Paradata analyses to inform population-based survey capture of pregnancy outcomes: EN-INDEPTH study.

BACKGROUND: Paradata are (timestamped) records tracking the process of (electronic) data collection. We analysed paradata from a large household survey of questions capturing pregnancy outcomes to assess performance (timing and correction processes). We examined how paradata can be used to inform and improve questionnaire design and survey implementation in nationally representative household surveys, the major source for maternal and newborn health data worldwide. METHODS: The EN-INDEPTH cross-sectional population-based survey of women of reproductive age in five Health and Demographic Surveillance System sites (in Bangladesh, Guinea-Bissau, Ethiopia, Ghana, and Uganda) randomly compared two modules to capture pregnancy outcomes: full pregnancy history (FPH) and the standard DHS-7 full birth history (FBH+). We used paradata related to answers recorded on tablets using the Survey Solutions platform. We evaluated the difference in paradata entries between the two reproductive modules and assessed which question characteristics (type, nature, structure) affect answer correction rates, using regression analyses. We also proposed and tested a new classification of answer correction types. RESULTS: We analysed 3.6 million timestamped entries from 65,768 interviews. 83.7% of all interviews had at least one corrected answer to a question. Of 3.3 million analysed questions, 7.5% had at least one correction. Among corrected questions, the median number of corrections was one, regardless of question characteristics. We classified answer corrections into eight types (no correction, impulsive, flat (simple), zigzag, flat zigzag, missing after correction, missing after flat (zigzag) correction, missing/incomplete). 84.6% of all corrections were judged not to be problematic with a flat (simple) mistake correction. Question characteristics were important predictors of probability to make answer corrections, even after adjusting for respondent's characteristics and location, with interviewer clustering accounted as a fixed effect. Answer correction patterns and types were similar between FPH and FBH+, as well as the overall response duration. Avoiding corrections has the potential to reduce interview duration and reproductive module completion by 0.4 min. CONCLUSIONS: The use of questionnaire paradata has the potential to improve measurement and the resultant quality of electronic data. Identifying sections or specific questions with multiple corrections sheds light on typically hidden challenges in the survey's content, process, and administration, allowing for earlier real-time intervention (e.g.,, questionnaire content revision or additional staff training). Given the size and complexity of paradata, additional time, data management, and programming skills are required to realise its potential

Advanced Sentinel-1 Analysis Ready Data for Africa (ESA EO4SD: SAR-4-Africa), D5 – Final Report

Sentinel-1 (S1) of the European Copernicus Program provide consistent global cloud-independent synthetic aperture radar (SAR) imagery. However, there is a strong reluctance to use SAR data because of its complexity. Combined with the vast amount of data, S1 is out of reach for many stakeholders that could benefit from its monitoring potential. This project aims to overcome these technical challenges and subjective reluctance by providing attractive, easy-to-use “Advanced Sentinel-1 Analysis Ready Data” (ASARD) imagery. The main objective is to incite especially African users to include S1 data in their operations and thereby support the UN Sustainable Development Goals.publishedVersio

Renewable Human Cell Model for Type 1 Diabetes Research: EndoC-βH5/HUVEC Coculture Spheroids

In vitro drug screening for type 1 diabetes therapies has largely been conducted on human organ donor islets for proof of efficacy. While native islets are the ultimate target of these drugs (either in situ or for transplantation), significant benefit can be difficult to ascertain due to the highly heterogeneous nature of individual donors and the overall scarcity of human islets for research. We present an in vitro coculture model based on immortalized insulin-producing beta-cell lines with human endothelial cells in 3D spheroids that aims to recapitulate the islet morphology in an effort towards developing a standardized cell model for in vitro diabetes research. Human insulin-producing immortalized EndoC-βH5 cells are cocultured with human endothelial cells in varying ratios to evaluate 3D cell culture models for type 1 diabetes research. Insulin secretion, metabolic activity, live cell fluorescence staining, and gene expression assays were used to compare the viability and functionality of spheroids composed of 100% beta-cells, 1 : 1 beta-cell/endothelial, and 1 : 3 beta-cell/endothelial. Monoculture and βH5/HUVEC cocultures formed compact spheroids within 7 days, with average diameter ~140 μm. This pilot study indicated that stimulated insulin release from 0 to 20 mM glucose increased from ~8-fold for monoculture and 1 : 1 coculture spheroids to over 20-fold for 1 : 3 EndoC-βH5/HUVEC spheroids. Metabolic activity was also ~12% higher in the 1 : 3 EndoC-βH5/HUVEC group compared to other groups. Stimulating monoculture beta-cell spheroids with 20 mM glucose +1 μg/mL glycine-modified INGAP-P increased the insulin stimulation index ~2-fold compared to glucose alone. Considering their availability and consistent phenotype, EndoC-βH5-based spheroids present a useful 3D cell model for in vitro testing and drug screening applications

Nile River Basin: Ecohydrological challenges, climate change and hydropolitics

Rainfed agriculture will continue to play an important role in achieving food security and reducing poverty in sub-Saharan Africa (SSA). But it is threatened by a combination of technology, policy, and institutional failures. Effects of recurrent drought and future climatic changes would affect rainfed systems and it would be most felt in SSA systems, where local institutions are not yet well prepared to respond to emerging climatic shocks. Rainwater management (RWM) is one strategy that could minimize drought effects through mapping, capturing, storing, and efficiently utilizing runoff and surface water emerging from farms and watershed for both productive purposes and ecosystem services. The extra water saved could be used to grow long maturing crops, producing more than one crop per season or diversify production systems. Enabling wider adoption of RWM interventions would improve the profitability of smallholder agriculture by increasing crop and livestock yield by factors of up to fivefold, while net returns on investment could double. However, adoptions of these interventions demand supportive policies and institutions, to enable farmer innovation, multi-institutional engagements, and collective action of actors at various levels. This is particularly critical in semiarid river basins, for instance the Nile basin, where because water availability is seasonal, upstream water towers are threatened by land degradation and deforestation and competition for surface water is becoming severe and could ignite regional conflict. This chapter contributes to the ongoing discussion on rainfed agriculture by not only inventorying the available RWM technologies and practices that could be used by small-scale farmers under various drought scenarios but also reviewing the challenges of technology uptake. It suggests institutional arrangements and policy recommendations required to improve uptake of RWM interventions at local, national, and regional levels

Estimating crop yields and production by integrating the FAO Crop Specific Water Balance model with real-time satellite data and ground-based ancillary data

An operational crop yield model was developed by introducing real-time satellite imagery into a Geographical Information System (GIS) and the Crop Specific Water Balance (CSWB) model of the Food and Agriculture Organization (FAO). Input databases were developed with three different resolutions; agro-ecological zone (AEZ) polygons, 7.6 km and 1.1 km pixels; from archived satellite data commonly used by Early Warning Systems (EWS) to simulate maize yield and production in Kenya from 1989 to 1997. Simulated production results from the GIS-based CSWB model were compared to historical maize production reports from two Government of Kenya (GoK) agencies. The coefficients of determination (r2) between the model and GoK district reports ranged from 0.86 to 0.89. The results indicated the 7.6 km pixel-by-pixel analysis was the most favorable method due to the Rainfall Estimate (RFE) input data having the same resolution. The GIS-based CSWB model developed by this study could also be easily expanded for use in other countries, extended for other crops, and improved in the future as satellite technologies improve

Knowledge and Practice of Wound Care and Associated Factors among Nurses Working in South Wollo Zone Government Hospitals, Ethiopia

Belachew Tegegne,1 Feruza Yimam,2 Zemen Mengesha Yalew,1 Mekuriaw Wuhib,1 Leul Mekonnen,1 Yibeltal Asmamaw Yitayew,3 Sewunet Ademe,1 Dejen Tsegaye,4 Yeshiambaw Eshetie,5 Muluken Chanie6 1Department of Comprehensive Nursing, College of Medicine and Health Sciences, Wollo University, Dessie, Ethiopia; 2Department of Nursing, Tropical College of Medicine, Dessie, Ethiopia; 3Department of Pediatrics and Child Health Nursing, College of Medicine and Health Sciences, Wollo University, Dessie, Ethiopia; 4Department of Nursing, College of Health Science, Debre Markos University, Debre Markos, Ethiopia; 5Department of Nursing, College of Health Science, Debre Tabor University, Debre Tabor, Ethiopia; 6Department of Nursing, Debre Tabor Health Science College, Debre Tabor, EthiopiaCorrespondence: Zemen Mengesha Yalew, Tel +251 91-805-7019, Email [email protected]: Wound infection is caused by pathogenic organisms invading viable tissue surrounding a localized defect or excavation in the skin or underlying soft tissue. Nurses have a critical role in wound care and dressing selection, and they should strive to stay current in this ever-changing field. To prevent wound infection, it is essential to improve wound-care knowledge and practice.Objective: To assess knowledge and practice of wound care and associated factors among nurses working in government hospitals of South Wollo Zone, Ethiopia.Methods: A hospital-based cross-sectional study design was used among 422 randomly selected nurses in government hospitals in South Wollo. A pretested structured self-administered questionnaire was used to collect data. Data were entered in EpiData 4.4.2 and exported to SPSS 25.0 for analysis. Descriptive statistics and bivariate and multivariate logistic regression were applied. Variables with P value < 0.05 were considered statistically significant for knowledge and good practice of wound care.Results: According to the findings, 40.3% and 51.0% had good knowledge and practice of wound care, respectively. Holding a bachelor’s degree or above (AOR 3.27, 95% CI 1.97– 5.43) and training (AOR 3.71, 95% CI 2.37– 5.81) were significantly associated with knowledge of wound care. More than 10 years of experience (AOR 3.15, 95% CI 1.96– 5.04), training (AOR 3.75, 95% CI, 2.38– 5.85), and not having a patient load (AOR 3.15, 95% CI 1.96– 5.04) were significantly associated with wound-care practices.Conclusion: Nurses’ wound-care knowledge and practice were low. Knowledge and practice on wound care were determined by educatio, training, patient load, and experience. Nurses should get training and share experience.Keywords: wound care, knowledge, practice, Ethiopi

Paradata analyses to inform population-based survey capture of pregnancy outcomes: EN-INDEPTH study

Background: Paradata are (timestamped) records tracking the process of (electronic) data collection. We analysed paradata from a large household survey of questions capturing pregnancy outcomes to assess performance (timing and correction processes). We examined how paradata can be used to inform and improve questionnaire design and survey implementation in nationally representative household surveys, the major source for maternal and newborn health data worldwide. Methods: The EN-INDEPTH cross-sectional population-based survey of women of reproductive age in five Health and Demographic Surveillance System sites (in Bangladesh, Guinea-Bissau, Ethiopia, Ghana, and Uganda) randomly compared two modules to capture pregnancy outcomes: full pregnancy history (FPH) and the standard DHS-7 full birth history (FBH+). We used paradata related to answers recorded on tablets using the Survey Solutions platform. We evaluated the difference in paradata entries between the two reproductive modules and assessed which question characteristics (type, nature, structure) affect answer correction rates, using regression analyses. We also proposed and tested a new classification of answer correction types. Results: We analysed 3.6 million timestamped entries from 65,768 interviews. 83.7% of all interviews had at least one corrected answer to a question. Of 3.3 million analysed questions, 7.5% had at least one correction. Among corrected questions, the median number of corrections was one, regardless of question characteristics. We classified answer corrections into eight types (no correction, impulsive, flat (simple), zigzag, flat zigzag, missing after correction, missing after flat (zigzag) correction, missing/incomplete). 84.6% of all corrections were judged not to be problematic with a flat (simple) mistake correction. Question characteristics were important predictors of probability to make answer corrections, even after adjusting for respondent’s characteristics and location, with interviewer clustering accounted as a fixed effect. Answer correction patterns and types were similar between FPH and FBH+, as well as the overall response duration. Avoiding corrections has the potential to reduce interview duration and reproductive module completion by 0.4 min. Conclusions: The use of questionnaire paradata has the potential to improve measurement and the resultant quality of electronic data. Identifying sections or specific questions with multiple corrections sheds light on typically hidden challenges in the survey’s content, process, and administration, allowing for earlier real-time intervention (e.g.,, questionnaire content revision or additional staff training). Given the size and complexity of paradata, additional time, data management, and programming skills are required to realise its potential. Keywords: Survey, Paradata, Neonatal, Newborn, Answer correction type, Survey desig