Practical Applications: Communication and Dissemination Considerations

Applying equity-centered approaches to communication and dissemination

1. Use plain language and clear visuals to describe findings and implications. Prioritize accessible formats and dissemination strategies that are culturally and linguistically relevant to your population. When disseminating information to multiple groups, consider creating multiple data products to ensure your findings are accessible and relevant to each group. Use plain language accessible to individuals with intellectual disability and communications tailored to individuals with visual and hearing impairments. Gather feedback on materials from the communities you are trying to reach by leveraging advocacy organizations or other groups that include people with relevant lived experience.

2. Articulate decisions made during data processing and cleaning.
Data equity calls for consistent and transparent communication. Communicating data limitations in the context of your results will strengthen the findings and reduce ambiguity. Programs should take steps to clearly describe what populations are represented in their data, the variability of the data in the setting of statistical analyses, and proposed interpretations. This approach invites others to suggest alternative interpretations and develops trust between syndromic surveillance analysts and the public. This is particularly important when findings may seem to contradict earlier evidence or commonly held beliefs. Further, review and refine interpretation with public health programs, partners, and community members. Emphasize that data reflect populations with access to care and may not reflect the true population at risk.

3. Partner with communities to identify, design, and prioritize future actions stemming from the analyses.
At every step of the data lifecycle, there are choices made about what data are collected, how data are analyzed, who interprets the results and how they are disseminated. Include information about the data decisions when communicating with partners to allow others to offer suggestions and feedback. Transparent communication around data leads to more refined and equitable data practices.

4. Include community input when interpreting public health data and developing messaging, communication, and dissemination plans and materials to reduce misconceptions and misunderstandings.
Syndromic surveillance programs can present syndromic surveillance data in concert with other public health data to inform community members about the local impact of conditions and diseases. Community members can help interpret and contextualize data, prioritize health needs and concerns, and explore designs and plans for improvement. Working directly with community members builds trust and enhances the usability of syndromic surveillance data to guide public health actions.