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World Prospects and Unmet Need for 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 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: ...... 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. ...... 26 IX. 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 , 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 Family Planning Cost ...... 24 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 Family Planning Cost ...... 33 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 Survey LAC Latin America and the Caribbean TFR UN United UNAIDS Joint 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 would be fewer, women’s health and would be improved, and the consequent impact on fertility would result in lower 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 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. Prospects: The 2008 Revision. Department of Economic and Social Affairs/Population Division, New York.

P a g e | 1 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 | 3 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 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 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.

P a g e | 4 and we did not project for developed countries, except for the United States. , although the largest , 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.

P a g e | 5 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

12

10

8

6

4 Unmet Need(%)

2

0 0 10 20 30 40 50 60 70 80 CPR

Second, as Westoff15points out, some adjustment may be required in the use of levels of unmet need to predict fertility. He reduces the 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.

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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 . 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 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 and union patterns would be influenced by levels of 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 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 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 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 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.

P a g e | 9 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 , for example, is only applied to new users.

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

Intrauterine device $758 $707 Male $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.

P a g e | 10 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 , 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.

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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

Years to Target Historic Meet Unmet Number of Increase Annual Need at Years to Required over Base Unmet Change in Historic Meet Unmet Annual Historic CPR Need CPR Trend Need Change 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.

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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 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 | 13 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 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 , 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).

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

2a: Global: Contraceptive Prevalence Rate UN Low UN Medium UN High Unmet Need 80

70

60

50

40

30

20

10

0 2005 2010 2015 2020 2025 2030 2035 2040 2045 2050

2b: Global: Total Fertility Rate

UN Low UN Medium UN High Unmet Need 3.5

3.0

2.5

2.0

1.5

1.0

0.5

0.0 2005 2010 2015 2020 2025 2030 2035 2040 2045 2050

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2c: Global: Population (billions) UN Low UN Medium UN High Unmet Need 9 8 7 6 5 4 3 2 1 0 2005 2010 2015 2020 2025 2030 2035 2040 2045 2050

2d: Global Cumulative Family Planning Costs 2005-2050 (Billions USD) 1,200 1,126 1,116 1,027 1,000 948

800

600

400

200

0 UN Low UN Medium UN High Unmet Need

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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.

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

3a: Developing Countries: Contraceptive Prevalence Rate UN Low UN Medium UN High Unmet Need 80 70 60 50 40 30 20 10 0 2005 2010 2015 2020 2025 2030 2035 2040 2045 2050

3b: Developing Countries: Total Fertility Rate UN Low UN Medium UN High Unmet Need 3.5

3.0

2.5

2.0

1.5

1.0

0.5

0.0 2005 2010 2015 2020 2025 2030 2035 2040 2045 2050

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3c: Developing Countries: Population (billions)

UN Low UN Medium UN High Unmet Need 8.0

7.0

6.0

5.0

4.0

3.0

2.0

1.0

0.0 2005 2010 2015 2020 2025 2030 2035 2040 2045 2050

3d: Developing Countries Cumulative Family Planning Costs 2005-2050 (Billions USD) 700 665 638 603 600 533 500

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0 UN Low UN Medium UN High Unmet Need

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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.

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

4a: Africa: Contraceptive Prevalence Rate

UN Low UN Medium UN High Unmet Need 70

60

50

40

30

20

10

0 2005 2010 2015 2020 2025 2030 2035 2040 2045 2050

4b: Africa: Total Fertility Rate UN Low UN Medium UN High Unmet Need 6

5

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3

2

1

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4c: Africa: Population (billions)

UN Low UN Medium UN High Unmet Need 2.5

2.0

1.5

1.0

0.5

0.0 2005 2010 2015 2020 2025 2030 2035 2040 2045 2050

4d: Africa Cumulative Family Planning Costs, 2005-2050 (Billions USD) 250

198 200 178 177 156 150

100

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0 UN Low UN Medium UN High Unmet Need

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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.

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

5a: ANE: Contraceptive Prevalence Rate UN Low UN Medium UN High Unmet Need 90 80 70 60 50 40 30 20 10 0 2005 2010 2015 2020 2025 2030 2035 2040 2045 2050 5b: ANE: Total Fertility Rate UN Low UN Medium UN High Unmet Need 3.5

3.0

2.5

2.0

1.5

1.0

0.5

0.0 2005 2010 2015 2020 2025 2030 2035 2040 2045 2050

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5c: ANE: Population (billions) UN Low UN Medium UN High Unmet Need 2.5

2.0

1.5

1.0

0.5

0.0 2005 2010 2015 2020 2025 2030 2035 2040 2045 2050

5d: ANE Cumulative Family Planning Costs 2005-2050 (Billions USD) 250

197 201 200 180 161 150

100

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0 UN Low UN Medium UN High Unmet Need

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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).

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

6a: India: Contraceptive Prevalence Rate UN Low UN Medium UN High Unmet Need 80

70

60

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20

10

0 2005 2010 2015 2020 2025 2030 2035 2040 2045 2050

6b: India: Total Fertility Rate UN Low UN Medium UN High Unmet Need 3.5

3.0

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1.0

0.5

0.0 2005 2010 2015 2020 2025 2030 2035 2040 2045 2050

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6c: India: Population (billions)

UN Low UN Medium UN High Unmet Need 2.5

2.0

1.5

1.0

0.5

0.0 2005 2010 2015 2020 2025 2030 2035 2040 2045 2050

6d: India Cumulative Family Planning Costs 2005-2050 (Billions USD) 180

157 160 141 143 140 123 120

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0 UN Low UN Medium UN High Unmet Need

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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).

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

7a: LAC: Contraceptive Prevalence Rate UN Medium UN High Unmet Need UN Low 90

80

70

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20

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0 2005 2010 2015 2020 2025 2030 2035 2040 2045 2050

7b: LAC: Total Fertility Rate UN Low UN Medium 3.0

2.5

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7c: LAC: Population (millions) UN Low UN Medium UN High Unmet Need 900

800

700

600

500

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0 2005 2010 2015 2020 2025 2030 2035 2040 2045 2050

7d: LAC Cumulative Family Planning Costs, 2005-2050 (Billions USD) 120 108 103 100 95 85 80

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0 UN Low UN Medium UN High Unmet Need

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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).

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

8a: Transition: Contraceptive Prevalence Rate UN Low UN Medium UN High Unmet Need 90 80 70 60 50 40 30 20 10 0 2005 2010 2015 2020 2025 2030 2035 2040 2045 2050 8b: Transition: Total Fertility Rate

UN Low UN Medium UN High Unmet Need 3.0

2.5

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8c: Transition: Population (millions) UN Low UN Medium 120

100

80

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0 2005 2010 2015 2020 2025 2030 2035 2040 2045 2050

8d: Transition Cumulative Family Planning Costs 2005- 2050 (Billions USD) 12

9.7 9.6 10 9.1 8.4 8

6

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0 UN Low UN Medium UN High Unmet Need

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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.

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

9a: USA: Contraceptive Prevalence Rate

UN Low UN Medium UN High Unmet Need 90

80

70

60

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0 2005 2010 2015 2020 2025 2030 2035 2040 2045 2050

9b: USA: Total Fertility Rate UN Low UN Medium UN High Unmet Need 2.5

2.0

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1.0

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0.0 2005 2010 2015 2020 2025 2030 2035 2040 2045 2050

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9c: USA: Population (millions)

UN Low UN Medium UN High Unmet Need 500 450 400 350 300 250 200 150 100 50 0 2005 2010 2015 2020 2025 2030 2035 2040 2045 2050

9d: USA Cumulative Family Planning Costs 2005-2050 (Billions USD) 478 500 461 450 424 415 400

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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

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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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Figure 10. Global Population in 2050 under Four Scenarios

Global: Population in 2050 Under Four Scenarios

9

8 7.69 Billions 7 6.68 6.32 6 5.77

5

4

3

2

1

0 UN Low UN Medium UN High Unmet Need

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

Developing Countries: Population in 2050 Under Four Scenarios

8 7.23 7 Billions 6.27 5.97 6 5.42

5

4

3

2

1

0 UN Low UN Medium UN High Unmet Need

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Appendix Table A 1: List of Countries Included in the Analysis

United States India Transition Latin America/ Sub-Saharan Africa Asia Caribbean 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 Jamaica Mongolia Mexico Gabon Morocco Nicaragua Gambia Myanmar Panama Ghana Nepal Paraguay Guinea Guinea-Bissau Trinidad & Tobago Kenya Sri Lanka Uruguay Lesotho Syria Venezuela Liberia Thailand Madagascar Turkey Mali Vietnam Mauritania Yemen Mauritius Mozambique Namibia Niger Republic of the Congo Rwanda Sierra Leone Somalia South Africa Sudan Swaziland Tanzania Togo Uganda Zambia Zimbabwe

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Table A 2. CPR and Unmet Need

Unmet India CPR Unmet Need LAC CPR 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 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

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Table A2. CPR and Unmet Need (Continued)

Unmet Africa CPR Unmet need Asia CPR 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

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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

Standard Coefficients 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

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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

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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

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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

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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

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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 100 Injectable 100 IUD 96 Implant 100 Pill 92 Traditional 50

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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 44.10 47.34 50.58 53.82 57.06 60.30 63.54 66.78 70.02 73.26 the Congo 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

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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 54.00 59.70 65.40 71.10 76.80 80.00 80.00 80.00 80.00 80.00 Republic 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 54.00 59.70 65.40 71.10 76.80 80.00 80.00 80.00 80.00 80.00 Tobago 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 UN UN Unmet UN UN UN Unmet Low Medium High Need Low Medium High 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 UN UN Unmet UN UN UN Unmet Low Medium High Need Low Medium High Need UN Low UN Medium UN High Unmet Need 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 UN UN Unmet UN UN UN Unmet Low Medium High Need Low Medium High Need UN Low UN Medium UN High Unmet Need 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 UN UN Unmet UN UN UN Unmet Low Medium High Need Low Medium High Need UN Low UN Medium UN High Unmet Need 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 UN UN Unmet UN UN UN Unmet Low Medium High Need Low Medium High Need UN Low UN Medium UN High Unmet Need 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 Unmet UN UN Unmet UN Low Medium UN High Need Low Medium UN High Need UN Low UN Medium UN High Unmet Need 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 UN UN Unmet UN UN Unmet Low Medium High Need UN Low Medium High Need UN Low UN Medium UN High Unmet Need 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 UN UN Unmet UN UN Unmet Low Medium High Need UN Low Medium High Need UN Low UN Medium UN High Unmet Need 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 UN Low UN Medium UN High Unmet Need UN Low UN Medium UN High Unmet Need 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 UN Low UN Medium UN High Unmet Need UN Low UN Medium UN High Unmet Need 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 UN Low UN Medium UN High Unmet Need UN Low UN Medium UN High Unmet Need 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

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

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

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Table A17 (Continued)

India LAC UN Low UN Medium UN High Unmet Need UN Low UN Medium UN High Unmet Need 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

Transition United States UN Low UN Medium UN High Unmet Need UN Low UN Medium UN High Unmet Need 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

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Table A 18. Annual Family Planning Costs (Millions US Dollars)

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

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Table A18 (Continued)

India LAC UN Low UN Medium UN High Unmet Need UN Low UN Medium UN High Unmet Need 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

Transition United States UN Low UN Medium UN High Unmet Need UN Low UN Medium UN High Unmet Need 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

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