What is the Best Way to Reduce Unintended Pregnancies? An Agent-Based Simulation of Contraceptive Switching, Discontinuation and Failure Patterns in France

Nadia Diamond-Smith, Johns Hopkins Bloomberg School of Public Health
Caroline Moreau, Institut National de la Santé et de la Recherche Médicale (INSERM)

Despite high rates of contraceptive use in France, over a third of pregnancies are unintended. We built a dynamic agent based model which applies data from the French COCON study on method switching, discontinuation, and failure rates to a hypothetical population of 10,000 women, followed for 10 years. We use the model to estimate the adjustment factor needed to make the survey data fit the demographic profile of France, by adjusting for underreporting of contraceptive non-use and abortions. We then test three policy scenarios which would aim to reduce unintended pregnancies: decreasing method failure, increasing time spent on effective methods, and increasing switching from less to more effective methods. Our model suggests that decreasing method failure is the most effective strategy for reducing unintended pregnancies, but all policy scenarios reduced unintended pregnancies by at least 25%. Dynamic micro simulations such as this can help guide policy makers.

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Presented in Session 168: Findings from Contraceptive History Calendars