Health situation analysis in the African Region. Basic indicators 2006

Health situation analysis in the African Region Basic indicators 2006

Health situation analysis in the African Region Basic indicators 2006

World Health Organization. Regional Office for Africa, 2006 All rights reserved. Publications of the World Health Organization can be obtained from WHO Press, World Health Organization, 20 Avenue Appia, 1211 Geneva 27, Switzerland (tel.: +41 22 791 3264; fax: +41 22 791 4857; e-mail: bookorders@who.int). Requests for permission to reproduce or translate WHO publications whether for sale or for noncommercial distribution should be addressed to WHO Press, at the above address (fax: +41 22 791 4806; e-mail: permissions@who.int). The designations employed and the presentation of the material in this publication do not imply the expression of any opinion whatsoever on the part of the World Health Organization concerning the legal status of any country, territory, city or area or of its authorities, or concerning the delimitation of its frontiers or boundaries. Dotted lines on maps represent approximate border lines for which there may not yet be full agreement. The mention of specific companies or of certain manufacturers products does not imply that they are endorsed or recommended by the World Health Organization in preference to others of a similar nature that are not mentioned. Errors and omissions excepted, the names of proprietary products are distinguished by initial capital letters. All reasonable precautions have been taken by the World Health Organization to verify the information contained in this publication. However, the published material is being distributed without warranty of any kind, either expressed or implied. The responsibility for the interpretation and use of the material lies with the reader. In no event shall the World Health Organization be liable for damages arising from its use. Printed in Switzerland More information about this publication can be obtained from: Health Situation Analysis (HSA) Health Information, Evidence and Research Policy (IER) Office of the Director of Program Management (DPM) WHO Regional Office for Africa Brazzaville / Republic of Congo

Contents Message from the Regional Director v Map of the African Region of the World Health Organization vi Introduction 1 Demographic and socioeconomic statistics 2 Health status: mortality 4 Health status: morbidity 6 Inequities in health 8 Risk factors 10 Health service coverage 12 Health workers 14 Health expenditure ratios, 1999 2003 16 Per capita expenditure on health, 1999 2003 18 Explanatory notes 19 iii

Message from the Regional Director Governments need reliable and timely data to give them an accurate picture of the health situation in their countries. These data can then be used as evidence to develop policies that respond to the public health needs of their people. Governments need to know, for example, at what age people die and why; who is treating patients; how many people can access care; how much care costs; and what treatment outcomes are. Although much progress has been made in recent years in terms of improving data from the 46-Members States in the African Region, most of these countries still do not have a health informattion system capable of collecting, storing, analysing and reporting this type of data. That means that governments and global agencies have to compensate for the lack of evidence by employing other methods, including using mathematical models to predict possible trends or best-guess scenarios based on estimates or extrapolations. Sometimes these methods provide the only available source of information, but they are clearly inadequate. A lack of reliable information can result in misdirected funds and the failure on the part of donors to renew aid in the face of continuing need. During the last decade, despite limited resources, several countries in the African Region have substantially improved their population health data. The data set out in the following statistical tables are, in part, the result. I would like to take this opportunity to thank all Member States and those in charge of their health information systems who have cooperated with us by providing country data. Finally, I urge all those, who may not have done so, to fully participate in this exercise in the future to ensure complete and accurate representation of their countries health and health-related outcomes and determinants. Dr Luis Gomes Sambo Regional Director WHO Regional Office for Africa

African Region of the World Health Organization WHO African Region Outside WHO African Region These data refer to the 46 Member States of the African Region of the World Health Organization (WHO), as illustrated in this map. The African Regional Office of WHO is based in Brazzaville, the Republic of the Congo. When tables refer to Africa, they refer to the continent and islands as a whole. When tables refer to the African Region or the Region, it is as defined by WHO. It is important to note that the WHO African Region does not include all the countries on the African continent and the Region itself is not limited to all of sub-saharan Africa. Please note: the World Bank divides the continent into two regions: North Africa and sub-saharan Africa, while UNICEF divides it into three regions: Eastern and South Africa, West and Central Africa, and the Middle East and North Africa. vi Health situation analysis in the African Region

Introduction These tables include some of the most recent statistics since 1997, based on health indicators from the African Region s 46 Member States. All of these tables have been selected from World Health Statistics 2006. In addition, historical data for some of these indicators have been reproduced from the World health report 2006: Working together for health. The statistical tables cover the following categories: mortality, morbidity, health service coverage, risk factors, health systems, inequities in health, and demographic and socioeconomic status. World Health Statistics 2006 includes an expanded set of statistics from all 192 WHO Member States, with a particular focus on equity between and within countries. It was collated from publications and databases of WHO s technical programmes and regional offices. The core set of indicators was selected on the basis of relevance for global health, availability and quality of data, and accuracy and comparability of estimates. The statistics for the indicators are based on an interactive process of data collection, compilation, quality assessment, and estimation between WHO technical programmes and its Member States. In this process, WHO strives to maximize accessibility, accuracy, comparability, and transparency of country health statistics. In addition to national statistics, this publication presents statistics on the distribution of selected health outcomes and interventions within countries, disaggregated by gender, age, urban/ rural setting, wealth/assets, and educational level. Such statistics are primarily derived from the analysis of household surveys and are only available for a limited number of countries. The number of countries reporting disaggregated data is expected to increase during the next few years. The core indicators do not aim to capture all relevant aspects of health, but to provide a comprehensive summary of the current status of population health and health systems at country level: 1) mortality outcomes; 2) morbidity outcomes; 3) risk factors; 4) coverage of selected health interventions; 5) health systems; 6) inequalities in health; and 7) demographic and socioeconomic statistics. All statistics have been cleared as WHO official figures in consultation with Member States, unless otherwise stated. The estimates published here should, however, still be regarded as the best estimates by WHO rather than the official view of Member States. As demand for timely, reliable, and consistent information on key health statistics continues to increase, users need to be well informed on definitions, quality, and limitations of health statistics. More detailed information is available from the WHO Statistical Information System (WHOSIS) at: http://www.who.int/whosis. Basic indicators 2006

Demographic and socioeconomic statistics Country Population a Total fertility rate a number annual in urban growth rate areas (000) 2005 (%) 1995 2004 (%) 2005 (per woman) 2004 1 Algeria 32 854 1.4 60 2.5... 2 Angola 15 941 2.3 37 6.7... Adolescent fertility proportion b (%) Year 3 Benin 8 439 2.8 46 5.7 9.3 1999 4 Botswana 1 765 0.9 53 3.1... 5 Burkina Faso 13 228 2.7 19 6.6 10.1 2002 6 Burundi 7 548 1.7 11 6.8... 7 Cameroon 16 322 1.9 53 4.5 13.9 2003 8 Cape Verde 507 2.1 58 3.6... 9 Central African Republic 4 038 1.6 44 4.9... 10 Chad 9 749 3.0 26 6.7 14.7 2003 11 Comoros 798 2.5 36 4.7... 12 Congo 3 999 2.9 54 6.3... 13 Côte d Ivoire 18 154 1.9 46 4.9 12.3 1997 14 Democratic Republic of the Congo 57 549 2.2 33 6.7... 15 Equatorial Guinea 504 2.1 50 5.9... 16 Eritrea 4 401 3.2 21 5.4 8.1 2000 17 Ethiopia 77 431 2.3 16 5.7 9.4 1998 18 Gabon 1 384 2.0 85 3.9 16.9 1998 19 Gambia 1 517 2.9 26 4.6... 20 Ghana 22 113 2.0 46 4.2 8.3 2002 21 Guinea 9 402 2.0 37 5.8 14.7 1997 22 Guinea-Bissau 1 586 2.6 36 7.1... 23 Kenya 34 256 2.1 42 5.0 11.7 2002 24 Lesotho 1 795 0.6 18 3.5... 25 Liberia 3 283 4.2 48 6.8... 26 Madagascar 18 606 2.6 27 5.3 14.5 2002 27 Malawi 12 884 2.2 17 6.0 13.0 1998 28 Mali 13 518 2.6 34 6.8 13.7 2000 29 Mauritania 3 069 2.6 64 5.7 8.9 1999 30 Mauritius 1 245 0.9 44 2.0 9.6 2000 31 Mozambique 19 792 2.1 38 5.4 16.2 2002 32 Namibia 2 031 2.0 34 3.8 10.5 1999 33 Niger 13 957 3.1 23 7.8 14.5 1997 34 Nigeria 131 530 2.2 48 5.7 11.1 2002 35 Rwanda 9 038 5.0 22 5.6 4.6 1999 36 Sao Tome and Principe 157 1.8 38 3.9... 37 Senegal 11 658 2.2 51 4.9... 38 Seychelles 81 0.6 50 2.1... 39 Sierra Leone 5 525 2.6 40 6.5... 40 South Africa 47 432 1.2 58 2.8... 41 Swaziland 1 032 0.8 24 3.8... 42 Togo 6 145 2.9 36 5.2... 43 Uganda 28 816 2.9 12 7.1 13.6 1999 44 United Republic of Tanzania 38 329 2.0 38 4.9 12.2 1998 45 Zambia 11 668 1.8 37 5.5 13.7 2000 46 Zimbabwe 13 010 0.9 36 3.4 13.3 1997 Region African Region 738 083 2.2 38 5.3 11.7... Data not available or not applicable. a World Population Prospects: The 2004 Revision. Population database. Population Division. Department of Economic and Social Affairs. United Nations Secretariat. (http://esa.un.org/unpp) b Population Division. Department of Economic and Social Affairs. United Nations Secretariat. c United Nations Educational, Scientific and Cultural Organization. (http://gmr.uis.unesco.org/selectindicators.aspx) Health situation analysis in the African Region

Adult literacy rate c Net primary school enrolment ratio d Gross national income per capita e Population living below the poverty line f Males (%) Females (%) (PPP Int.$) 1998 2004 2004 69.8 96 94 6 260... (%) 2000 2004 (% with <$1 a day) 66.8 66 57 2 030... 33.6 69 47 1 120... 78.9 79 83 8 920... 12.8 42 31 1 220 44.9 1998 58.9 62 52 660 54.6 1998 67.9...... 2 090 17.1 2001 75.7 100 98 5 650... 48.6...... 1 110... 25.5 72 49 1 420... 56.2 59 50 1 840... 82.8 55 53 750... 48.1 67 54 1 390 10.8 2002 65.3...... 680... 84.2 91 78 7 400...... 49 42 1 050... 41.5 55 47 810 23.0 1999-00... 79 78 5 600...... 79 78 1 900 59.3 1998 54.1 64 62 2 280 44.8 1998-99... 73 58 2 130...... 53 37 690... 73.6 66 66 1 050 22.8 1997 81.4 83 89 3 210... 55.9 79 61...... 70.6 78 79 830 61.0 2001 64.1...... 620 41.7 1997-98 19.0 50 39 980... 51.2 68 67 2 050 25.9 2000 84.3 96 98 11 870... 46.5 58 53 1 160... 85.0 76 81 6 960... 14.4 45 31 830... 66.8 74 60 930 70.2 1997 64.0 85 88 1 300 51.7 1999-00... 100 94...... 39.3 71 66 1 720... 91.9 100 99 15 590... 29.6...... 790... 82.4 89 89 10 960 10.7 2000 79.2 75 75 4 970... 53.0 99 83 1 690... 68.9...... 1 520 84.9 1999 69.4 83 81 660... 67.9 69 68 890 63.7 1998 90.0 79 80 2 180... Year 60.1 70 63 2 074 44 d United Nations Educational, Scientific and Cultural Organization. (http://www.uis.unesco.org/ev.php?url_id=5187&url_do=do_topic&url_section=201) e The World Bank Group. (http://siteresources.worldbank.org/datastatistics/resources/gnipc.pdf) f The World Bank Group. (http://devdata.worldbank.org/wdi2005/table2_5.htm) Basic indicators 2006

Health status: mortality Country Life expectancy at birth a (years) Healthy life expectancy (HALE) at birth b (years) Probability of dying per 1000 population between 15 and 60 years a (adult mortality rate) Probability of dying per 1000 live births under 5 years a (under-5 mortality rate) Infant mortality rate c (per 1000 live births) Neonatal mortality rate d (per 1000 live births) Maternal mortality ratio d (per 100 000 live births) Males Females Males Females Males Females Both sexes Both sexes Both sexes Females 2004 2004 2002 2002 2004 2004 2004 2004 2000 2000 1 Algeria 69 72 60 62 153 124 40 35 20 140 2 Angola 38 42 32 35 591 504 260 154 54 1 700 3 Benin 52 53 43 45 388 350 152 90 38 850 4 Botswana 40 40 36 35 786 770 116 75 40 100 5 Burkina Faso 47 48 35 36 472 410 192 97 36 1 000 6 Burundi 42 47 33 37 593 457 190 114 41 1 000 7 Cameroon 50 51 41 42 444 432 149 87 40 730 8 Cape Verde 67 71 59 63 209 139 36 27 10 150 9 Central African Republic 40 41 37 38 667 624 193 115 48 1 100 10 Chad 45 48 40 42 497 422 200 117 45 1 100 11 Comoros 62 67 54 55 254 182 70 52 29 480 12 Congo 53 55 45 47 442 390 108 79 32 510 13 Côte d Ivoire 41 47 38 41 585 500 194 118 65 690 14 Democratic Republic of the Congo 42 47 35 39 576 446 205 129 47 990 15 Equatorial Guinea 42 44 45 46 577 522 204 123 40 880 16 Eritrea 58 62 49 51 345 281 82 52 25 630 17 Ethiopia 49 51 41 42 451 389 166 110 51 850 18 Gabon 55 59 50 53 411 344 91 59 31 420 19 Gambia 55 59 48 51 344 263 122 89 46 540 20 Ghana 56 58 49 50 349 319 112 68 27 540 21 Guinea 52 55 44 46 364 319 155 101 48 740 22 Guinea-Bissau 45 48 40 41 482 413 203 126 48 1 100 23 Kenya 51 50 44 45 477 502 120 78 29 1 000 24 Lesotho 39 44 30 33 845 728 82 55 28 550 25 Liberia 39 44 34 37 596 477 235 157 66 760 26 Madagascar 55 59 47 50 338 270 123 76 33 550 27 Malawi 41 41 35 35 663 638 175 109 40 1 800 28 Mali 44 47 37 38 490 414 219 121 55 1 200 29 Mauritania 55 60 43 46 325 246 125 78 70 1 000 30 Mauritius 69 75 60 65 217 112 15 12 12 24 31 Mozambique 44 46 36 38 627 549 152 102 48 1 000 32 Namibia 52 55 43 44 548 489 63 42 25 300 33 Niger 42 41 36 35 506 478 259 152 43 1 600 34 Nigeria 45 46 41 42 513 478 197 103 53 800 35 Rwanda 44 47 36 40 518 435 203 118 45 1 400 36 Sao Tome and Principe 57 60 54 55 301 236 118 75 38... 37 Senegal 54 57 47 49 358 288 137 78 31 690 38 Seychelles 67 78 57 65 232 83 14 12 9... 39 Sierra Leone 37 40 27 30 579 497 283 165 56 2 000 40 South Africa 47 49 43 45 667 598 67 54 21 230 41 Swaziland 36 39 33 35 823 741 156 102 38 370 42 Togo 52 56 44 46 401 327 140 79 40 570 43 Uganda 48 51 42 44 525 446 138 81 32 880 44 United Republic of Tanzania 47 49 40 41 551 524 126 78 43 1 500 45 Zambia 40 40 35 35 683 656 182 104 40 750 46 Zimbabwe 37 34 34 33 857 849 129 78 33 1 100 Region African Region 47 49 40 42 519 465 167 100 43 910... Data not available or not applicable. a World health report 2006: working together for health. Geneva, World Health Organization, 2006. (http://www.who.int/whr/2006/annex/en) b World health report 2004: changing history. Geneva, World Health Organization, 2004. (http://www.who.int/whr/2004/en/index.html) c (i) WHO Mortality Database. World Health Organization. (http://www.who.int/healthinfo/morttables/en/index.html); (ii) United Nations Children s Fund. State of the World s Children 2006. New York: United Nations Children s Fund, 2005. d World health report 2005: make every mother and child count. Geneva, World Health Organization, 2005. (http://www.who.int/whr/2005/en/index.html) e UNAIDS 2004 report on global HIV/AIDS epidemic: 4th global report. Geneva, Joint United Nations Programme on HIV/AIDS 2004. (http://www.unaids.org/bangkok2004/gar2004_pdf/unaidsglobalreport2004_en.pdf) f These are classified as deaths from tuberculosis (A15-A19, B90) according to the ICD-10. Source: Global tuberculosis control: surveillance, planning, financing. WHO report 2006. Geneva, World Health Organization (WHO/HTM/TB/2006.362). (http://www.who.int/tb/publications/global_report) 4 Health situation analysis in the African Region

Cause-specific mortality rate (per 100 000 population) Age-standardized mortality rate by cause h,i (per 100 000 population) Years of life lost by broader causes h,j (%) Causes of death among children under 5 years of age j,l (%) HIV/AIDS e TB among HIV-negative people f TB among HIV-positive people g Non-communicable diseases Cardiovascular diseases Cancer Injuries Communicable diseases k Non-communicable diseases Injuries Neonatal causes HIV/AIDS Diarrhoeal diseases Measles Malaria Pneumonia Injuries Other Both sexes Both sexes Both sexes Both sexes 2003 2004 2004 2002 2002 2002 2002 2002 2002 2002 2000 2000 2000 2000 2000 2000 2000 2000 <10 2 <1 598 314 103 85 50 30 20 48.0 0.0 11.9 0.9 0.5 13.7 5.0 20.0 140 25 7 982 486 179 231 84 8 8 22.2 2.2 19.1 4.8 8.3 24.8 1.4 17.2 73 14 2 852 432 154 116 82 10 8 25.0 2.2 17.1 5.3 27.2 21.1 2.1 0.0 1 863 37 58 653 338 124 72 93 4 3 40.3 53.8 1.1 0.1 0.0 1.4 3.3 0.0 234 38 16 901 459 162 149 87 7 7 18.3 4.0 18.8 3.4 20.3 23.3 1.5 10.4 355 59 33 843 439 146 301 81 7 12 23.3 8.0 18.2 3.0 8.4 22.8 1.8 14.6 311 19 12 848 436 150 118 81 11 8 24.8 7.2 17.3 4.1 22.8 21.5 2.2 0.0... 35 1 692 356 127 39 51 37 12 25.9 3.7 12.2 4.4 4.3 13.3 3.5 32.6 584 55 58 863 445 154 146 84 9 7 27.2 12.4 14.7 6.5 18.5 18.7 2.0 0.0 197 60 22 869 443 156 131 85 8 7 24.0 4.1 18.1 7.0 22.3 22.8 1.8 0.1... 7 <1 736 381 128 83 70 18 12 37.3 3.7 13.6 5.9 19.4 16.3 3.4 0.5 257 52 18 762 393 134 147 79 11 11 30.9 9.3 11.2 6.6 25.7 13.6 2.6 0.0 267 67 37 873 436 160 179 78 11 10 34.9 5.6 14.8 2.5 20.5 19.6 2.2 0.0 184 57 21 909 465 161 273 82 7 11 25.7 3.7 18.1 4.7 16.9 23.1 1.6 6.3... 30 27 864 438 155 144 79 12 9 27.5 7.4 13.6 7.4 24.0 17.3 2.5 0.3 155 52 9 762 398 133 92 81 11 8 27.4 6.2 15.6 2.5 13.6 18.6 3.0 13.0 163 60 19 859 435 147 104 82 12 6 30.2 3.8 17.3 4.2 6.1 22.3 1.7 14.3 224 33 22 813 410 158 103 72 18 9 35.1 10.1 8.8 4.4 28.3 10.7 2.5 0.0 42 38 2 805 413 144 109 75 15 10 36.6 1.3 12.2 2.5 29.4 15.5 2.6 0.0 141 40 10 786 404 138 97 74 16 10 28.5 5.7 12.2 2.9 33.0 14.6 3.0 0.0 100 44 12 853 432 156 147 80 11 9 28.8 2.3 16.5 5.5 24.5 20.9 1.4 0.0... 33 9 883 449 159 138 86 8 6 24.1 2.6 18.6 3.4 21.0 23.4 1.4 5.5 458 90 43 782 401 139 95 81 11 8 24.2 14.6 16.5 3.2 13.6 19.9 2.7 5.3 1 611 41 58 785 404 139 88 90 7 3 32.8 56.2 3.9 0.1 0.0 4.7 2.2 0.0 223 46 27 955 485 169 270 83 7 10 29.1 3.6 17.3 6.0 18.9 23.0 1.7 0.3 43 37 6 837 430 147 112 79 12 9 25.6 1.3 16.9 5.0 20.1 20.7 2.4 8.0 681 48 49 835 430 150 105 89 6 5 21.7 14.0 18.1 0.3 14.1 22.6 1.7 7.6 94 62 11 909 456 166 145 86 8 6 25.9 1.6 18.3 6.1 16.9 23.9 1.4 5.9 17 57 3 884 451 158 138 79 12 9 39.4 0.3 16.2 1.7 12.2 22.3 1.9 5.9... 11 <1 701 434 79 42 11 75 13 66.0 0.0 1.2 0.0 0.0 3.9 5.2 23.6 577 62 67 720 371 124 66 91 7 2 29.0 12.9 16.5 0.3 18.9 21.2 1.0 0.1 806 44 41 754 385 146 93 83 10 6 38.5 53.0 2.5 0.1 0.0 3.0 3.0 0.0 37 31 3 916 456 169 163 87 7 6 16.7 0.6 19.8 7.3 14.3 25.1 1.4 14.8 246 56 27 889 452 157 132 83 10 7 26.1 5.0 15.7 6.3 24.1 20.1 1.9 0.8 251 69 33 831 425 150 126 85 8 7 21.7 5.0 18.5 1.6 4.6 23.2 1.8 23.7... 28 <1 764 396 133 87 67 21 12 32.1 3.7 16.0 4.8 0.6 21.2 3.5 18.1 31 49 3 832 426 146 125 76 13 11 22.8 1.0 17.1 8.1 27.6 20.7 2.6 0.2... 6 <1 657 336 131 69 16 64 21 27.2 0.0 0.0 0.0 0.0 10.1 12.3 50.3... 92 13 1 017 515 181 250 86 6 8 21.9 1.3 19.7 5.3 12.4 25.5 1.2 12.7 789 56 78 808 410 154 120 77 15 8 35.1 57.1 0.8 0.0 0.0 0.9 5.0 1.1 1 643 93 176 732 364 162 72 91 5 4 26.8 47.0 9.6 0.2 0.2 11.8 3.8 0.5 171 77 21 831 427 147 117 79 12 9 29.0 5.8 13.8 6.6 25.3 17.1 2.5 0.0 290 71 22 824 422 146 154 84 8 8 23.6 7.7 17.2 3.0 23.1 21.1 2.2 2.1 433 47 31 847 435 151 115 85 8 6 26.9 9.3 16.8 1.3 22.7 21.1 2.0 0.0 788 70 68 700 359 122 58 92 6 2 22.9 16.1 17.5 1.2 19.4 21.8 1.0 0.1 1 322 62 89 685 347 122 103 90 7 4 28.1 40.6 12.1 2.9 0.2 14.7 1.2 0.3 313 53 28 800 404 144 133 59 10 8 26.2 6.8 16.6 4.3 17.5 21.1 1.9 5.6 g These deaths are classified under HIV disease resulting in tuberculosis (B20.0) according to the ICD-10. They are already counted in the number of deaths from HIV/AIDS (B20-B24). Source: Global tuberculosis control: surveillance, planning, financing. WHO report 2006. Geneva, World Health Organization (WHO/HTM/TB/2006.362). (http://www.who.int/tb/publications/global_report) h Mortality and burden of disease estimates for WHO Member States in 2002. World Health Organization, December 2004. (http://www.who.int/entity/healthinfo/statistics/bodgbddeathdalyestimates.xls) i Rates are age-standardized to the WHO world standard population. Source: Ahmad OB, Boschi-Pinto C, Lopez AD, Murray CJL, Lozano R, Inoue M. Age standardization of rates: a new WHO standard. GPE Discussion Paper Series: No.31. EIP/GPE/EBD. World Health Organization. 2001. (http://www3.who.int/whosis/discussion_papers) j Sum of individual proportions may not add up to 100% due to rounding. k Communicable diseases include maternal causes, conditions arising in the perinatal period and nutritional deficiencies. l Neonatal causes include diarrhoea during the neonatal period. Sources: (i) Bryce J, Boschi-Pinto C, Shibuya K, Black RE; WHO Child Health Epidemiology Reference Group. WHO estimates of the causes of death in children. Lancet, 2005;365:1147-52; (ii) WHO mortality profiles. (http://www.who.int/whostatistics/mortality) Basic indicators 2006

Health status: morbidity Country 1 Algeria HIV prevalence among adults a (15-49) (%) Both sexes 2003 0.1 TB prevalence b (per 100 000 population) Both sexes 2004 TB incidence b (per 100 000 population) Both sexes 2004 Number of confirmed polio cases c Both sexes 2005 54 54 0 2 Angola 3.9 310 259 10 3 Benin 1.9 142 87 0 4 Botswana 37.3 553 670 0 5 Burkina Faso 4.2 365 191 0 6 Burundi 6 564 343 0 7 Cameroon 6.9 227 179 1 8 Cape Verde... 314 172 0 9 Central African Republic 13.5 549 322 0 10 Chad 4.8 566 279 2 11 Comoros... 95 46 0 12 Congo 4.9 464 377 0 13 Côte d Ivoire 7 651 393 0 14 Democratic Republic of the Congo 4.2 551 366 0 15 Equatorial Guinea... 322 239 0 16 Eritrea 2.7 437 271 1 17 Ethiopia 4.4 533 353 22 18 Gabon 8.1 339 280 0 19 Gambia 1.2 329 233 0 20 Ghana 3.1 376 206 0 21 Guinea 3.2 410 240 0 22 Guinea-Bissau... 306 199 0 23 Kenya 6.7 888 619 0 24 Lesotho 28.9 544 696 0 25 Liberia 5.9 447 310 0... Data not available or not applicable. a UNAIDS 2004 report on global HIV/AIDS epidemic: 4th global report. Geneva, Joint United Nations Programme on HIV/AIDS 2004. (http://www.unaids.org/bangkok2004/gar2004_pdf/unaidsglobalreport2004_en.pdf) b All forms of TB, including TB in people with HIV infection. Source: Global tuberculosis control: surveillance, planning, financing. WHO report 2006. Geneva, World Health Organization (WHO/HTM/TB/2006.362). (http://www.who.int/tb/publications/global_report) c World Health Organization, Polio Eradication Initiative. Data as of 25 April 2006. (http://www.who.int/immunization_monitoring/en/diseases/poliomyelitis/case_count.cfm) 6 Health situation analysis in the African Region

Country HIV prevalence among adults a (15-49) (%) Both sexes 2003 TB prevalence b (per 100 000 population) Both sexes 2004 TB incidence b (per 100 000 population) Both sexes 2004 Number of confirmed polio cases c 26 Madagascar 1.7 351 218 4 27 Malawi 14.2 501 413 0 28 Mali 1.9 578 281 3 29 Mauritania 0.6 502 287 0 30 Mauritius... 135 64 0 31 Mozambique 12.2 635 460 0 32 Namibia 21.3 586 717 0 33 Niger 1.2 288 157 10 34 Nigeria 5.4 531 290 801 35 Rwanda 5.1 660 371 0 36 Sao Tome and Principe... 253 107 0 37 Senegal 0.8 451 245 0 38 Seychelles... 83 34 0 39 Sierra Leone... 847 443 0 40 South Africa 21.5 670 718 0 41 Swaziland 38.8 1120 1226 0 42 Togo 4.1 718 355 0 43 Uganda 4.1 646 402 0 44 United Republic of Tanzania 8.8 479 347 0 45 Zambia 16.5 707 680 0 46 Zimbabwe 24.6 673 674 0 Both sexes 2005 Region )update 2004( African Region 7.1 518 356 854 Basic indicators 2006

Inequities in health Country Year Probability of dying per 1000 live births under 5 years a (under-5 mortality rate) Children under 5 years stunted for age a (%) Place of residence Wealth quintile Educational level of mother b Place of residence Wealth quintile Rural Urban Rural urban ratio Lowest Highest 1 Benin 2001 175.5 133.6 1.3 198.2 93.1 2.1 174.5 80.8 2.2 33.4 24.2 1.4 35.4 18.2 1.9 2 Botswana 1988 55.2 55.3 1.0......... 62.0 46.3 1.3.................. 3 Burkina Faso 2003 201.5 136.4 1.5 206.0 144.0 1.4 198.4 108.0 1.8 41.4 19.8 2.1 45.7 20.6 2.2 4 Burundi 1987 184.2 163.7 1.1......... 191.2 80.7 2.4 48.6 27.1 1.8......... 5 Cameroon 2004 168.8 119.3 1.4 189.0 88.0 2.1 185.7 93.3 2.0 38.2 23.1 1.7 40.9 12.3 3.3 6 Central African Republic 1994-95 178.4 128.6 1.4 192.9 98.3 2.0 175.2 83.1 2.1 37.2 28.6 1.3 42.3 25.0 1.7 7 Chad 2004 208.0 179.0 1.2 176.0 187.0 0.9 200.0 143.0 1.4 43.0 32.3 1.3 50.7 31.7 1.6 8 Comoros 1996 122.6 80.7 1.5 128.9 86.6 1.5 120.6 74.5 1.6 35.0 29.9 1.2 44.8 23.3 1.9 9 Côte d Ivoire 1998-99 196.8 125.2 1.6......... 192.7 79.4 2.4 28.6 18.3 1.6......... 10 Eritrea 2002 117.1 86.1 1.4 100.0 65.0 1.5 120.6 58.5 2.1 42.6 27.8 1.5 44.8 17.6 2.5 11 Ethiopia 2000 192.5 148.6 1.3 159.2 147.1 1.1 197.4 89.2 2.2 52.3 41.6 1.3 52.9 43.2 1.2 12 Gabon 2000 99.9 88.4 1.1 93.1 55.4 1.7 112.0 87.1 1.3 29.0 17.4 1.7 32.8 11.5 2.9 13 Ghana 2003 118.3 92.7 1.3 128.0 88.0 1.5 124.9 84.5 1.5 34.0 19.9 1.7 41.8 13.2 3.2 14 Guinea 1999 210.6 148.7 1.4 229.9 133.0 1.7 203.8 104.2 2.0 29.4 18.2 1.6 32.4 15.7 2.1 15 Kenya 2003 116.9 93.5 1.3 149.0 91.0 1.6 126.5 62.9 2.0 32.0 23.8 1.3 38.1 19.2 2.0 16 Liberia 1986 239.7 217.8 1.1......... 242.1 176.1 1.4.................. 17 Madagascar 2003-04 120.0 73.3 1.6 141.8 49.4 2.9 148.6 65.4 2.3 48.9 40.9 1.2 50.5 38.2 1.3 18 Malawi 2000 210.3 147.9 1.4 230.8 149.0 1.5 214.5 118.0 1.8 51.3 34.2 1.5 57.8 33.5 1.7 19 Mali 2001 253.2 184.6 1.4 247.8 148.1 1.7 246.9 89.6 2.8 42.1 23.2 1.8 44.8 19.7 2.3 20 Mauritania 2000-01 96.2 110.7 0.9 98.1 78.5 1.2 110.5 85.5 1.3 37.9 30.2 1.3 38.7 23.4 1.7 21 Mozambique 2003 192.0 143.2 1.3 196.0 108.0 1.8 200.5 85.7 2.3 45.7 28.5 1.6 49.3 20.0 2.5 22 Namibia 2000 66.1 49.5 1.3 55.4 31.4 1.8 83.6 47.1 1.8 23.0 21.7 1.1 26.7 15.3 1.7 23 Niger 1998 327.4 178.1 1.8 281.8 183.7 1.5 314.0 129.6 2.4 43.0 31.2 1.4 41.9 32.3 1.3 24 Nigeria 2003 242.7 152.9 1.6 257.0 79.0 3.3 269.4 107.2 2.5 42.9 28.9 1.5 48.8 17.9 2.7 25 Rwanda 2000 216.2 141.3 1.5 246.4 154.1 1.6 232.7 116.7 2.0 44.9 27.8 1.6 49.4 26.9 1.8 26 Senegal 1999 171.2 92.1 1.9......... 159.9 80.1 2.0.................. 27 South Africa 1998 71.2 43.2 1.6 87.4 21.9 4.0 83.8 45.6 1.8.................. 28 Sudan 1990 144.0 117.0 1.2......... 151.9 84.3 1.8.................. 29 Togo 1998 157.4 101.3 1.6 167.7 97.0 1.7 159.1 82.5 1.9 23.9 14.8 1.6 29.0 11.0 2.6 30 Uganda 2000-01 163.8 100.5 1.6 191.8 106.4 1.8 186.9 93.0 2.0 39.9 26.5 1.5 43.3 25.1 1.7 31 United Republic of Tanzania 1999 165.9 141.6 1.2 160.0 135.2 1.2 165.4 62.6 2.6 46.5 24.5 1.9 49.5 23.4 2.1 32 Zambia 2001-02 182.3 140.0 1.3 191.7 92.4 2.1 197.8 121.1 1.6 51.1 37.1 1.4 54.1 31.6 1.7 33 Zimbabwe 1999 99.7 69.0 1.4 99.5 62.2 1.6 118.8 78.7 1.5 29.2 20.6 1.4 32.7 18.6 1.8 Lowest highest ratio Lowest Highest Lowest highest ratio Rural Urban Rural urban ratio Lowest Highest Lowest highest ratio Statistics by gender are presented elsewhere in this report.... Data not available or not applicable. a Source: Demographic and Health Surveys. (http://www.measuredhs.com) b Lowest and highest mother s educational levels are no education and secondary or higher, respectively. c Data correspond to births in 3 years preceding survey, not 5 years. Health situation analysis in the African Region

Births attended by skilled health personnel a (%) Measles immunization coverage among 1-year-olds a (%) Educational level Place of residence Wealth quintile Educational level Place of residence Wealth quintile Educational level of mother b of mother b of mother b Lowest Highest Lowest highest ratio Rural Urban Urban rural ratio Highest Lowest Highest-lowest ratio Lowest Highest Highest-lowest ratio Urban Rural Urban rural ratio Highest Lowest Highest-lowest ratio Highest Lowest Highest-lowest ratio 33.0 17.1 1.9 68.4 82.9 1.2 99.3 49.6 2.0 67.6 98.6 1.5 75.3 64.1 1.2 83.1 56.9 1.5 88.6 63.4 1.4......... 71.7 93.5 1.3......... 53.6 96.6 1.8 65.4 69.9 0.9......... 63.0 67.8 0.9 40.8 12.4 3.3 30.5 87.7 2.9 90.8 38.8 2.3 32.7 94.7 2.9 73.1 53.3 1.4 71.3 48.3 1.5 80.4 54.3 1.5 49.0 24.6 2.0 16.8 85.2 5.1......... 15.6 75.7 4.9 51.1 47.8 1.1......... 56.3 45.2 1.2 40.1 21.0 1.9 44.2 84.2 1.9 94.5 29.3 3.2 22.9 91.7 4.0 72.5 58.3 1.2 83.2 52.1 1.6 79.3 46.1 1.7 37.2 24.1 1.5 c 23.7 77.7 3.3 81.7 14.3 5.7 29.4 84.8 2.9 c 68.4 40.5 1.7 79.8 31.3 2.5 79.2 38.6 2.1 44.3 22.1 2.0 6.4 45.6 7.1 55.4 3.6 15.4 9.3 66.7 7.2 37.5 19.2 2.0 38.1 8.2 4.6 53.7 18.2 3.0 38.2 25.0 1.5 c 43.1 78.9 1.8 84.8 26.2 3.2 40.8 82.9 2.0 c 63.0 63.5 1.0 86.0 51.1 1.7 75.5 58.7 1.3 28.3 14.2 2.0 32.1 79.1 2.5......... 37.9 83.6 2.2 82.0 58.8 1.4......... 94.6 57.8 1.6 44.6 16.2 2.8 10.4 64.7 6.2 81.0 6.7 12.1 12.0 87.9 7.3 93.8 78.5 1.2 96.4 83.8 1.2 95.6 77.1 1.2 52.8 32.5 1.6 2.3 34.5 15.0 25.3 0.9 28.1 2.5 45.0 18.0 63.1 22.3 2.8 52.2 18.2 2.9 61.7 22.1 2.8 22.5 16.5 1.4 69.4 92.9 1.3 97.1 67.2 1.4 83.9 92.9 1.1 61.1 37.1 1.6 71.3 34.1 2.1 63.9 42.3 1.5 38.0 23.7 1.6 30.9 79.7 2.6 90.4 20.6 4.4 29.7 67.9 2.3 85.8 81.8 1.0 88.8 75.0 1.2 89.3 78.2 1.1 27.9 13.3 2.1 21.3 75.6 3.5 81.5 12.1 6.7 29.1 83.5 2.9 66.9 46.7 1.4 73.0 33.1 2.2 82.3 48.4 1.7 36.4 19.0 1.9 34.5 72.0 2.1 75.4 17.0 4.4 15.8 72.0 4.6 85.9 69.7 1.2 88.0 54.8 1.6 84.9 51.1 1.7......... 44.9 76.7 1.7......... 49.3 86.6 1.8 30.2 28.0 1.1......... 42.7 24.9 1.7 49.1 38.0 1.3 39.6 70.6 1.8 93.9 29.9 3.1 21.9 80.5 3.7 73.9 55.9 1.3 84.0 38.4 2.2 85.2 36.1 2.4 54.2 27.1 2.0 51.9 81.6 1.6 83.0 43.0 1.9 45.0 87.7 1.9 90.6 82.0 1.1 90.4 79.8 1.1 93.4 79.2 1.2 40.1 13.6 2.9 26.6 80.8 3.0 81.9 8.1 10.1 34.4 90.8 2.6 70.8 41.3 1.7 76.5 39.7 1.9 78.7 44.9 1.8 37.1 21.4 1.7 28.9 85.8 3.0 92.8 14.7 6.3 40.4 91.6 2.3 74.3 53.0 1.4 86.2 42.0 2.1 79.8 55.4 1.4 47.7 14.5 3.3 34.1 80.7 2.4 88.6 24.8 3.6 31.4 94.8 3.0 90.8 70.8 1.3 96.4 60.8 1.6 99.1 65.6 1.5 28.5 17.9 1.6 66.3 93.1 1.4 97.1 55.4 1.8 46.8 89.1 1.9 84.3 78.4 1.1 85.7 76.2 1.1 83.3 69.5 1.2 42.3 23.6 1.8 c 8.1 68.7 8.5 62.8 4.2 15.0 13.8 68.5 5.0 c 67.1 27.8 2.4 65.8 23.0 2.9 73.9 31.8 2.3 50.5 20.0 2.5 27.1 58.8 2.2 84.5 13.0 6.5 13.8 75.0 5.4 52.1 28.5 1.8 70.7 15.9 4.4 66.5 15.6 4.3 47.9 26.1 1.8 19.9 65.7 3.3 59.6 17.3 3.4 13.9 68.9 5.0 89.9 86.3 1.0 88.8 83.8 1.1 93.2 82.2 1.1......... 75.7 95.6 1.3......... 78.5 97.1 1.2 78.7 58.1 1.4......... 90.9 54.0 1.7......... 75.5 93.4 1.2 98.1 67.8 1.4 59.7 91.4 1.5 85.1 79.3 1.1 84.5 73.5 1.1 85.6 64.0 1.3......... 59.3 85.9 1.4......... 52.6 95.5 1.8 69.9 56.3 1.2......... 84.8 50.3 1.7 25.5 12.0 2.1 c 39.8 86.4 2.2 91.2 25.1 3.6 36.7 86.8 2.4 c 58.0 38.2 1.5 63.2 34.5 1.8 63.7 36.5 1.7 45.5 28.9 1.6 33.1 80.4 2.4 77.3 19.7 3.9 21.5 75.8 3.5 68.4 55.3 1.2 64.5 49.1 1.3 69.4 54.1 1.3 46.7 16.6 2.8 34.7 83.3 2.4 82.8 28.9 2.9 25.3 81.5 3.2 90.3 75.3 1.2 89.0 63.4 1.4 98.1 63.3 1.5 53.8 36.1 1.5 27.6 79.0 2.9 91.1 19.7 4.6 17.3 77.8 4.5 85.5 83.9 1.0 88.4 81.2 1.1 87.2 79.8 1.1 35.3 22.5 1.6 64.2 89.4 1.4 93.5 56.7 1.6 42.8 85.6 2.0 86.2 75.7 1.1 85.8 80.2 1.1 85.2 69.4 1.2 Basic indicators 2006

Risk factors Country Children under-5 stunted for age a Children under-5 underweight for age a Children under-5 over-weight for age a Newborns with low birth weight b Adults ( 15 years old) who are obese c (%) Year (%) Year (%) Year (%) (%) Year Both sexes Both sexes Both sexes Both sexes 2000 02 1 Algeria 19.1 2002 10.4 2002 10.1 2000 7...... 2 Angola 45.2 2001 30.5 2001... 12...... 3 Benin 30.7 2001 22.9 2001 1.8 2001 16... 6.1 2001 m 4 Botswana 23.1 2000 12.5 2000 6.9 2000 10...... 5 Burkina Faso 38.8 2003 37.7 2003 2.9 2003 19... 2.4 2003 m 6 Burundi 56.8 2000 45.1 2000 0.7 2000 16...... 7 Cameroon 31.7 2004 18.1 2004 5.2 2004 11... 4.2 2004 m 8 Cape Verde......... 13...... 9 Central African Republic......... 14...... 10 Chad 29.1 2000 28.0 2000 1.5 2000 17...... 11 Comoros 42.3 2000 25.4 2000 13.6 2000 25...... 12 Congo.................. 13 Côte d Ivoire 25.1 1998-99 21.2 1998-99 2.5 1998-99 17... 5.0 1998-99 m 14 Democratic Republic of the Congo 38.1 2001 31.0 2001 3.9 2001 12...... 15 Equatorial Guinea......... 13...... 16 Eritrea 37.6 2002 39.6 2002 0.7 2002 21... 1.6 2002 m 17 Ethiopia 51.5 2000 47.2 2000 1.2 2000 15... 0.3 2000 m 18 Gabon 20.7 2000-01 11.9 2000-01 3.7 2000-01 14...... 19 Gambia 19.2 2000 17.2 2000 1.5 2000 17...... 20 Ghana 29.9 2003 22.1 2003 2.9 2003 11... 8.1 2003 m 21 Guinea 26.1 1999 23.2 1999 2.7 1999 12...... 22 Guinea-Bissau 30.5 2000 25.0 2000 3.3 2000 22...... 23 Kenya 30.3 2003 19.9 2003 3.7 2003 11... 6.3 2003 m 24 Lesotho 46.1 2000 18.0 2000 12.1 2000 14... 16.2 2004 m 25 Liberia 39.5 1999-00 26.5 1999-00 2.3 1999-00......... 26 Madagascar 47.7 2003-04 41.9 2003-04 2.0 2003-04 14... 0.9 2003 m 27 Malawi 49.0 2000 25.4 2000 4.3 2000 16... 2.1 2000 m 28 Mali 38.2 2001 33.2 2001 1.5 2001 23... 3.7 2001 m 29 Mauritania 34.5 2000-01 31.8 2000-01......... 16.7 2000-01 m 30 Mauritius......... 13 8.0 20.0 1998 l 31 Mozambique 41.0 2003 23.7 2003 3.0 2003 14... 3.8 2003 m 32 Namibia 23.6 2000 24.0 2000 2.2 2000 14...... 33 Niger 39.7 2000 40.1 2000 0.8 2000 17...... 34 Nigeria 38.3 2003 28.7 2003 3.6 2003 14... 5.8 2003 m 35 Rwanda 42.6 2000 24.3 2000 4.0 2000 9...... 36 Sao Tome and Principe 28.9 2000 12.9 2000............ 37 Senegal 25.4 2000 22.7 2000 2.2 2000 18...... 38 Seychelles.................. 39 Sierra Leone 33.8 2000 27.2 2000............ 40 South Africa 24.9 1999 11.5 1999 6.2 1999 15 9.4 30.1 1998 41 Swaziland 30.2 2000 10.3 2000... 9...... 42 Togo 21.7 1998 25.1 1998 1.5 1998 15...... 43 Uganda 39.1 2000-01 22.9 2000-01 2.6 2000-01 12...... 44 United Republic of Tanzania 43.8 1999 29.4 1999 1.7 1999 13... 4.4 2004-05 m 45 Zambia 46.8 2001-02 28.1 2001-02 3.0 2001-02 12... 3.0 2001-02 m 46 Zimbabwe 26.5 1999 13.0 1999 7.0 1999 11... 7.5 1999 m Males Females Region African Region......... 14......... Data not available or not applicable. a Global Database on Child Growth and Malnutrition. World Health Organization. (http://www.who.int/nutgrowthdb/database/en/) b United Nations Children s Fund and World Health Organization. Low Birthweight: Country, regional and global estimates. UNICEF, New York, 2004. (http://www.who.int/reproductive-health/publications/low_birthweight/low_birthweight_estimates.pdf) c WHO Global Database on Body Mass Index (BMI). World Health Organization. (http//www.who.int/bmi). Comparisons between countries may be limited due to differences in definitions, sample characteristics, or survey years. d World Health Organization and United Nations Children s Fund. Joint Monitoring Programme for Water Supply and Sanitation. Online database. (http://www.wssinfo.org/en/wecome.html) e Programme on Household Energy and Health, Department for Public Health and Environment. World Health Organization. (http://www.who.int/indoorair/en/) f In adolescents, data relate to daily or occasional tobacco use, while in adults they relate to daily or occasional tobacco smoking. Comparisons between countries may be limited due to differeences in definitions, sample characteristics, or survey years. g Global NCD InfoBase/Online Tool. World Health Organization. (http://www.who.int/ncd_surveillance/infobase/en) 10 Health situation analysis in the African Region

Access to improved water sources d Access to improved sanitation d Population using solid fuels e Prevalence of current tobacco use (%) f Condom use by young people (aged 15 24) at higher risk sex i (%) Urban 2002 (%) (%) (%) Adolescents (13-15) g Adults ( 15) h Rural 2002 Urban 2002 Rural 2002 Urban 2003 Rural 2003 Both sexes Year Males Females Year Males Females Year 92 80 99 82..................... 70 40 56 16..................... 79 60 58 12 88 99 14.5 2003...... 34 19 2001 100 90 57 25...... 11.3 2001...... 88 75 2000 82 44 45 5 91 100... 24.2 11.1 2003 l 67 54 2003 90 78 47 35 98 100............... 84 41 63 33 62 98......... 57 46 2004 86 73 61 19..................... 93 61 47 12..................... 40 32 30 0 95 98... 18.3 3.7 2003 l 25 17 2004 90 96 38 15 46 90 k... 27.5 17.0 2003 k,l...... 72 17 14 2 84 98 k... 16.5 1.7 2003 k,l...... 98 74 61 23 63 95 k... 20.7 3.2 2003 k,l...... 83 29 43 23..................... 45 42 60 46..................... 72 54 34 3 31 97 6.6 2006............ 81 11 19 4 78 100... 7.3 0.6 2003 l 30 17 2000 95 47 37 30 14 81......... 48 33 2000 95 77 72 46..................... 93 68 74 46 75 96 11.7 2006 9.9 1.3 2003 l 52 33 2003 78 38 25 6..................... 79 49 57 23..................... 89 46 56 43 17 94 12.7 2001 27.2 1.9 2003 l 47 25 2003 88 74 61 32...... 20.3 2002...... 53 53 2004 72 52 49 7..................... 75 34 49 27............... 12 5 2003 96 62 66 42 90 99... 25.3 5.8 2003 l 47 35 2004 76 35 59 38 99 100... 24.7 3.0 2003 l 30 14 2001 63 45 64 9 35 84 24.7 2001 29.6 4.7 2003 l...... 100 100 100 99 0 2 13.2 2003 42.7 2.8 2003 l...... 76 24 51 14............... 33 29 2003 98 72 66 14 24 84 25.8 2004 28.3 12.4 2003 l 69 48 2000 80 36 43 4 95 98 18.4 2001............ 72 49 48 30............ 0.0 2003 m,n 46 24 2003 92 69 56 38 98 100......... 41 28 2004 89 73 32 20..................... 90 54 70 34 24 80 16.6 2002 24.1 1.9 2003 l...... 100 75... 100...... 28.9 2002............ 75 46 53 30..................... 98 73 86 44 7 40 23.6 2002 37.0 11.2 2003 l...... 87 42 78 44 23 82 11.5 2001 15.1 3.2 2003 l...... 80 36 71 15...... 16.1 2002............ 87 52 53 39 85 99... 25.2 3.3 2001 m 55 53 2004 92 62 54 41............... 46 34 2004 90 36 68 32 68 99... 23.3 5.7 2003 l 42 33 2001 100 74 69 51 26 94... 26.2 3.1 2003 l...... 84 45 58 28..................... h (i) Global NCD InfoBase/Online Tool. World Health Organization. (http://www.who.int/ncd_surveillance/infobase/en); (ii) Ustun TB, Chatterji S, Mechbal A, Murray CJL, WHS Collaborating Groups. The World Health Surveys in Health Systems Performance Assessment: Debates, Methods and Empiricism (eds. Murray CJL and Evans D), World Health Organization, Geneva, 2003; (iii) Results from the World Health Survey. World Health Organization. (http://www.who.int/healthinfo/survey/en/) i Multiple Indicator Cluster Survey (http://childinfo.org) and Demographic and Health Surveys (http://www.measuredhs.com). j Self-reported data. k Sample is not necessarily nationally representative. l Lower age limit above 15. m Upper age limit at 50. n Cigarettes are the only smoked tobacco product under consideration. Basic indicators 2006 11

Health service coverage Country Immunization coverage among 1-year-olds a Measles DTP3 HepB3 (%) 2004 (%) 2004 (%) 2004 At least 1 visit Antenatal care coverage b At least 4 visits Births attended by skilled health personnel c Contraceptive prevalence d (%) (%) Year (%) Year (%) Year 1 Algeria 81 86 81 79... 2000 92 2000 64.0 2000 2 Angola 64 59......... 47 2000 6.2 2001 3 Benin 85 83 89 88 61 2001 66 2001 18.6 2001 4 Botswana 90 97 79 99 97 2001 94 2000 40.4 2000 5 Burkina Faso 78 88... 72 18 2003 57 k 2003 13.8 2003 6 Burundi 75 74 83 93 79 2001 25 2000 15.7 2000 7 Cameroon 64 73... 77 52 1998 62 2004 26.0 2004 8 Cape Verde 69 75 68... 99 2001 89 k 1998 52.9 1998 9 Central African Republic 35 40......... 44 2000 27.9 2000 10 Chad 56 50... 51 13 1997 14 2004 7.9 2000 11 Comoros 73 76 77...... 62 2000 25.7 2000 12 Congo 65 67............... 13 Côte d Ivoire 49 50 50 84 35 1998-99 63 2000 15.0 1998-99 14 Democratic Republic of the Congo 64 64......... 61 2001 31.4 2001 15 Equatorial Guinea 51 33...... 37 2001 65 2000... 16 Eritrea 84 83 83... 49 2001 28 2002 8.0 2002 17 Ethiopia 71 80... 27 10 2000 6 2000 8.1 2000 18 Gabon 55 38... 94 63 2000 86 2000 32.7 2000 19 Gambia 90 92 90 92... 2000 55 2000 9.6 2000 20 Ghana 83 80 80 90 69 2003 47 2003 25.2 2003 21 Guinea 73 69... 74 48 1999 35 1999 6.2 1999 22 Guinea-Bissau 80 80... 89 62 2001 35 2000 7.6 2000 23 Kenya 73 73 73 88 52 2003 42 2003 39.3 2003 24 Lesotho 70 78 67 91 88 2001 55 2004 30.4 2000 25 Liberia 42 31...... 84 2001 51 2000... 26 Madagascar 59 61 61 91 38 1997 51 2003-04 27.1 2003-04 27 Malawi 80 89 89 94 55 2000 61 2002 30.6 2000 28 Mali 75 76 73 53 30 2001 41 2001 8.1 2001 29 Mauritania 64 70... 63 16 2000-01 57 k 2001 8.0 2000-01 30 Mauritius 98 98 98...... 99 1998... 31 Mozambique 77 72 72 71 41 1997 48 2003 16.5 2003 32 Namibia 70 81... 85 69 2000 76 2000 43.9 2000 33 Niger 74 62... 39 11 1998 16 2000 14.0 2000 34 Nigeria 35 25... 61 47 2003 35 2003 12.6 2003 35 Rwanda 84 89 89 93 10 2001 31 2000 13.2 2000 36 Sao Tome and Principe 91 99 99 91... 2000 79 2000 29.3 2000 37 Senegal 57 87 54 82 64 1999 58 2000 10.5 1999 38 Seychelles 99 99 99............ 39 Sierra Leone 64 61... 82 68 2001 42 2000 4.3 2000 40 South Africa 81 93 92 89 72 1998 84 1998 56.3 1998 41 Swaziland 70 83 78...... 70 2000 27.7 2000 42 Togo 70 71... 78 46 1998 49 2000 25.7 2000 43 Uganda 91 87 87 92 40 2000-01 39 2000 22.8 2000-01 44 United Republic of Tanzania 94 95 95 96 69 1999 46 2004-05 25.4 1999 45 Zambia 84 80... 94 71 2001-02 43 2001-02 34.2 2001-02 46 Zimbabwe 80 85 85 82 64 1999 73 1999 53.5 1999 Region African Region 66 66 35............... Data not available or not applicable. a WHO/UNICEF estimates of national coverage for year 2004 (as of September 2005). (http://www.who.int/immunization_monitoring/routine/immunization_coverage/en/index4.html) b World health report 2005: make every mother and child count. Geneva, World Health Organization, 2005. (http://www.who.int/whr/2005/en/index.html) c WHO Database on Skilled Attendant at Delivery. World Health Organization. (http://www.who.int//reproductive-health/global_monitoring/data.html) d World Contraceptive Use 2005 database. Population Division, Department of Economic and Social Affairs, United Nations. e World malaria report 2005. Geneva, World Health Organization and United Nations Children s Fund, 2005. Values for Cameroon and Chad have been updated. f Progress on global access to HIV antiretroviral therapy. A report on 3 by 5 and beyond. Geneva, World Health Organization and Joint United Nations Programme on HIV/AIDS, March 2006. Data for high-income countries have been added to the original list which consisted of 152 low- and middle-income countries. Regional values relate to low- and middle-income countries only. (http://www. who.int/hiv/fullreport_en_highres.pdf) 12 Health situation analysis in the African Region

Children under-5 sleeping under insecticide-treated nets e Antiretroviral therapy coverage f TB detection rate under DOTS g TB treatment success under DOTS h Children under-5 with ARI symptoms taken to facility i Children under-5 with diarrhoea receiving ORT i Children under-5 with fever who received treatment with any antimalarial e Children 6 59 months who received vitamin A supplementation j Births by Caesarean section b (%) Year (%) Dec 2005 (%) 2004 (%) 2003 cohort (%) Year (%) Year (%) Year (%) 2002 (%) Year... 39 105 90............ 6 2000 2.3 2001 6 94 68...... 63.0 2001 87.5... 7.4 2001 33 82 81 35.1 2001 39.3 2001 60.4 2001 84.6 4 2001... 85 67 77............... 1.6 2003 24 18 66 35.9 2003 49.0 2003 49.6 2003 97.0 1 2003 1.3 2000 14 29 79...... 31.3 2000 89.2... 0.9 2004 22 91... 36.6 2000 47.7 2004 53.1 2004 86.1 3 1998........................ 6 1998 1.5 2000 3 4 59...... 68.8 2000... 2 1994-95 0.6 2000 17 16 78 11.8 2004 27.8 2004 55.8 2004 85.3 1 1996-97 9.3 2000... 39......... 62.7 2000... 5 1996... 17 65 69......... 85.6... 1.1 2000 17 38 72...... 57.5 2000... 3 1998-99 0.7 2001 4 70 83...... 45.4 2001 61.7... 0.7 2000 0 82 51...... 48.6 2000...... 4.2 2002 5 14 85 43.6 2002 38.2 2002 3.6 2002 51.1 2 1995... 7 36 70 15.8 2000 34.9 2000 3.0 2000... 1 2000... 23 81 34 47.7 2000 62.7 2000... 86.6 6 2000 14.7 2000 9 66 75...... 55.2 2000 93.0... 3.5 2003 7 37 66 44.0 2003 39.6 2003 62.8 2003 98.6 4 2003... 9 52 75 38.4 1999...... 94.5 2 1999 7.4 2000 1 75 80...... 58.4 2000 79.7... 4.6 2003 24 46 80 49.1 2003 34.2 2003 26.5 2003 91.4 4 2003... 14 86 70 54.4 2004 32.1 2004............ 3 58 73......... 40.0... 0.2 2000 0 74 71 47.9 2003-04 34.9 2004 41.1 2004 95.0 1 1997 35.5 2004 20 40 73 26.7 2000 35.4 2000 31.6 2004 85.8 3 2000... 31 19 65 35.6 2001 53.5 2001 37.6 2003 68.3 1 2001 2.1 2003-04 40 43 58 40.7 2000-01... 33.4 2003-04 89.0 3 2000-01...... 33 87.................. 9 46 76 55.4 2003 46.7 2003...... 3 1997... 71 88 63 53.1 2000 15.3 2000 14.4 2000 96.4 7 1992 1.0 2000 5 46 70...... 48.1 2000 76.6 1 1998 1.2 2003 6 21 59 32.8 2003 20.4 2003 33.8 2003 79.0 2 2003 5.0 2000 39 29 67 15.5 2000 17.3 2000 12.6 2000 36.2 2 2000 22.8 2000............... 61.2 2000...... 1.7 2000 47 52 70... 48.3 1999 36.2 2000 82.7 2 1997...... 106 100............... 1.5 2000 2 36 83...... 60.7 2000 87.2 2 1997... 21 83 67 73.9 1998......... 16 1998 0.1 2000 31 38 42...... 25.5 2000...... 2.0 2000 27 17 63...... 60.0 2000 95.0 2 1998 0.2 2000-01 51 43 68 66.5 2000-01 27.7 2000-01... 46.0 3 2000-01 2.1 1999 7 47 81 45.8 2003 36.3 2003 53.4 1999 94.2 3 1999 6.5 2001-02 26 54 75 69.1 2001-02 40.9 2000-02 51.9 2001-02 79.8 2 2001-02... 8 42 66 49.0 1999 51.0 1999... 78.2 7 1999... 17 48 72............... g The number of new smear-positive cases notified to WHO divided by the estimated number of new smear-positive cases. Source: Global tuberculosis control: surveillance, planning, financing. WHO report 2006. Geneva, World Health Organization (WHO/HTM/TB/2006.362). h The percentage of new smear-positive patients registered for treatment under DOTS during 2003 who were cured (with laboratory confirmation) or completed their course of treatment. Source: Global tuberculosis control: surveillance, planning, financing. i Demographic and Health Surveys. (http://www.measuredhs.com) j UNICEF Global Database on Vitamin A Supplementation Coverage. The United Nations Children s Fund. (http://www.childinfo.org/eddb/vita_a/framedb.htm) k Data do not exactly relate to skilled health personnel as defined in the document: Making pregnancy safer: the critical role of the skilled attendant: a joint statement by WHO, ICM and FIGO. Geneva, World Health Organization, 2004. Further information can be found on http://www.who.int/whosis. Basic indicators 2006 13

Health workers Country Number Human resources for health a Physicians Nurses Midwives Dentists Density per 1000 Year 1 Algeria 35 368 1.13 2002 68 950 2.21 2002 799 0.03 2002 9 553 0.31 2002 2 Angola 881 0.08 1997 13 135 1.15 1997 492 0.04 1997 2 0.00 1997 3 Benin 311 0.04 2004 5 789 0.84 2004...... 12 0.00 2004 4 Botswana 715 0.40 2004 4 753 2.65 2004...... 38 0.02 2004 5 Burkina Faso 789 0.06 2004 5 518 0.41 2004 1 732 0.13 2004 58 0.00 2004 6 Burundi 200 0.03 2004 1 348 0.19 2004...... 14 0.00 2004 7 Cameroon 3 124 0.19 2004 26 042 1.60 2004...... 147 0.01 2004 8 Cape Verde 231 0.49 2004 410 0.87 2004...... 11 0.02 2004 9 Central African Republic 331 0.08 2004 1 188 0.30 2004 519 0.13 2004 13 0.00 2004 10 Chad 345 0.04 2004 2 387 0.27 2004 112 0.01 2004 15 0.00 2004 11 Comoros 115 0.15 2004 588 0.74 2004...... 29 0.04 2004 12 Congo 756 0.20 2004 3 672 0.96 2004...... 12 0.00 2004 13 Côte d Ivoire 2 081 0.12 2004 10 180 0.60 2004...... 339 0.02 2004 14 Democratic Republic of the Congo 5 827 0.11 2004 28 789 0.53 2004...... 159 0.00 2004 15 Equatorial Guinea 153 0.30 2004 228 0.45 2004 43 0.08 2004 15 0.03 2004 16 Eritrea 215 0.05 2004 2 505 0.58 2004...... 16 0.00 2004 17 Ethiopia 1 936 0.03 2003 14 893 0.21 2003 651 0.01 2003 93 0.00 2003 18 Gabon 395 0.29 2004 6 974 5.16 2004...... 66 0.05 2004 19 Gambia 156 0.11 2003 1 719 1.21 2003 162 0.11 2003 43 0.03 2003 20 Ghana 3 240 0.15 2004 19 707 0.92 2004...... 393 0.02 2004 21 Guinea 987 0.11 2004 4 757 0.55 2004 64 0.01 2004 60 0.01 2004 22 Guinea-Bissau 188 0.12 2004 1 037 0.67 2004 35 0.02 2004 22 0.01 2004 23 Kenya 4 506 0.14 2004 37 113 1.14 2004...... 1 340 0.04 2004 24 Lesotho 89 0.05 2003 1 123 0.62 2003...... 16 0.01 2003 25 Liberia 103 0.03 2004 613 0.18 2004 422 0.12 2004 13 0.00 2004 26 Madagascar 5 201 0.29 2004 5 661 0.32 2004...... 410 0.02 2004 27 Malawi 266 0.02 2004 7 264 0.59 2004............ 28 Mali 1 053 0.08 2004 6 538 0.49 2004 573 0.04 2004 84 0.01 2004 29 Mauritania 313 0.11 2004 1 893 0.64 2004...... 64 0.02 2004 30 Mauritius 1 303 1.06 2004 4 550 3.69 2004 54 0.04 2004 233 0.19 2004 31 Mozambique 514 0.03 2004 3 954 0.21 2004 2 229 0.12 2004 159 0.01 2004 32 Namibia 598 0.30 2004 6 145 3.06 2004...... 113 0.06 2004 33 Niger 377 0.03 2004 2 716 0.22 2004 21 0.00 2004 15 0.00 2004 34 Nigeria 34 923 0.28 2003 210 306 1.70 2003...... 2 482 0.02 2003 35 Rwanda 401 0.05 2004 3 593 0.42 2004 54 0.01 2004 21 0.00 2004 36 Sao Tome and Principe 81 0.49 2004 256 1.55 2004 52 0.32 2004 11 0.07 2004 37 Senegal 594 0.06 2004 3 287 0.32 2004...... 97 0.01 2004 38 Seychelles 121 1.51 2004 634 7.93 2004...... 94 1.17 2004 39 Sierra Leone 168 0.03 2004 1 841 0.36 2004...... 5 0.00 2004 40 South Africa 34 829 0.77 2004 184 459 4.08 2004...... 5 995 0.13 2004 41 Swaziland 171 0.16 2004 6 828 6.30 2004...... 32 0.03 2004 42 Togo 225 0.04 2004 2 141 0.43 2004 5 0.00 2004 19 0.00 2004 43 Uganda 2 209 0.08 2004 16 221 0.61 2004 3 104 0.12 2004 363 0.01 2004 44 United Republic of Tanzania 822 0.02 2002 13 292 0.37 2002...... 267 0.01 2002 45 Zambia 1 264 0.12 2004 19 014 1.74 2004 2 996 0.27 2004 491 0.04 2004 46 Zimbabwe 2 086 0.16 2004 9 357 0.72 2004...... 310 0.02 2004 Number Density per 1000 Year Number Density per 1000 Year Number Density per 1000 Year... Data not available or not applicable. a World health report 2006: working together for health. Geneva, World Health Organization, 2006. (http://www.who.int/whr/2006/annex/en) 14 Health situation analysis in the African Region

Human resources for health a Pharmacists Public and environmental health workers Community health workers Lab technicians Other health workers Health management and support workers Number Density per 1000 Year Number Density per 1000 Year Number Density per 1000 Year Number Density per 1000 Year Number Density per 1000 Year Number Density per 1000 Year 6 333 0.20 2002 2 534 0.08 2002 1 062 0.03 2002 8 838 0.28 2002 5 088 0.16 2002 60 882 1.95 2002 24 0.00 1997.............................. 11 0.00 2004 178 0.03 2004 88 0.01 2004 477 0.07 2004 128 0.02 2004 3 281 0.47 2004 333 0.19 2004 172 0.10 2004...... 277 0.15 2004...... 829 0.46 2004 343 0.03 2004 46 0.00 2004 1 291 0.10 2004 424 0.03 2004 975 0.07 2004 325 0.02 2004 76 0.01 2004...... 657 0.09 2004 147 0.02 2004 1 186 0.17 2004 2 087 0.30 2004 700 0.04 2004 28 0.00 2004...... 1 793 0.11 2004 16 0.00 2004 5 902 0.36 2004 43 0.09 2004 9 0.02 2004 65 0.14 2004 78 0.16 2004 42 0.09 2004 74 0.16 2004 17 0.00 2004 55 0.01 2004 211 0.05 2004 48 0.01 2004 367 0.09 2004 167 0.04 2004 37 0.00 2004 230 0.03 2004 268 0.03 2004 317 0.04 2004 153 0.02 2004 1 502 0.17 2004 41 0.05 2004 17 0.02 2004 41 0.05 2004 63 0.08 2004 9 0.01 2004 272 0.34 2004 99 0.03 2004 9 0.00 2004 124 0.03 2004 554 0.15 2004 957 0.25 2004 987 0.26 2004 1 015 0.06 2004 155 0.01 2004...... 1 165 0.07 2004 172 0.01 2004 2 107 0.12 2004 1 200 0.02 2004............ 512 0.01 2004 1 042 0.02 2004 15 013 0.28 2004 130 0.26 2004 18 0.04 2004 1 275 2.51 2004 75 0.15 2004...... 74 0.15 2004 107 0.02 2004 88 0.02 2004...... 248 0.06 2004 56 0.01 2004 765 0.18 2004 1 343 0.02 2003 1 347 0.02 2003 18 652 0.26 2003 2 703 0.04 2003 7 354 0.10 2003...... 63 0.05 2004 150 0.11 2004...... 276 0.20 2004 1 0.00 2004 144 0.11 2004 48 0.03 2003 33 0.02 2003 968 0.68 2003 99 0.07 2003 3 0.00 2003 391 0.27 2003 1 388 0.06 2004............ 899 0.04 2004 7 132 0.33 2004 19 151 0.90 2004 530 0.06 2004 135 0.02 2004 93 0.01 2004 268 0.03 2004 17 0.00 2004 511 0.06 2004 40 0.03 2004 13 0.01 2004 4 486 2.92 2004 230 0.15 2004 61 0.04 2004 38 0.02 2004 3 094 0.10 2004 6 496 0.20 2004...... 7 000 0.22 2004 5 610 0.17 2004 1 797 0.06 2004 62 0.03 2003 55 0.03 2003...... 146 0.08 2003 23 0.01 2003 18 0.01 2003 35 0.01 2004 150 0.04 2004 142 0.04 2004 218 0.06 2004 540 0.15 2004 518 0.15 2004 175 0.01 2004 130 0.01 2004 385 0.02 2004 172 0.01 2004 530 0.03 2004 6 036 0.34 2004...... 26 0.00 2004...... 46 0.00 2004 707 0.06 2004...... 351 0.03 2004 231 0.02 2004 1 295 0.10 2004 264 0.02 2004 377 0.03 2004 652 0.05 2004 81 0.03 2004...... 429 0.14 2004 106 0.04 2004 48 0.02 2004 1 056 0.35 2004 1 428 1.16 2004 238 0.19 2004 236 0.19 2004 324 0.26 2004 134 0.11 2004 2 038 1.65 2004 618 0.03 2004 564 0.03 2004...... 941 0.05 2004 1 633 0.09 2004 9 517 0.50 2004 288 0.14 2004 240 0.12 2004...... 481 0.24 2004 597 0.30 2004 7 782 3.87 2004 20 0.00 2004 268 0.02 2004...... 294 0.02 2004 213 0.02 2004 513 0.04 2004 6 344 0.05 2004...... 115 761 0.91 2004 690 0.01 2004 1 220 0.01 2004...... 278 0.03 2004 101 0.01 2004 12 000 1.41 2004 39 0.00 2004 521 0.06 2004 1 419 0.17 2004 24 0.15 2004 19 0.12 2004 374 2.27 2004 51 0.31 2004 291 1.76 2004 288 1.75 2004 85 0.01 2004 705 0.07 2004...... 66 0.01 2004 704 0.07 2004 564 0.05 2004 61 0.76 2004 77 0.96 2004...... 59 0.74 2004 35 0.44 2004...... 340 0.07 2004 136 0.03 2004 1 227 0.24 2004............ 4 0.00 2004 12 521 0.28 2004 2 529 0.06 2004 9 160 0.20 2004 1 968 0.04 2004 40 526 0.90 2004 28 005 0.62 2004 70 0.06 2004 110 0.10 2004 4 700 4.34 2004 78 0.07 2004 551 0.51 2004 374 0.35 2004 134 0.03 2004 289 0.06 2004 475 0.09 2004 528 0.11 2004 397 0.08 2004 1 335 0.27 2004 688 0.03 2004 1 042 0.04 2004...... 1 702 0.06 2004 3 617 0.14 2004 6 499 0.24 2004 365 0.01 2002 1 831 0.05 2002...... 1 520 0.04 2002 29 722 0.82 2002 689 0.02 2002 1 039 0.10 2004 1 027 0.09 2004...... 1 415 0.13 2004 3 330 0.30 2004 10 853 0.99 2004 883 0.07 2004 1 803 0.14 2004...... 917 0.07 2004 743 0.06 2004 581 0.04 2004 Basic indicators 2006 15

Health expenditure ratios, 1999 2003 Figures computed to assure comparability; a they are not necessarily the official statistics of Member States, which may use alternative methods Total expenditure on health as % of gross domestic product General government expenditure on health as % of total expenditure on health b Private expenditure on health as % of total expenditure on health b General government expenditure on health as % of total government expenditure Member State 1999 2000 2001 2002 2003 1999 2000 2001 2002 2003 1999 2000 2001 2002 2003 1999 2000 2001 2002 2003 1 Algeria 3.7 3.5 3.8 4.2 4.1 71.9 73.3 77.4 78.9 80.8 28.1 26.7 22.6 21.1 19.2 9 9 9.5 9.6 10 2 Angola 3.2 2.5 3.3 2.4 2.8 45.3 82.2 84.6 80.9 84.2 54.7 17.8 15.4 19.1 15.8 2.4 3.4 5.5 4.1 5.3 3 Benin 4.8 4.7 5 4.7 4.4 43.8 44.5 46.9 43.5 43.1 56.2 55.5 53.1 56.5 56.9 11.1 10 9.8 8 9.8 4 Botswana 5.2 5.4 4.8 5.1 5.6 54.3 57.2 50.4 54 58.2 45.7 42.8 49.6 46 41.8 6.7 7.4 6 6.4 7.5 5 Burkina Faso 5.4 5.2 5 5.4 5.6 44 42.4 39.5 44.2 46.8 56 57.6 60.5 55.8 53.2 10 9.4 10.5 12.8 12.7 6 Burundi 3 3.1 3.1 3.1 3.1 19.9 17.9 21.6 21 23.3 80.1 82.1 78.4 79 76.7 2.8 2 2.2 2 2 7 Cameroon 4.9 4.4 4.5 4.6 4.2 24.4 28 27.6 27.6 28.9 75.6 72 72.4 72.4 71.1 7.2 9.6 8 8.4 8 8 Cape Verde 4.5 4.6 5 5 4.6 73.9 73.5 75.8 75.1 73.2 26.1 26.5 24.2 24.9 26.8 9 9.6 12.4 11.1 11.1 Central African 9 Republic 3.6 4 3.9 4 4 38 41.1 38.6 41.2 38.6 62 58.9 61.4 58.8 61.4 6.7 10 11.5 11.2 12.4 10 Chad 6.1 6.7 6.8 6.3 6.5 33.6 42 40.9 35.5 39.9 66.4 58 59.1 64.5 60.1 11.9 13.1 13.8 9.4 10.5 11 Comoros 3.2 2.7 2.3 2.9 2.7 60.8 54.9 47.7 58 54.1 39.2 45.1 52.3 42 45.9 10.5 9.5 5 6.4 6.4 12 Congo 2.4 1.8 2 1.9 2 63.8 66.5 67 66.9 64.2 36.2 33.5 33 33.1 35.8 4.9 4.8 4.2 3.7 4.3 13 Côte d Ivoire c 5.1 4.7 3.9 3.8 3.6 17.4 19.8 18.3 31.6 27.6 82.6 80.2 81.7 68.4 72.4 4.5 5.2 4.3 6.2 5 Democratic Republic 14 of Congo 3.2 3.7 3.1 3.3 4 7.7 5.3 6.8 13.1 18.3 92.3 94.7 93.2 86.9 81.7 2.6 2.6 4.7 4.2 5.4 15 Equatorial Guinea 2.8 2 1.7 1.8 1.5 60.8 67.6 70.2 72.2 67.5 39.2 32.4 29.8 27.8 32.5 9.9 11 10.1 8.8 7 16 Eritrea 3.8 4.5 4.6 4.5 4.4 70.3 66.9 59.2 50.9 45.5 29.7 33.1 40.8 49.1 54.5 2.9 4.4 4.6 3.9 4 17 Ethiopia 5.4 5.7 5.8 6 5.9 53 54.6 53.2 56.9 58.4 47 45.4 46.8 43.1 41.6 8.9 9.3 10.5 9.9 9.6 18 Gabon 4.5 4.2 4.2 4.4 4.4 68.4 73.1 73 69.8 66.6 31.6 26.9 27 30.2 33.4 10.9 13.9 9.9 10.7 12.8 19 Gambia 7 7.9 7.8 7.5 8.1 32.3 40.5 40.1 40.9 40 67.7 59.5 59.9 59.1 60 10 14.4 9.4 12 13.9 20 Ghana 5.5 5.4 4.8 4.7 4.5 35.3 35.3 28.8 30.5 31.8 64.7 64.7 71.2 69.5 68.2 7.8 6.8 4.2 5.4 5 21 Guinea 4.7 4.8 4.8 5.2 5.4 13.4 13.5 18.3 14.7 16.6 86.6 86.5 81.7 85.3 83.4 3.9 3.9 4.7 4.2 4.9 22 Guinea-Bissau 4.8 4.1 4.3 6.2 5.6 29.7 23.7 21.3 40.8 45.8 70.3 76.3 78.7 59.2 54.2 4.6 2.2 2.1 6.6 6.9 23 Kenya 4.6 4.3 4.2 4.5 4.3 41.1 46.5 42.8 44 38.7 58.9 53.5 57.2 56 61.3 4.1 11.1 8 9.2 7.2 24 Lesotho 5.4 5.8 5.6 6.5 5.2 80.9 82.6 82 83.1 79.7 19.1 17.4 18 16.9 20.3 9.1 9.7 10.1 10.9 9.5 25 Liberia 6.3 4.8 4.1 3.9 4.7 67.7 57.7 50.3 47.7 56.7 32.3 42.3 49.7 52.3 43.3 18.1 13 12.4 10.5 17.6 26 Madagascar 2.2 2.1 1.9 2.8 2.7 53.7 53 64.7 63 63.4 46.3 47 35.3 37 36.6 6.9 6.5 7 11.4 9.3 27 Malawi 9.8 8.6 10.5 9.4 9.3 36.9 30.2 45.2 34 35.2 63.1 69.8 54.8 66 64.8 12.2 7.5 11.7 9.1 9.1 28 Mali 4 4.7 4.3 4.5 4.8 42.9 49.5 50.1 52.6 57.4 57.1 50.5 49.9 47.4 42.6 6.6 8.5 8.2 9 9.2 29 Mauritania 2.7 2.5 2.9 3.9 4.2 64.2 63.3 67.9 74.2 76.8 35.8 36.7 32.1 25.8 23.2 8.6 6.5 6.8 9.2 14.3 30 Mauritius 3.1 3.3 3.5 3.6 3.7 62 58.7 60.5 60.7 60.8 38 41.3 39.5 39.3 39.2 7.2 6.6 9 9.4 9.2 31 Mozambique 4.7 5.5 4.8 5.1 4.7 63 67.8 66.2 67.6 61.7 37 32.2 33.8 32.4 38.3 12.1 12.9 10.7 11.5 10.9 32 Namibia 7 7 6.4 5.9 6.4 73.3 68.9 69.4 68.6 70 26.7 31.1 30.6 31.4 30 13.1 12.3 11.1 11 12.4 33 Niger 4.5 4.4 4.3 4.3 4.7 49.7 52.4 53.1 52.8 53 50.3 47.6 46.9 47.2 47 12.5 12.3 12 11.5 12.4 34 Nigeria 5.4 4.3 5.3 5 5 29.1 33.5 31.4 25.6 25.5 70.9 66.5 68.6 74.4 74.5 5.4 4.2 3.2 3.1 3.2 35 Rwanda 4.6 4.3 4.1 4.2 3.7 47.7 34.6 38.8 47 43.5 52.3 65.4 61.2 53 56.5 9.9 8 7.7 10.2 7.2 Sao Tome and 36 Principe 10 8.6 10.5 9 8.6 87.3 85.9 85.8 85 83.9 12.7 14.1 14.2 15 16.1 12.5 11.2 10.9 11.3 11.1 37 Senegal 4.5 4.4 4.7 5 5.1 36.2 36.4 38.5 39.8 41.8 63.8 63.6 61.5 60.2 58.2 7.8 8.1 8 9.5 9.3 38 Seychelles 5.3 5.2 5.1 5.1 5.9 74.8 75 74.7 74.9 73.2 25.2 25 25.3 25.1 26.8 6.9 6.8 8.1 7 10.2 39 Sierra Leone 3.1 3.8 3.4 3.5 3.5 46.1 55.5 53.7 63.6 58.3 53.9 44.5 46.3 36.4 41.7 6.9 7.6 6.4 7.9 7.9 40 South Africa 8.7 8.1 8.4 8.4 8.4 41.1 42.4 41.2 40.6 38.6 58.9 57.6 58.8 59.4 61.4 10.7 10.9 11.2 11.6 10.2 41 Swaziland 6.4 6.1 6 5.9 5.8 59 58.6 57.8 59.3 57.3 41 41.4 42.2 40.7 42.7 11.8 11.6 11.3 10.9 10.9 42 Togo d 5.4 4.6 5.4 4.9 5.6 40 29 25.2 18.7 24.8 60 71 74.8 81.3 75.2 12.4 7.5 8.6 6.9 9.3 43 Uganda 6.3 6.6 7.3 7.6 7.3 30.6 26.8 27.3 31.1 30.4 69.4 73.2 72.7 68.9 69.6 9.4 9 9.6 10.8 10.7 United Republic of 44 Tanzania 4.3 4.4 4.5 4.5 4.3 43.4 48.1 48.5 51.6 55.4 56.6 51.9 51.5 48.4 44.6 12.4 12.6 12.8 12.8 12.7 45 Zambia 5.7 5.5 5.8 6 5.4 48.8 50.6 56.5 56.7 51.4 51.2 49.4 43.5 43.3 48.6 9.5 9.1 10.2 10.6 11.8 46 Zimbabwe 8.1 7.8 9.1 8.4 7.9 48.9 48.3 38.6 37.7 35.9 51.1 51.7 61.4 62.3 64.1 10 7.4 9.3 9.8 9.2 Equatorial Guinea, Gabon, Guinea Bissau, Liberia and Sao Tome and Principe: estimates for these countries should be read with caution as these are derived from limited sources (mostly macro data that are publicly accessible). Burkina Faso, Guinea, Mauritius and Rwanda: new NHA reports, surveys, and/or country consultations provided new bases for the estimates. a See explanatory notes for sources and methods. b In some cases the sum of the ratios of general government and private expenditures on health may not add to 100 because of rounding. c The series was adjusted for the removal of social security expenditure on health, which could not be confirmed due to incomplete information. d Togo data on health research and development and training were adjusted to harmonize with the standard methodology used for World Health Reports. n/a Used when the information accessed indicates that a cell should have an entry but no estimates could be made. 0 Used when no evidence of the schemes to which the cell relates exist. Some estimates yielding a ratio below 0.04% are shown as 0. 16 Health situation analysis in the African Region

External resources for health as % of total expenditure on health Social security expenditure on health as % of general government expenditure on health Out-of-pocket expenditure as % of private expenditure on health Private prepaid plans as % of private expenditure on health 1999 2000 2001 2002 2003 1999 2000 2001 2002 2003 1999 2000 2001 2002 2003 1999 2000 2001 2002 2003 0.1 0.1 0.1 0 0 40.8 35.5 33.3 29.1 28.4 97 96.7 96 95.7 95.3 2.9 3.1 3.8 4.1 4.4 5.7 17.5 16.7 8.3 6.7 0 0 0 0 0 100 100 100 100 100 0 0 0 0 0 14.6 16.8 12.2 8.5 11.5 n/a n/a n/a n/a n/a 91 91 90.6 90.3 90.3 8.4 8.4 8.7 9 9 2.2 1.8 2.9 3.4 2.9 n/a n/a n/a n/a n/a 30.3 31.3 31.5 29.7 28.8 22.7 20.6 20 19.6 21.8 10.2 9.9 10.1 7 7.4 0.3 0.8 1.2 0.7 1 98.1 98.1 98.1 98.1 98.1 0.9 0.9 0.9 0.9 0.9 10.7 8 10.6 10.3 14.1 n/a n/a n/a n/a n/a 100 100 100 100 100 n/a n/a n/a n/a n/a 5.2 6 6.9 2.3 3.2 0.1 0.1 0.1 0.1 0.1 94.2 93.3 93.4 93.6 98.3 n/a n/a n/a n/a n/a 8.4 13.5 15.1 15.2 10 36.9 36.1 35.1 33.6 35.5 99.7 99.6 99.5 99.8 99.7 0.3 0.4 0.5 0.2 0.3 20 20 15.4 13.4 2.9 n/a n/a n/a n/a n/a 95.1 95.5 95.5 95.5 95.3 n/a n/a n/a n/a n/a 29.1 36.6 33.8 17 11.8 n/a n/a n/a n/a n/a 96.7 96.5 96.6 96.5 96.3 0.3 0.4 0.4 0.4 0.4 47.6 35.9 26.2 43 40.5 0 0 0 0 0 100 100 100 100 100 0 0 0 0 0 2.8 2.4 2.5 2.4 2.2 0 0 0 0 0 100 100 100 100 100 n/a n/a n/a n/a n/a 2.7 2.9 3.5 3.7 3.4 n/a n/a n/a n/a n/a 94 93.4 92.1 90.3 90.5 6 6.6 7.9 9.7 9.5 6 4.9 6.6 12.7 15.1 0 0 0 0 0 100 100 100 100 100 n/a n/a n/a n/a n/a 9.2 7.7 5.9 3.6 5.5 0 0 0 0 0 91.8 83.9 81.3 80.5 80.5 0 0 0 0 0 20.2 30.6 24.1 22.5 19.6 0 0 0 0 0 100 100 100 100 100 0 0 0 0 0 22.6 19.3 23.4 21.7 26 0.4 0.4 0.4 0.4 0.4 79.7 79.1 79.8 79.3 78.7 0.4 0.5 0.5 0.5 0.5 2.4 1 1.6 0.7 0.7 1.7 1.6 1.7 1.7 1.7 100 100 100 100 100 n/a n/a n/a n/a n/a 29.8 35.8 30.8 18.5 21.8 0 0 0 0 0 68.1 69.3 69.6 69.2 67 n/a n/a n/a n/a n/a 6.4 12.8 20.7 14.4 15.8 n/a n/a n/a n/a n/a 100 100 100 100 100 0 0 0 0 0 5.5 5.8 10.5 6.3 7.3 1.8 1.8 1.5 1.7 1.5 99.4 99.4 99.4 99.5 99.4 0 0 0 0 0 22.4 16 15.8 35.5 26.8 1.2 2.1 3 1.5 2.2 85.1 83.7 85.2 84.1 80.2 0 0 0 0 0 13.3 13.2 17.2 16.4 15.3 16.7 11.7 14.8 9.2 10 79.3 80.1 80.5 80 82.6 7.4 7.1 6.8 6.9 6 3.6 10.8 16.2 6.4 8.2 0 0 0 0 0 20 20 19.4 18.6 18.2 n/a n/a n/a n/a n/a 55.7 43.6 31.2 25.5 32.3 0 0 0 0 0 98.5 98.5 98.5 98.5 98.5 0 0 0 0 0 40.5 43.3 39.1 31.6 22 n/a n/a n/a n/a n/a 89.7 90.5 87.1 91.6 91.7 10.3 9.5 12.9 8.4 8.3 26.1 18.5 31 23 25.1 0 0 0 0 0 42.3 41.7 42 42.5 42.7 1.7 1.6 1.7 1.6 1.6 18.8 24.1 20.8 3.4 13.7 24 21.8 22.9 27.7 26 89.3 88.6 89.1 89.2 89.3 0 0 0 0 0 5.5 5.7 4.9 2.5 4.7 0 0 0 0 0 100 100 100 100 100 0 0 0 0 0 1.2 1.1 1.6 1.4 1 6.5 7.8 8.3 8.3 8.7 100 100 100 100 100 n/a n/a n/a n/a n/a 39.6 42.9 47.6 38.3 40.8 0 0 0 0 0 38.5 39 34.3 32 38.8 0.6 0.6 0.6 0.6 0.5 2.4 3.8 4 4.3 5.3 1.2 1.8 2 2 1.9 21.3 18.2 20.1 20.4 19.2 74.7 77.3 75.1 74.9 76 28.6 46.6 23.1 22.7 32.8 2.6 2.8 2.6 2.4 2.2 88.9 88 88.2 88.8 89.2 6.4 7.4 7.3 7 7.2 13.8 16.2 5.6 6.1 5.3 0 0 0 0 0 94.8 92.7 91.4 90.4 91.2 3.4 5.1 6.5 6.7 6.7 43 48.9 38.2 46.9 54.5 5.1 6.8 8.3 9 9.8 41.4 35.6 39.2 43.8 41.7 3.8 5.6 6.5 7.5 7.1 59.9 62.5 62.9 74.9 56 0 0 0 0 0 100 100 100 100 100 0 0 0 0 0 12.6 14 19.2 10.3 15.4 19 19.2 18.8 16.6 15.8 96.7 96.6 96.5 95.4 95.3 2.1 2.2 2.2 3.3 3.4 1.3 0.6 0.4 0.5 2 5.3 5.2 5.1 4.8 3.3 62.5 61.8 62.5 62.5 62.5 0 0 0 0 0 8.8 11.8 14.8 5.8 15.5 0 0 0 0 0 100 100 100 100 100 0 0 0 0 0 0.1 0.4 0.4 0.4 0.5 3.5 3.3 3.1 3.8 4.6 17.1 18.9 17.8 16.8 17.1 77.4 75.6 76.7 77.7 77.7 10.3 5.5 5.2 5.1 5.5 0 0 0 0 0 40.9 42.4 41.8 41.7 42.4 18.6 18.9 20 20 19.6 4.9 7.1 4.8 11.4 2.3 8.1 13.4 11.6 14.4 14.6 87 86.6 87.8 87.7 88 5.1 5.4 4.3 4.3 4.1 27.6 28.3 27.4 29.1 28.5 0 0 0 0 0 61.5 56.7 51.8 51 52.8 0.2 0.1 0.2 0.2 0.2 29.3 32.1 34.1 29.6 21.9 0 0 5 3.2 2.6 83.5 83.6 83.8 83.5 81.1 4.5 4.5 4.5 4.7 5.4 8.9 18.2 13.7 18.3 44.7 0 0 0 0 0 82 81.1 74.9 72.7 68.2 n/a n/a n/a n/a n/a 15.7 11.7 5.6 1.4 6.8 0 0 0 0 0 44.9 46.7 50.7 51.7 56.7 39.6 31.1 29 25.9 21 Basic indicators 2006 17

Per capita expenditure on health, 1999 2003 Figures computed to assure comparability; a they are not necessarily the official statistics of Member States, which may use alternative methods Member State Per capita total expenditure on health at average exchange rate (US$) Per capita total expenditure on health at international dollar rate Per capita government expenditure on health at average exchange rate (US$) Per capita government expenditure on health at international dollar rate 1999 2000 2001 2002 2003 1999 2000 2001 2002 2003 1999 2000 2001 2002 2003 1999 2000 2001 2002 2003 1 Algeria 61 63 68 75 89 137 132 149 174 186 43 46 53 60 71 99 97 115 137 150 2 Angola 15 16 21 18 26 43 34 48 41 49 7 13 18 15 22 20 28 41 33 41 3 Benin 16 15 16 16 20 34 34 38 37 36 7 7 7 7 9 15 15 18 16 16 4 Botswana 138 152 132 144 232 259 294 284 312 375 75 87 67 78 135 141 168 143 169 218 5 Burkina Faso 15 12 12 15 19 55 54 55 62 68 6 5 5 6 9 24 23 22 27 32 6 Burundi 4 3 3 3 3 14 14 15 15 15 1 1 1 1 1 3 3 3 3 4 7 Cameroon 31 29 29 32 37 62 58 62 66 64 8 8 8 9 11 15 16 17 18 19 8 Cape Verde 61 55 61 66 78 148 163 186 193 185 45 41 46 50 57 110 119 141 145 135 9 Central African Republic 10 10 10 11 12 44 50 49 51 47 4 4 4 4 5 17 20 19 21 18 10 Chad 11 11 12 12 16 37 40 43 44 51 4 4 5 4 7 12 17 18 16 20 11 Comoros 11 8 7 10 11 30 25 21 27 25 6 4 3 6 6 18 14 10 16 14 12 Congo 17 17 16 16 19 25 20 23 22 23 11 11 10 11 12 16 13 15 15 15 13 Côte d Ivoire 39 30 24 25 28 87 79 65 62 57 7 6 4 8 8 15 16 12 20 16 14 Democratic Republic of Congo 8 10 4 3 4 12 13 10 11 14 1 1 <1 <1 1 1 1 1 1 3 15 Equatorial Guinea 46 54 67 85 96 125 106 152 193 179 28 37 47 61 65 76 72 107 139 121 16 Eritrea 8 8 8 7 8 47 48 53 51 50 6 5 5 4 4 33 32 31 26 23 17 Ethiopia 5 5 5 5 5 17 19 21 21 20 3 3 3 3 3 9 10 11 12 12 18 Gabon 165 164 148 158 196 250 229 235 244 255 113 120 108 111 130 171 167 171 171 170 19 Gambia 24 25 23 20 21 76 88 92 84 96 8 10 9 8 8 24 36 37 34 38 20 Ghana 22 13 12 14 16 100 102 94 95 98 8 5 4 4 5 35 36 27 29 31 21 Guinea 20 18 17 19 22 74 76 81 90 95 3 2 3 3 4 10 10 15 13 16 22 Guinea-Bissau 8 6 6 9 9 45 38 38 49 45 2 2 1 4 4 13 9 8 20 21 23 Kenya 16 18 18 19 20 60 61 62 66 65 7 8 8 8 8 25 28 27 29 25 24 Lesotho 28 28 24 25 31 91 100 103 125 106 23 23 20 21 25 74 83 84 104 84 25 Liberia 10 8 7 7 6 26 23 21 20 17 6 5 3 3 4 18 13 10 10 10 26 Madagascar b 5 5 5 7 8 20 20 19 24 24 3 3 3 5 5 11 10 12 15 15 27 Malawi 16 13 15 15 13 47 41 48 44 46 6 4 7 5 5 17 12 22 15 16 28 Mali 11 11 11 12 16 27 32 32 35 39 5 5 5 6 9 11 16 16 18 22 29 Mauritania 10 9 10 14 17 32 32 38 53 59 7 6 7 10 13 21 20 26 39 46 30 Mauritius 113 127 132 143 172 281 331 373 398 430 70 74 80 87 105 174 194 226 242 261 31 Mozambique 11 12 10 11 12 34 40 39 45 45 7 8 6 7 7 21 27 26 30 28 32 Namibia 127 126 107 95 145 328 340 323 318 359 93 87 75 65 101 240 235 224 218 252 33 Niger 8 6 6 7 9 27 25 26 27 30 4 3 3 4 5 14 13 14 15 16 34 Nigeria 17 18 19 19 22 48 39 50 49 51 5 6 6 5 6 14 13 16 12 13 35 Rwanda 11 10 8 9 7 33 32 31 35 32 5 3 3 4 3 16 11 12 17 14 36 Sao Tome and Principe 34 29 35 31 34 94 84 107 95 93 30 25 30 26 29 82 72 92 81 78 37 Senegal 21 18 20 23 29 44 45 51 55 58 8 7 8 9 12 16 16 19 22 24 38 Seychelles 431 405 403 456 522 548 555 535 554 599 322 304 301 342 382 410 417 400 415 439 39 Sierra Leone 5 5 6 7 7 19 24 25 32 34 2 3 3 4 4 9 13 13 21 20 40 South Africa 257 236 216 198 295 595 579 626 649 669 105 100 89 80 114 244 245 258 263 258 41 Swaziland 87 83 73 68 107 305 302 308 315 324 51 48 42 40 61 180 177 178 187 185 42 Togo 16 11 13 13 16 59 49 58 54 62 7 3 3 2 4 24 14 15 10 15 43 Uganda 16 16 17 18 18 55 60 70 75 75 5 4 5 5 5 17 16 19 23 23 44 United Republic of Tanzania 11 12 12 12 12 23 25 27 28 29 5 6 6 6 7 10 12 13 15 16 45 Zambia 17 17 19 20 21 45 46 51 53 51 8 9 11 11 11 22 23 29 30 26 46 Zimbabwe 36 44 65 132 40 185 168 184 161 132 17 21 25 50 14 91 81 71 61 47 a See explanatory notes for sources and methods. b The currency now called Ariary is worth one fifth of the Francs previously used. 18 Health situation analysis in the African Region

Explanatory notes The following provides the definition of the health statistics categories included in this statistical annex, as well as the rationale for including them and the estimation methods used to produce them. 1. Life expectancy at birth Rationale for use: life expectancy at birth reflects the overall mortality level of a population. It summarizes the mortality pattern that prevails across all age groups children and adolescents, adults and the elderly. Definition: average number of years that a newborn is expected to live if current mortality rates continue to apply. Methods of estimation: WHO has developed a model life table based on about 1800 life tables from vital registration judged to be of good quality. For countries with vital registration, the level of completeness of recorded mortality data in the population is assessed and mortality rates are adjusted accordingly. Where vital registration data for 2003 were available, these were used directly to construct the life table. For countries where the information system provided a time series of annual life tables, parameters from the life table were projected using a weighted regression model, giving more weight to recent years. Projected values of the two life table parameters were then applied to the modified logit life table model, where the most recent national data provided an age pattern, to predict the full life table for 2003. In case of inadequate sources of age-specific mortality rates, the life table is derived from estimated under-5 mortality rates and adult mortality rates that are applied to a global standard (defined as the average of all the 1800 life tables using a modified logit model.) 2. Healthy life expectancy (HALE) Rationale for use: substantial resources are devoted to reducing the incidence, duration and severity of major diseases that cause morbidity but not mortality and to reducing their impact on people s lives. It is important to capture both fatal and non-fatal health outcomes in a summary measure of average levels of population health. Healthy life expectancy (HALE) at birth adds up expectation of life for different health states, adjusted for severity distribution making it sensitive to changes over time or differences between countries in the severity distribution of health states. Definition: average number of years that a person can expect to live in full health by taking into account years lived in less than full health due to disease and/or injury. Methods of estimation: since comparable health state prevalence data are not available for all countries, a four-stage strategy is used. Data from the WHOGBD study are used to estimate severity-adjusted prevalence by age and sex for all countries. Data from the WHOMCSS and WHS are used to make independent estimates of severity-adjusted prevalence by age and sex for survey countries. Prevalence for all countries is calculated based on GBD, MCSS and WHS estimates. Life tables constructed by WHO are used with Sullivan s method to compute HALE for countries. 3. Probability of dying (per 1000) between ages 15 and 60 years (adult mortality rate) Rationale for use: disease burden from noncommunicable diseases among adults the most economically productive age span is rapidly increasing in developing countries due to ageing and health transitions. Therefore, the level of adult mortality is becoming an important indicator for the comprehensive assessment of the mortality pattern in a population. Definition: probability that a 15-year-old person will die before reaching his/her 60th birthday. 4. Life table (see life expectancy at birth). Data sources: civil or sample registration: Mortality by age and sex are used to calculate age specific rates. Census: Mortality by age and sex tabulated from questions on recent deaths that occurred in the household during a given period preceding the census (usually 12 months). Census or surveys: Direct or indirect methods provide adult mortality rates based on information on survival of parents or siblings. Methods of estimation: empirical data from different sources are consolidated to obtain estimates of the level and trend in adult mortality by fitting a curve to the observed mortality points. However, to obtain the best possible estimates, judgement needs to be made on data quality and how representative it is of the population. Recent statistics based on data availability in most countries are point estimates dated by at least 3 4 years which need to be projected forward in order to obtain estimates of adult mortality for the current year. When no adequate source of age-specific mortality exists, the life table is derived as described in the life expectancy indicator. 5. Probability of dying (per 1000) under age five years (under-five mortality rate) 6. Probability of dying (per 1000) under age one year (infant morality rate) Rationale for use: under-five mortality rate and infant mortality rate are leading indicators of the level of child health and overall development in countries. They are also MDG indicators. Definition: under-five mortality rate is the probability of a child born in a specific year or period dying before reaching the age of five, if subject to agespecific mortality rates of that period. Infant mortality rate is the probability of a child born in a specific year or period dying before reaching the age of one, if subject to age-specific mortality rates of that period. Methods of estimation: empirical data from different sources are consolidated to obtain estimates of the level and trend in under-five mortality by fitting a curve to the observed mortality points. However, to obtain the best possible estimates, judgement needs to be made on data quality and how representative it is of the population. Recent statistics based on data availability in most countries are point estimates dated by at least 3 4 years which need to be projected forward in order to obtain estimates of under-five mortality for the current year. Those are then converted to their corresponding infant mortality rates through model life table systems: the one developed by WHO for countries with adequate vital registration data; Coale-Demeny model life tables for the other countries. It should be noted that the infant mortality from surveys are exposed to recall bias, hence their estimates are derived from under-five mortality, which leads to a supplementary step to estimate infant mortality rates. 6. Neonatal mortality rate (per 1000 live births) Rationale for use: neonatal deaths account for a large proportion of child deaths. Mortality during neonatal period is considered a useful indicator of both maternal and newborn health and care. Definition: number of deaths during the first 28 completed days of life per 1000 live births in a given year or period. Neonatal deaths may be subdivided Basic indicators 2006 19

into early neonatal deaths, occurring during the first seven days of life, and late neonatal deaths, occurring after the seventh day but before the 28 completed days of life. 7. Maternal mortality ratio (per 100 000 live births) Rationale for use: complications during pregnancy and childbirth are leading causes of death and disability among women of reproductive age in developing countries. Maternal mortality ratio (MMR) represents the risk associated with each pregnancy, i.e. the obstetric risk. It is also an MDG indicator for monitoring goal 5 of improving maternal health. Definition: number of maternal deaths per 100 000 live births during a specified time period, usually one year. Methods of estimation: measuring maternal mortality accurately is difficult except where comprehensive registration of deaths and their causes exist. Elsewwhere, censuses or surveys can be used to measure levels of maternal mortality. Data derived from health services records are problematic where not all births take place in health facilities because of biases whose dimensions and direction cannot be determined. Reproductive-age mortality studies (RAMOS) use triangulation of different sources of data on deaths of women of reproductive age including record review and/or verbal autopsy to accurately identify maternal deaths. Based on multiple sources of information, RAMOS are considered the best way to estimate levels of maternal mortality. Estimates derived from household surveys are usually based on information retrospectively collected about the deaths of sisters of the respondents and could refer back up to an average 12 years and they are subject to wide confidence intervals. For countries without any reliable data on maternal mortality, statistical models are applied. Global and regional estimates of maternal mortality are developed every five years, using a regression model. 8. Estimated rate of adults (15 years and older) dying of HIV/AIDS (per 1000) 9. Estimated rate of children below 15 years of age dying of HIV/AIDS (per 1000) Rationale for use: adult and children below 15 mortality rate are leading indicators of the level of impact of HIV/AIDS epidemic and impact of interventions specially scale up of treatment and prevention to mother to child transmission in countries. Definition: estimated mortality due to HIV/AIDS is the number of adults and children that have died in a specific year based in the modeling of HIV surveillance data using standard and appropriate tools. Methods of estimation: empirical data from different HIV surveillance sources are consolidated to obtain estimates of the level and trend in adults and children mortality by using standard methods and tools for HIV estimates appropriate to the level of HIV epidemic. However, to obtain the best possible estimates, judgement needs to be made on data quality and how representative it is of the population. UNAIDS/WHO produce country specific estimates every two years. 9. Tuberculosis mortality Rationale for use: prevalence and mortality are direct indicators of the burden of tuberculosis (TB), indicating the number of people suffering from the disease at a given point in time, and the number dying each year. Furthermore, prevalence and mortality respond quickly to improvements in control, as timely and effective treatment reduce the average duration of disease (thus decreasing prevalence) and the likelihood of dying from the disease (thus reducing diseasespecific mortality). Definition: estimated number of deaths due to TB in given time period. Expressed in this database as deaths per 100 000 population per year. Includes deaths from all forms of TB, and deaths from TB in people with HIV. Methods of estimation: estimates of TB incidence, prevalence and mortality are based on a consultative and analytical process in WHO and are published annually. The methods used to estimate TB mortality rates are described in detail elsewhere. Country-specific estimates of TB mortality are, in most instances, derived from estimates of incidence, combined with assumptions about the case fatality rate. The case fatality rate is assumed to vary according to whether the disease is smear-positive or not; whether the individual receives treatment in a DOTS programme or non-dots programmes, or is not treated at all; and whether the individual is infected with HIV. 10. Age-standardized death rates per 100 000 by cause Rationale for use: the numbers of deaths per 100 000 population are influenced by the age distribution of the population. Two populations with the same age-specific mortality rates for a cause of death will have different overall death rates if the age distributions of their populations are different. Age-standardiized mortality rates adjust for differences in population age distribution by applying the observed age-specific mortality rates for each population to a standard population. Definition: the age-standardized mortality rate is a weighted average of the age-specific mortality rates per 100 000 persons, where the weights are the proportions of persons in the corresponding age groups of the WHO standard population. 11. Years of life lost (percentage of total) Rationale for use: years of life are lost (YLL) take into account the age at which deaths occur by giving greater weight to deaths at younger age and lower weight to deaths at older age. The years of life lost (percentage of total) indicator measures the YLL due to a cause as a proportion of the total YLL lost in the population due to premature mortality. Definition: YLL are calculated from the number of deaths multiplied by a standard life expectancy at the age at which death occurs. The standard life expectancy used for YLL at each age is the same for deaths in all regions of the world and is the same as that used for the calculation of disability-adjusted-lifeyears (DALY). Additionally 3% time discounting and non-uniform age weights which give less weight to years lived at young and older ages were used as for the DALY. With non-uniform age weights and 3% discounting, a death in infancy corresponds to 33 YLL, and deaths at ages 5 to 20 to around 36 YLL. 12. The disability-adjusted-life-year or DALY DALY is a health gap measure that extends the concept of potential years of life lost due to premature death (PYLL) to include equivalent years of healthy life lost by virtue of being in states of poor health or disability (1). DALYs for a disease or health condition are calculated as the sum of the years of life lost due to premature mortality (YLL) in the population and the years lost due to disability (YLD) for incident cases of the health condition. Methods of estimation: life tables specifying all-cause mortality rates by age and sex for 192 WHO Member States were developed for 2002 from availaable death registration data, sample registration systems (India, China) and data on child and adult mortality from censuses and surveys. Cause of death distributions were estimated from death registration data for 107 countries, together with data from population-based epidemiological studies, disease registers and notifications systems for selected specific causes of death. Causes of death for populations without useable death registration data were estimated using cause-of-death models together with data from population-based epidemiological studies, disease registers and notifications systems for 21 specific causes of death. 20 Health situation analysis in the African Region

13. Causes of death among children under five years of age (percentage) Rationale for use: MDG4 consists in the reduction of under-five mortality by two-thirds in 2015, from its level in 1990. Child survival efforts can be effective only if they are based on reasonably accurate information about the causes of childhood deaths. Cause-of-death information is needed to prioritize interventtions and plan for their delivery, to determine the effectiveness of disease-specific interventions, and to assess trends in disease burden in relation to national and international goals. Definition: the cause(s) of death (CoD) as entered on the medical certificate of cause of death in countries with civil (vital) registration system. The underlying CoD is being analysed. In countries with incomplete or no civil registration, causes of death are those reported as such in epidemiological studies that use verbal autopsy algorithms to establish CoD. Methods of estimation: CoD data from civil registration systems were evaluated for their completeness. Complete and nationally-representative data were then grouped by ICD codes into the cause categories and their proportions to total under-five deaths were then computed. For countries with incomplete data or no data, the distribution of deaths by cause was estimated in two steps. In the first step, a statistical model was used to assign deaths to one of three broad categories of causes: communicable diseases; noncommunicable diseases; or injuries and external causes. In a second step, cause-specific under-five mortality estimates from Child Health Epidemiology Reference Group (CHERG), WHO Technical Programmes, and the Joint United Nations Programme on HIV/AIDS (UNAIDS) were taken into account in assigning the distribution of deaths to specific causes. A variety of methods, including proportional mortality and natural history models, were used by CHERG and WHO to develop country-level cause-specific mortality estimates. All CHERG working groups developed comparable and standardized procedures to generate estimates from the databases. 14. HIV prevalence among the population aged 15 49 years Rationale for use: HIV and AIDS has become a major public health problem in many countries and monitoring the course of the epidemic and impact of interventions is crucial. Both the Millenium Development Goals (MDG) and the United Nations General Assembly Special Session on HIV and AIDS (UNGAS) have set goals of reducing HIV prevalence. Definition: percent of people with HIV infection among all people aged 15 49 years. Methods of estimation: HIV prevalence data from HIV sentinel surveillance systems, which may include national population surveys with HIV testing, are used to estimate HIV prevalence using standardized tools and methods of estimation developed by UNAIDS and WHO in collaboration with the UNAIDS Reference Group on Estimation, Modelling and Projections. Tools for estimating the level of HIV infection are different for generalized epidemics, and concenttrated or low level epidemic. 15. Incidence of tuberculosis Rationale for use: incidence (cases arising in a given time period) gives an indication of the burden of tuberculosis (TB) in a population, and of the size of the task faced by a national TB control programme. Incidence can change as the result of changes in transmission (the rate at which people become infected with M. tuberculosis, the bacterium which causes TB), or changes in the rate at which people infected with M. tuberculosis develop TB disease (e.g. as a result of changes in nutritional status or of HIV infection). Because TB can develop in people who became infected many years previously, the effect of TB control on incidence is less immediate than the effect on prevalence or mortality. Millennium Development Goal 6, Target 8 is have halted by 2015 and begun to reverse the incidence of TB. WHO estimates that in 2004 the per capita incidence of TB was stable or falling in 5 out of 6 WHO regions, but growing globally at 0.6% per year. The exception was the African Region, where incidence is apparently still increasing, but less rapidly each year. Implementation of the Stop TB Strategy, following the Global Plan to Stop TB 2006 2015, is expected to reverse the rise in incidence globally by 2015. Definition: estimated number of TB cases arising in a given time period (expressed as per capita rate). All forms of TB are included, as are cases in people with HIV. Methods of estimation: estimates of TB incidence, prevalence and mortality are based on a consultative and analytical process in WHO and are published annually. Estimates of incidence for each country are derived using one or more of four approaches, depending on the available data: 1. incidence = case notifications / proportion of cases detected 2. incidence = prevalence / duration of condition 3. incidence = annual risk of TB infection x Stýblo coefficient 4. incidence = deaths / proportion of incident cases that die. 16. Prevalence of tuberculosis Rationale for use: prevalence and mortality are direct indicators of the burden of tuberculosis (TB), indicating the number of people suffering from the disease at a given point in time, and the number dying each year. Furthermore, prevalence and mortality respond quickly to improvements in control, as timely and effective treatment reduce the average duration of disease (thus decreasing prevalence) and the likelihood of dying from the disease (thus reducing diseasespecific mortality). Millennium Development Goal 6 is to combat HIV/AIDS, malaria and other diseases [including TB]. This goal is linked to Target 8 to have halted by 2015 and begun to reverse the incidence of malaria and other major diseases and MDG Indicator 24 prevalence and mortality rates associated with TB. The Stop TB Partnership has endorsed the related targets of reducing per capita TB prevalence and mortality by 50% relative to 1990, by the year 2015. There are few good data with which to establish TB prevalence and mortality, particularly for the baseline year of 1990. However, current best estimates suggest that implementation of the Global Plan to Stop TB 2006 2015 will halve 1990 prevalence and mortality rates globally and in most regions by 2015, though not in Africa and eastern Europe. Definition: the number of cases of TB (all forms) in a population at a given point in time (sometimes referred to as point prevalence ) expressed in this database as number of cases per 100 000 population. Methods of estimation: estimates of TB incidence, prevalence and mortality are based on a consultative and analytical process in WHO and are published annually. The methods used to estimate TB prevalence and mortality rates are described in detail elsewhere. Country-specific estimates of prevalence are, in most instances, derived from estimates of incidence [please link to incidence page of compendium], combined with assumptions about the duration of disease. The duration of disease is assumed to vary according to whether the disease is smear-positive or not; whether the individual receives treatment in a DOTS programme, non-dots programmes, or is not treated at all; and whether the individual is infected with HIV. 17. Number of poliomyelitis cases Rationale for use: the 1988 World Health Assembly (WHA) called for the global eradication of poliomyelitis. The number of poliomyelitis cases is used to monitor progress towards this goal and to inform eradication strategies. Countries implement strategies supplementing routine immunization e.g. national immunization days and sub-national campaigns or more targeted mop-up activities, depending on the levels of poliomyelitis cases. Definition: suspected polio cases (acute-flaccid paralysis AFP, other paralytic diseases, and contacts with polio cases) that are confirmed by laboratory examination or are consistent with polio infection. Methods of estimation: estimates of polio cases are based exclusively on unadjusted surveillance data. Basic indicators 2006 21

18. One-year-olds immunized with: one dose of measles (%) three doses of diphtheria, tetanus toxoid and pertussis (DTP3) (%) three doses of hepatitis B (HepB3 )(%) Rationale for use: immunization coverage estimates are used to monitor immunization services, to guide disease eradication and elimination efforts, and are a good indicator of health systems performance. Definition: measles immunization coverage is the percentage of one-year-olds who have received at least one dose of measles containing vaccine in a given year. For countries recommending the first dose of measles among children older than 12 months of age, the indicator is calculated as the proportion of children less than 24 months of age receiving one dose of measles containing vaccine. DTP3 immunization coverage is the percentage of one-year-olds who have received three doses of the combined diphtheria and tetanus toxoid and pertussis vaccine in a given year. HepB3 immunization coverage is the percentage of one-year-olds who have received three doses of Hepatitis B3 vaccine in a given year. Methods of estimation: WHO and UNICEF rely on reports from countries, household surveys and other sources such as research studies. Both organizattions have developed common review process and estimation methodologies. Draft estimates are made, reviewed by country and external experts and then finalized. 19. Antenatal care coverage (%) Rationale for use: antenatal care coverage is an indicator of access and utilization of health care during pregnancy. Definition: percentage of women who utilized antenatal care provided by skilled health personnel for reasons related to pregnancy at least once during pregnancy as a percentage of live births in a given time period. Methods of estimation: empirical data from household surveys are used. At global level, facility data are not used. 20. Births attended by skilled health personnel (%) Rationale for use: all women should have access to skilled care during pregnancy and at delivery to ensure detection and management of complications. Moreoover, because it is difficult to measure accurately maternal mortality and model-based maternal mortality ratio (MMR) estimates cannot be used for monitoring short -term trends. The proportion of births attended by skilled health personnel is used as a proxy indicator for this purpose. Definition: percentage of live births attended by skilled health personnel in a given period of time. Methods of estimation: empirical data from household surveys are used. At global level, facility data are not used. 21. Contraceptive prevalence (%) Rationale for use: contraceptive prevalence is an indicator of health, population, development and women s empowerment. It also serves as a proxy measure of access to reproductive health services that are essential for meeting many of the Millennium Development Goals (MDG)s, especially the child mortality, maternal health HIV/AIDS, and gender related goals. Definition: contraceptive prevalence is the proportion of women of reproductive age who are using (or whose partner is using) a contraceptive method at a given point in time Methods of estimation: empirical data only. 22. Children under five years of age sleeping under insecticide-treated nets (%) Rationale for use: in areas of intense malaria transmission, malaria-related morbidity and mortality are concentrated in young children, and the use of insectticide-treated nets (ITN) by children under 5 years of age has been demonstrated to considerably reduce malaria disease incidence, malaria-related anaemia and all-cause under-5 mortality. Vector control through the use of ITNs constitute one of the four intervention strategies of the Roll Back Malaria Initiative. It is also listed as an MDG indicator. Definition: percentage of children under five years of age in malaria endemic areas who slept under an ITN the previous night, ITN being defined as a mosquito net that has been treated within 12 months or is a long-lasting insecticidal net (LLIN). Methods of estimation: empirical data only. 23. People with advanced HIV infection receiving antiretroviral (ARV) combination therapy (%) Rationale for use: as the HIV epidemic matures, increasing numbers of people are reaching advanced stages of HIV infection. ARV combination therapy has been shown to reduce mortality among those infected and efforts are being made to make it more affordable even in less developed countries. This indicator assesses the progress in providing ARV combination therapy to everyone with advanced HIV infection. Definition: percentage of people with advanced HIV infection receiving ARV therapy according to nationally approved treatment protocol (or WHO/Joint UN Programme on HIV and AIDS standards) among the estimated number of people with advanced HIV infection. Methods of estimation: the denominator of the coverage estimate is obtained from models that also generate the HIV prevalence, incidence and mortality estimates. The number of adults with advanced HIV infection who need to start treatment is estimated as the number of AIDS cases in the current year times two. The total number of adults needing ARV therapy is calculated by adding the number of adults that need to start ARV therapy to the number of adults who are being treated in the previous year and have survived into the current year. 24. Tuberculosis: DOTS case detection rate Rationale for use: the proportion of estimated new smear-positive cases which are detected (diagnosed and notified to WHO) by DOTS programmes provides an indication of how effective national tuberculosis programmes are in finding people with tuberculosis and diagnosing the disease. Methods of estimation: estimates of incidence are based on a consultative and analytical process in WHO and are published annually. The DOTS detecttion rate for new smear-positive cases is calculated by dividing the number of new smear-positive cases notified to WHO by the estimated number of incident smear-positive cases for the same year. 25. Tuberculosis: DOTS treatment success Rationale for use: treatment success is an indicator of the performance of national tuberculosis control programmes. In addition to the obvious benefit to individual patients, successful treatment of infectious cases of TB is essential to prevent the spread of the infection. Detecting and successfully treating a large proportion of TB cases should have an immediate impact on TB prevalence and mortality. By reducing transmission, successfully treating the majority of cases will also affect, with some delay, the incidence of disease. 22 Health situation analysis in the African Region

Definition: the proportion of new smear-positive TB cases registered under DOTS in a given year that successfully completed treatment, whether with bacteriologic evidence of success ( cured ) or without ( treatment completed ). At the end of treatment, each patient is assigned one of the following six muttually exclusive treatment outcomes: cured; completed; died; failed; defaulted; and transferred out with outcome unknown. The proportions of cases assigned to these outcomes, plus any additional cases registered for treatment but not assigned to an outcome, add up to 100% of cases registered. 26. Children under five years of age with acute respiratory infection and fever (ARI) taken to facility Rationale for use: respiratory infections are responsible for almost 20% of all under-five deaths worldwide. Under-fives with ARI that are taken to an appropriate health provider is a key indicator for both coverage of intervention and care-seeking and provides critical inputs to the monitoring of progress towards the child survival related millennium development goals (MDGs) and strategies. Definition: proportion of children aged 0-59 months who had presumed pneumonia (ARI) in the last two weeks and were taken to an appropriate health provider. Methods of estimation: empirical data. 27. Children under five years of age with diarrhoea who received ORT Rationale for use: diarrhoeal diseases remain one of the major causes of under-five mortality, accounting for 1.8 million child deaths worldwide, despite all the progress in their management and the undeniable success of the oral rehydration therapy (ORT). Therefore, the monitoring of the coverage of this very costeffective intervention is crucial for the monitoring of progress towards the child survival related Millennium Development Goals (MDGs) and strategies. Definition: proportion of children aged 0 59 months of age who had diarrhoea in the last two weeks and were treated with oral rehydration salts or an appropriate household solution (ORT) Methods of estimation: empirical data. 28. Children under five years of age with fever who received treatment with any antimalarial (%) Rationale for use: prompt treatment with effective anti-malaria drugs for children with fever in malaria risk areas is a key intervention to reduce mortality. In addition to be listed as a global MDG indicator under Goal 6, malaria effective treatment is also identified by WHO, UNICEF, and the World Bank as one of the four main interventions to reduce the burden of malaria in Africa: (i) use of insecticide-treated nets (ITNs), (ii) prompt access to effective treatments in or near the home, (iii) providing antimalarial drugs to symptom-free pregnant women in stable transmission areas, and (iv) improved forecasting, prevention and response, essential to respond quickly and effectively to malaria epidemics. In areas of sub-saharan Africa with stable levels of malaria transmission, it is essential that access to prompt treatment is ensured. This requires drug availability at household or community level and, for complicated cases, availability of transport to the nearest equipped facility. Reserve drug stocks, transport, and hospital capacity are needed to mount an appropriate response to malaria cases and prevent the onset of malaria to degenerate to a highly lethal complicated malaria picture. Definition: percentage of population under five years of age in malaria-risk areas with fever being treated with effective antimalarial drugs. Methods of estimation: for prevention, the indicator is calculated as the percentage of children under five years of age who received effective anti-malaria drugs upon a fever episode. The information is obtained directly from household surveys. The empiric values are directly reported without further estimation. 29. Children 6 59 months of age who received vitamin A supplementation Rationale for use: vitamin A supplementation is considered a critically important intervention for child survival due to the strong evidence that exists of its impact on child mortality. Therefore, measuring the proportion of children who have received vitamin A in the last six months is crucial for monitoring coverage of interventions towards the child survival related MDGs and strategies. Definition: proportion of children 6 59 months of age who have received a high dose vitamin A supplement in the last 6 months Methods of estimation: empirical data. 30. Births by caesarean section (%) Rationale for use: births by caesarean section is an indicator of access to and utilization of health care during childbirth. Definition: percentage of births by caesarean section among all live births in a given time period. Methods of estimation: empirical data from household surveys are used. 31. Children under five years of age - stunted for age (%) - underweight for age (%) - overweight for age (%) Rationale for use: all three indicators measure growth in young children. Child growth is internationally recognized as an important public health indicattor for monitoring nutritional status and health in populations. In addition, children who suffer from growth retardation as a result of poor diets and/or recurrent infections tend to have greater risks of illness and death. Definition: percentage of children stunted describes how many children under five years have a height-for-age below minus two standard deviations of the National Center for Health Statistics (NCHS)/WHO reference median. Percentage of children underweight describes how many children under five years have a weight-for-age below minus two standard deviations of the NCHS/WHO reference median. Percentage of children overweight describes how many children under five years have a weight-for-height above two standard deviations of the NCHS/WHO reference median. Methods of estimation: empirical values are used. Several countries have limited data for recent years and current estimations are made using models that make projections based on past trends. 32. Newborns with low birth weight (%) Rationale for use: the low-birth-weight rate at the population level is an indicator of a public health problem that includes long-term maternal malnutrition, ill-health and poor health care. On an individual basis, low birth weight is an important predictor of newborn health and survival. Definition: percentage of live born infants with birth weight less than 2500 g in a given time period. Low birth weight may be subdivided into very low birth weight (less than 1500 g) and extremely low birth weight (less than 1000 g). Basic indicators 2006 23

Methods of estimation: where reliable health service statistics with a high level of coverage exist ; Percentage of low birth weight births. For househhold survey data different adjustments are made according to the type of information available (numerical birth weight data or subjective assessment of the mother). 33. Prevalence of adults (15 years and older) who are obese (%) Rationale for use: the prevalence of overweight and obesity in adults has been increasing globally. Obese adults (BMI = 30.0) are at increased risk of adverse metabolic outcomes including increased blood pressure, cholesterol, triglycerides, and insulin resistance. Subsequently, an increase in BMI exponentially increases the risk of noncommunicable diseases (NCDs), such as coronary heart disease, ischaemic stroke and type-2 diabetes mellitus. Raised BMI is also associated with an increased risk of cancer. Definition: percentage of adults classified as obese (BMI = 30.0 kg/m²) among total adult population (15 years and older). Methods of estimation: estimates are still under development and will be published later in 2006. Only nationally representative surveys with either anthropometric data collection or self-reported weight and height (mostly in high income countries) are included in the 2006 World health statistics. 34. Population with: - sustainable access to an improved water source (%) - access to improved sanitation (%) Rationale for use: access to drinking water and improved sanitation is a fundamental need and a human right vital for the dignity and health of all people. The health and economic benefits of improved water supply to households and individuals (especially children) are well documented. Both indicators are used to monitor progress towards the MDGs. Definition: access to an improved water source is the percentage of population with access to an improved drinking water source in a given year. Access to improved sanitation is the percentage of population with access to improved sanitation in a given year. Methods of estimation: estimates are generated through analysis of survey data and linear regression of data points. Coverage estimates are updated every two years. 35. Population using solid fuels (%) Rationale for use: the use of solid fuels in households is associated with increased mortality from pneumonia and other acute lower respiratory diseases among children as well as increased mortality from chronic obstructive pulmonary disease and lung cancer (where coal is used) among adults. It is also a Millennium Development Goal indicator. Definition: percentage of population using solid fuels. Methods of estimation: the data from surveys and censuses are used as reported in the surveys and censuses. All countries with a Gross National Income (GNI) per capita above US$ 10 500 are assumed to have made a complete transition to cooking with non-solid fuels. For low- and middle-income countries with a GNI per capita below US$ 10 500 and for which no household solid fuel use data are available, a regression model based on GNI, percentaage of rural population and location or non-location within the Eastern Mediterranean Region is used to estimate the indicator. 36. Prevalence of current tobacco use in adolescents (13 15 years of age) Rationale for use: the risk of chronic diseases starts early in childhood and tobacco use continues to adulthood. Tobacco is an addictive substance and smokiing often starts in adolescence, before the development of risk perception. By the time the risk to health is recognized, the addicted individuals find it difficult to stop tobacco use. Definition: prevalence of tobacco use (including smoking, oral tobacco and snuff) on more than one occasion in the 30 days preceding the survey, among adolescent 13 15 year olds. 37. Prevalence of current (daily or occasional) tobacco smoking among adults (15 years and older) (%) Rationale for use: prevalence of current tobacco smoking among adults is an important measure of the health and economic burden of tobacco, and provides a baseline for evaluating the effectiveness of tobacco control programmes over time. While a more general measure of tobacco use, including both smoked and smokeless products, would be ideal, data limitations restrict the present indicator to smoked tobacco. Occasional tobacco smoking constitutes a significant risk factor for tobacco-related disease, and is therefore included along with daily tobacco smoking. Definition: prevalence of current tobacco smoking (including cigarettes, cigars, pipes or any other smoked tobacco products). Current smoking includes both daily and non-daily or occasional smoking. Methods of estimation: empirical data only. 38. Condom use at higher risk sex among young people aged 15 24 years (percentage) Rationale for use: consistent correct use of condoms within non-regular sexual partnerships substantially reduces the risk of sexual HIV transmission. Definition: percentage of young people aged 15 24 years reporting the use of a condom during the last sexual intercourse with a non-regular partner among those who had sex with a non-regular partner in the last 12 months. Methods of estimation: empirical data only. Survey respondents aged 15-24 years are asked whether they have commenced sexual activity. Those who report sexual activity and have had sexual intercourse with a non-regular partner in the last 12 months, are further asked about the number of non-regular partners and condom use the last time they had sex with a non-regular partner. 39. Number of: -physicians per 1000 population -nurses per 1000 population -midwives per 1000 population -dentists per 1000 population -pharmacists per 1000 population -public and environmental health workers per 1000 population -community health workers per 1000 population 24 Health situation analysis in the African Region

-laboratory health workers per 1000 population -other health workers per 1000 population -health management and support workers per 1000 population Rationale for use: the availability and composition of human resources for health is an important indicator of the strength of the health system. Even though there is no consensus about the optimal level of health workers for a population, there is ample evidence that worker numbers and quality are positively associated with immunization coverage, outreach of primary care, and infant, child and maternal survival. Definition: Physicians: includes generalists and specialists. Nurses: includes professional nurses, auxiliary nurses, enrolled nurses and other nurses, such as dental nurses and primary care nurses. Midwives: includes professional midwives, auxiliary midwives and enrolled midwives. Traditional birth attendants, who are counted as community health workers, appear elsewhere. Dentists: includes dentists, dental assistants and dental technicians. Pharmacists: includes pharmacists, pharmaceutical assistants and pharmaceutical technicians. Laboratory health workers: includes laboratory scientists, laboratory assistants, laboratory technicians and radiographers. Environment and public health workers: includes environmental and public health officers, sanitarians, hygienists, environmental and public health technicians, district health officers, malaria technicians, meat inspectors, public health supervisors and similar professions. Community health workers: includes traditional medicine practitioners, faith healers, assistant/community health education workers, community health officers, family health workers, lady health visitors, health extension package workers, community midwives, institution-based personal care workers and traditional birth attendants. Other health workers: includes a large number of occupations such as dieticians and nutritionists, medical assistants, occupational therapists, operators of medical and dentistry equipment, optometrists and opticians, physiotherapists, podiatrists, prosthetic/orthetic engineers, psychologists, respiratory therapists, speech pathologists, medical trainees and interns. Health management and support workers: includes general managers, statisticians, lawyers, accountants, medical secretaries, gardeners, computer techniccians, ambulance staff, cleaning staff, building and engineering staff, skilled administrative staff and general support staff. Methods of estimation: no methods of estimation have been developed. 40. Total expenditure on health as percentage of GDP 41. General government expenditure on health as percentage of total general government expenditure 42. Per capita total expenditure on health at international dollar rate Rationale for use: health financing is a critical component of health systems. National health accounts (NHA) provide a large set of indicators based on the expenditure information collected within a internationally recognized framework. NHA are a synthesis of the financing and spending flows recorded in the operation of a health system, from funding sources to the distribution of funds across providers and functions of health systems and benefits across geographiccal, demographic, socioeconomic and epidemiological dimensions. Definition: total health expenditure as percentage of gross domestic product (GDP). Percentage of total general government expenditure that is spent on health. Per capita total expenditure on health at international dollar rate. Data sources & Methods of estimation. Only about 95 countries either have produced full NHA or report expenditure on health to OECD. Standard accounting estimation and extrapolation techniques have been used to provide time series. The principal international references used are the International Monetary Fund (IMF) Government finance statistics and International financial statistics; OECD health data and International development statistics; and the United Nations National accounts statisttics. National sources include: national health accounts reports, public expenditure reports, statistical yearbooks and other periodicals, budgetary documents, national accounts reports, statistical data on official web sites, central bank reports, nongovernmental organization reports, academic studies, and reports and data provided by central statistical offices and ministries. 43. General government expenditure on health as percentage of total expenditure on health 44. General government expenditure on health as percentage of total government expenditure 45. External resources for health as percentage of total expenditure on health 46. Social security expenditure on health as percentage of general government expenditure on health 47. Out-of-pocket expenditure as percentage of private expenditure on health 48. Private prepaid plans as percentage of private expenditure on health 49. Per capita total expenditure on health at average exchange rate (US$) 50. Per capita government expenditure on health at average exchange rate (US$) 51. Per capita government expenditure on health at international dollar rate Rationale for use: health financing is a critical component of health systems. National health accounts (NHA) provide large set of indicators based on the expenditure information collected within a internationally recognized framework. NHA are a synthesis of the financing and spending flows recorded in the operation of a health system, from funding sources to the distribution of funds across providers and functions of health systems and benefits across geographiccal, demographic, socioeconomic and epidemiological dimensions. Definition: key indicators for which the data are available: Basic indicators 2006 25

Level of total expenditure on health as % of GDP, and per capita health expenditures in US dollars and in international dollars. Distribution of public and private sectors in financing health and their main components, such as: - Extent of social and private health insurance - Burden on households through out-of-pocket spending - Reliance on external resources in financing health Associated terms: Gross domestic product (GDP) is the value of all goods and services provided in a country by residents and non-residents. This corresponds to the total sum of expenditure (consumption and investment) of the private and government agents of the economy during the reference year. General government expenditure (GGE) includes consolidated direct outlays and indirect outlays, such as subsidies and transfers, including capital, of all levels of government social security institutions, autonomous bodies, and other extrabudgetary funds. Total expenditure on health (THE) is the sum of general government health expenditure and private health expenditure in a given year, calculated in national currency units in current prices. It comprises the outlays earmarked for health maintenance, restoration or enhancement of the health status of the population, paid for in cash or in kind General government expenditure on health (GGHE) is the sum of outlays by government entities to purchase health care services and goods. It comprises the outlays on health by all levels of government, social security agencies, and direct expenditure by parastatals and public firms. Expenditures on health include final consumption, subsidies to producers, and transfers to households (chiefly reimbursements for medical and pharmaceutical bills). It includes both recurrent and investment expenditures (including capital transfers) made during the year. Besides domestic funds it also includes externnal resources (mainly as grants passing through the government or loans channelled through the national budget). Social security expenditure on health (SSHE) includes outlays for purchases of health goods and services by schemes that are mandatory and controlled by government. Such social security schemes that apply only to a selected group of the population, such as public sector employees only, are also included here. External resources health expenditure (ExtHE) includes all grants and loans whether passing through governments or private entities for health goods and services, in cash or in kind. Private health expenditure (PvtHE) is defined as the sum of expenditures on health by the following entities: Prepaid plans and risk-pooling arrangements (PrepaidHE): the outlays of private insurance schemes and private social insurance schemes (with no government control over payment rates and participating providers but with broad guidelines from government) Firms expenditure on health: the outlays by private enterprises for medical care and health enhancing benefits other than payment to social security or other pre-paid schemes. Non-profit institutions serving mainly households: outlays of those entities whose status do not permit them to be a source of financial gain for the units that establish, control or finance them. This includes funding from internal and external sources. Household out-of-pocket spending (OOPS): the direct outlays of households, including gratuities and in-kind payments made to health practittioners and to suppliers of pharmaceuticals, therapeutic appliances and other goods and services. This includes household direct payments to public and private providers of health care services, non-profit institutions, and non-reimbursable cost sharing, such as deductibles, copayments and fee for services. Exchange rate: the annual average or year end number of units at which a currency is traded in the banking system. International dollars: derived by dividing local currency units by an estimate of their Purchasing Power Parity (PPP) compared to the US dollar, i.e. the measure which minimizes the consequences of differences in price levels between countries. Data sources & methods of estimation: about 100 countries either have produced full national health accounts or report expenditure on health to OECD. Standard accounting estimation and extrapolation techniques have been used to provide time series (1998-2004). Ministries of Health have responded to the draft updates sent for their inputs and comments. For details on sources and methods see www.who.int/nha. 52. Coverage of vital registration of deaths Rationale for use: health information is an essential component of health systems. The registration of births and deaths with causes of death, called civil registration (vital registration), is an important component of a country health information system. Definition: percentage of estimated total deaths that are counted through civil registration system. Methods of estimation: expected numbers of deaths by age and sex are estimated from current life tables, based on multiple sources. Reported numbers are compared with expected numbers by age and sex to obtain an estimate of coverage of the vital registration system. 53. Number of hospital beds per 10 000 population Rationale for use: service delivery is an important component of health systems. To capture availability, access and distribution of health services delivery a range of indicators or a composite indicator is needed. Currently, there is no such data for the majority of countries. Inpatient beds density is one of the few available indicators on a component of level of health service delivery. Definition: number of inpatient beds per 10 000 population. Methods of estimation: empirical data only with possible adjustment for underreporting (e.g. missing private facilities). 26 Health situation analysis in the African Region