Big Data for Reproductive Health (2018-2019)
One-third of women who begin using a modern method of contraception in low-income countries discontinue within the first year, and half within the first two years, putting them at risk for unintended pregnancies as well as maternal morbidity and mortality.
The current method of measuring contraceptive discontinuation (quitting, switching and method failure) relies on household surveys collected in five-year intervals through a retrospective monthly contraceptive calendar. This measurement provides a broad overview of discontinuation, but does not show the granular details often needed to develop programs to effect change.
This Bass Connections project aims to curate available data into an online, user-friendly tool, apply advanced data analysis techniques and develop methods for collecting big data to provide dynamic information on contraceptive discontinuation to family planning researchers and advocates.
The specific goals of this project are to:
- Build a web-based platform that curates freely available, raw data on contraceptive discontinuation from household surveys into a tool that makes higher-resolution inferences possible by members of the family planning community (researchers, advocates, government officials). The team will refine this tool through stakeholder engagement meetings.
- Determine how big data analytic techniques can be applied to contraceptive calendar data to develop a deeper understanding about the types of women who discontinue and for what reasons. This will enable family planning advocates to tailor and target programs for women in need of support to continue using contraceptives.
- Identify how big data sources (e.g., high-volume, high-velocity data such as internet search and social media data) can provide real-time surveillance around reproductive health, to improve family planning policies.
A Data+ team in Summer 2018 will produce:
- A prototype of a web-based, open-access platform to visualize the contraceptive calendar data from the Demographic and Health Surveys of several countries
- A roadmap for publishing, hosting and maintaining the tool
- An internal memo on the use of big data to measure contraceptive discontinuation.
Extensive research on contraceptive discontinuation has been done by organizations in the Triangle including the Carolina Population Center, FHI360, RTI, IntraHealth International, MEASURE Evaluation and Ipas. The Bass Connections project team will organize a stakeholder engagement meeting with these stakeholders in the fall semester to present and receive feedback on the tool. The team will organize a second stakeholder engagement meeting at the end of the spring semester to present the final version of the tool.
Web-based data visualization tool focusing on contraceptive discontinuation; literature review on the use of big data in reproductive health; proposals for additional grant funding
Fall 2018 – Spring 2019
- Fall 2018: Meet weekly to develop shared understanding of measures of contraceptive discontinuation and measurement gaps; form sub-groups on user-centered design, tool programming, data analysis of the contraceptive calendar data, big data collection and validation; plan stakeholder feedback session; conduct systematic review of the literature; share results of stakeholder engagement meeting; incorporate feedback into the tool.
- Spring 2019: Meet weekly in sub-groups, report on progress through small group presentations; develop and finalize codebook for searching big data sources for family planning information; begin to collect data and develop ways to validate it; apply big data analysis techniques to contraceptive calendar data; finalize visualization tool to use at a second stakeholder engagement meeting; finalize systematic review manuscript; hold a high-level stakeholder engagement meeting in April.
This Team in the News
See related Data+ summer project, Big Data for Reproductive Health (2018).
/faculty/staff Team Members
Amy Finnegan, Sanford School of Public Policy*
Amy Herring, Arts & Sciences-Statistical Science
Megan Huchko, School of Medicine-Obstetrics and Gynecology*
/graduate Team Members
Kelly Hunter, Public Policy Studies-PHD
Anuraadhaa Kandadai, Economics and Computation-MS
Melanie Lai Wai, Statistical Science - MS
/undergraduate Team Members
Cecelia Mizelle, Biology (BS)
Molly Paley, Public Policy Studies (AB)
Nicole Rapfogel, Public Policy Studies (AB), Global Health (AB2)
Saumya Sao, Gender Sexuality & Fem St(AB), Global Health (AB2)
/zcommunity Team Members
Alex Pavluck, RTI International