AI Qualitative Analysis for Public Health: Dengue Lessons

According to the Strengthening community engagement for the control of Aedes-borne diseases: Insights from an international workshop in Rio de Janeiro, Brazil article published on November 4, 2026, community engagement is a core condition for effective, equitable, and sustainable mosquito-borne disease control.

AI qualitative analysis for public health can help teams turn large collections of community interviews, workshop records, and open-ended responses into traceable themes about trust, acceptability, barriers, and local priorities.

• The Rio workshop took place from September 22 to 24, 2025, and included more than 60 in-person participants plus 37 remote participants, according to Poinsignon and colleagues.
• The PLOS article reports that Brazil recorded 6.3 million dengue cases and more than 6, 000 dengue-related deaths in 2024, with disproportionate effects in neglected neighborhoods.
• The article states that more than 90% of Aedes breeding sites are found in household and peridomestic environments, making community consent and participation important to vector-control access.
• A Cuban sterile insect technique case discussed in the article recorded 67.9% community acceptance, showing why perception monitoring should continue during implementation.
• The workshop participants described meaningful engagement as a process that treats communities as partners rather than research subjects.

The Rio workshop shows that public health interventions are more likely to be durable when researchers combine technical evidence with community knowledge, according to Poinsignon and colleagues.

The workshop examined three connected questions: how social sciences can respond to environmental and climate change, how communities perceive interventions such as Wolbachia and sterile insect techniques, and how citizen science and digital tools can support surveillance.

The PLOS authors reported that the workshop brought together researchers, public health professionals, and community actors from the Americas, Europe, and Africa. The authors concluded that trust, locally grounded knowledge, participatory governance, and intersectoral collaboration shape the acceptability and sustainability of vector-control programs.

The article also identifies recurring barriers that qualitative research can make visible: misinformation, institutional mistrust, participation fatigue, security constraints, weak coordination, inadequate infrastructure, and the risk of placing responsibility on households while structural problems remain unresolved.

Poinsignon and colleagues quote a workshop message that “the biggest disease is poverty, ” linking mosquito control to broader conditions such as sanitation, waste management, housing, violence, and access to public services.

Public health teams should analyze community feedback as implementation evidence, not as a final communications check, according to the PLOS workshop article.

For intervention design, researchers should identify how residents describe local risks, which institutions they trust, and what practical constraints affect participation. The article reports that stakeholder mapping, community profiling, local dialogue, and community reference groups helped intervention teams understand social organization and decision-making before implementation.

For implementation monitoring, researchers should track changes in awareness, acceptability, concerns, rumors, and reported problems over time. The article describes periodic surveys and issue-management systems as ways to adapt communication and intervention strategies during Wolbachia and other vector-control programs.

For equity analysis, researchers should compare themes across neighborhoods, language groups, socioeconomic contexts, age groups, and other relevant segments. The workshop article warns that punitive approaches can blame residents for breeding sites when inadequate sanitation, waste services, or infrastructure limit what households can do.

For citizen science, researchers should analyze both the data produced by residents and the relationships created through participation. The article describes citizen-generated observations as useful for surveillance, while also emphasizing that long-term value depends on institutional support, stakeholder coordination, and trust.

Public health findings are research evidence, not medical diagnoses. AI-assisted analysis should support, rather than replace, ethical review, community governance, and expert interpretation.

The 2026 PLOS workshop article shows that sustainable Aedes-borne disease control depends on more than technology: trust, local knowledge, participation, and institutional support must be analyzed and maintained.

AI qualitative analysis can help public health and community-engagement teams synthesize interviews, open-ended surveys, workshop records, and citizen feedback at a practical scale while preserving comparisons across communities and stakeholder groups.

Evidano gives researchers a focused environment for thematic analysis, cross-segment comparison, document-based AI chat, and multilingual qualitative workflows. Try Evidano for free to turn community evidence into clearer research decisions.