Recent breakthroughs in large language models (LLMs) have generated both interest and concern about their potential adoption as information sources or communication tools across different domains. In public health, where stakes are high and impacts extend across diverse populations, adopting LLMs poses unique challenges that require thorough evaluation. However, structured approaches for assessing potential risks in public health remain under-explored. To address this gap, we conducted focus groups with public health professionals and individuals with lived experience to unpack their concerns, situated across three distinct and critical public health issues that demand high-quality information: infectious disease prevention (vaccines), chronic and wellbeing care (opioid use disorder), and community health and safety (intimate partner violence). We synthesize participants' perspectives into a risk taxonomy, identifying and contextualizing the potential harms LLMs may introduce when positioned alongside traditional health communication. This taxonomy highlights four dimensions of risk to individuals, human-centered care, information ecosystems, and technology accountability. For each dimension, we unpack specific risks and offer example reflection questions to help practitioners adopt a risk-reflexive approach. By summarizing distinctive LLM characteristics and linking them to identified risks, we discuss the need to revisit prior mental models of information behaviors and complement evaluations with external validity and domain expertise through lived experience and real-world practices. Together, this work contributes a shared vocabulary and reflection tool for people in both computing and public health to collaboratively reflect and assess risks in deciding when to employ LLM capabilities (or not) and how to mitigate harm.

While social computing technologies are increasingly being used to counter misinformation, more work is needed to understand how they can support the crucial work of community-based trusted messengers, especially in marginalized communities where distrust in health authorities is rooted in historical inequities. We describe an early exploration of these opportunities in our collaboration with Black and Latinx young adult "Peer Champions" addressing COVID-19 vaccine hesitancy the U.S. state of Georgia. We conducted interviews engaging them with a social media monitoring and outreach dashboard we designed, to probe their understanding of their roles and current and potential use of digital platforms. With the concept of cultural code-switching as a framing, we found that the Peer Champions leveraged their particular combination of cultural, health, and digital literacy skills to understand their communities' concerns surrounding misinformation and to communicate health information in a culturally appropriate manner. While being positioned between their communities and public health research and practice motivated and enabled their work, it also introduced challenges in finding (mis)information online and navigating tensions around authenticity and respect when engaging those close to them. Our research contributes towards characterizing the valuable and difficult work trusted messengers do, and (re)imagining collaboratively designed interpretive digital tools to support them.