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 project team partnered with local and international stakeholders to built a prototype of an online 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. 

Team members also conducted a literature review on the intersection of big data and contraceptive use. Using this research, the team applied two big data methods (neural networks and unsupervised machine learning) to contraceptive calendar data from the Demographic and Health Survey (DHS). The team’s work led to the creation of a “See the Switch” infographic that highlights the frequency of use for various contraception methods.

Timing

Fall 2018 – Spring 2019  

Team Outputs

Amy Finnegan, Saumya S. Sao, Megan J. Huchko. 2019. “Using a chord diagram to visualize dynamics in contraceptive use: Bringing data into practice,” Global Health: Science and Practice 7(3).

Big Data for Reproductive Health (poster by Amy Finnegan, Megan Huchko, Kelly Hunter, Daisy Fang, Katherine Gan, Anu Kandadai, Colby Matthiasson, Celia Mizelle, Molly Paley, Nicole Rapfogel, Saumya Sao, Liz Shulman, Samhitha Sunkara, Melanie Lai Wai, presented at Bass Connections Showcase, Duke University, April 17, 2019; winner, Bass Connections Poster Competition, Judges’ Selection)

Reflections

Molly Paley

Celia Mizelle

Video

Big Data for Reproductive Health

This Team in the News

Students Design App to Mine Big Data on Reproductive Health

Duke Students in Action

Class of 2019: Learning What It Takes to Take Innovative Health Care Global

Meet the 2019 Recipients of Bass Connections Student Research Awards

Visualizing DHS Contraceptive Calendar Data

Big Data for Reproductive Health Team Goes to DC!

Team Shares Novel Tools to Explore Data on Contraceptive Use

3 Questions with Social Demographer Amy Finnegan

Director's Blog: Fall 2018

Demystifying Research at Duke

Data+ Team Introduces Novel Visualization Methods to Understand Contraceptive Trends

See related team, Big Data for Reproductive Health (2019-2020), and Data+ summer projects, Big Data for Reproductive Health (2019) and Big Data for Reproductive Health (2018).

BD4RH logo

Team Leaders

  • Amy Finnegan, IntraHealth International
  • 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

  • Zhou Fang, Statistical Science (BS), Psychology (BS2)
  • Katherine Gan, Public Policy Studies (AB), History (AB2)
  • Anna Matthiasson, Computer Science (BS)
  • 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)
  • Elizabeth Shulman, Interdepartmental Major
  • Samhitha Sunkara, Economics (BS)

/yfaculty/staff Team Members

  • Amy Herring, Arts & Sciences-Statistical Science

/zcommunity Team Members

  • Alex Pavluck, RTI International