Learning from an equitable, data-informed response to COVID-19: Translating knowledge into future action and preparation

Introduction

The COVID-19 pandemic revealed numerous barriers to effectively managing public health crises, including difficulties in using publicly available, community-level data to create learning systems in support of local public health decision responses. Early in the COVID-19 pandemic, a group of health care partners began meeting to learn from their collective experiences. We identified key tools and processes for using data and learning system structures to drive equitable public health decision making throughout different phases of the pandemic.

Methods

In fall of 2021, the team developed an initial theory of change directed at achieving herd immunity for COVID-19. The theoretical drivers were explored qualitatively through a series of nine 45-min telephonic interviews conducted with 16 public health and community leaders across the United States. Interview responses were analyzed into key themes to inform potential future practices, tools, and systems. In addition to the interviews, partners in Dallas and Cincinnati reflected on their own COVID-19 experiences.

Results

Interview responses fell broadly into four themes that contribute to effective, community driven responses to COVID-19: real-time, accessible data that are mindful of the tension between community transparency and individual privacy; a continued fostering of public trust; adaptable infrastructures and systems; and creating cohesive community coalitions with shared alignment and goals. These themes and partner experiences helped us revise our preliminary theory of change around the importance of community collaboration and trust building and also helped refine the development of the Community Protection Dashboard tool.

Conclusions

There was broad agreement amongst public health and community leaders about the key elements of the data and learning systems required to manage public health responses to COVID-19. These findings may be informative for guiding the use of data and learning in the management of future public health crises or population health initiatives.

Using Collaborative Coalition Processes to Advance Community Health, Well-Being, and Equity: A Multiple-Case Study Analysis From a National Community Transformation Initiative

Spreading Community Accelerators Through Learning and Evaluation (SCALE) was a Robert Wood Johnson Foundation-funded initiative from 2015 to 2017 to build capability of 24 community coalitions to advance health, well-being, and equity. The SCALE theory of change had three components: develop leadership capability, build relationships within and between communities, and create an intercommunity system to spread promising ideas. The theory was operationalized through training academies, coaching, and peer-to-peer learning that explicitly addressed equity and systems change. In this article, we describe how SCALE facilitated community transformation related to Collaborating for Equity and Justice Principles 1, 3, 4, and 6. We conducted a multiple-case study approach with two community coalitions including site visits, interviews, and observation to illuminate underlying mechanisms of change by exploring how and why change occurs. Skid Row Women worked with women experiencing homelessness in Los Angeles to address diabetes and food systems. Healthy Livable Communities of Cattaraugus County used a portfolio of projects in order to create system changes to improve population health and increase access to services for people with disabilities in rural New York State. Through our analysis, we describe how two coalitions used SCALE tools for collaborative coalition processes such as aim setting, relationship building, and shared decision making with community residents. Our findings suggest that advancing Collaborating for Equity and Justice principles requires self-reflection and courage; new ways of being in relationship; learning from failure; productive conflict to explicitly address power, racism, and other forms of oppression; and methods to test systems improvement ideas.