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Background: Human transmission of Chagas disease (CD) most commonly occurs in domiciliary spaces where triatomines remain hidden to feed on blood sources during inhabitants’ sleep. Similar to other neglected tropical diseases (NTDs), sustainable control of CD requires attention to the structural conditions of life of populations at risk, in this case, the conditions of their living environments. Considering socio-cultural and political dynamics involved in dwellings’ construction, this study aimed to explore social factors that contribute or limit sustainability of CD’s prevention models focused on home improvement. Methods and main findings: Using Healthy Homes for Healthy Living (HHHL)—a health promotion strategy focused on improvement of living environments and system-based health promotion—as a reference, a qualitative study was conducted. Research participants were selected from three rural communities of a CD endemic region in southern Ecuador involved in HHHL’s refurbishment and reconstruction interventions between 2013 and 2016. Folowing an ethnographic approach, data were collected through interviews, participant observation, informal conversations and document analysis. Our results indicate that the HHHL model addressed risk factors for CD at the household level, while simultaneously promoting wellbeing at emotional, economic and social levels in local communities. We argue that sustainability of the CD prevention model proposed by HHHL is enhanced by the confluence of three factors: systemic improvement of families’ quality of life, perceived usefulness of control measures, and flexibility to adapt to emerging dynamics of the context. Conclusion: HHHL’s proposed home improvement, facilitated through system-based rather than disease specific health promotion processes, enhances agency in populations at risk and facilitates community partnerships forged around CD prevention. Although an independent analysis of cost-effectiveness is recommended, structural poverty experienced by local families is still the most important factor to consider when evaluating the sustainability and scalability of this model. [ABSTRACT FROM AUTHOR]

Season is a major determinant of infectious disease rates, including arboviruses spread by mosquitoes, such as dengue, chikungunya, and Zika. Seasonal patterns of disease are driven by a combination of climatic or environmental factors, such as temperature or rainfall, and human behavioral time trends, such as school year schedules, holidays, and weekday-weekend patterns. These factors affect both disease rates and healthcare-seeking behavior. Seasonality of dengue fever has been studied in the context of climatic factors, but short- and long-term time trends are less well-understood. With 2009–2016 medical record data from patients diagnosed with dengue fever at two hospitals in rural Ecuador, we used Poisson generalized linear modeling to determine short- and long-term seasonal patterns of dengue fever, as well as the effect of day of the week and public holidays. In a subset analysis, we determined the impact of school schedules on school-aged children. With a separate model, we examined the effect of climate on diagnosis patterns. In the first model, the most important predictors of dengue fever were annual sinusoidal fluctuations in disease, long-term trends (as represented by a spline for the full study duration), day of the week, and hospital. Seasonal trends showed single peaks in case diagnoses, during mid-March. Compared to the average of all days, cases were more likely to be diagnosed on Tuesdays (risk ratio (RR): 1.26, 95% confidence interval (CI) 1.05–1.51) and Thursdays (RR: 1.25, 95% CI 1.02–1.53), and less likely to be diagnosed on Saturdays (RR: 0.81, 95% CI 0.65–1.01) and Sundays (RR: 0.74, 95% CI 0.58–0.95). Public holidays were not significant predictors of dengue fever diagnoses, except for an increase in diagnoses on the day after Christmas (RR: 2.77, 95% CI 1.46–5.24). School schedules did not impact dengue diagnoses in school-aged children. In the climate model, important climate variables included the monthly total precipitation, an interaction between total precipitation and monthly absolute minimum temperature, an interaction between total precipitation and monthly precipitation days, and a three-way interaction between minimum temperature, total precipitation, and precipitation days. This is the first report of long-term dengue fever seasonality in Ecuador, one of few reports from rural patients, and one of very few studies utilizing daily disease reports. These results can inform local disease prevention efforts, public health planning, as well as global and regional models of dengue fever trends. [ABSTRACT FROM AUTHOR]