"Exploring vulnerabilities A mixed-method Transdisciplinary Study of Dengue and Diarrhea in Peru"

Introduction: This study explores the multifactorial vulnerabilities to dengue and diarrhea in Peru, particularly within the municipality of Caballococha, in the Loreto department (region). It elucidates the complex interactions between climate change, socio-economic inequalities, and public health, while emphasizing the importance of combining collaborative knowledge strategies with both macro-level data analysis and micro-level experiential insights.
Methods: We employed a transdisciplinary-inspired methodology, integrating mixed method approaches with active participant engagement across multiple research stages. Utilizing literature and publicly available datasets, we developed a statistical model, the National Vulnerability Index (NVI), to identify risk factors for dengue and diarrhea at the national level. Through the Dialogue of Knowledge (DoK) methodology—a participatory framework that melds local and scientific knowledge—we explored perspectives and the lived experiences related to dengue and diarrhea in one single municipality, Caballococha. This approach facilitated a deeper understanding of vulnerability processes and enabled joint planning of mitigation strategies with the community.
Results: The NVI indicated that dengue and diarrhea exhibit contrasting spatial patterns of vulnerablity, with the jungle more vulnerable for diarrhea than for dengue. This pattern may be more associated with gender-based vulnerabilities and self identification from an Amazonic population, rather than by water access and sanitation.
Infrastructure: The DoK sessions identified critical local factors contributing to increased disease incidence, including inadequate water and sanitation infrastructure, unplanned urbanization, occupational exposure, and geographic isolation. These factors not only corroborate themes discussed in the literature but also reveal some gaps. Additionally, we co-created mitigation strategies that centered on strengthening municipal infrastructure, expanding preventive education, and fostering cross-sector collaboration.
Conclusions: This study underscores the critical importance of integrating scientific data with local knowledge to devise effective public health interventions. Despite challenges such as data granularity and model fit, our findings provide actionable insights for context-specific strategies, especially in under-resourced, climate-sensitive areas. Our research emphasizes the value of transdisciplinary frameworks in addressing the complex challenges posed by climate-sensitive diseases and highlights the role of borderland regions like Caballococha as crucial epistemic sites for boosting public health resilience.