KI INSIGHT STORY – CHAMPS
Ki Insight Stories are an opportunity for us to thank the Ki Community for your generous data contributions and keep you informed on the important insights that Ki and our BMGF partners are generating.
Our latest Insight Story presents the results of the Child Health and Mortality Prevention Surveillance (CHAMPS) Network data science rallies. The outcome of these data science rallies was the development of programmatic tools that researchers need to build reports, compute statistics, and complete custom data analyses from CHAMPS data.
CHAMPS provides robust, standardized, longitudinal mortality data on stillbirths and deaths in children under age 5. These data help countries, public health programs, and local and global child health policymakers in their efforts to prevent childhood deaths and illness.
We deeply appreciate the hard work and involvement of all our data contributors, domain experts, and partners. Without you, this work would not be possible. We would particularly like to acknowledge the partners at the seven sites of the CHAMPS global network for their work in collecting these data:
- Bangladesh
- Ethiopia
- Kenya
- Mali
- Mozambique
- Sierra Leone
- South Africa
If you are a Ki data contributor or partner, we invite you to download the full Insight story by joining the Ki Insight Stories space on Synapse, a collaborative research platform.
COMMENTARY ARTICLE ON COVID-19 VACCINES AND TREATMENTS
In April 2021, Ki members Ted Grasela and David Price published a commentary on lessons learned during the height of the COVID-19 pandemic, providing a perspective for the biopharmaceutical industry, regulatory agencies, global health, and community engagement. The article discusses the generational opportunity presented by the pandemic to gain a new perspective on what is possible as a global society and make changes based on these learnings for the broadest public good.
Read the full commentary in Clinical and Translational Science, COVID-19 vaccines and treatments: When speed is necessary and not enough.
The commentary identifies factors contributing to accelerated research and development cycles, including improved global collaboration, data sharing, and coordination of research methods. However, poorly designed trials, a lack of reporting, and competition can lead to wasted effort and resources. The commentary discusses how to consider and communicate evidence for vaccine safety and efficacy for the global community.
The authors also shared recommendations to accelerate learning by continually revising research plans as new information comes to light, accelerate data sharing and results through collaboration, and avoid unnecessary duplication through better communication.
KI GRAND CHALLENEGES WEBINARS
Over the past few months, Ki Grand Challenges community members hosted a series of webinars focusing on data sharing and the challenges of pooling data from different resources. Initiated during the KiGC annual data science convening in October 2020, these discussions were led by Gilberto Kac PhD from the Rio de Janeiro Federal University, a grantee from the first round of KiGC in Brazil.
The first follow-up discussion focused on data sharing best practices through presentations of successful examples, such as the Ki repository and CIDACS. Subsequent sessions focused on the challenges of pooling data from different resources and other aspects of practical data-preprocessing, such as data harmonization and handling outliers.
These sessions created a rich and engaging peer learning and sharing space during which KiGC community members from Africa, India, and Brazil shared experiences, best practices, and other experiences working on different maternal, newborn, and child health (MNCH) topics.
UPDATE ON DATA SETS
Thanks to you, Ki’s repository is ever-expanding. Please find below a list of studies that have completed QC since the last announcement.
- AKU-MMN – Pakistan
A comparative evaluation of multiple micronutrient and iron–folic acid supplementation during pregnancy in Pakistan: impact on pregnancy outcomes.
- AKU-VitD – Pakistan
Evaluation of the Effectiveness of Vitamin D Supplementation to Pregnant Women and Their Infants in Pakistan
- HERO-G – Gambia
Identification of nutritionally modifiable hormonal and epigenetic drivers of positive and negative growth deviance in rural African fetuses and infants: Project protocol and cohort description
- ICDDR-MINIMat – Bangladesh
The Maternal and Infant Nutrition Interventions in Matlab (MINIMat) cohort in Bangladesh
- IMIP-BRAMAG – Brazil
A randomized clinical trial of oral magnesium supplementation in pregnancy for the prevention of preterm birth and perinatal and maternal morbidity
- IMIP-GestDM – Brazil
Physical activity pattern in early pregnancy and gestational diabetes mellitus risk among low-income women: A prospective cross-sectional study
- INPer-GDM – Mexico
Longitudinal evaluation of adiposity, inflammation and metabolic control during pregnancy and its association with the development of gestational diabetes.
- SHU-BMIGWG – Indonesia
Pre-pregnancy body mass index and gestational weight gain and their effects on pregnancy and birth outcomes: a cohort study in West Sumatra, Indonesia
- XJU-RuralChina – China
Impact of micronutrient supplementation during pregnancy on birth weight, duration of gestation, and perinatal mortality in rural western China: double blind cluster randomised controlled trial
- XJU-Tibet – Tibet
Multi-micronutrient supplementation during pregnancy for prevention of maternal anaemia and adverse birth outcomes in a high-altitude area: a prospective cohort study in rural Tibet of China
If you would like to learn more about these datasets or any other datasets in the repository, use our study explorer tool. The study explorer tool allows you to see all the data in the repository, at a metadata level, including the data you contributed. Here is the link: http://www.studyexplorer.io/