Rally Updates

Analysis Progress

A key part of the discovery phase of Ki 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. Ki 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.

Research NoteThese are initial findings of rapid ongoing research that haven't been finalized or validated. Their purpose is to share results of our ongoing work.
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.
Key Outcomes
A model using SuperLearner was constructed to better predict gestational age, with the precision of the model nearing ± 2 weeks precision.
STATUS COMPLETE
DATES 06.07.2017 to 06.21.2017
TAGSgestational age, estimation, physical measurements, Super Learner
Sprint 1B: Accuracy and Precision in Gestational Age Measurement: Physical Assessment Tools
What combination(s) of physical assessments can accurately predict gestational age, especially in SGA and LGA children? Does that differ by geography?
Key Outcomes
The SuperLearner model was updated to weight age groups to mitigate bias in both preterm & SGA populations, improving the accuracy of the model.
STATUS COMPLETE
DATES 07.13.2017 to 07.31.2017
TAGSgestational age, estimation, physical measurements, Super Learner, SGA, geography
Sprint 2A: Characterizing Fetal Growth and Relations Between Maternal Covariates, Fetal Growth, and Birth Outcomes
Determine fetal growth patterns and population differences using several data sets and determine if one growth standard can be applied to all geographies.
Key Outcomes
Nonparametric function estimation methods were used to examine several questions about fetal growth trajetories and birth outcomes, finding effects between maternal characteristics and birth outcomes.
STATUS COMPLETE
DATES 07.16.2017 to 07.30.2017
TAGSfetal 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?
Key Outcomes
Population growth curves were constructed by combining all available datasets and were compated with intergrowth standards.
STATUS COMPLETE
DATES 08.03.2017 to 08.17.2017
TAGSfetal growth trajectories, geography, maternal, SGA, IUGR, population
Sprint 4A: Descriptive Epidemiology of Wasting
Describe the epidemiology of incident wasting (WHZ < −2) from birth to age 24 months.
Key Outcomes
A broad look at wasting across many populations revealed many interesting insights and led to additional addressed in the following sprints.
STATUS COMPLETE
DATES 07.21.2017 to 08.07.2017
TAGSwasting, WHZ, WAZ, MAM, SAM, malnutrition, incidence, recovery
Sprint 4B: Pilot of the Analysis of Risk Factors for Wasting Incidence and Recovery
The focus of this ral;y 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.
Key Outcomes
Created and a single, harmonized data analysis pipeline and then used it to summarize the descriptive wasting epidemiology across 22 contemporary cohorts.
STATUS COMPLETE
DATES 08.18.2017 to 09.07.2017
TAGSWasting, undernutrition, wasting recovery
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.
Key Outcomes
Exploratory analyses and visualizations uncovered some interesting insights about the relationship of breastfeeding and wasting.
STATUS COMPLETE
DATES 08.08.2017 to 09.14.2017
TAGSbreastfeeding, wasting, WHZ
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
Key Outcomes
Prepared and presented a webinar to GHAP data contributors and other interested parties.
STATUS COMPLETE
DATES 09.13.2017 to 10.11.2017
TAGSdata checking, documentation, planning
Sprint 5A: Gestational Age Shift Analysis
The focus of this first two-week rally sprint: using US data, if we could shift the gestational age of 26-29 week-olds by 1, 2, 3, 4 weeks, what would be the impact on mortality?
Key Outcomes
Built and studied a model that investigates the impact on mortality if we could shift the gestational age of 26-29 week olds, by 1, 2, 3, 4 weeks, enabling, for example, a look at a hypothetical population of 140 million, where there is possibility of saving more than 150,000 lives by merely increasing the Gestational Age of those born less than 39 weeks by just one week.
STATUS COMPLETE
DATES 09.25.2017 to 10.10.2017
TAGSgestational age, neonatal mortality
Sprint 6A: Descriptive Epidemiology of Wasting and Stunting in India
Describe the India-specific epidemiology of incident wasting and stunting (WHZ and HAZ < −2) and severe wasting and severe stunting (WHZ and HAZ < −3) from birth to age 24 months.
Key Outcomes
Wasting methodology from rally 4 was applied to India-specific data, uncovering insights and providing a way to engage with PIs in India.
STATUS COMPLETE
DATES 02.12.2018 to 02.23.2018
TAGSwasting, WHZ, WAZ, HAZ, stunting
Sprint 7A: Epidemiology of Stunting Analysis Plan
Prepare an analysis plan to describe the epidemiology of stunting (HAZ < −2) from birth to age 24 months.
Key Outcomes
An analysis plan for the rally was developed.
STATUS COMPLETE
DATES 02.26.2018 to 03.12.2018
TAGSstunting, HAZ
Sprint 7B: Stunting Objective 1a. Age-specific incidence and prevalence
Key Outcomes
Many insights gained from descriptive statistics and visualizations of the same large collection of longitudinal data as created in rally 4, providing an unprecendented in-depth look at the progression, prevalence, and incidence of stunting across many populations, and producing many insights.
STATUS COMPLETE
DATES 04.11.2018 to 04.27.2018
TAGS
Sprint 7C: Catch up Growth, Growth Velocity and Population Attributable Fractions
Key Outcomes
Continued analysis of the stunting dataset, revealing evidence for a large percentage of children having multiple stunting episodes, where the traditional view of stunting has been that it is a chronic, cumulative process.
STATUS COMPLETE
DATES 05.07.2018 to 05.18.2018
TAGS
Sprint 7D: Catch up Growth, Growth Velocity and Nutritional Interventions
Key Outcomes
This effort will focus on analyzing risk factors which will inform our understanding of the causes and underlying drivers of stunting and how they differ by region.
STATUS COMPLETE
DATES 06.18.2018 to 07.13.2018
TAGS
Sprint 8A: Pregnancy Risk Stratification Placemat Development
Key Outcomes
To help get a view of the landscape of the state of research in algorithms for pregnancy risk stratification, a large number of journal articles related on this topic were processed by ConceptualEyes, and a placemat of the findings was produced.
STATUS COMPLETE
DATES 03.26.2018 to 04.24.2018
TAGS
Sprint 8B: PRS TPP Phase I - Data, SME Survey and Model Prep
Key Outcomes
To begin defining the PRS TPP, SME engagement plans were created and SMEs were identified, a draft TPP was created, datasets in GHAP were studied for relevance to PRS-related goals, and a ki scenario modeling tool was created based on the BCG model from 2017 for pre-eclampsia to better elicit input from subject matter experts for determining the TPP.
STATUS COMPLETE
DATES 05.07.2018 to 06.01.2018
TAGS
Sprint 8CD: PRS SME Engagement with TPP/Iteration on modeling tool and data acquisition/mapping
Key Outcomes
Conducting SME interviews using modeling tool developed in 8B and TPP. Mapping of prioritized data in GHAP and focused effort on key data set acquisition.
STATUS COMPLETE
DATES 06.26.2018 to 08.10.2018
TAGS
Sprint 9A: Determining Characteristics of Population Surveillance Estimates for Pre-Term Birth Rates
Key Outcomes
Compute covariate means for 15 groups defined by 5 sites x 3 size categories (SGA/AGA/LGA). Weighted logistic regression models were fitted to different population groups for various small subsets of covariates that accurately estimated the pre-term birth rates in LGA and SGA segments of the population.
STATUS COMPLETE
DATES 05.21.2018 to 06.04.2018
TAGS
Sprint 10AB: Childhood Acute Illness and Nutrition (CHAIN) Collaboration: Optimizing Prevention and Treatment of Acute Illness
Key Outcomes
Identified groupings of children based upon a predictive algorithm allowing for the design of interventions that reduce death after discharge or readmission to the hospital.
STATUS COMPLETE
DATES 05.29.2018 to 06.22.2018
TAGS