World Population Prospects and Unmet Need for Family Planning

World Population Prospects and

Unmet Need for Family Planning

Scott Moreland

Ellen Smith

Suneeta Sharma

April 2010

Futures Group

One Thomas Circle, NW

Washington, DC 20005

United States of America

Prepared with support from the William and Flora Hewlett Foundation

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Table of Contents

Abbreviations ................................................................................................................................................ v

Acknowledgments ........................................................................................................................................ vi

Executive Summary ....................................................................................................................................... 1

Introduction .................................................................................................................................................. 3

I. Methodology ..................................................................................................................................... 4

II. Scenarios ........................................................................................................................................... 5

Assumptions: Demographic Parameters and Values ............................................................................ 7

Assumptions: Family Planning .............................................................................................................. 7

Results ......................................................................................................................................................... 12

III. Global Results.............................................................................................................................. 13

IV. Developing Countries .................................................................................................................. 17

V. Regional Projections ....................................................................................................................... 20

VI. Africa ........................................................................................................................................... 20

VII. Asia and the Near East ................................................................................................................ 23

VIII. India ............................................................................................................................................ 26

IX. Latin America and the Caribbean ................................................................................................ 29

X. Transition Countries ........................................................................................................................ 32

XI. United States ............................................................................................................................... 35

XII. Summary and Conclusions .......................................................................................................... 38

Appendix ..................................................................................................................................................... 41

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List of Figures

Figure 1. Relationship between Unmet Need and CPR ................................................................................ 6

Figure 2. Global: Contraceptive Prevalence, Total Fertility, Population, and Cumulative Family Planning

Cost ................................................................................................................................................ 15

Figure 3. Developing Countries: Contraceptive Prevalence, Total Fertility, Population, and Cumulative

Family Planning Cost ...................................................................................................................... 18

Figure 4. Africa: Contraceptive Prevalence, Total Fertility, Population, and Cumulative Family Planning

Cost ................................................................................................................................................ 21

Figure 5. Asia and the Near East: Contraceptive Prevalence, Total Fertility, Population, and Cumulative


Figure 6. India: Contraceptive Prevalence, Total Fertility, Population, and Cumulative Family Planning

Cost ................................................................................................................................................ 27

Figure 7. Latin America and the Caribbean: Contraceptive Prevalence, Total Fertility, Population, and

Cumulative Family Planning Cost ................................................................................................... 30

Figure 8. Transition Countries: Contraceptive Prevalence, Total Fertility, Population, and Cumulative


Figure 9. United States: Contraceptive Prevalence, Total Fertility, Population, and Cumulative Family

Planning Cost ................................................................................................................................. 36

Figure 10. Global Population in 2050 under Four Scenarios ...................................................................... 40

Figure 11. Developing Countries: Population in 2050 under Four Scenarios ............................................. 40

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List of Tables

Table 1. Changes in Percentage of Women in Union by Region ................................................................... 8

Table 2. Average Annual Change in the Percentage of All Users Who Use a Modern Method in Countries

with More than One DHS by Region ................................................................................................ 9

Table 3. Average Family Planning Cost per User ........................................................................................ 10

Table 4. One-Year Cost of Contraceptives in the United States ................................................................. 10

Table 5. Average CPR and Unmet Need for Family Planning by Region and Years to Meet Unmet Need . 12

Table A 1: List of Countries Included in the Analysis ................................................................................. 41

Table A 2. CPR and Unmet Need ................................................................................................................. 42

Table A 3. Regression Results on Unmet Need ........................................................................................... 44

Table A 4. Regression Results for Percentage of Women in Union ............................................................ 44

Table A 5. Percentage of Women in Union, Ages 15–49 ............................................................................ 45

Table A 6. Method Effectiveness Assumptions ........................................................................................... 49

Table A 7. CPR Projections ......................................................................................................................... 50

Table A 8. Global Demographic Results ..................................................................................................... 53

Table A 9. Developing World Demographic Results ................................................................................... 53

Table A 10. Africa Demographic Results ..................................................................................................... 54

Table A 11. Asia and Near East Demographic Results ................................................................................ 54

Table A 12. India Demographic Results ...................................................................................................... 55

Table A 13. Latin America Demographic Results ........................................................................................ 55

Table A 14. Transition Countries Demographic Results .............................................................................. 56

Table A 15. United States Demographic Results ......................................................................................... 56

Table A 16. Cumulative Family Planning Costs ........................................................................................... 57

Table A 17. Present Value of Cumulative Family Planning Costs ................................................................ 59

Table A 18. Annual Family Planning Costs .................................................................................................. 61

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Abbreviations

ANE Asia and the Near East

CPR Contraceptive prevalence rate

DHS Demographic and Health Survey

LAC Latin America and the Caribbean

TFR Total fertility rate

UN United Nations

UNAIDS Joint United Nations Programme for AIDS

US United States

WRA Women of reproductive age

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Acknowledgments

This study has benefited from the efforts of many people. We would like to first acknowledge the

assistance of Priya Emmart, Krishna Aditi, Elizabeth Miller, Manal El Fiki, and Sarah Staveteig, all of

whom spent long hours helping to produce the projections presented in this report. We would also like

to thank our colleagues at the Futures Group, especially Sarah Clark and Rachel Sanders, for their advice

and assistance in terms of some of the approaches and data that we have drawn upon. Katrina Dusek

provided valuable administrative support during the report production stage. We are also grateful for

the advice provided by Jennifer Frost and Jacqui Darroch at the Allan Guttmacher Institute, Leiwen Jiang

of the National Center for Atmospheric Research, and Ilene Speizer of the University of North Carolina at

Chapel Hill. Last, we wish to thank the Hewlett Foundation for providing us with the opportunity to

conduct this study and especially to Peter Belden who has provided invaluable guidance and feedback

throughout the study.

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Executive Summary

Over the past 30 years, the use of modern family planning methods has increased dramatically in the

developing world, leading to a fall in fertility rates. Yet there are still significant levels of demand for

family planning that are unmet. If this unmet need were met, unintended pregnancies would be fewer,

women’s health and lives would be improved, and the consequent impact on fertility would result in

lower population growth and measured development benefits.

This paper estimates what the demographic impact of meeting this unmet need would be for the

developing world and the United States, and compares this scenario with three United Nations fertility

variants. The United Nations (UN) provides estimates of future fertility trajectories for the countries of

the world through 2050.1 These estimates are widely used by researchers, planners, and policy makers

and are a widely respected reference source when detailed population projections prepared at the

country level are unavailable. The UN estimates are based on projections of fertility derived from past

trends, as well as estimates of future life expectancy. We estimate the family planning implications of

the three UN projections and compare them with the fourth “unmet need” scenario. We compare the

demographic implications of the unmet need scenario with those of the three UN scenarios, as well as

the implied family planning costs.

To prepare the four projection scenarios, we used the DEMPROJ and FAMPLAN modules of the

Spectrum model and applied this to each of the 99 countries we modeled. This approach combines a

cohort-component population projection with the proximate determinant model of fertility. For the

unmet need scenario, we assumed that the contraceptive prevalence rate (CPR) would increase at a rate

that was reasonable, given past trends, until all currently observed unmet need was satisfied. We also

developed future projections of the percentage of women who are in union, and the contraceptive

method mix. For the UN scenarios, we used the model to estimate the level of CPR that, in conjunction

with the other proximate determinants would yield the UN fertility assumptions. Family planning costs

were projected for each scenario based on family planning unit costs and the projected number of

users.

The results for all countries together show that the CPR and total fertility rate (TFR) projections under

the unmet need scenario first follow the UN medium scenario, then steadily move toward the UN low

scenario in later years. Global population under the unmet need scenario follows a trajectory between

that of the UN medium and UN low scenarios, although closer to the UN medium scenario. The 2005

starting population is 4.05 billion, and by 2050, the total population is 5.78 billion, 6.7 billion, and 7.7

billion, respectively, under the UN low, medium, and high scenarios, and 6.3 billion under the unmet

need scenario. The cumulative costs of the family planning program for the entire projection period

(2005–2050) for the unmet need scenario is slightly less than that estimated for the UN low ($1.116

1 United Nations. 2008. World Population Prospects: The 2008 Revision. Department of Economic and Social

Affairs/Population Division, New York.

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trillion vs. $1.126 trillion). Costs for the UN medium and high scenarios are estimated to be $1.027

trillion and $948 billion, respectively.

For the developing countries that were modeled, the CPR and TFR paths under the unmet need

scenarios are very similar to the UN medium scenario in earlier years, and then approach and nearly

meet the UN low scenario by the end of the projection period. The unmet need projection of total

population is similar to the UN medium total population path, diverging significantly only in the later

years. This later divergence reflects the unmet need scenario’s effect on continued decline in TFR in

later years, when the TFR declines in the UN scenarios are small. The initial 2005 population in the

developing countries is 3.7 billion, with a projected 2050 population of 6 billion for the unmet need

scenario, compared with 5.4 billion for the UN low, 6.3 billion for the UN medium, and 7.2 billion for the

UN high scenarios. The estimated cumulative cost for the unmet need scenario is $638 billion, which

falls between the estimated costs for the UN low scenario of $665 billion and the costs for the UN

medium scenario of $603 billion. . Assuming the UN high scenario as a baseline, the additional annual

costs to meet unmet need for family planning are estimated to be approximately $3.7 billion per year

over the 45-year projection period; $1.4 billion of this would be from the United States, and $2.3 billion

from the 99 developing countries.

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World Population Prospects and Unmet Need for Family Planning

Introduction

Over the past 30 years, the use of modern family planning methods has increased dramatically in the

developing world leading to a fall in fertility rates. Yet there are still significant levels of demand for

family planning that are unmet. For example, Westoff has estimated unmet need between 5% and 33%

in the countries of Asia, 6% and 40% for Latin America and the Caribbean, and between 13% and 38% in

sub-Saharan Africa.2 Another recent study estimates that more than 200 million women in the

developing world have an unmet need for family planning.3 If this unmet need were met, unintended

pregnancies would be fewer, women’s health and lives would be improved, and the consequent impact

on fertility would result in lower population growth and measurable development benefits.

This paper estimates what the demographic impact of meeting this unmet need would be for the

developing world and compares it with three United Nations population scenarios. The United Nations

provides estimates of future population trajectories for the countries of the world through 2050.4 These

estimates are widely used by researchers, planners, and policy makers and are a widely respected

reference source when detailed population projections prepared at the country level are unavailable.

The UN estimates are based on projections of fertility derived from past trends, as well as estimates of

future life expectancy. If population growth is to be viewed as a possible factor in economic or

environmental change, the policy and program variables that affect population need to be taken into

account. This paper estimates the family planning implications of the UN projections and compares

them with a family planning policy scenario. Specifically, the paper estimates the impact on population

growth of satisfying observed base levels of the “unmet need”5 for family planning in the developing

world and the United States. Another question addressed by the paper is the cost of providing the levels

of family planning required in each of the scenarios.

A few existing studies look at the family planning implications of the UN projections and of meeting

unmet need for family planning. Guengant evaluated the contraceptive prevalence required to reach the

2025 and 2050 medium variant fertility levels proposed in the 2000 revision of the UN projections.6 Ross

2 Charles F. Westoff. 2006. New Estimates of Unmet Need and the Demand for Family Planning. DHS

Comparative Reports No. 14. Macro International Inc., Calverton, Maryland. 3 Susheela Singh, Jacqueline E. Darroch, Lori S. Ashford, and Michael Vlassoff. 2009. Adding It Up: The Costs and

Benefits of Investing in Family Planning and Maternal and Newborn Health. the Guttmacher Institute, New York. 4 United Nations 2008, op. cit.

5 Unmet need for family planning is the percentage of women of reproductive age in a union who do not want a

birth in the next two years or who do not want any more children, but are not using contraception. 6 Jean-Pierre Guengant. 2004. “The Proximate Determinants during the Fertility Transition,” in Expert Group

Meeting on Completing the Fertility Transition. March 11-14, 2002: 308-29. United Nations Department of Economic and Social Affairs, Population Division, New York.

P a g e | 4

et al. project family planning needs for 116 countries using a statistical model in conjunction with the UN

population projections.7

I. Methodology

The relationship between fertility and contraceptive use has long been established. Various methods of

analyzing the relationship are available. Ross et al. use a statistical model of the association between the

TFR and the CPR.8 Similarly, Westoff uses a regression equation to predict the impact on fertility of

increasing contraceptive use by a level sufficient to satisfy the unmet need for family planning.9 In this

paper, we used a modeling, rather than statistical approach. A modeling approach has the advantage of

taking into account more factors than a statistical approach. We used a standard cohort-component

population projection with an additional family planning module to prepare the estimates. Specifically,

we used two relevant submodules of the SPECTRUM software program: DEMPROJ, the population

projection program, and FAMPLAN, which handles the proximate determinants of fertility,10 including

family planning. Assumptions about the future trajectory of family planning use (as measured by

contraceptive prevalence), along with other proximate determinants of fertility (such as the percentage

of women in union, spontaneous abortion rates, etc.), are used to project the fertility rate, which in turn

is fed into the population projection through the calculation of births.

Family planning costs were projected for each scenario based on family planning unit costs and the level

of family planning use. For this paper, we used the number of users as our level of family planning use

and regional estimates of average costs per user.11 (These data are discussed in more detail below.) We

assumed constant unit costs (in 2006 United States [US] dollars) over the 45-year period. There is some

evidence that family planning unit costs may decline with the level of CPR due to economies of scale.12 If

that holds true, the cost estimates in this paper would be overestimates.

We projected for 99 individual developing countries and the United States and aggregated the data up

to the regional and global levels. While it was possible to project at a more aggregate level, for example,

by region, we thought that projecting at the country level would give more precision and allow us to

maximize the use of country-specific data. It would also allow us to create a database that could be used

for other purposes at the country level. However, in this paper we only report at the regional level.

The 99 countries that were included in the analysis (listed in Table A1 in the Appendix) represent a

population of 4.03 billion in 2005. We did not project for countries with fewer than 1 million inhabitants,

7 John Ross, John Stover, and Demi Adalaja. 2005. Profiles for Family Planning and Reproductive Health Programs.

Second Edition. Futures Group International, Washington, D.C. 8 Ross, Stover, and Adalaja. 2005, op. cit.

9 Westoff. 2006, op. cit.

10 J. Bongaarts. 1978. "A Framework for Analyzing the Proximate Determinants of Fertility." Population and Development Review 4 (1): 105-32. 11

For the United States, we used cost per user for short-term methods and cost per acceptor for long-term or permanent methods. 12

John Stover, Laura Heaton, and John Ross. 2005. FAMPLAN, Version 4. Futures Group International, Washington, D.C.

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and we did not project for developed countries, except for the United States. China, although the largest

developing country, was excluded because of its already low fertility and high contraceptive use. Also,

most observers, including the authors, assume that there is no aggregate unmet need for family

planning in China, given that desired fertility is higher than actual. The United States was included

because it actually has a significant, if small, level of unmet need for family planning. We grouped the 99

countries into the following major regions: Asia and the Near East (ANE), sub-Saharan Africa, Latin

America and the Caribbean, “transition countries” (formerly part of the Soviet Union), India, and the

United States (see Table A1).

II. Scenarios

As mentioned, we prepared four projections. It is not unusual when preparing family planning

projections to define a base or reference projection in which fertility and contraceptive use are

constant. While such an approach may be acceptable for a short period, we wanted to project for 45

years (2005–2050). An assumption of constant fertility and contraceptive use for comparative purposes

would be unrealistic, given the steady rise in contraceptive use and fall in fertility that have been

observed in the last 25 years. We therefore chose as our basis of comparison three of the UN population

projection variants (low, medium, and high) as reported in World Population Prospects: The 2008

Revision.13

The UN medium projection is based on an analysis of past fertility trends, which are then

continued into the future. The UN medium variant scenarios were prepared assuming an eventual

convergence of the total fertility rate of 1.85, although not all countries reach 1.85 by 2050. Fertility in

high- and medium-fertility countries follows a path derived from models of fertility decline estimated by

the UN on the basis of historical experience. For low-fertility countries, recently observed trends are

used.14 The UN high projection adds 0.5 to the medium scenario’s variant fertility rate each year, and

the UN low variant subtracts 0.5 from the fertility rate over most of the projection period. The three

scenarios have floor TFRs of 1.35, 1.85, and 2.35, respectively. We used the FAMPLAN model to estimate

the family planning levels that would correspond with each of the three UN fertility scenarios, while

taking account of expected changes in other proximate determinants of fertility, as described below.

In the fourth scenario, referred to as the “unmet need scenario,” we used the most current estimates of

unmet need for family planning from the Demographic and Health Surveys (DHSs). We assumed that

baseline unmet need will be met in all countries in a given target year. (Although the target years varied

by region, they were the same for all countries within each region.) This required calculating a trajectory

for the CPR that started at its observed or estimated value in 2005 and increased linearly until reaching

the base year total demand. The year in which that level of CPR was met is the target year. While it may

have been preferable to choose country-specific target dates, we did not have access to all the country-

specific factors that would have allowed that level of detail. International targets, such as the

Millennium Development Goals, are often specified at a global level and require some countries to have

more ambitious goals than others; by varying the target year by region, we took into account regional

13

United Nations. 2008, op. cit. 14

http://esa.un.org/unpp, accessed February 17, 2010.

http://esa.un.org/unpp

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differences. We discuss how we arrived at the target years for each region in more detail below, and

Table A2 in the Appendix shows the CPR assumptions for the unmet need scenario.

Some caution is required, however, in interpreting the unmet need scenarios. First, while we added the

base year unmet need percentage to the base year CPR to arrive at a target CPR equal to 2005 total

demand, it should be recognized that levels of unmet need change over time and with the CPR. Hence,

when a country reaches the target CPR, it is very likely to still have unmet need for family planning. This

is because, as the CPR increases, there may be a “demonstration effect” that increases the acceptability

of family planning among couples. Furthermore, as fertility preferences decrease, total demand for

family planning increases, and this may change levels of unmet need. Figure 1 below, for example,

shows how unmet need varies with the level of CPR. We regressed the observed levels of total unmet

need against the overall CPR for all women for 150 DHS surveys and present the results in Table A3.

Figure 1. Relationship between Unmet Need and CPR

Second, as Westoff15points out, some adjustment may be required in the use of levels of unmet need to

predict fertility. He reduces the birth spacing component of unmet need by 30%, because at some point,

some women who currently want to space births will want to become pregnant. Third, Westoff also

adjusts total unmet need downward to take account of women with an unmet need who have never

used contraceptives and say they do not intend to use them.

15

Westoff. 2006, op. cit.

0

2

4

6

8

10

12

0 10 20 30 40 50 60 70 80

Un

me

t N

ee

d (

%)

CPR

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Working in the opposite direction, however, is the approach taken by the Guttmacher Institute.16 Its

calculations of women with an unmet need for family planning include users of traditional methods. We

did not do this, because in our projections, we take account of expected changes in the method mix

away from traditional methods in favor of modern methods. For the developing countries in our study,

9.3% used a traditional method of family planning in the base year. If we had followed the Guttmacher

methodology, we would have needed to increase the unmet need by that same percentage.

Assumptions: Demographic Parameters and Values

For all scenarios, we used the UN population estimates for the base year (2005) population by age and

sex. While other country-specific population data are undoubtedly available for some countries,

especially those with a recent census, the UN figures ensure consistency.

Mortality is defined from the appropriate life-table survivor rates that are applied using values of life

expectancy at birth. We used the life expectancy values in the UN medium variant projections in all

scenarios. Depending on the inferred level of the infant mortality rate, either the Coale-Demny Model

West or Model North tables were used. The 2008 UN estimates are consistent with Joint United Nations

Program for AIDS (UNAIDS) figures for HIV prevalence and AIDS mortality.17

For total fertility, in all three UN scenarios, we used the values of the TFR in each scenario for that same

projection by the United Nations, so our population projection for each scenario duplicates the three UN

projections.

Other demographic parameters, such as the age distribution of fertility, international migration, and the

sex ratio at birth, are all taken from the UN medium variant projection estimates for all scenarios.

Assumptions: Family Planning

Projections of family planning require a number of parameters and assumptions, which we discuss in

this section. We first estimated family planning level as measured by the CPR for the three UN variant

projections. As stated, we did so because one goal of this analysis was to compare the family planning

level required under the unmet need scenario with that of the UN scenarios. Another objective was to

estimate how much it would cost to meet each of the four scenarios. We needed to estimate the

contraceptive levels for each country that correspond to the TFRs in the three UN projections so these

could be compared with those in the unmet need scenario. To do this, as mentioned above, we used the

proximate determinant model of fertility, but solved it for the CPR using the TFRs in each of the UN

scenarios as an input. It should be noted that the CPR in this paper is for all women of reproductive age

(WRA) using all methods, including traditional methods, and not only for married women (or women in

union).

16

Michael Vlassoff, Susheela Singh, Jacqueline E. Darroch, Erin Carbone, and Stan Bernstein. 2004. Assessing Costs and Benefits of Sexual and Reproductive Health Interventions: Occasional Report, No. 11. New York: The Alan Guttmacher Institute. 17

United Nations. 2008, op. cit., pp. 12-13.

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Proximate determinants and percentage of women in union. Because we prepared a 45-year

projection in which TFR was changing, we wanted also to take account of likely changes in factors that

affect fertility other than family planning. The other proximate determinants of fertility are (1)

percentage of women 15–49 years of age in union, (2) number of months of postpartum insusceptibility,

(3) percentage of women who are sterile, and (4) the abortion rate. Among these proximate

determinants, changes in the percentage of women in union are likely to be the most important

influence on fertility change over a 45-year period, especially for developing countries. So, with one

exception, we held the other proximate determinants constant at their 2005 levels and we modeled the

percentage of women in union. As the abortion rate is a significant proximate determinant in the

transition region, we assumed that abortion rates in these countries would decline linearly from their

baseline values to 0 in 2050; elsewhere, abortion rates were assumed to be 0 throughout the projection

period. In order to model changes in percentage of WRA in union, we hypothesized that marriage and

union patterns would be influenced by levels of female education: as women become more educated,

they stay in school longer, enter the labor force more, and generally delay decisions on marriage. To

model the percentage of women in union, we used DHS data to estimate a regression equation that

takes into account the percentage of women who had achieved a primary education and the percentage

of women with a secondary education; we used a dummy variable for countries that were in the

transition region as independent variables. The regression results are shown in Table A4 in the

Appendix.

We then used the estimated regression equation to project the percentage of women in union from

2005 until 2050. As inputs for the two education variables, we used the “GET” education projections

computed by the International Institute for Applied Systems Analysis (IIASA).18The results of these

projections are shown in Table A4 of the Appendix. We see that, in all countries, there is a projected

decline in the percentage of women in union. Average declines by region are shown in Table 1 below.

For our sample of countries, we predicted an average 6.36% decline in the percentage of women in

union over the 45-year period.

Table 1. Changes in Percentage of Women in Union by Region

(unweighted averages)

Region Change in Percentage of Women in Union

Africa –8.58

Asia and Near East –8.58

India –10.75

LAC –3.87

Transition –3.10

United States –4.59

All countries –6.36

18

K. C. Samir, B. Barakat; A. Goujon; V. Skirbekk, and W. Lutz. 2008. Projection of Populations by Level of Educational Attainment, Age, and Sex for 120 Countries for 2005-2050. IIASA Interim Report IR-08-038.

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Method mix. Contraceptive method mix is another important parameter that can influence the

relationship between contraceptive use and fertility. Since modern methods tend to be more effective

at preventing pregnancy than traditional methods, a country with more modern methods would be

expected to have a lower TFR than a country with the same CPR, but a higher proportion of users of

traditional methods.19 If the TFR or the CPR changes appreciably during a projection period, it is likely

that method mix will also change. In particular, we expect that as a country modernizes and as family

planning becomes more prevalent, the proportion of users of modern methods would tend to increase

over time. In an analysis similar to that used for women in union, we again used DHS data to perform

regression analyses of the method-specific CPR, with education and urbanization as independent

variables, as well as a dummy variable for Muslim countries. The statistical results were mixed, and

often the independent variables were not statistically significant. In a similar exercise, Ross et al. project

the method mix based on a set of regression equations, but again the level of statistical significance is

low.20 We therefore calculated the average annual change in the modern CPR for countries and used

regional averages to project the proportion of modern users among all users (see Table 2). The table

shows that only in sub-Saharan Africa, where CPR tends to be low and where traditional methods are

more popular, have there been significant increases in modern methods. To project the method mix

distribution, we assumed that the distribution of each modern method as a percentage of all modern

methods did not change.

Table 2. Average Annual Change in the Percentage of All Users Who Use a Modern Method in Countries with More than One DHS by Region

Sub-Saharan Africa 1.71

North Africa, West Asia, and Europe 0.02

South & Southeast Asia 0.00

Latin America & Caribbean 0.65

India 0.02

Costs of family planning. Estimating the costs of family planning, as with other health services, is

challenging. Gathering data on a specific health service is time consuming and subject to many different

factors, depending on the country and institutional setting. Costs for the same services will vary

depending on how those services are delivered. For example, services delivered at an urban tertiary

institution will be higher than the same services delivered by a community organization in a rural

setting. Moreover, many cost studies only take account of the costs of providing the services and do not

take account of any costs in generating demand for those services.

In this paper, we used cost per user and multiplied that by cost per user times the number of users. The

number of users was calculated by multiplying the modern CPR times the number of women of

reproductive age. The modern, rather than overall, CPR was used for this calculation in order to align

19

The effectiveness assumptions for the main methods included in our analysis are in Table A6 in the Appendix. 20

Ross, Stover, and Adalaja. 2005, op. cit.

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with the methodology used to create the cost-per-user data. For the United States, we used costs per

user for temporary methods and costs per acceptor for long-term and permanent methods

Costs per user were taken from the 2004 Guttmacher Institute report.21 While the Guttmacher report

recognizes the wide range of unit cost estimates for family planning, we thought that it did a good job of

summarizing the available unit cost information and providing it in a format that was usable for the

present analysis. Moreover, unlike many cost studies, the Guttmacher data cover drugs and supplies,

labor, overheads, and other clinic-related costs. Table 3 shows the unit costs that were used after

adjusting 2003 US dollar costs in the Guttmacher report to 2005 US dollars based on a 3% inflation rate.

Table 3. Average Family Planning Cost per User

Annual User Costs (2005 dollars)

Africa $27.60

Asia $18.00

LAC $22.30

Source: Vlassoff et al. 2004, Table 3.15.

For the United States, we used data on the annual costs per user from a recent study by Trussell et al.22

In their paper, method costs were calculated that covered drugs or supplies and professional fees. The

costs included in the US projections in this paper are listed below in Table 4. As mentioned, the

FAMPLAN model distinguishes between temporary and long-term methods, so the cost of a tubal

ligation, for example, is only applied to new users.

Table 4. One-Year Cost of Contraceptives in the United States

Intrauterine device $758

Vasectomy $707

Male condom $120

Implant $961

Injectable $551

Tubal ligation $2,896

Pills $674

Source: Trussell et al., Table 2a.

Unmet need scenario. As discussed in the methodology section, the fourth scenario assumes that

countries can satisfy currently observed levels of unmet need after a specified period. The choice of any

target date is always somewhat arbitrary, but for this analysis, we wanted a target date that was

ambitious, yet feasible. We looked at the experiences of countries with more than one DHS and

calculated the average annual CPR changes by countries in a region. The results are shown in Table 5

below. It can be seen that countries in the Latin America and Caribbean (LAC) and transition regions

21

Vlassoff et al. 2004, op. cit. 22

Trussell, James, Anjana M. Lalla, Quan V. Doan, Eileen Reyes, Lionel Pinto, and Joseph Gricar. 2009. “Cost Effectiveness of Contraceptives in the United States.” Contraception 79: 5–14.

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were able to add about 1% annually to the CPR for all methods for all women. However, in sub-Saharan

Africa and Asia, these increases were lower.

Levels of unmet need vary by country and region. Table 5 also presents the average number of years

that a country in each region would require to meet the current level of unmet need. In Africa and India,

the required time is more than the 45-year projection period in the current study. We therefore chose a

target number of years to meet unmet need that is optimistic, given current trends, but still somewhat

feasible. Our criteria for a feasible target date came down to what required annual change in CPR would

be needed to meet unmet need and how that compared with recent historic experience. The last two

columns of Table 5 show the required annual changes and the difference between these changes and

the historic record. The sub-Saharan African rate is above its recent historic experience, but we thought

that it was feasible, given that the CPR is so low in this region that large gains are possible if a significant

family planning commitment were made. Recent experience in Rwanda, where the CPR among married

women rose from 13% in 2000 to 36% in 2007, demonstrates that large CPR annual increases are

possible in this region.23 In LAC and Asia, levels of unmet need tend to be lower and CPR tends to be

higher than in Africa. The required change to meet unmet need in 15 years in North Africa, the Middle

East, and Asia is 1.1 CPR points. For both India and the United States, which appear to have experienced

recent CPR plateaus, the required CPR annual changes are also above the recent historic experience.

Some discussion of how we calculated unmet need for the United States is in order. As there is no DHS

for the United States, we used data from the 2002 National Survey of Family Growth to provide data on

the contraceptive prevalence rate, the method mix, infecundability, the percentage of women in union,

and unmet need for family planning.24 In most studies, the unmet need for family planning is calculated

for women in union or married women, all of whom are presumed to be sexually active. It is possible to

calculate unmet need for sexually active unmarried women in developing countries, but many

researchers feel the quality of those data may be problematic, since fertility intentions of this population

may be less clear.25 Since we are applying both the contraceptive prevalence rate and by implication

unmet need to all women, and since the proximate determinants model already account for sexual

activity through the women in union variable, we calculated unmet need as the percentage of all

women who are sexually active, not seeking to be pregnant, not pregnant intentionally, and not using

contraception. The National Survey of Family Growth reported, for example, that the percentage of US

women who are sexually active and not using contraception in 2002 was 7.4%. The report also says that

34.9% of births in the previous five years were unwanted or mistimed. We applied this 34.9% to the

percentage of women who were currently pregnant in 2002 (5.3%) to arrive at an estimate of the

percentage of those women who were pregnant unintentionally, and added that to those who were

sexually active, but not using contraception. This gave us a base year estimate of 9.2% unmet need for

family planning among all women.

23

Rwanda, Ministry of Health (MOH), National Institute of Statistics of Rwanda (NISR), and ICF Macro. 2009. Rwanda Interim Demographic and Health Survey 2007-08. Calverton, Maryland. 24

A. Chandra, G. M. Martinez, W. D. Mosher, J. D. Abma, and J. Jones. 2005. “Fertility, Family Planning, and Reproductive Health of U.S. Women: Data from the 2002 National Survey of Family Growth.” Vital Health Stat 23 (25). National Center for Health Statistics, Atlanta. 25

Westoff. 2006, op. cit.

P a g e | 12

The CPR projections for the unmet need scenario are reported in Table A7. As stated, these projections

used levels of unmet need, as well as the base year CPRs. We used recent DHS data whenever possible.

For countries with no recent DHS, we relied on the Population Reference Bureau’s 2009 World

Population Data Sheet.26

Table 5. Average CPR and Unmet Need for Family Planning by Region and Years to Meet Unmet Need

Base CPR

Unmet Need

Historic Annual

Change in CPR

Years to Meet Unmet

Need at Historic Trend

Target Number of

Years to Meet Unmet

Need

Required Annual Change

Increase over

Historic Rate

Africa 22.72 24.53 0.49 50 25 0.98 0.49

ANE 42.6 16.5 0.89 19 15 1.10 0.21

Indiaa 43.8 12.8 0.24 53 25 0.57 0.27

LAC 49.32 12.91 1.09 12 10 1.29 0.20

Transitionb 47.0 12.25 1.12 11 10 1.23 0.11

USc 62.1 9.2 –0.3 – 20 0.46 0.76

a. Between 1992–1993 and 2005–2006 b. Kazakhstan only c. 2002

Results

Major findings of the projections are presented in Figures 2–10. The CPR, TFR, total population, and

cumulative family planning costs are shown aggregated across all countries (“global”) for the group of

developing countries included in this study, and for each of the six regions analyzed, under the four

scenarios. Detailed projection data are found in the Appendix in Tables A8- A15.. In each region, the CPR

and TFR of the unmet need scenario display a more linear trajectory than do the paths of the UN

scenarios. This is because the unmet need scenario assumed a constant CPR increase, both before and

after meeting unmet need for family planning, up to a cap of 80%. The unmet need scenario produces

2050 CPRs and TFRs that are in the range of the UN low scenario; in ANE, LAC, and the United States, the

unmet need scenario produces the highest CPR and lowest TFR, whereas in Africa, India, and the

transition countries, the unmet need scenario falls between the UN low and medium scenarios. All 2050

UN low scenarios produce TFRs below the standard replacement level of 2.1, as do all of the UN medium

and unmet need scenarios, except Africa. None of the UN high scenarios produces TFRs below 2.1.

26

Population Reference Bureau. 2009. World Population Data Sheet, 2009.Washington, DC.

P a g e | 13

III. Global Results

In this section, we present the results for all countries modeled, aggregated on a global level. In doing

so, it is important to understand the weight that each region’s population plays. The results from the

global projections are most heavily weighted by the Asian countries with large populations and numbers

of WRA. For instance, in 2005 the ANE region accounts for 32% of the WRA and India for an additional

28%; in that year, Africa contributed 17%, LAC 14%, and transition countries and the United States only

2% and 7%, respectively. By 2050 the makeup of the global projection has shifted slightly; for example,

the global WRA in the UN medium projection consists of 29% from the ANE region, 24% from India, 31%

from Africa, 10% from LAC, 1% from transition, and 5% from the United States. The regional breakdown

is important to keep in mind, as some regions contribute significantly more or less to the global

projections.

As seen in Figure 2a, the unmet need scenario’s global CPR moves steadily from a path similar to the UN

medium scenario to almost meeting the UN low CPR in 2050. The 2005 CPR is 45%, increasing to 71% in

the UN low scenario, 61% in the UN medium scenario, 51% in the UN high scenario, and 70% in the

unmet need scenario. As we will see in other CPR and TFR trajectories, the path through time of the

unmet need CPR is different from that of the UN scenarios. Whereas the UN scenarios can reach specific

TFR floors (and in some cases do reach them earlier in the projection period) and display a leveling off of

CPRs, the unmet need scenario assumes a constant increase in CPR up to and before meeting the

baseline unmet need, only leveling off if and when CPR reaches the assumed ceiling of 80%. These

underlying assumptions create different shapes of CPR and TFR projections between the UN scenarios

and the unmet need scenario.

Like the CPR projections, the global TFR projection (see Figure 2b) under the unmet need scenario first

follows the UN medium scenario, then steadily moves toward the UN low TFR in later years. The

baseline TFR is 3.17, falling to 1.55, 2.04, and 2.54 respectively under the UN low, medium, and high

scenarios and to 1.62 under the unmet need scenario.

Global population (Figure 2c) under the unmet need scenario follows a trajectory between that of the

UN medium and low scenarios, although closer to the UN medium scenario. The 2005 starting

population is 4.05 billion; by 2050 the total population is 5.78 billion, 6.7 billion, and 7.7 billion under

the UN low, medium, and high scenarios, respectively, and 6.3 billion under the unmet need scenario.27

We see the cumulative costs of the family planning program for the entire projection period (2005–

2050) under the four scenarios in Figure 2d. The costs under the UN low, medium, and high scenarios

are estimated to be $1.126 trillion, $1.027 trillion, and $948 billion, respectively, while the unmet need

scenario family planning program costs are estimated at $1.116 trillion. These costs are heavily

influenced (in terms of population size or number of family planning users) by the US costs, which

represent 41% of the global costs in the UN low and medium scenarios, 44% of the costs in the UN high

scenario, and 43% of the costs in the unmet need scenario. This is due to much higher costs per user in

27

As noted in the methodology section, these differences are due only to differences in fertility rates, as mortality is assumed to follow the UN medium mortality pattern in all scenarios, and international migration is assumed to be zero.

P a g e | 14

the United States than in the other regions. The general pattern of costs across the three UN scenarios is

to be expected in all regions, given that the most users are in the UN low scenario and the fewest users

in the UN high scenario.

The unmet need cumulative costs are also a function of the number of users; however, the cumulative

cost is less straightforward to predict than the UN scenarios for two reasons. First, the different shape of

its CPR curve can lead to a different number of users in some years, even though the population

trajectory of the unmet need scenario closely matches the UN scenario. Second, because of population

momentum, CPR increases early in the projection period lead to lower cumulative family planning costs

more than CPR increases do later in the projection period, because they reduce numbers of WRA in

subsequent years. Thus, the fact that global unmet need scenario costs are nearly as high as the global

UN low scenario costs is partly due to the United States’ aggressive—compared with the UN scenarios—

family planning program in the unmet need scenario (see Figure 9a) and partly due to the developing

countries’ slower initial CPR increases in the unmet need scenario—compared with the UN scenarios—

in the earlier years of the projection period (see Figure 3a).

P a g e | 15

Figure 2. Global: Contraceptive Prevalence, Total Fertility, Population, and Cumulative Family Planning Cost

0

10

20

30

40

50

60

70

80

2005 2010 2015 2020 2025 2030 2035 2040 2045 2050

2a: Global: Contraceptive Prevalence Rate

UN Low UN Medium UN High Unmet Need

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

2005 2010 2015 2020 2025 2030 2035 2040 2045 2050

2b: Global: Total Fertility Rate


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0

1

2

3

4

5

6

7

8

9

2005 2010 2015 2020 2025 2030 2035 2040 2045 2050

2c: Global: Population (billions) UN Low UN Medium UN High Unmet Need

1,126

1,027 948

1,116

0

200

400

600

800

1,000

1,200


2d: Global Cumulative Family Planning Costs 2005-2050 (Billions USD)

P a g e | 17

IV. Developing Countries

Data from the developing countries, like the global projections, are most heavily weighted by the ANE

region and India, while the transition region is the least populous. Like the global projections, the

relative weight of each region changes throughout the projection period in accordance with its growth

rate.

The base year CPR for the developing countries is 45%. By 2050 the CPR reaches 71%, 61%, and 51% in

the three UN scenarios and 70% in the unmet need scenario. As shown in Figure 3a, the developing

countries’ CPR path is very similar to the UN medium scenario in earlier years, then increases to nearly

meet the UN low scenario by the end of the projection period.

Figure 3b illustrates a similar pattern for the TFR; early years of the unmet need projection are nearly

identical to the UN medium scenario, but the continued decline leads to a 2050 TFR similar to the UN

low scenario. The 2005 TFR is 3.25, while final year TFRs are 1.56, 2.05, and 2.55 under the UN scenarios,

and 1.65 under the unmet need scenario.

Figure 3c shows the population projections resulting from these TFRs. The unmet need projection of

total population is very similar to the UN medium total population path, diverging significantly only in

the later years. This later divergence reflects the unmet need scenario’s effect on the continued decline

in TFR in later years, when the TFR declines in the UN scenarios are small. The 2005 population in the

developing countries is 3.7 billion, with final year populations of 5.4 billion, 6.3 billion, and 7.2 billion for

the UN low, UN medium, and UN high scenarios, respectively, and 6 billion in the unmet need scenario.

Because costs per user do not vary hugely between regions, the developing countries’ cumulative family

planning costs are largely a function of the number of WRA and the CPR in each region. Figure 3d shows

the cumulative costs of $665 billion, $603 billion, and $533 billion for the UN low, medium, and high

scenarios, respectively, and $638 billion under the unmet need scenario. This reflects the unmet need’s

projected CPR path that begins near the UN medium CPR path and ends near the UN low CPR path.

P a g e | 18

Figure 3. Developing Countries: Contraceptive Prevalence, Total Fertility, Population, and Cumulative Family Planning Cost

0

10

20

30

40

50

60

70

80

2005 2010 2015 2020 2025 2030 2035 2040 2045 2050

3a: Developing Countries: Contraceptive Prevalence Rate


0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

2005 2010 2015 2020 2025 2030 2035 2040 2045 2050

3b: Developing Countries: Total Fertility Rate UN Low UN Medium UN High Unmet Need

P a g e | 19

0.0

1.0

2.0

3.0

4.0

5.0

6.0

7.0

8.0

2005 2010 2015 2020 2025 2030 2035 2040 2045 2050

3c: Developing Countries: Population (billions)


665

603

533

638

0

100

200

300

400

500

600

700


3d: Developing Countries Cumulative Family Planning Costs 2005-2050 (Billions USD)

P a g e | 20

V. Regional Projections

While the projections for the developing countries as a group are interesting, there are significant

regional differences. In the following sections, we present the results of the four scenarios for each of

the regions, including India and the United States, both of which are treated as a region unto

themselves.

VI. Africa

While the unmet need scenario does not imply as fast an initial CPR increase as the UN low scenario, the

unmet need scenario’s constant CPR increase leads to a final-year CPR of 61%, compared with the UN

low scenario’s final-year CPR of 66%. A similar pattern is seen in the TFR graph. However, the total

population of the unmet need scenario falls almost precisely in line with the UN medium scenario. This

is because of population momentum: higher fertility earlier in the projection period caused the unmet

need scenario to produce more women of reproductive age in the second half of the projection period,

thus producing a population similar in size to the UN medium scenario, despite its lower fertility rate. In

2030, the year when unmet need is assumed met in Africa in the unmet need scenario, the TFR is still

higher and CPR still lower than even the UN medium scenario, because of the aforementioned slower

rate of change of the TFR and CPR in the early years of the projection.

TFR decreases between 2.29 and 3.30 births per woman or between 44% and 64% from the 2005 TFR of

5.17. This represents the largest fertility decline of all the regions, both in absolute and relative terms.

CPR increases were also the largest of all regions, with absolute gains of 29–45 percentage points over

the 45-year projection period. The Africa projections produce the only case of a CPR projected to more

than double; in the UN low scenario, the CPR increases by 216%.

In terms of family planning costs in Africa, we see that the cumulative costs for the unmet need scenario

over the 45-year period are $1 billion less than the UN medium variant. This is because the CPR, and

consequently the number of family planning users, is lower in the unmet need scenario compared with

the UN medium variant until after 2035. The average annual cost of the unmet need scenario is $3.93

billion, compared with $3.95 billion for the UN medium scenario.

In conclusion, we can say the unmet need scenario falls between the UN medium and low scenarios in

terms of contraceptive prevalence and fertility. However, because of the dynamics of population

momentum, the unmet need scenario’s population projection approximates the UN medium projection.

P a g e | 21

Figure 4. Africa: Contraceptive Prevalence, Total Fertility, Population, and Cumulative Family Planning Cost

0

10

20

30

40

50

60

70

2005 2010 2015 2020 2025 2030 2035 2040 2045 2050

4a: Africa: Contraceptive Prevalence Rate


0

1

2

3

4

5

6

2005 2010 2015 2020 2025 2030 2035 2040 2045 2050

4b: Africa: Total Fertility Rate


P a g e | 22

0.0

0.5

1.0

1.5

2.0

2.5

2005 2010 2015 2020 2025 2030 2035 2040 2045 2050

4c: Africa: Population (billions)


198 178

156 177

0

50

100

150

200

250


4d: Africa Cumulative Family Planning Costs, 2005-2050 (Billions USD)

P a g e | 23

VII. Asia and the Near East

The CPR in the unmet need scenario for Asia and the Near East finishes above the UN low scenario,

again because of the near flattening of the UN low TFR after 2025 and consequent plateau of the

corresponding CPR. Continuing a constant CPR increase in the years after unmet need is met produces a

CPR of 79% by 2050. Up until 2030 the unmet need scenario falls between the UN low and medium

rates of contraceptive use and fertility, but after 2030 the unmet need scenario implies greater

contraceptive use and concomitant lower TFRs. Earlier population momentum is compensated by later

fertility rates that dip below the UN low scenario, resulting in a 2050 population size of approximately

1.6 billion people in both scenarios. Both the TFR and the CPR fall between the levels of the UN low and

medium scenarios in 2020, the year that unmet need is assumed met in the unmet need scenario.

Fertility rates are projected to decrease by approximately one birth per woman in the ANE region, with a

range of 0.40–1.41 fewer births per woman in 2050, compared with 2005. Moderate CPR increases of

7%–53% are projected, producing final year CPRs of 55%–79%.

In terms of costs, the cumulative cost of the unmet need scenario is estimated at $201 billion, some $4

billion more than the UN low scenario and $21 billion more than the UN medium scenario. Average

annual costs for the unmet need scenario are estimated at $4.45 billion, compared with $4.37 billion for

the UN low scenario and $3.99 billion for the UN medium scenario.

In conclusion, we can say that, in the ANE region, the unmet need scenario is approximated as closest to

the UN low scenario. The CPR for the unmet need scenario is 79%, compared with 77% for the UN low

scenario. The TFR is 1.46 for the unmet need scenario vs. 1.48 for the UN low scenario. The total

population is approximately the same in both scenarios.

P a g e | 24

Figure 5. Asia and the Near East: Contraceptive Prevalence, Total Fertility, Population, and Cumulative Family Planning Cost

0

10

20

30

40

50

60

70

80

90

2005 2010 2015 2020 2025 2030 2035 2040 2045 2050

5a: ANE: Contraceptive Prevalence Rate


0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

2005 2010 2015 2020 2025 2030 2035 2040 2045 2050

5b: ANE: Total Fertility Rate


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0.0

0.5

1.0

1.5

2.0

2.5

2005 2010 2015 2020 2025 2030 2035 2040 2045 2050

5c: ANE: Population (billions) UN Low UN Medium UN High Unmet Need

197 180

161

201

0

50

100

150

200

250


5d: ANE Cumulative Family Planning Costs 2005-2050 (Billions USD)

P a g e | 26

VIII. India

The Indian CPR and TFR initial rate of change is lower than that of both the UN medium and low

scenarios. The unmet need CPR and TFR only surpass the UN medium projection in 2038, when the UN

projections display stagnation in the fertility rate. Because the initial lower fertility rates counteract the

later higher fertility rates, the unmet need scenario and the UN medium scenario produce nearly

identical population trajectories, with 2050 populations of approximately 1.7 billion. As in ANE and LAC,

when unmet need is assumed met in 2030 (in the unmet need scenario), India’s CPR and TFR are

between the UN low and medium scenario values, again because of the initial inertia of the UN

projections, compared with the unmet need projection.

As with Asia and the Near East, the India projections show moderate contraceptive increases and

fertility decreases. Fertility rates decrease by about one birth per woman (0.59–1.59) or about 40%

(20%–54%) from the initial TFR of 2.94. Similarly, contraceptive use increases by about 15 percentage

points (3.7–26.71) or by about 40% (8%–61%).

Cumulative family planning costs for the unmet need scenario are estimated at $143 billion. This falls

between the UN medium scenario ($141 billion) and the UN low scenario ($157). Average annual costs

for the unmet need scenario are $3.17 billion and slightly higher than the UN medium scenario

estimated at $3.14 billion.

In conclusion, for India we can say that the unmet need scenario falls between the UN medium and low

scenarios for both contraceptive use and fertility. However, because of the pace of contraceptive use

and consequent impact on fertility, the unmet need scenario produces a higher population by 2050 than

the UN medium scenario (1.7 billion vs. 1.6 billion).

P a g e | 27

Figure 6. India: Contraceptive Prevalence, Total Fertility, Population, and Cumulative Family Planning Cost

0

10

20

30

40

50

60

70

80

2005 2010 2015 2020 2025 2030 2035 2040 2045 2050

6a: India: Contraceptive Prevalence Rate


0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

2005 2010 2015 2020 2025 2030 2035 2040 2045 2050

6b: India: Total Fertility Rate


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0.0

0.5

1.0

1.5

2.0

2.5

2005 2010 2015 2020 2025 2030 2035 2040 2045 2050

6c: India: Population (billions)


157

141

123

143

0

20

40

60

80

100

120

140

160

180


6d: India Cumulative Family Planning Costs 2005-2050 (Billions USD)

P a g e | 29

IX. Latin America and the Caribbean

Overall, the unmet need scenario for Latin America and the Caribbean implies greater contraceptive use

and lower rates of growth than does the UN low scenario by 2050. The unmet need scenario produces

larger CPRs and implies lower TFRs than the UN low scenario from 2026 onward. Similar to Asia and the

Near East and India, the unmet need CPR and TFR fall between the values produced by the UN low and

medium scenarios in the year 2015, when unmet need is assumed met in the unmet need scenario.

The LAC region is one of only two regions to reach the 80% CPR cap for the unmet need scenario (other

regions have individual countries that reach a CPR of 80%, but not the region as a whole). From 2046

through 2050, the CPR for LAC remains constant at the maximum of 80%. However, this represents a

moderate increase in CPR, similar to those seen in ANE region and India. The CPR increases

approximately 15 percentage points (from 4 to 27) or by about 30% (8%–50%), for final year CPRs of

49%–70% for the three UN scenarios. Similarly, the UN TFR decreases are less than for other regions:

0.07–1.07 births per woman (or 3%–45%) for the UN scenarios, compared with the decrease of 1.54

births per woman (or 64%) in the unmet need scenario.

Because the unmet need scenario CPR surpasses the UN low scenario CPR, the cumulative family

planning costs for the unmet need scenario exceed the UN low by $5 billion ($108 billion vs. $103

billion). Average annual costs are estimated at $2.4 billion for the unmet need scenario vs. $2.1 billion

for the UN low scenario.

In summary, we can see that the unmet need scenario results in a CPR that is higher than the UN low

scenario by 2050 and consequently a fertility rate that is lower than the UN low. Similarly, the projected

population for the unmet need scenario is smaller than that of the UN low scenario (600 million vs. 614

million).

P a g e | 30

Figure 7. Latin America and the Caribbean: Contraceptive Prevalence, Total Fertility, Population, and Cumulative Family Planning Cost

0

10

20

30

40

50

60

70

80

90

2005 2010 2015 2020 2025 2030 2035 2040 2045 2050

7a: LAC: Contraceptive Prevalence Rate

UN Medium UN High Unmet Need UN Low

0.0

0.5

1.0

1.5

2.0

2.5

3.0

2005 2010 2015 2020 2025 2030 2035 2040 2045 2050

7b: LAC: Total Fertility Rate UN Low UN Medium

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0

100

200

300

400

500

600

700

800

900

2005 2010 2015 2020 2025 2030 2035 2040 2045 2050

7c: LAC: Population (millions)


103

95

85

108

0

20

40

60

80

100

120


7d: LAC Cumulative Family Planning Costs, 2005-2050 (Billions USD)

P a g e | 32

X. Transition Countries

In the transition countries of Central Asia, the unmet need scenario displays contraceptive use and

fertility rates very similar to the UN low scenario until the final five years of the projection. The

divergence in the final years of the projection is due to the fact that, while the unmet need scenario

reaches its cap of 80% CPR in the year 2047, no such CPR constraint can be placed on the UN scenarios.

The result is that the final years of the UN low scenario for the transition region produces the only

regional CPR above 80%, with a 2050 CPR of 84.16%. Because contraceptive use and fertility rates have a

delayed effect in overall population size, the paths of the total population projections for the unmet

need scenario and the UN low scenario are nearly identical, with a final year population of

approximately 83 million. As in Latin America and the Caribbean, unmet need is assumed met in 2015 in

the unmet need scenario; in this year the CPR and TFR are nearly identical to those of the UN low

scenario.

The CPR increases for the transition region are slightly larger than the other regions (with the exception

of Africa). This may be in part because we assumed that abortion rates decrease during the projection

period, implying in the UN scenarios that contraceptive use must increase even more than might

otherwise be expected in order to produce the decreasing TFRs projected. In the case of the unmet

need scenario, the decreasing abortion rates imply higher fertility rates than might otherwise be

expected, since pregnancies that would have been terminated in an earlier period now produce live

births. The results are CPR increases of 46%–61% and TFR decreases of between 0.02 and 1.02 births per

woman.

Regarding cumulative family planning costs over the projection period, we see that the unmet need

scenario and the UN low scenario are nearly identical at $9.6 billion and $9.7 billion respectively. This is

$600 million more than the UN medium scenario. The average annual costs for the Unmet Need

scenario are estimated at $214 million, slightly less than the $215 million estimated for the UN low

scenario.

In summary, for this region, the unmet need scenario is about halfway between the UN medium and low

scenarios in terms of contraceptive use and total fertility by the end of the projection period in 2050.

However, the effect of the unmet need scenario on the projected total population in 2050 (83.4 million)

puts it closer to the UN low scenario (82 million) than to the UN medium scenario (96.3 million).

P a g e | 33

Figure 8. Transition Countries: Contraceptive Prevalence, Total Fertility, Population, and Cumulative Family Planning Cost

0

10

20

30

40

50

60

70

80

90

2005 2010 2015 2020 2025 2030 2035 2040 2045 2050

8a: Transition: Contraceptive Prevalence Rate


0.0

0.5

1.0

1.5

2.0

2.5

3.0

2005 2010 2015 2020 2025 2030 2035 2040 2045 2050

8b: Transition: Total Fertility Rate


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0

20

40

60

80

100

120

2005 2010 2015 2020 2025 2030 2035 2040 2045 2050

8c: Transition: Population (millions)

UN Low UN Medium

9.7 9.1

8.4

9.6

0

2

4

6

8

10

12


8d: Transition Cumulative Family Planning Costs 2005-2050 (Billions USD)

P a g e | 35

XI. United States

As discussed, we performed the same projections for the United States as we did for the other

countries, using the DEMPROJ and FAMPLAN models. We used the three UN population projections to

estimate implied levels of contraceptive use, but we used US data for the proximate determinants of

fertility, including initial year contraceptive use and cost. Data on contraceptive costs have already been

presented and discussed above. Because all of our US data were for 2002, we used 2002 as a base year

for our projections, although we only report from 2005 onward to be consistent with the other regions.

Results for the United States are shown in Figure 9.28 Looking at the contraceptive prevalence rate and

fertility, we can see that in 2025—the target year for the unmet need scenario for the United States—

the UN low and the unmet need scenarios are almost identical: the CPR is 73% in both scenarios, and

the TFRs are 1.36 and 1.4 respectively. However, by the end of our projection period in 2050, the unmet

need CPR has reached 80% with a TFR of 1.02, compared with the UN low scenario with a CPR of 73%

and TFR of 1.35. The lower TFR in the unmet need scenario leads to a lower total population, compared

with the UN low (342 million vs. 359 million).

Cumulative family planning costs under the unmet need scenario are estimated to reach $478 billion,

$17 billion more than in the UN low scenario. Average annual family costs are high in the United States,

primarily because unit costs in the United States are so high; for the Unmet Need scenario, the cost is

$10.6 billion, compared with $10.2 billion for the UN low scenario.

In conclusion, we can say that the Unmet Need scenario in the United States leads to a higher CPR,

lower TFR, and consequently lower total population by 2050, compared with the UN low scenario.

28

The 2002 base year for US projections accounts for the minor differences in the starting year values of the TFR and CPR in the graphs and tables.

P a g e | 36

Figure 9. United States: Contraceptive Prevalence, Total Fertility, Population, and Cumulative Family Planning Cost

0

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9a: USA: Contraceptive Prevalence Rate


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9b: USA: Total Fertility Rate


P a g e | 37

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9c: USA: Population (millions)


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478

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P a g e | 38

XII. Summary and Conclusions

Despite impressive falls in fertility with concomitant increases in family planning use over the past few

decades, there are still significant levels of unmet need for family planning, not only in the developing

countries, but also in the United States. This paper compared a population projection based on meeting

unmet need for family planning with UN fertility projections. The “unmet need” scenario was based on

country-specific CPR projections designed to meet baseline unmet need for family planning in a

reasonable period, followed by continued CPR increases to keep pace with continued rising demand for

family planning. This unmet need scenario was compared with three of the UN variants for low,

medium, and high population growth, which are based on fertility projections. All four scenarios are

developed for each developing country with a population greater than one million (except China, which

has no aggregate unmet need), as well as the United States. Country results were aggregated into six

regions (with India and the United States considered as stand-alone regions), as well as the developing

country totals (all countries analyzed, except the United States) and global (including the United States).

Annual family planning program costs were also calculated for each scenario. The aggregated global

results show that the CPR and TFR projections under the unmet need scenario initially track the UN

medium scenario and then steadily move toward the UN low scenario in later years. Global population

under the unmet need scenario follows a trajectory between that of the UN medium and UN low

scenarios, although closer to the UN medium scenario. As seen in Figure 10, by 2050 the total “global”

population is 5.77 billion, 6.68 billion, and 7.69 billion, respectively, under the UN low, medium, and

high scenarios and 6.32 billion under the unmet need scenario. The UN low scenario results in a world

that has a lower population by some 900 million, compared with the UN medium scenario. The unmet

need scenario results in a 2050 population that is 365 million lower than the UN medium scenario or

40% of the difference between the UN medium and low scenarios.

For the developing countries modeled, the CPR and TFR paths under the unmet need scenario are

similar to the UN medium scenario in earlier years and then approach and nearly meet the UN low

scenario by the end of the projection period. The unmet need projection of total population is similar to

the UN medium total population path, diverging significantly only in the later years. The projected 2050

population for the unmet need scenario is 5.97 billion, compared with 5.42 billion for the UN low, 6.27

billion for the UN medium, and 7.23 billion for the UN medium scenarios (Figure 11). Again, the UN low

scenario results in a world that has a lower population by some 857 million, compared with the UN

medium scenario. The Unmet Need scenario results in an end line population that is 300 million lower

than the UN medium scenario or 35% of the difference between the UN medium and low scenarios.

For all the countries combined, the cumulative costs of the family planning program for the entire

projection period (2005–2050) for the unmet need scenario is slightly less than that estimated for the

UN low scenario ($1.116 trillion vs. $1.126 trillion). Costs for the UN medium and high scenarios are

estimated to be $1.027 trillion and $948 billion, respectively. For the developing countries by

themselves, the estimated cumulative costs for the unmet need scenario is $638 billion, which falls

between the estimated costs for the UN low scenario of $665 billion, and the costs for the UN medium

scenario of $603 billion. . Assuming the UN high scenario as a baseline, the additional annual costs to

meet unmet need for family planning are estimated to be approximately $3.7 billion per year over the

P a g e | 39

45-year projection period; $1.4 billion of this would be from the United States, and $2.3 billion from the

99 developing countries.

P a g e | 40

Figure 10. Global Population in 2050 under Four Scenarios

Figure 11. Developing Countries: Population in 2050 under Four Scenarios

5.77

6.68

7.69

6.32

0

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2

3

4

5

6

7

8

9


Bill

ion

s

Global: Population in 2050 Under Four Scenarios

5.42

6.27

7.23

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Developing Countries: Population in 2050 Under Four Scenarios

P a g e | 41

Appendix

Table A 1: List of Countries Included in the Analysis

United States India Transition Latin America/ Caribbean

Sub-Saharan Africa Asia

United States India Armenia Argentina Angola Afghanistan Azerbaijan Bolivia Benin Algeria Georgia Brazil Botswana Bangladesh Kazakhstan Chile Burkina Faso Cambodia Kyrgyzstan Colombia Burundi Egypt Tajikistan Costa Rica Cameroon Indonesia Turkmenistan Dominican Republic CAR Iraq Ecuador Chad Jordan El Salvador Côte d’Ivoire Laos Guatemala Djibouti Lebanon Haiti DRC Libya Honduras Eritrea Malaysia Jamaica Ethiopia Mongolia Mexico Gabon Morocco Nicaragua Gambia Myanmar Panama Ghana Nepal Paraguay Guinea Pakistan Peru Guinea-Bissau Philippines Trinidad & Tobago Kenya Sri Lanka Uruguay Lesotho Syria Venezuela Liberia Thailand Madagascar Tunisia Malawi Turkey Mali Vietnam Mauritania Yemen Mauritius Mozambique Namibia Niger Nigeria Republic of the Congo Rwanda Senegal Sierra Leone Somalia South Africa Sudan Swaziland Tanzania Togo Uganda Zambia Zimbabwe

P a g e | 42

Table A 2. CPR and Unmet Need

India CPR Unmet Need LAC CPR Unmet Need

India 43.8 12.8 Argentina 56.4 5.8

Bolivia 39.3 22.7

Transition CPR Unmet Need Brazil 56.4 5.8

Armenia 33.1 13.3 Chile 56.4 5.8

Azerbaijan 32 22.7 Colombia 56.4 5.8

Georgia 47 16 Costa Rica 56.4 5.8

Kazakhstan 51 9 Dominican Republic 54 11.4

Kyrgyzstan 48 9 Ecuador 39.3 22.7

Tajikistan 38 10 El Salvador 43.2 16.9

Turkmenistan 62 10 Guatemala 39.3 22.7

Uzbekistan 65 8 Haiti 22.9 37.5

Average 47.01 12.25 Honduras 43.2 16.9

Jamaica 54 11.4

Mexico 56.4 5.8

Nicaragua 43.2 16.9

Panama 56.4 5.8

Paraguay 56.4 5.8

Peru 39.3 22.7

Trinidad and Tobago 54 11.4

Uruguay 56.4 5.8

Venezuela 56.4 5.8

Average 49.32 12.91

P a g e | 43

Table A2. CPR and Unmet Need (Continued)

Africa CPR Unmet need Asia CPR Unmet Need

Angola 29.9 26.5 Afghanistan 29.6 24.9

Benin 17.2 29.9 Algeria 33.3 10

Botswana 46.6 20.6 Bangladesh 58.5 11.1

Burkina Faso 14 28.8 Cambodia 24.1 25.1

Burundi 9.6 37.9 Egypt 59.2 10.3

Cameroon 26.1 20.2 Indonesia 61.4 9.1

CAR 7.5 31.2 Iraq 57.1 11.9

Chad 2.5 20.7 Jordan 57.1 11.9

Côte d'Ivoire 13.3 35.6 Laos 24.1 25.1

Djibouti 57.1 11.9 Lebanon 57.1 11.9

DRC 20.1 24.4 Libya 57.1 11.9

Eritrea 10.3 33.8 Malaysia 61.4 9.1

Ethiopia 10.3 33.8 Mongolia 37.3 24.6

Gabon 44.1 16.2 Morocco 33.3 10

Gambia 10.5 21.2 Myanmar 24.1 25.1

Ghana 19.3 35.3 Nepal 37.3 24.6

Guinea 10.5 21.2 Pakistan 29.6 24.9

Guinea-Bissau 10.5 21.2 Philippines 31.6 17.3

Kenya 28.4 24.5 Sri Lanka 61.4 9.1

Lesotho 29 31 Syria 59.2 10.3

Liberia 13.3 35.6 Thailand 24.1 25.1

Madagascar 21.6 23.6 Tunisia 33.3 10

Malawi 25.7 27.6 Turkey 61.4 9.1

Mali 7.5 31.2 Vietnam 24.1 25.1

Mauritania 33.3 10 Yemen 28 25

Mauritius 21.6 23.6 Average 42.59 16.50

Mozambique 25.6 18.4

Namibia 46.6 20.6

Niger 10 15.8

Nigeria 13.3 16.9

Republic of the Congo 44.1 16.2

Rwanda 9.6 37.9

Senegal 8.7 31.6

Sierra Leone 10.5 21.2

Somalia 2.5 20.7

South Africa 46.6 20.6

Sudan 59.2 10.3

Swaziland 37.9 24

Tanzania 22.5 21.8

Togo 10.5 21.2

Uganda 19.6 40.6

Zambia 29.9 26.5

Zimbabwe 40.1 12.8

Average 22.72 24.53

P a g e | 44

Table A 3. Regression Results on Unmet Need

Regression Statistics

Multiple R 0.426564

R Square 0.181957 Adjusted R Square 0.170902

Standard Error 4.153927

Observations 151

Coefficients Standard

Error t Stat P-value

Intercept 7.172423 1.114276 6.436848 1.6E-09

CPR 0.276622 0.075304 3.673387 0.000334

CPR Squared –0.00514 0.001092 –4.70154 5.86E-06

Table A 4. Regression Results for Percentage of Women in Union

Regression Statistics

Multiple R 0.678181

R Square 0.45993

Adjusted R Square 0.450564

Standard Error 7.149899

Observations 177

Coefficients Standard Error t Stat P-value

Intercept 80.25978 1.521225059 52.75997 1.5E-108

Primary –0.20292 0.031274948 –6.48838 8.8E-10

Secondary –0.07775 0.03909582 –1.98868 0.048314

Transition 12.69296 3.179659599 3.991924 9.67E-05

P a g e | 45

Table A 5. Percentage of Women in Union, Ages 15–49

Country 2005 2010 2015 2020 2025 2030 2035 2040 2045 2050

Sub-Saharan Africa Angola 54.93 54.87 54.80 54.76 54.75 54.78 54.78 54.79 54.70 54.71

Benin 75.60 74.10 72.62 71.21 69.72 68.23 66.83 65.54 64.36 63.29

Botswana 35.30 35.05 34.54 33.99 33.51 32.90 32.44 32.06 31.59 31.23

Burkina Faso 76.93 75.58 74.07 72.43 70.74 69.09 67.51 66.00 64.56 63.23

Burundi 48.70 47.49 46.45 45.55 44.72 43.87 43.09 42.37 41.77 41.23

Cameroon 66.94 65.82 64.84 63.90 63.05 62.29 61.63 61.06 60.58 60.18

CAR 67.76 66.17 64.74 63.43 62.12 60.90 59.82 58.89 58.00 57.24

Chad 76.30 74.93 73.37 71.78 70.22 68.68 67.27 65.91 64.66 63.48

Côte d'Ivoire 64.48 63.27 61.94 60.58 59.31 58.00 56.64 55.36 54.20 53.17

Djibouti 54.77 54.34 53.70 53.14 52.69 52.31 52.17 52.02 51.92 51.84

DRC 66.65 65.52 64.51 63.60 62.76 61.99 61.34 60.76 60.25 59.80

Eritrea 63.91 62.13 60.66 59.13 57.73 56.37 55.49 54.75 54.11 53.55

Ethiopia 64.50 63.22 61.81 60.28 58.72 57.14 55.53 53.93 52.36 50.88

Gabon 53.40 52.70 52.08 51.74 51.27 50.84 50.53 50.28 50.08 49.77

Gambia 71.17 69.95 68.52 66.96 65.28 63.61 62.04 60.53 59.08 57.73

Ghana 61.75 60.53 59.28 58.19 57.16 56.42 55.84 55.33 54.92 54.58

Guinea 79.10 77.88 76.45 74.89 73.21 71.54 69.97 68.45 67.01 65.66

Guinea-

Bissau 79.10 77.88 76.45 74.89 73.21 71.54 69.97 68.45 67.01 65.66

Kenya 59.75 58.99 58.29 57.53 56.75 55.99 55.41 54.92 54.51 54.17

Lesotho 52.09 51.11 50.14 49.38 48.78 48.29 48.02 47.79 47.59 47.44

Liberia 64.48 63.27 61.94 60.58 59.31 58.00 56.64 55.36 54.20 53.17

Madagascar 64.59 63.86 63.12 62.34 61.40 60.48 59.65 58.92 58.27 57.70

Malawi 70.76 69.13 67.66 66.41 65.34 64.37 63.59 62.88 62.21 61.59

Mali 85.01 83.98 82.79 81.41 79.85 78.21 76.62 75.07 73.60 72.21

P a g e | 46

Country 2005 2010 2015 2020 2025 2030 2035 2040 2045 2050 Mauritania 57.21 55.25 53.40 51.82 50.43 49.10 47.99 46.97 46.04 45.18

Mauritius 59.15 58.31 57.95 57.49 57.18 56.84 56.45 56.36 56.08 55.75

Mozambique 69.71 68.34 67.00 65.71 64.52 63.54 62.74 61.97 61.23 60.54

Namibia 35.30 35.05 34.54 33.99 33.51 32.90 32.44 32.06 31.59 31.23

Niger 86.29 85.35 84.23 82.97 81.57 80.04 78.44 76.82 75.22 73.67

Nigeria 69.26 67.57 66.12 64.74 63.57 62.56 61.66 60.88 60.21 59.63

Republic of

the Congo 56.40 55.28 54.30 53.36 52.51 51.74 51.08 50.51 50.04 49.63

Rwanda 48.70 47.49 46.45 45.55 44.72 43.87 43.09 42.37 41.77 41.23

Senegal 67.60 66.10 64.62 63.21 61.72 60.23 58.82 57.54 56.36 55.29

Sierra Leone 69.92 68.70 67.26 65.70 64.02 62.36 60.79 59.27 57.83 56.47

Somalia 76.30 74.93 73.37 71.78 70.22 68.68 67.27 65.91 64.66 63.48

South Africa 42.13 41.15 40.18 39.43 38.83 38.33 38.06 37.83 37.64 37.48

Sudan 62.10 60.60 59.19 58.06 57.05 56.29 55.61 55.03 54.57 54.20

Swaziland 41.79 40.81 39.85 39.09 38.49 37.99 37.72 37.49 37.30 37.14

Tanzania 67.30 66.55 65.78 65.03 64.22 63.37 62.59 61.85 61.15 60.48

Togo 66.13 64.43 62.86 61.46 60.09 58.87 57.84 56.91 56.06 55.29

Uganda 62.83 61.70 60.68 59.78 58.93 58.17 57.52 56.93 56.42 55.97

Zambia 61.94 61.10 60.25 59.50 58.79 58.09 57.55 57.08 56.67 56.32

Zimbabwe 57.91 56.87 56.18 55.81 55.52 55.26 55.01 54.79 54.62 54.48

Asia (excluding China and India) Afghanistan 49.77 49.38 49.01 48.67 48.36 48.03 47.79 47.60 47.43 47.30

Algeria 38.49 38.42 38.36 38.31 38.30 38.34 38.33 38.34 38.25 38.26

Bangladesh 78.70 76.95 75.30 73.80 72.43 71.37 70.55 69.83 69.21 68.69

Cambodia 60.00 58.94 57.79 57.00 56.25 55.35 54.43 53.59 52.82 52.18

Egypt 62.10 60.60 59.19 58.06 57.05 56.29 55.61 55.03 54.57 54.20

P a g e | 47

Country 2005 2010 2015 2020 2025 2030 2035 2040 2045 2050 Indonesia 72.33 71.51 70.85 70.36 69.93 69.60 69.30 69.05 68.83 68.65

Iraq 54.77 54.34 53.70 53.14 52.69 52.31 52.17 52.02 51.92 51.84

Jordan 54.77 54.34 53.70 53.14 52.69 52.31 52.17 52.02 51.92 51.84

Laos 61.04 59.68 58.55 57.54 56.48 55.36 54.43 53.55 52.73 52.05

Lebanon 54.77 54.34 53.70 53.14 52.69 52.31 52.17 52.02 51.92 51.84

Libya 54.77 54.34 53.70 53.14 52.69 52.31 52.17 52.02 51.92 51.84

Malaysia 70.57 69.89 69.40 69.03 68.76 68.56 68.40 68.27 68.18 68.11

Mongolia 50.26 50.08 49.91 49.79 49.64 49.49 49.24 49.06 48.86 48.85

Morocco 51.97 50.29 48.72 47.36 45.96 44.57 43.46 42.49 41.67 41.00

Myanmar 56.75 55.86 55.01 54.24 53.46 52.71 52.02 51.42 50.91 50.50

Nepal 76.96 74.66 72.46 70.55 68.81 67.32 66.15 65.08 64.09 63.24

Pakistan 62.93 61.10 59.46 57.94 56.46 55.10 53.81 52.59 51.54 50.64

Philippines 63.43 63.04 62.70 62.40 62.14 61.93 61.76 61.62 61.52 61.44

Sri Lanka 70.55 70.01 69.52 69.11 68.87 68.68 68.46 68.31 68.21 68.12

Syria 59.42 58.79 58.20 57.37 56.50 55.67 55.07 54.54 54.10 53.72

Thailand 62.81 62.04 61.26 60.54 59.93 59.52 59.15 58.83 58.60 58.40

Tunisia 51.97 50.29 48.72 47.36 45.96 44.57 43.46 42.49 41.67 41.00

Turkey 68.03 67.16 66.25 65.41 64.60 63.85 63.10 62.48 61.95 61.52

Vietnam 63.86 63.37 62.92 62.41 61.89 61.30 60.74 60.21 59.75 59.39

Yemen 66.72 66.28 65.64 65.09 64.64 64.26 64.11 63.97 63.86 63.78

Latin America and the Caribbean Argentina 60.51 58.75 57.11 55.60 54.24 53.18 52.35 51.63 51.01 50.50

Bolivia 59.49 58.66 57.99 57.46 56.98 56.63 56.37 56.16 55.97 55.83

Brazil 59.40 58.78 58.20 57.65 57.17 56.78 56.50 56.28 56.11 55.97

Chile 50.58 50.21 49.85 49.56 49.33 49.17 49.01 48.88 48.79 48.72

Colombia 51.50 50.96 50.51 50.11 49.79 49.53 49.31 49.14 48.99 48.88

Costa Rica 52.41 52.02 51.66 51.24 50.86 50.42 50.11 49.82 49.57 49.36

P a g e | 48

Country 2005 2010 2015 2020 2025 2030 2035 2040 2045 2050 Dominican

Republic 56.86 56.46 56.07 55.70 55.34 55.07 54.85 54.66 54.51 54.39

Ecuador 56.61 56.07 55.57 55.15 54.75 54.36 54.04 53.75 53.53 53.33

El Salvador 55.70 54.88 54.18 53.53 52.99 52.51 52.16 51.86 51.62 51.43

Guatemala 65.82 64.61 63.42 62.35 61.33 60.37 59.56 58.85 58.23 57.70

Haiti 59.14 57.42 55.83 54.60 53.57 52.74 52.12 51.60 51.16 50.80

Honduras 58.46 57.65 56.86 56.15 55.48 54.79 54.18 53.63 53.16 52.73

Jamaica 56.86 56.46 56.07 55.70 55.34 55.07 54.85 54.66 54.51 54.39

Mexico 52.84 52.20 51.63 51.15 50.72 50.30 49.97 49.68 49.44 49.24

Nicaragua 56.55 56.22 55.86 55.55 55.24 54.90 54.62 54.40 54.18 53.99

Panama 51.63 51.25 50.87 50.53 50.20 49.81 49.52 49.26 49.13 48.99

Paraguay 52.83 52.19 51.57 51.07 50.61 50.20 49.90 49.63 49.42 49.22

Peru 55.56 55.02 54.58 54.26 54.06 53.76 53.53 53.33 53.16 53.04

Trinidad and

Tobago 56.86 56.46 56.07 55.70 55.34 55.07 54.85 54.66 54.51 54.39

Uruguay 50.92 50.69 50.32 50.04 49.78 49.57 49.37 49.20 49.02 48.89

Venezuela 51.50 50.96 50.51 50.11 49.79 49.53 49.31 49.14 48.99 48.88

Transition Countries Armenia 79.89 61.44 61.37 61.32 61.32 61.35 61.34 61.35 61.26 61.28

Azerbaijan 66.35 65.51 64.85 64.31 63.84 63.49 63.22 63.01 62.82 62.68

Georgia 61.50 61.44 61.37 61.32 61.32 61.35 61.34 61.35 61.26 61.28

Kazakhstan 62.86 62.85 62.85 62.84 62.83 62.80 62.79 62.77 62.78 62.78

Kyrgyzstan 62.90 62.85 62.82 62.76 62.78 62.77 62.79 62.78 62.78 62.76

Tajikistan 52.33 52.26 52.03 51.79 51.52 51.19 50.98 50.78 50.64 50.51

Turkmenistan 61.63 61.57 61.54 61.50 61.46 61.45 61.43 61.43 61.43 61.43

Uzbekistan 70.17 70.15 70.14 70.12 70.10 70.10 70.10 70.09 70.09 70.10

United States United States 54.9 53.7 52.9 52.0 51.2 50.3 50.0 50.0 50.0 50.0

P a g e | 49

Country 2005 2010 2015 2020 2025 2030 2035 2040 2045 2050 India

India 75.13 73.48 71.88 70.36 68.97 67.74 66.73 65.84 65.05 64.38

Table A 6. Method Effectiveness Assumptions

(percentage)

Condom 81

Female sterilization 100

Injectable 100

IUD 96

Implant 100

Pill 92

Traditional 50

P a g e | 50

Table A 7. CPR Projections

Country 2005 2010 2015 2020 2025 2030 2035 2040 2045 2050

Sub-Saharan Africa

Angola 29.90 35.20 40.50 45.80 51.10 56.40 61.70 67.00 72.30 77.60

Benin 17.20 23.18 29.16 35.14 41.12 47.10 53.08 59.06 65.04 71.02

Botswana 46.60 50.72 54.84 58.96 63.08 67.20 71.32 75.44 79.56 80.00

Burkina Faso 14.00 19.76 25.52 31.28 37.04 42.80 48.56 54.32 60.08 65.84

Burundi 9.60 17.18 24.76 32.34 39.92 47.50 55.08 62.66 70.24 77.82

Cameroon 26.10 30.14 34.18 38.22 42.26 46.30 50.34 54.38 58.42 62.46

CAR 7.50 13.74 19.98 26.22 32.46 38.70 44.94 51.18 57.42 63.66

Chad 2.50 6.64 10.78 14.92 19.06 23.20 27.34 31.48 35.62 39.76

Côte d'Ivoire 13.30 20.42 27.54 34.66 41.78 48.90 56.02 63.14 70.26 77.38

Djibouti 57.10 61.07 65.03 69.00 72.97 76.93 80.00 80.00 80.00 80.00

DRC 20.10 24.98 29.86 34.74 39.62 44.50 49.38 54.26 59.14 64.02

Eritrea 10.30 17.06 23.82 30.58 37.34 44.10 50.86 57.62 64.38 71.14

Ethiopia 10.30 17.06 23.82 30.58 37.34 44.10 50.86 57.62 64.38 71.14

Gabon 44.10 47.34 50.58 53.82 57.06 60.30 63.54 66.78 70.02 73.26

Gambia 10.50 14.74 18.98 23.22 27.46 31.70 35.94 40.18 44.42 48.66

Ghana 19.30 26.36 33.42 40.48 47.54 54.60 61.66 68.72 75.78 80.00

Guinea 10.50 14.74 18.98 23.22 27.46 31.70 35.94 40.18 44.42 48.66

Guinea-Bissau 10.50 14.74 18.98 23.22 27.46 31.70 35.94 40.18 44.42 48.66

Kenya 28.40 33.30 38.20 43.10 48.00 52.90 57.80 62.70 67.60 72.50

Lesotho 29.00 35.20 41.40 47.60 53.80 60.00 66.20 72.40 78.60 80.00

Liberia 13.30 20.42 27.54 34.66 41.78 48.90 56.02 63.14 70.26 77.38

Madagascar 21.60 26.32 31.04 35.76 40.48 45.20 49.92 54.64 59.36 64.08

Malawi 25.70 31.22 36.74 42.26 47.78 53.30 58.82 64.34 69.86 75.38

Mali 7.50 13.74 19.98 26.22 32.46 38.70 44.94 51.18 57.42 63.66

Mauritania 33.30 35.30 37.30 39.30 41.30 43.30 45.30 47.30 49.30 51.30

Mauritius 21.60 26.32 31.04 35.76 40.48 45.20 49.92 54.64 59.36 64.08

Mozambique 25.60 29.28 32.96 36.64 40.32 44.00 47.68 51.36 55.04 58.72

Namibia 46.60 50.72 54.84 58.96 63.08 67.20 71.32 75.44 79.56 80.00

Niger 10.00 13.16 16.32 19.48 22.64 25.80 28.96 32.12 35.28 38.44

Nigeria 13.30 16.68 20.06 23.44 26.82 30.20 33.58 36.96 40.34 43.72

Republic of the Congo

44.10 47.34 50.58 53.82 57.06 60.30 63.54 66.78 70.02 73.26

Rwanda 9.60 17.18 24.76 32.34 39.92 47.50 55.08 62.66 70.24 77.82

Senegal 8.70 15.02 21.34 27.66 33.98 40.30 46.62 52.94 59.26 65.58

Sierra Leone 10.50 14.74 18.98 23.22 27.46 31.70 35.94 40.18 44.42 48.66

Somalia 2.50 6.64 10.78 14.92 19.06 23.20 27.34 31.48 35.62 39.76

South Africa 46.60 50.72 54.84 58.96 63.08 67.20 71.32 75.44 79.56 80.00

Sudan 59.20 61.26 63.32 65.38 67.44 69.50 71.56 73.62 75.68 77.74

Swaziland 37.90 42.70 47.50 52.30 57.10 61.90 66.70 71.50 76.30 80.00

Tanzania 22.50 26.86 31.22 35.58 39.94 44.30 48.66 53.02 57.38 61.74

Togo 10.50 14.74 18.98 23.22 27.46 31.70 35.94 40.18 44.42 48.66

Uganda 19.60 27.72 35.84 43.96 52.08 60.20 68.32 76.44 80.00 80.00

P a g e | 51

Country 2005 2010 2015 2020 2025 2030 2035 2040 2045 2050

Zambia 29.90 35.20 40.50 45.80 51.10 56.40 61.70 67.00 72.30 77.60

Zimbabwe 40.10 42.66 45.22 47.78 50.34 52.90 55.46 58.02 60.58 63.14

Asia

Afghanistan 29.60 37.90 46.20 54.50 62.80 71.10 79.40 80.00 80.00 80.00

Algeria 33.30 36.63 39.97 43.30 46.63 49.97 53.30 56.63 59.97 63.30

Bangladesh 58.50 62.20 65.90 69.60 73.30 77.00 80.00 80.00 80.00 80.00

Cambodia 24.10 32.47 40.83 49.20 57.57 65.93 74.30 80.00 80.00 80.00

Egypt 59.20 62.63 66.07 69.50 72.93 76.37 79.80 80.00 80.00 80.00

Indonesia 61.40 64.43 67.47 70.50 73.53 76.57 79.60 80.00 80.00 80.00

Iraq 57.10 61.07 65.03 69.00 72.97 76.93 80.00 80.00 80.00 80.00

Jordan 57.10 61.07 65.03 69.00 72.97 76.93 80.00 80.00 80.00 80.00

Laos 24.10 32.47 40.83 49.20 57.57 65.93 74.30 80.00 80.00 80.00

Lebanon 57.10 61.07 65.03 69.00 72.97 76.93 80.00 80.00 80.00 80.00

Libya 57.10 61.07 65.03 69.00 72.97 76.93 80.00 80.00 80.00 80.00

Malaysia 61.40 64.43 67.47 70.50 73.53 76.57 79.60 80.00 80.00 80.00

Mongolia 37.30 45.50 53.70 61.90 70.10 78.30 80.00 80.00 80.00 80.00

Morocco 33.30 36.63 39.97 43.30 46.63 49.97 53.30 56.63 59.97 63.30

Myanmar 24.10 32.47 40.83 49.20 57.57 65.93 74.30 80.00 80.00 80.00

Nepal 37.30 45.50 53.70 61.90 70.10 78.30 80.00 80.00 80.00 80.00

Pakistan 29.60 37.90 46.20 54.50 62.80 71.10 79.40 80.00 80.00 80.00

Philippines 31.60 37.37 43.13 48.90 54.67 60.43 66.20 71.97 77.73 80.00

Sri Lanka 61.40 64.43 67.47 70.50 73.53 76.57 79.60 80.00 80.00 80.00

Syria 59.20 62.63 66.07 69.50 72.93 76.37 79.80 80.00 80.00 80.00

Thailand 24.10 32.47 40.83 49.20 57.57 65.93 74.30 80.00 80.00 80.00

Tunisia 33.30 36.63 39.97 43.30 46.63 49.97 53.30 56.63 59.97 63.30

Turkey 61.40 64.43 67.47 70.50 73.53 76.57 79.60 80.00 80.00 80.00

Vietnam 24.10 32.47 40.83 49.20 57.57 65.93 74.30 80.00 80.00 80.00

Yemen 28.00 39.27 50.53 61.80 73.07 80.00 80.00 80.00 80.00 80.00

Latin America and Caribbean

Argentina 56.40 59.30 62.20 65.10 68.00 70.90 73.80 76.70 79.60 80.00

Bolivia 39.30 50.65 62.00 73.35 80.00 80.00 80.00 80.00 80.00 80.00

Brazil 56.40 59.30 62.20 65.10 68.00 70.90 73.80 76.70 79.60 80.00

Chile 56.40 59.30 62.20 65.10 68.00 70.90 73.80 76.70 79.60 80.00

Colombia 56.40 59.30 62.20 65.10 68.00 70.90 73.80 76.70 79.60 80.00

Costa Rica 56.40 59.30 62.20 65.10 68.00 70.90 73.80 76.70 79.60 80.00

Dominican Republic

54.00 59.70 65.40 71.10 76.80 80.00 80.00 80.00 80.00 80.00

Ecuador 39.30 50.65 62.00 73.35 80.00 80.00 80.00 80.00 80.00 80.00

El Salvador 43.20 51.65 60.10 68.55 77.00 80.00 80.00 80.00 80.00 80.00

Guatemala 39.30 50.65 62.00 73.35 80.00 80.00 80.00 80.00 80.00 80.00

Haiti 22.90 41.65 60.40 79.15 80.00 80.00 80.00 80.00 80.00 80.00

Honduras 43.20 51.65 60.10 68.55 77.00 80.00 80.00 80.00 80.00 80.00

Jamaica 54.00 59.70 65.40 71.10 76.80 80.00 80.00 80.00 80.00 80.00

Mexico 56.40 59.30 62.20 65.10 68.00 70.90 73.80 76.70 79.60 80.00

Nicaragua 43.20 51.65 60.10 68.55 77.00 80.00 80.00 80.00 80.00 80.00

Panama 56.40 59.30 62.20 65.10 68.00 70.90 73.80 76.70 79.60 80.00

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Country 2005 2010 2015 2020 2025 2030 2035 2040 2045 2050

Paraguay 56.40 59.30 62.20 65.10 68.00 70.90 73.80 76.70 79.60 80.00

Peru 39.30 50.65 62.00 73.35 80.00 80.00 80.00 80.00 80.00 80.00

Trinidad and Tobago

54.00 59.70 65.40 71.10 76.80 80.00 80.00 80.00 80.00 80.00

Uruguay 56.40 59.30 62.20 65.10 68.00 70.90 73.80 76.70 79.60 80.00

Venezuela 56.40 59.30 62.20 65.10 68.00 70.90 73.80 76.70 79.60 80.00

Transition Countries

Armenia 33.10 39.75 46.40 53.05 59.70 66.35 73.00 79.65 80.00 80.00

Azerbaijan 32.00 43.35 54.70 66.05 77.40 80.00 80.00 80.00 80.00 80.00

Georgia 33.10 39.75 46.40 53.05 59.70 66.35 73.00 79.65 80.00 80.00

Kazakhstan 37.30 49.60 61.90 74.20 80.00 80.00 80.00 80.00 80.00 80.00

Kyrgyzstan 37.30 49.60 61.90 74.20 80.00 80.00 80.00 80.00 80.00 80.00

Tajikistan 37.30 49.60 61.90 74.20 80.00 80.00 80.00 80.00 80.00 80.00

Turkmenistan 37.30 49.60 61.90 74.20 80.00 80.00 80.00 80.00 80.00 80.00

Uzbekistan 37.30 49.60 61.90 74.20 80.00 80.00 80.00 80.00 80.00 80.00

India

India 43.80 46.36 48.92 51.48 54.04 56.60 59.16 61.72 64.28 66.84

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Table A 8. Global Demographic Results

Global

CPR TFR Population

UN Low

UN Medium

UN High

Unmet Need

UN Low

UN Medium

UN High

Unmet Need UN Low UN Medium UN High Unmet Need

2005 45.11 45.12 45.12 45.30 3.17 3.17 3.17 3.16 4,045,802,699 4,045,801,824 4,045,802,699 4,042,073,272

2010 50.83 48.27 45.80 48.47 2.82 2.94 3.07 2.93 4,386,133,471 4,393,753,601 4,401,544,380 4,391,058,107

2015 57.67 51.17 44.74 51.79 2.43 2.74 3.07 2.71 4,693,219,045 4,746,336,505 4,800,261,064 4,741,115,041

2020 62.86 53.95 45.02 55.32 2.12 2.57 3.02 2.51 4,960,755,372 5,090,366,340 5,221,180,520 5,076,519,056

2025 66.03 56.08 46.12 58.57 1.92 2.42 2.92 2.31 5,189,371,477 5,416,123,592 5,644,495,236 5,383,840,991

2030 67.85 57.85 47.84 61.67 1.80 2.30 2.80 2.12 5,387,414,092 5,718,865,270 6,053,927,444 5,656,247,679

2035 68.99 58.98 48.95 64.62 1.72 2.21 2.71 1.95 5,550,523,375 5,998,838,193 6,458,365,541 5,887,954,446

2040 69.68 59.67 49.71 66.82 1.65 2.15 2.65 1.82 5,673,328,489 6,256,889,997 6,869,420,366 6,078,142,609

2045 70.21 60.20 50.21 68.68 1.60 2.10 2.59 1.71 5,750,584,954 6,488,778,147 7,285,698,812 6,224,023,814

2050 70.97 60.92 50.88 70.25 1.55 2.04 2.54 1.62 5,774,839,147 6,682,107,130 7,688,821,476 6,316,336,472

Table A 9. Developing World Demographic Results

Developing World

CPR TFR Population

UN Low

UN Medium

UN High

Unmet Need

UN Low

UN Medium

UN High


2005 43.86 43.86 43.86 43.87 3.25 3.25 3.25 3.25 3,743,656,800 3,743,656,800 3,743,656,800 3,743,656,800

2010 49.94 47.38 44.91 47.22 2.89 3.00 3.13 3.01 4,069,639,915 4,076,779,441 4,084,090,316 4,078,623,440

2015 56.97 50.49 44.07 50.69 2.48 2.79 3.12 2.78 4,364,219,110 4,414,026,013 4,464,640,639 4,415,870,864

2020 62.31 53.42 44.53 54.36 2.16 2.61 3.06 2.57 4,621,583,489 4,743,240,087 4,866,102,243 4,740,286,455

2025 65.59 55.68 45.76 57.72 1.96 2.46 2.96 2.36 4,842,561,257 5,055,569,468 5,270,199,420 5,039,215,289

2030 67.54 57.59 47.63 60.90 1.83 2.33 2.82 2.18 5,034,848,651 5,346,554,934 5,661,859,807 5,306,449,418

2035 68.77 58.80 48.82 63.91 1.74 2.23 2.73 2.00 5,193,917,203 5,616,225,539 6,049,608,921 5,536,441,832

2040 69.50 59.54 49.63 66.13 1.67 2.17 2.66 1.86 5,314,356,977 5,864,963,541 6,443,875,782 5,727,993,027

2045 70.06 60.09 50.16 68.10 1.62 2.11 2.61 1.74 5,390,963,795 6,088,144,675 6,842,137,428 5,877,299,745

2050 70.86 60.86 50.87 69.77 1.56 2.05 2.55 1.65 5,415,823,938 6,272,866,237 7,225,394,451 5,973,794,098

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Table A 10. Africa Demographic Results

Africa

CPR TFR Population

UN Low

UN Medium

UN High

Unmet Need

UN Low

UN Medium

UN High


2005 21.17 21.17 21.17 21.19 5.25 5.25 5.25 5.25 760,677,912 760,677,912 760,677,912 760,677,912

2010 28.15 25.58 23.48 25.37 4.74 4.79 4.91 4.79 867,528,372 868,930,581 870,511,427 868,650,050

2015 37.14 31.22 25.79 29.85 4.09 4.36 4.68 4.42 974,928,980 984,877,926 995,265,717 985,452,696

2020 44.93 37.43 29.91 34.77 3.52 3.97 4.42 4.10 1,079,925,941 1,105,129,984 1,131,047,292 1,109,215,892

2025 50.65 42.43 34.20 39.34 3.07 3.57 4.07 3.72 1,181,444,963 1,227,625,355 1,274,849,504 1,237,766,384

2030 55.14 46.93 38.72 43.89 2.73 3.23 3.73 3.39 1,280,805,098 1,351,614,129 1,424,071,305 1,369,177,056

2035 58.63 50.42 42.23 48.39 2.45 2.95 3.45 3.05 1,376,203,733 1,476,599,712 1,580,152,980 1,500,747,234

2040 61.24 53.04 45.19 53.26 2.23 2.72 3.24 2.69 1,464,421,664 1,600,938,442 1,744,037,852 1,627,859,934

2045 63.40 55.18 47.28 57.47 2.04 2.54 3.05 2.39 1,542,273,679 1,721,830,770 1,913,959,827 1,745,468,667

2050 65.82 57.50 49.54 61.26 1.87 2.36 2.87 2.14 1,605,534,302 1,833,731,862 2,083,145,212 1,849,163,072

Table A 11. Asia and Near East Demographic Results

ANE

CPR TFR Population

UN Low

UN Medium

UN High

Unmet Need

UN Low

UN Medium

UN High


2005 51.57 51.58 51.58 51.58 2.86 2.86 2.86 2.86 1,239,858,192 1,239,858,192 1,239,858,192 1,239,858,192

2010 57.39 54.90 52.40 55.67 2.53 2.66 2.78 2.63 1,337,467,814 1,339,868,255 1,342,304,788 1,339,452,800

2015 64.11 57.57 50.95 59.89 2.17 2.49 2.82 2.39 1,423,625,542 1,440,584,951 1,457,609,984 1,436,349,698

2020 68.91 59.70 50.49 64.31 1.91 2.36 2.81 2.15 1,496,354,793 1,537,368,964 1,578,575,718 1,523,841,500

2025 71.50 61.16 50.81 68.61 1.77 2.27 2.77 1.93 1,556,558,962 1,627,489,813 1,698,643,804 1,596,998,154

2030 72.82 62.37 51.92 72.99 1.69 2.19 2.69 1.71 1,607,228,384 1,709,668,297 1,812,780,521 1,653,212,262

2035 73.99 63.47 52.93 77.05 1.62 2.12 2.62 1.50 1,646,941,799 1,784,150,525 1,924,142,581 1,691,165,806

2040 74.93 64.32 53.70 78.16 1.57 2.06 2.56 1.47 1,673,339,940 1,850,820,654 2,036,430,842 1,715,987,297

2045 75.69 65.01 54.30 78.77 1.52 2.02 2.51 1.45 1,684,855,980 1,908,375,342 2,149,234,569 1,730,778,890

2050 76.50 65.73 54.93 79.10 1.48 1.97 2.47 1.46 1,679,536,100 1,953,114,852 2,256,604,445 1,731,654,766

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Table A 12. India Demographic Results

India

CPR TFR Population

UN Low

UN Medium

UN High

Unmet Need

UN Low

UN Medium

UN High


2005 43.80 43.80 43.80 43.80 2.94 2.94 2.94 2.94 1,134,403,200 1,134,403,200 1,134,403,200 1,134,403,200

2010 50.97 48.54 45.91 46.36 2.52 2.64 2.77 2.75 1,219,982,126 1,222,144,602 1,224,221,242 1,225,632,455

2015 58.70 52.09 45.26 48.92 2.09 2.41 2.74 2.56 1,292,703,328 1,307,424,774 1,322,356,425 1,317,698,389

2020 64.71 55.21 45.71 51.48 1.76 2.21 2.66 2.39 1,351,213,731 1,387,113,698 1,423,220,361 1,406,266,280

2025 68.67 57.90 47.14 54.04 1.54 2.04 2.54 2.22 1,395,491,449 1,457,960,343 1,520,659,460 1,487,082,948

2030 70.88 59.92 48.97 56.60 1.41 1.91 2.41 2.06 1,427,676,134 1,518,224,161 1,609,504,754 1,557,705,778

2035 71.49 60.37 49.26 59.16 1.36 1.86 2.36 1.91 1,447,377,549 1,568,559,246 1,692,858,152 1,616,812,147

2040 71.27 60.01 48.75 61.72 1.35 1.85 2.35 1.77 1,455,553,305 1,611,265,896 1,775,543,928 1,663,250,496

2045 70.87 59.48 48.09 64.28 1.35 1.85 2.35 1.64 1,451,701,438 1,645,722,906 1,856,973,562 1,695,352,022

2050 70.51 59.01 47.50 66.84 1.35 1.85 2.35 1.51 1,434,215,566 1,668,884,106 1,932,108,647 1,710,057,910

Table A 13. Latin America Demographic Results

LAC

CPR TFR Population

UN Low UN

Medium UN High Unmet Need

UN Low

UN Medium UN High


2005 53.46 53.46 53.46 53.46 2.40 2.40 2.40 2.40 534,405,396 534,405,396 534,405,396 534,405,396

2010 59.03 56.48 53.90 57.75 2.07 2.20 2.32 2.14 566,592,711 567,618,891 568,686,941 566,994,409

2015 65.00 58.37 51.69 62.15 1.72 2.05 2.37 1.87 591,435,588 598,583,709 605,809,833 594,943,777

2020 68.87 59.65 50.44 66.66 1.49 1.94 2.39 1.61 610,081,405 627,184,740 644,378,585 616,886,242

2025 70.55 60.31 50.06 70.34 1.37 1.87 2.37 1.39 623,583,144 652,958,462 682,454,621 631,776,634

2030 70.83 60.54 50.26 72.86 1.34 1.84 2.34 1.24 632,950,280 675,199,344 717,967,081 640,012,780

2035 70.83 60.53 50.22 75.14 1.32 1.82 2.32 1.12 637,163,578 693,269,053 751,237,113 641,169,573

2040 70.59 60.27 49.94 77.40 1.32 1.82 2.32 1.00 635,441,780 706,871,547 782,859,542 634,719,841

2045 70.21 59.86 49.51 79.68 1.33 1.83 2.33 0.88 627,904,832 716,210,339 813,193,646 620,529,799

2050 70.02 59.64 49.24 80.00 1.33 1.83 2.33 0.86 614,474,575 720,876,979 841,412,738 599,456,642

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Table A 14. Transition Countries Demographic Results

Transition

CPR TFR Population

UN Low

UN Medium

UN High

Unmet Need UN Low

UN Medium

UN High


2005 52.14 52.14 52.14 52.14 2.37 2.37 2.37 2.37 74,312,100 74,312,100 74,312,100 74,312,100

2010 56.92 54.47 51.80 57.87 2.17 2.30 2.42 2.14 78,068,892 78,217,112 78,365,918 77,893,726

2015 63.74 57.75 51.92 63.44 1.87 2.20 2.52 1.91 81,525,672 82,554,653 83,598,680 81,426,304

2020 69.13 61.18 53.12 68.93 1.64 2.09 2.54 1.68 84,007,619 86,442,701 88,880,287 84,076,541

2025 72.95 64.22 55.31 73.69 1.50 2.00 2.50 1.49 85,482,739 89,535,495 93,592,031 85,591,169

2030 75.77 66.99 58.00 75.79 1.43 1.93 2.43 1.46 86,188,755 91,849,003 97,536,146 86,341,542

2035 78.19 69.35 60.27 77.60 1.38 1.88 2.38 1.45 86,230,544 93,647,003 101,218,095 86,547,072

2040 80.36 71.46 62.30 79.03 1.36 1.86 2.36 1.46 85,600,288 95,067,002 105,003,618 86,175,459

2045 82.27 73.32 64.07 79.72 1.35 1.85 2.35 1.50 84,227,866 96,005,318 108,775,824 85,170,367

2050 84.16 75.14 65.77 80.00 1.35 1.85 2.35 1.56 82,063,395 96,258,438 112,123,409 83,461,708

Table A 15. United States Demographic Results

United States

CPR TFR Population

UN Low

UN Medium

UN High

Unmet Need UN Low

UN Medium

UN High


2005 61.03 61.09 61.09 63.49 2.06 2.06 2.06 1.94 302,145,899 302,145,024 302,145,899 298,416,472

2010 63.10 60.63 58.11 65.80 1.93 2.06 2.18 1.80 316,493,556 316,974,160 317,454,064 312,434,667

2015 68.01 61.40 54.72 68.11 1.66 1.99 2.31 1.66 328,999,935 332,310,492 335,620,425 325,244,177

2020 71.52 62.19 52.78 70.42 1.47 1.92 2.37 1.52 339,171,883 347,126,253 355,078,277 336,232,601

2025 73.13 62.58 51.96 72.74 1.36 1.86 2.37 1.38 346,810,220 360,554,124 374,295,816 344,625,702

2030 72.96 62.23 51.42 75.05 1.35 1.85 2.35 1.25 352,565,441 372,310,336 392,067,637 349,798,261

2035 72.78 61.99 51.12 77.36 1.35 1.85 2.35 1.14 356,606,172 382,612,654 408,756,620 351,512,614

2040 72.78 61.99 51.12 79.67 1.35 1.85 2.35 1.03 358,971,512 391,926,456 425,544,584 350,149,582

2045 72.78 61.99 51.12 80.00 1.35 1.85 2.35 1.02 359,621,159 400,633,472 443,561,384 346,724,069

2050 72.78 61.99 51.12 80.00 1.35 1.85 2.35 1.02 359,015,209 409,240,893 463,427,025 342,542,374

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Table A 16. Cumulative Family Planning Costs (Millions US Dollars Not Discounted)

Developing Countries Global

UN Low UN Medium UN High Unmet Need UN Low UN Medium UN High Unmet Need

2005 6,627 6,627 6,627 6,627 15,520 15,396 16,048 16,037

2010 44,929 44,179 43,426 44,020 97,921 96,829 98,229 101,315

2015 95,217 89,745 84,219 89,614 195,871 186,691 181,871 196,184

2020 157,051 143,282 129,438 143,661 308,136 285,298 268,985 301,216

2025 229,474 204,756 179,934 206,651 433,626 392,725 361,610 416,773

2030 309,891 273,919 237,590 278,651 567,523 507,976 462,245 542,450

2035 395,910 349,736 302,436 359,164 706,060 630,375 571,654 677,697

2040 484,785 430,488 373,708 446,821 846,670 758,321 689,496 820,573

2045 574,788 515,023 450,611 540,157 987,055 890,481 814,847 967,420

2050 665,033 602,946 533,182 637,890 1,126,321 1,026,634 948,002 1,116,381

Africa ANE


2005 590 590 590 589 2,591 2,592 2,592 2,592

2010 4,763 4,613 4,465 4,601 17,096 16,855 16,609 16,930

2015 12,915 11,698 10,480 11,451 34,746 33,021 31,288 33,557

2020 25,556 22,288 19,016 21,341 55,125 50,897 46,645 52,511

2025 43,284 37,069 30,842 34,972 77,645 70,208 62,743 73,802

2030 66,098 56,547 46,933 53,035 101,377 90,763 80,041 97,381

2035 93,666 80,743 67,589 75,977 125,641 112,286 98,584 122,879

2040 125,195 109,227 92,833 104,249 149,828 134,441 118,244 149,149

2045 160,090 141,671 122,439 138,028 173,559 156,977 138,876 175,159

2050 197,948 177,940 156,479 177,077 196,709 179,857 160,531 200,514

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Table A 16 (Continued)

India LAC


2005 1,825 1,825 1,825 1,825 1,483 1,483 1,483 1,483

2010 12,412 12,204 12,002 11,862 9,769 9,632 9,490 9,718

2015 25,944 24,473 22,974 23,442 19,834 18,856 17,866 19,366

2020 42,201 38,519 34,808 36,558 31,381 28,981 26,568 30,451

2025 60,718 54,167 47,575 51,170 43,928 39,737 35,529 42,793

2030 80,576 71,132 61,578 67,231 56,758 50,843 44,867 55,903

2035 100,903 88,894 76,565 84,632 69,404 62,063 54,523 69,369

2040 120,772 106,755 92,007 103,168 81,509 73,184 64,395 82,775

2045 139,649 124,304 107,593 122,561 92,885 84,070 74,391 95,831

2050 157,266 141,362 123,231 142,584 103,436 94,666 84,504 108,103

Transition United States


2005 138 138 138 138 8,893 8,769 9,420 9,411

2010 888 875 860 908 52,992 52,650 54,804 57,295

2015 1,778 1,697 1,611 1,798 100,654 96,946 97,652 106,570

2020 2,787 2,597 2,401 2,800 151,085 142,016 139,547 157,555

2025 3,900 3,576 3,245 3,915 204,152 187,968 181,676 210,121

2030 5,083 4,634 4,170 5,100 257,631 234,056 224,654 263,800

2035 6,296 5,750 5,174 6,307 310,150 280,639 269,218 318,534

2040 7,481 6,882 6,229 7,481 361,885 327,833 315,788 373,752

2045 8,604 8,002 7,312 8,579 412,267 375,458 364,236 427,263 2050 9,674 9,121 8,438 9,612 461,288 423,688 414,819 478,491

P a g e | 59

Table A 17. Present Value of Cumulative Family Planning Costs (Millions US Dollars Discounted at 4%)



2005 6,627 6,627 6,627 6,627 15,520 15,396 16,048 16,037

2010 41,455 39,952 39,320 39,810 89,613 87,782 89,199 91,837

2015 80,842 73,211 69,131 73,085 163,839 153,452 150,382 161,155

2020 122,542 105,337 96,285 105,511 235,846 212,677 202,738 224,231

2025 164,625 135,670 121,202 136,583 304,146 265,725 248,474 281,280

2030 204,875 163,727 144,583 165,782 366,130 312,512 289,316 332,287

2035 242,004 189,020 166,207 192,632 420,804 353,358 325,812 377,411

2040 275,174 211,170 185,746 216,668 468,181 388,462 358,127 416,606

2045 304,286 230,232 203,079 237,709 508,665 418,267 386,384 449,729

2050 329,614 246,528 218,375 255,824 543,088 443,506 411,055 477,351

Africa ANE


2005 590 590 590 589 2,591 2,592 2,592 2,592

2010 4,262 4,136 4,012 4,126 15,465 15,263 15,056 15,326

2015 10,182 9,287 8,391 9,109 28,348 27,073 25,791 27,468

2020 17,739 15,619 13,497 15,025 40,583 37,811 35,023 38,846

2025 26,465 22,893 19,315 21,733 51,703 47,348 42,974 49,354

2030 35,703 30,777 25,825 29,042 61,342 55,693 49,995 58,922

2035 44,888 38,835 32,701 36,679 69,445 62,878 56,182 67,429

2040 53,528 46,637 39,611 44,416 76,086 68,957 61,575 74,641

2045 61,390 53,944 46,276 52,018 81,442 74,041 66,226 80,511

2050 68,403 60,659 52,576 59,245 85,738 78,284 70,239 85,216

P a g e | 60

Table A17 (Continued)

India LAC


2005 1,825 1,825 1,825 1,825 1,483 1,483 1,483 1,483

2010 11,214 11,038 10,869 10,740 9,710 8,722 8,603 8,796

2015 21,083 19,996 18,890 19,197 19,775 15,461 14,729 15,840

2020 30,838 28,429 26,000 27,072 31,322 21,545 19,961 22,494

2025 39,979 36,153 32,303 34,284 43,869 26,858 24,389 28,588

2030 48,042 43,040 37,985 40,802 56,699 31,370 28,181 33,912

2035 54,832 48,970 42,988 46,607 69,345 35,117 31,405 38,408

2040 60,290 53,874 47,226 51,691 81,450 38,171 34,114 42,089

2045 64,553 57,836 50,742 56,064 92,826 40,628 36,369 45,037

2050 67,824 61,001 53,642 59,776 103,377 42,594 38,244 47,316



2005 138 138 138 138 8,893 8,769 9,420 9,411

2010 804 793 780 822 48,158 47,830 49,879 52,027

2015 1,454 1,393 1,329 1,472 82,996 80,241 81,251 88,070

2020 2,060 1,934 1,804 2,074 113,304 107,340 106,453 118,721

2025 2,609 2,418 2,221 2,624 139,520 130,055 127,273 144,698

2030 3,090 2,847 2,596 3,105 161,254 148,785 144,733 166,505

2035 3,495 3,219 2,931 3,508 178,800 164,338 159,605 184,779

2040 3,820 3,530 3,221 3,831 193,007 177,292 172,381 199,938

2045 4,074 3,783 3,465 4,079 204,380 188,035 183,306 212,020

2050 4,272 3,991 3,674 4,270 213,474 196,978 192,680 221,527

P a g e | 61

Table A 18. Annual Family Planning Costs (Millions US Dollars)



2005 6,627 6,627 6,627 6,627 15,520 15,396 16,048 16,037

2010 8,625 8,201 7,767 8,180 17,544 17,019 16,568 17,862

2015 10,960 9,722 8,468 9,765 20,750 18,621 16,925 19,746

2020 13,252 11,343 9,431 11,520 23,564 20,450 17,787 21,857

2025 15,177 12,903 10,617 13,320 25,941 22,129 19,126 23,941

2030 16,618 14,412 12,122 15,120 27,267 23,608 20,769 25,916

2035 17,484 15,582 13,472 16,726 27,954 24,964 22,556 27,747

2040 17,895 16,469 14,713 18,019 28,141 25,941 24,174 29,024

2045 18,039 17,178 15,814 19,070 28,002 26,744 25,663 29,602

2050 18,025 17,841 16,986 19,820 27,729 27,542 27,288 29,869

Average 14,779 13,399 11,848 14,175 25,029 22,814 21,067 24,808

Africa ANE


2005 590 590 590 589 2,591 2,592 2,592 2,592

2010 1,178 1,086 996 1,075 3,147 3,010 2,873 3,052

2015 1,952 1,662 1,373 1,586 3,755 3,372 2,984 3,508

2020 2,924 2,436 1,947 2,259 4,264 3,694 3,124 3,979

2025 3,940 3,307 2,672 3,059 4,622 3,964 3,302 4,445

2030 4,962 4,280 3,580 3,996 4,807 4,195 3,558 4,887

2035 5,843 5,184 4,478 4,988 4,862 4,363 3,800 5,220

2040 6,585 6,016 5,398 6,094 4,805 4,463 4,009 5,248

2045 7,229 6,797 6,267 7,190 4,700 4,531 4,200 5,162

2050 7,784 7,551 7,172 8,212 4,576 4,602 4,418 4,995

Average 4,399 3,954 3,477 3,935 4,371 3,997 3,567 4,456

P a g e | 62

Table A18 (Continued)

India LAC


2005 1,825 1,825 1,825 1,825 1,483 1,483 1,483 1,483

2010 2,342 2,231 2,110 2,131 1,797 1,720 1,641 1,758

2015 2,927 2,598 2,257 2,440 2,139 1,921 1,701 2,045

2020 3,449 2,943 2,437 2,745 2,404 2,083 1,761 2,327

2025 3,836 3,243 2,647 3,040 2,551 2,187 1,821 2,546

2030 4,038 3,476 2,892 3,324 2,571 2,243 1,901 2,672

2035 4,045 3,570 3,039 3,579 2,493 2,239 1,949 2,699

2040 3,906 3,556 3,106 3,785 2,366 2,208 1,986 2,662

2045 3,680 3,473 3,121 3,934 2,212 2,155 2,007 2,570

2050 3,415 3,369 3,133 4,046 2,039 2,093 2,033 2,364

Average 3,495 3,141 2,738 3,169 2,299 2,104 1,878 2,402



2005 138 138 138 138 8,893 8,769 9,420 9,411

2010 162 155 147 165 8,919 8,818 8,801 9,682

2015 187 170 153 186 9,790 8,898 8,457 9,980

2020 211 186 162 210 10,312 9,107 8,356 10,337

2025 229 202 175 230 10,764 9,226 8,509 10,621

2030 241 217 192 240 10,649 9,196 8,647 10,796

2035 242 226 206 241 10,470 9,382 9,084 11,021

2040 232 226 213 229 10,246 9,471 9,461 11,005

2045 220 223 219 214 9,962 9,566 9,849 10,532

2050 211 225 230 202 9,704 9,701 10,302 10,049

Average 215 203 188 214 10,251 9,415 9,218 10,633

World Population Prospects and Unmet Need for Family Planning

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