A key part of the discovery phase of HBGDki involves data science rallies, which are based on efficient, sprint-like efforts adapted from the Agile software development method. This approach to data science is producing actionable answers to specific questions about child growth and development. HBGDki models are used during rally sprints, which usually run for 2 weeks and address a specific question, hypothesis, and deliverable. The continual communication happens by having the rally team work in a cloud-based collaborative work space specifically developed for Team Science.
Sprint 4C: Dose-Response Relationship of Breastfeeding on Wasting
Investigate the dose-response relationship of breastfeeding on wasting through exploratory visualization of the MAL-ED data, providing a basis for future modeling efforts. In this rally sprint, we seek to understand the effect of a 0-6 months breastfeeding dose on growth from 0-24 months and also how this effect varies across different groupings of wasted infants.
Sprint 1A: Accuracy and Precision in Gestational Age Measurement: Physical Assessment Tools
Improve the postnatal estimation of gestational age in order to determine preterm birth rates and small for gestational age rates with the goal of 90% to be ± 2 weeks across the gestational age spectrum to 28 weeks out to 42 weeks. Evaluate across sites and by sex.
TOPIC TAGS fetal growth trajectories, geography, maternal, SGA, IUGR, population
Sprint 2B: Fetal Growth: One Standard Fits all?
Are small for gestational age (SGA) and large for gestational age (LGA) proportions different between countries? What are the results of constructing population fetal growth curves by combining all available data sets and comparing these curves with the INTERGROWTH standard?
Sprint 4B: Pilot of the Analysis of Risk Factors for Wasting Incidence and Recovery
The focus of this raly will be to: 1. Refine the descriptive analysis report for each cohort. 2. Explore additional measures of wasting recovery, and the proportion of children wasted who recover within 30, 60, and 90 days. 3. Summarize prevalence, incidence, and duration in figures rather than tables. 4. Extend the descriptive analysis to all 22 cohorts that include a monthly measurement. 5. Begin the risk factor analyses to identify time-invariant characteristics associated with wasting episodes and recovery among children ages 0-6 months.
Sprint 4D: Wasting Analysis Clean-Up and Documentation
In this rally, we will: 1. Clean up and document prior analyses. 2. Verify accuracy of incidence calculations against simulated data with a known incidence rate. 3. Combine prior analysis results with a more extensive literature review in order to make plans for further analyses. 4. Investigate context of all the studies that were combined in prior analyses and quality-assurance check each cohort's anthropometry measurements. 5. Draft an analysis plan formalizing all preliminary analyses completed in the rally and finalizing analyses to be completed and publications to be written as part of the project. 6. Draft a timeline for project completion