FPEM

FPEM estimates family planning indicators for individual countries or smaller geographic areas using the Family Planning Estimation Model (FPEM) framework and fixed non-population-specific parameters from prior global model runs, implemented via the fpemlocal R package.


Key Features:

  • Bayesian Hierarchical Modeling: Employs a Bayesian hierarchical model with country-specific time trends to estimate contraceptive prevalence and unmet need for family planning.
  • Integration with FPEMglobal: Uses non-population-specific parameters fixed from global FPEM outcomes to maintain consistency with FPEMglobal.
  • Data Handling: Includes and accepts comprehensive datasets such as survey data, country unit data, and population counts for one-country analyses.
  • Aggregation Capability: Allows aggregation of estimates across multiple populations.
  • Computational Efficiency and Accuracy: Emphasizes computational efficiency and accuracy for single-country or small-area runs.

Scientific Applications:

  • Family Planning Indicators Estimation: Produces estimates of contraceptive prevalence and unmet need within specific countries or regions.
  • FP2020 and Track20 Support: Supports the Track20 Family Planning Estimation Tool and monitoring activities under the FP2020 initiative.

Methodology:

Accepts package-provided and user-specified databases as input, processes these inputs through a Bayesian hierarchical model with country-specific time trends using fixed non-population-specific parameters from prior global FPEM runs, and supports aggregation of resulting estimates across populations.

Topics

Details

License:
MIT
Tool Type:
library
Programming Languages:
R
Added:
9/8/2021
Last Updated:
9/20/2021

Operations

Publications

Guranich G, Cahill N, Alkema L. Fpemlocal: Estimating family planning indicators in R for a single population of interest. Gates Open Research. 2021;5:24. doi:10.12688/gatesopenres.13211.1. PMID:33842844. PMCID:PMC8008158.

PMID: 33842844
PMCID: PMC8008158
Funding: - Bill and Melinda Gates Foundation: INV-008441

Links