Zooming in and Out: A Holistic Framework for Research on Maternal, Late Fetal, and Newborn Survival and Health

Research is needed to understand why some countries succeed in greater improvements maternal, late fetal and newborn health and reducing mortality than others. Pathways towards these health outcomes operate at many levels, making it difficult to understand which factors contribute most to these health improvements. Conceptual frameworks provide a cognitive means of rendering order to these factors, and how they interrelate to positively influence maternal, late fetal and newborn health. We developed a conceptual framework by integrating theories and frameworks from different disciplines to encapsulate the range of factors that explain reductions in maternal, late fetal and newborn mortality and improvements in health. We developed our framework iteratively, combining our interdisciplinary research team’s knowledge, experience, and review of the literature. We present a framework that includes health policy and systems levers (or intentional actions that policy makers can implement) to improve maternal, late fetal and newborn health; service delivery and coverage of interventions across the continuum of care, and epidemiological and behavioural risk factors. The framework also considers the role of context in influencing for whom and where health and non-health efforts have the most impact, to recognise ‘the causes of the causes’ at play at the individual/household, community, national and transnational levels. Our framework holistically reflects the range of interrelated factors influencing improved maternal, late fetal and newborn health and survival. The framework lends itself to studying how different factors work together to influence these outcomes using an array of methods. Such research should inform future efforts to improve maternal, late fetal and newborn health and survival in different contexts. By re-orienting research in this way, we hope to equip policymakers and practitioners alike with the insight necessary to make the world a safer and fairer place for mothers and their babies.

Indicators for Sanitation Quality in Low-Income Urban Settlements: Evidence from Kenya, Ghana, and Bangladesh

In recent years, shared facilities have contributed substantially to increased access to sanitation in urban areas. While shared sanitation is often the only viable option in densely-populated, low-income urban areas, it is currently considered a “limited" solution by the international community. In this paper, we analyze the conditions under which shared sanitation could be considered of adequate quality and propose a set of indicators associated with sanitation quality to be included in national household surveys. We conducted a survey with 3600 households and 2026 observational spot-checks of shared and individual household toilets in Kisumu (Kenya), Kumasi (Ghana), and Dhaka (Bangladesh). We develop a composite sanitation quality outcome measure based on observational data. Using regression analysis, we identify self-reported indicators that correlate with the spot-checked composite measure and are, therefore, robust with regard to reporting bias. Results show that (pour-) flush toilets are a highly informative indicator for sanitation quality compared to other toilet technologies. In contrast to previous arguments and depending on the context, sharing a toilet has a comparatively lower correlation with sanitation quality. Toilets still show good quality if shared among only 2–3 households. Toilet location and lighting, as well as the presence of a lockable door, are equally strong indicators for sanitation quality and could serve as alternative indicators. The findings suggest that the sanitation service levels defined by the WHO and UNICEF might be reconsidered to better capture the quality of sanitation facilities in low-income urban settlements.

Exploiting Smart Meter Power Consumption Measurements for Human Activity Recognition (HAR) with a Motif-Detection-Based Non-Intrusive Load Monitoring (NILM) Approach

Numerous approaches exist for disaggregating power consumption data, referred to as non-intrusive load monitoring (NILM). Whereas NILM is primarily used for energy monitoring, we intend to disaggregate a household’s power consumption to detect human activity in the residence. Therefore, this paper presents a novel approach for NILM, which uses pattern recognition on the raw power waveform of the smart meter measurements to recognize individual household appliance actions. The presented NILM approach is capable of (near) real-time appliance action detection in a streaming setting, using edge computing. It is unique in our approach that we quantify the disaggregating uncertainty using continuous pattern correlation instead of binary device activity states. Further, we outline using the disaggregated appliance activity data for human activity recognition (HAR). To evaluate our approach, we use a dataset collected from actual households. We show that the developed NILM approach works, and the disaggregation quality depends on the pattern selection and the appliance type. In summary, we demonstrate that it is possible to detect human activity within the residence using a motif-detection-based NILM approach applied to smart meter measurements.

Unravelling adolescent girls’ aspirations in Nepal: Status and associations with individual-, household-, and community-level characteristics

Background Adolescents’ aspirations have potential to influence their present and future well-being. Limited knowledge exists on adolescent girls’ aspirations and their determinants, particularly in low-income contexts. Methods and findings Using cross-sectional data, collected in 2018 in Nepal, within the Suaahara II Adolescent Panel Survey, (n = 840), adolescent girls’ aspirations in several domains—education, occupation, marriage, fertility, health, and nutrition–were described. Regression models were estimated to explore associations between individual, household and community characteristics and these aspirations for all adolescents and separately for younger (10–14 years) and older (15–19 years) girls. Age, school attendance, and self-efficacy, as well as household wealth, caste/ethnicity, size, and agro-ecological zone of residence were significantly associated with aspirations, although effect sizes and significance varied by aspiration domain and age group. Conclusions Findings underscore the curtailing effect of poverty on aspirations and the dynamic nature of aspirations. Initiatives to foster girls’ aspirations must address both individual and contextual factors.

Tactical Target Date Funds

We propose target date funds modified to exploit stock return predictability driven by the variance risk premium. The portfolio rule of these tactical target date funds (TTDFs) is extremely simplified relative to the optimal one, making it easy to implement and to communicate to investors. We show that saving for retirement in TTDFs generates economically large welfare gains, even after we introduce turnover restrictions and transaction costs, and after taking into account parameter uncertainty. This predictability also appears to be uncorrelated with individual household risk, suggesting that households are in a prime position to exploit it. This paper was accepted by Tomasz Piskorski, finance.