The maximum contraceptive prevalence ‘demand curve’: guiding discussions on programmatic investments [version 1; referees: 1 approved, 2 approved with reservations]

Most frameworks for family planning include both access and demand interventions. Understanding how these two are linked and when each should be prioritized is difficult. The maximum contraceptive prevalence ‘demand curve’ was created based on a relationship between the modern contraceptive prevalence rate (mCPR) and mean ideal number of children to allow for a quantitative assessment of the balance between access and demand interventions. The curve represents the maximum mCPR that is likely to be seen given fertility intentions and related norms and constructs that influence contraceptive use. The gap between a country’s mCPR and this maximum is referred to as the ‘potential use gap.’ This concept can be used by countries to prioritize access investments where the gap is large, and discuss implications for future contraceptive use where the gap is small. It is also used within the FP Goals model to ensure mCPR growth from access interventions does not exceed available demand

Modern contraceptive use, unmet need, and demand satisfied among women of reproductive age who are married or in a union in the focus countries of the Family Planning 2020 initiative: a systematic analysis using the Family Planning Estimation Tool

Background The London Summit on Family Planning in 2012 inspired the Family Planning 2020 (FP2020) initiative and the 120×20 goal of having an additional 120 million women and adolescent girls become users of modern contraceptives in 69 of the world’s poorest countries by the year 2020. Working towards achieving 120×20 is crucial for ultimately achieving the Sustainable Development Goals of universal access and satisfying demand for reproductive health. Thus, a performance assessment is required to determine countries’ progress. Methods An updated version of the Family Planning Estimation Tool (FPET) was used to construct estimates and projections of the modern contraceptive prevalence rate (mCPR), unmet need for, and demand satisfied with modern methods of contraception among women of reproductive age who are married or in a union in the focus countries of the FP2020 initiative. We assessed current levels of family planning indicators and changes between 2012 and 2017. A counterfactual analysis was used to assess if recent levels of mCPR exceeded pre-FP2020 expectations. Findings In 2017, the mCPR among women of reproductive age who are married or in a union in the FP2020 focus countries was 45·7% (95% uncertainty interval [UI] 42·4–49·1), unmet need for modern methods was 21·6% (19·7–23·9), and the demand satisfied with modern methods was 67·9% (64·4–71·1). Between 2012 and 2017 the number of women of reproductive age who are married or in a union who use modern methods increased by 28·8 million (95% UI 5·8–52·5). At the regional level, Asia has seen the mCPR among women of reproductive age who are married or in a union grow from 51·0% (95% UI 48·5–53·4) to 51·8% (47·3–56·5) between 2012 and 2017, which is slow growth, particularly when compared with a change from 23·9% (22·9–25·0) to 28·5% (26·8–30·2) across Africa. At the country level, based on a counterfactual analysis, we found that 61% of the countries that have made a commitment to FP2020 exceeded pre-FP2020 expectations for modern contraceptive use. Country success stories include rapid increases in Kenya, Mozambique, Malawi, Lesotho, Sierra Leone, Liberia, and Chad relative to what was expected in 2012. Interpretation Whereas the estimate of additional users up to 2017 for women of reproductive age who are married or in a union would suggest that the 120×20 goal for all women is overly ambitious, the aggregate outcomes mask the diversity in progress at the country level. We identified countries with accelerated progress, that provide inspiration and guidance on how to increase the use of family planning and inform future efforts, especially in countries where progress has been poor. Funding The Bill & Melinda Gates Foundation, through grant support to the University of Massachusetts Amherst and Avenir Health

Using family planning service statistics to inform model-based estimates of modern contraceptive prevalence

The annual assessment of Family Planning (FP) indicators, such as the modern contraceptive prevalence rate (mCPR), is a key component of monitoring and evaluating goals of global FP programs and initiatives. To that end, the Family Planning Estimation Model (FPEM) was developed with the aim of producing survey-informed estimates and projections of mCPR and other key FP indictors over time. With large-scale surveys being carried out on average every 3–5 years, data gaps since the most recent survey often exceed one year. As a result, survey-based estimates for the current year from FPEM are often based on projections that carry a larger uncertainty than data informed estimates. In order to bridge recent data gaps we consider the use of a measure, termed Estimated Modern Use (EMU), which has been derived from routinely collected family planning service statistics. However, EMU data come with known limitations, namely measurement errors which result in biases and additional variation with respect to survey-based estimates of mCPR. Here we present a data model for the incorporation of EMU data into FPEM, which accounts for these limitations. Based on known biases, we assume that only changes in EMU can inform FPEM estimates, while also taking inherent variation into account. The addition of this EMU data model to FPEM allows us to provide a secondary data source for informing and reducing uncertainty in current estimates of mCPR. We present model validations using a survey-only model as a baseline comparison and we illustrate the impact of including the EMU data model in FPEM. Results show that the inclusion of EMU data can change point-estimates of mCPR by up to 6.7 percentage points compared to using surveys only. Observed reductions in uncertainty were modest, with the width of uncertainty intervals being reduced by up to 2.7 percentage points

Using family planning service statistics to inform model-based estimates of modern contraceptive prevalence

The annual assessment of Family Planning (FP) indicators, such as the modern contraceptive prevalence rate (mCPR), is a key component of monitoring and evaluating goals of global FP programs and initiatives. To that end, the Family Planning Estimation Model (FPEM) was developed with the aim of producing survey-informed estimates and projections of mCPR and other key FP indictors over time. With large-scale surveys being carried out on average every 3–5 years, data gaps since the most recent survey often exceed one year. As a result, survey-based estimates for the current year from FPEM are often based on projections that carry a larger uncertainty than data informed estimates. In order to bridge recent data gaps we consider the use of a measure, termed Estimated Modern Use (EMU), which has been derived from routinely collected family planning service statistics. However, EMU data come with known limitations, namely measurement errors which result in biases and additional variation with respect to survey-based estimates of mCPR. Here we present a data model for the incorporation of EMU data into FPEM, which accounts for these limitations. Based on known biases, we assume that only changes in EMU can inform FPEM estimates, while also taking inherent variation into account. The addition of this EMU data model to FPEM allows us to provide a secondary data source for informing and reducing uncertainty in current estimates of mCPR. We present model validations using a survey-only model as a baseline comparison and we illustrate the impact of including the EMU data model in FPEM. Results show that the inclusion of EMU data can change point-estimates of mCPR by up to 6.7 percentage points compared to using surveys only. Observed reductions in uncertainty were modest, with the width of uncertainty intervals being reduced by up to 2.7 percentage points

Using family planning service statistics to inform model-based estimates of modern contraceptive prevalence

The annual assessment of Family Planning (FP) indicators, such as the modern contraceptive prevalence rate (mCPR), is a key component of monitoring and evaluating goals of global FP programs and initiatives. To that end, the Family Planning Estimation Model (FPEM) was developed with the aim of producing survey-informed estimates and projections of mCPR and other key FP indictors over time. With large-scale surveys being carried out on average every 3–5 years, data gaps since the most recent survey often exceed one year. As a result, survey-based estimates for the current year from FPEM are often based on projections that carry a larger uncertainty than data informed estimates. In order to bridge recent data gaps we consider the use of a measure, termed Estimated Modern Use (EMU), which has been derived from routinely collected family planning service statistics. However, EMU data come with known limitations, namely measurement errors which result in biases and additional variation with respect to survey-based estimates of mCPR. Here we present a data model for the incorporation of EMU data into FPEM, which accounts for these limitations. Based on known biases, we assume that only changes in EMU can inform FPEM estimates, while also taking inherent variation into account. The addition of this EMU data model to FPEM allows us to provide a secondary data source for informing and reducing uncertainty in current estimates of mCPR. We present model validations using a survey-only model as a baseline comparison and we illustrate the impact of including the EMU data model in FPEM. Results show that the inclusion of EMU data can change point-estimates of mCPR by up to 6.7 percentage points compared to using surveys only. Observed reductions in uncertainty were modest, with the width of uncertainty intervals being reduced by up to 2.7 percentage points