Participatory Methods for Climate Change and Mental Health Research: Photovoice in Nepal

Background: The relationship between mental health and climate change are poorly understood. Participatory methods represent ethical, feasible, and culturally-appropriate approaches to engage community members for mental health promotion in the context of climate change. Aim: Photovoice, a community-based participatory research methodology uses images as a tool to deconstruct problems by posing meaningful questions in a community to find actionable solutions. This community-enhancing technique was used to elicit experiences of climate change among women in rural Nepal and the association of climate change with mental health. Subjects and methods: Mixed-methods, including in-depth interviews and self-report questionnaires, were used to evaluate the experience of 10 women participating in photovoice. Quantitative tools included Nepali versions of Beck Depression Inventory (BDI) and Beck Anxiety Inventory (BAI) and a resilience scale. Results: In qualitative interviews after photovoice, women reported climate change adaptation and behavior change strategies including environmental knowledge-sharing, group mobilization, and increased hygiene practices. Women also reported beneficial effects for mental health. The mean BDI score prior to photovoice was 23.20 (SD=9.00) and two weeks after completion of photovoice, the mean BDI score was 7.40 (SD=7.93), paired t-test = 8.02, p<.001, n=10. Conclusion: Photovoice, as a participatory method, has potential to inform resources, adaptive strategies and potential interventions to for climate change and mental health.

Using GIS and Remote Sensing Technologies to Identify Environmental Variables of Malaria Vector Breeding Sites in Western Kenya

This study used Landsat 8 satellite imagery to identify environmental variables of households with malaria vector breeding sites in a malaria endemic rural district in Western Kenya. Understanding the influence of environmental variables on the distribution of malaria has been critical in the strengthening of malaria control programs. Using remote sensing and GIS technologies, this study performed a land classification, NDVI, Tasseled Cap Wetness Index, and derived land surface temperature values of the study area and examined the significance of each variable in predicting the probability of a household with a mosquito breeding site with and without larvae. The findings of this study revealed that households with any potential breeding sites were characterized by higher moisture, higher vegetation density (NDVI) and in urban areas or roads. The results of this study also confirmed that land surface temperature was significant in explaining the presence of active mosquito breeding sites (P< 0.000). The present study showed that freely available Landsat 8 imagery has limited use in deriving environmental characteristics of malaria vector habitats at the scale of the Bungoma East District in Western Kenya.