Correlates of maternal depression, anxiety and functioning across an urban-rural gradient in northern Ecuador.

Maternal depression remains under characterised in many low- and middle-income countries, especially in rural settings. We aimed to describe maternal depression and anxiety symptoms in rural and urban communities in northern Ecuador and to identify socioeconomic and demographic factors associated with these symptoms. Data from 508 mothers participating in a longitudinal cohort study were included. Depression and anxiety symptoms were assessed using the Hopkins Symptom Checklist (HSCL-25), and maternal psychological functioning was assessed using a checklist of daily activities. Tobit regression models were used to examine associations with sociodemographic variables and urbanicity. The median HSCL-25 score was 1.2 (IQR: 0.4) and 14% of women scored above the threshold for clinically relevant symptoms. Rural women reported similar food insecurity, less education, younger age of first pregnancy, and lower socio-economic status compared to their urban counterparts. After adjusting for these factors, rural women reported lower HSCL-25 scores compared to women lin urban areas (ß = -0.48, 95%CI:0.65, -0.31). Rural residence was also associated with lower depression and anxiety HSCL-25 sub-scale scores, and similar levels of maternal functioning, compared to urban residence. Our results suggest that both household and community-level factors are risk factors for maternal depression and anxiety in this context.

Characterizing Behaviors Associated with Enteric Pathogen Exposure among Infants in Rural Ecuador through Structured Observations.

The relative importance of environmental pathways that results in enteropathogen transmission may vary by context. However, measurement of contact events between individuals and the environment remains a challenge, especially for infants and young children who may use their mouth and hands to explore their environment. Using a mixed-method approach, we combined 1) semistructured observations to characterize key behaviors associated with enteric pathogen exposure and 2) structured observations using Livetrak, a customized software application, to quantify the frequency and duration of contacts events among infants in rural Ecuador. After developing and iteratively piloting the structured observation instrument, we loaded the final list of prompts onto a LiveTrak pallet to assess environmental exposures of 6-month infants (N = 19) enrolled in a prospective cohort study of diarrheal disease. Here we provide a detailed account of the lessons learned. For example, in our field site, 1) most mothers reported washing their hands after diaper changes (14/18, 77.8%); however only a third (4/11, 36.4%) were observed washing their hands; 2) the observers noted that animal ownership differed from observed animal exposure because animals owned by neighboring households were reported during the observation; and 3) using Livetrak, we found that infants frequently mouthed their hands (median = 1.9 episodes/hour, median duration: 1.6 min) and mouthed surroundings objects (1.8 episodes/hour, 1.9 min). Structured observations that track events in real time, can complement environmental sampling, quantitative survey data and qualitative interviews. Customizing these observations enabled us to quantify enteric exposures most relevant to our rural Ecuadorian context.

Gut microbiome, enteric infections and child growth across a rural-urban gradient: protocol for the ECoMiD prospective cohort study.

INTRODUCTION: The functional consequences of the bacterial gut microbiome for child health are not well understood. Characteristics of the early child gut microbiome may influence the course of enteric infections, and enteric infections may change the composition of the gut microbiome, all of which may have long-term implications for child growth and development. METHODS AND ANALYSIS: We are conducting a community-based birth cohort study to examine interactions between gut microbiome conditions and enteric infections, and how environmental conditions affect the development of the gut microbiome. We will follow 360 newborns from 3 sites along a rural-urban gradient in northern coastal Ecuador, characterising enteric infections and gut microbial communities in the children every 3 to 6 months over their first 2 years of life. We will use longitudinal regression models to assess the correlation between environmental conditions and gut microbiome diversity and presence of specific taxa, controlling for factors that are known to be associated with the gut microbiome, such as diet. From 6 to 12 months of age, we will collect weekly stool samples to compare microbiome conditions in diarrhoea stools versus stools from healthy children prior to, during and after acute enteric infections, using principal-coordinate analysis and other multivariate statistical methods. ETHICS AND DISSEMINATION: Ethics approvals have been obtained from Emory University and the Universidad San Francisco de Quito institutional review boards. The findings will be disseminated through conference presentations and peer-reviewed journals.

A dengue outbreak in a rural community in Northern Coastal Ecuador: An analysis using unmanned aerial vehicle mapping.

Dengue is recognized as a major health issue in large urban tropical cities but is also observed in rural areas. In these environments, physical characteristics of the landscape and sociodemographic factors may influence vector populations at small geographic scales, while prior immunity to the four dengue virus serotypes affects incidence. In 2019, a rural northwestern Ecuadorian community, only accessible by river, experienced a dengue outbreak. The village is 2-3 hours by boat away from the nearest population center and comprises both Afro-Ecuadorian and Indigenous Chachi households. We used multiple data streams to examine spatial risk factors associated with this outbreak, combining maps collected with an unmanned aerial vehicle (UAV), an entomological survey, a community census, and active surveillance of febrile cases. We mapped visible water containers seen in UAV images and calculated both the green-red vegetation index (GRVI) and household proximity to public spaces like schools and meeting areas. To identify risk factors for symptomatic dengue infection, we used mixed-effect logistic regression models to account for the clustering of symptomatic cases within households. We identified 55 dengue cases (9.5% of the population) from 37 households. Cases peaked in June and continued through October. Rural spatial organization helped to explain disease risk. Afro-Ecuadorian (versus Indigenous) households experience more symptomatic dengue (OR = 3.0, 95%CI: 1.3, 6.9). This association was explained by differences in vegetation (measured by GRVI) near the household (OR: 11.3 95% 0.38, 38.0) and proximity to the football field (OR: 13.9, 95% 4.0, 48.4). The integration of UAV mapping with other data streams adds to our understanding of these dynamics.