed to bring an intersectional lens to the field of knowledge translation. This paper reports on key moments and resulting tensions we experienced through the project, which reflect debates in intersectionality: discomfort with social justice, disciplinary divides, and tokenism. We consider how our project advances intersectionality practice and suggests recommendations for using intersectionality in health research contexts. We argue that while we encountered many challenges, our process and the resulting co-created tools can serve as a valuable starting point and example of how intersectionality can transform fields and practices.

In the aftermath of shock events, policy responses tend to be crafted under significant time constraints and high levels of uncertainty. The extent to which individuals comply with different policy designs can further influence how effective the policy responses are and how equitably their impacts are distributed in the population. Tools which allow policymakers to model different crisis trajectories, policy responses, and behavioral scenariosex antecan provide crucial timely support in the decision-making process. Set in the context of COVID-19 shelter in place policies, in this paper we present the COVID-19 Policy Evaluation (CoPE) tool, which is an agent-based modeling framework that enables researchers and policymakers to anticipate the relative impacts of policy decisions. Specifically, this framework illuminates the extent to which policy design features and behavioral responsiveness influence the efficacy and equity of policy responses to shock events. We show that while an early policy response can be highly effective, the impact of the timing is moderated by other aspects of policy design such as duration and targeting of the policy, as well as societal aspects such as trust and compliance among the population. More importantly, we show that even policies that are more effective overall can have disproportionate impacts on vulnerable populations. By disaggregating the impact of different policy design elements on different population groups, we provide an additional tool for policymakers to use in the design of targeted strategies for disproportionately affected populations.