Alain MOREL Sr Water and Sanitation Specialist WSP-Africa The World Bank

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Les reformes dans le secteur de leau et de lassainissement: Lexprience de lAfrique sub-saharienne. Alain MOREL Sr Water and Sanitation Specialist WSP-Africa The World Bank. Plan. La toile de fond en Afrique Les Objectifs de Dveloppements du Millnaire Pourquoi la reforme? - PowerPoint PPT Presentation

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  • Les reformes dans le secteur de leau et de lassainissement: Lexprience de lAfrique sub-saharienne Alain MORELSr Water and Sanitation Specialist

    WSP-Africa The World Bank

    *

    PlanLa toile de fond en AfriqueLes Objectifs de Dveloppements du Millnaire Pourquoi la reforme?Le mouvement de reforme en AfriqueLes leons des annes 1990

    *

    Toile de fond: Le dfiPlus de 1/3 de la population sans accs aux services deau, et beaucoup plus sans accs lassainissementUn rythme durbanisation trs levDes infrastructures en nombre insuffisant et en mauvais tatPeu dinvestissements de la part des gouvernements (financement interne) ou des agences de dveloppement bilatrales ou multilatrales.

    *

    Toile de fond: Le revers de la mdailleDes socits de gestion de services peu performantesTechniquement Pertes en eau leves, personnel en surnombreFinancirement Taux de facturation et de recouvrement bas, tarifs inadapts et non lies aux couts de production et de distributionAutonomie de gestion et financire limiteMandat et rpartition des responsabilits peu clairs

    *

    ODMs: Le programme pour le secteur eau et assainissementRduire de moiti la proportion de population sans accs a une source deau saine et durableRduire de moiti la proportion de population sans accs a un mode dassainissement hyginique

    *

    ODMs: La dimension du problme en Afrique350 millions de plus dici 2015350 millions couverts rural villesDoubler la population couverte dici 2015

    Chart3

    175Rural 2000235

    175Urban 200040

    350Total 2000275

    175190152

    17517836

    350368188

    Served 2000

    Added 2000-2015

    Not Served

    Population (million)

    Couverture eau potable en Afrique

    Model I

    WATER AND SANITATION MILLENNIUM DEVELOPMENT GOALS FINANCING POLICY MODEL

    MDG related Investments and financing optionsAssumptions on financing policyAssumptions on MDGs

    Investments (US$ millions)Sources of financing (US$ millions)Main assumption on financing sources

    Investments in:Compliance with Water MDG:

    Water Access facilitiesOwn country resources6,547

    Urb. populations > 500,0005,992DonorsEuropean UnionGrant fundingUrban Centers > 500,000100.0%

    Urb. populations < 500,0006,200UNICEFCredit fundingUrban Centers < 500,000100.0%

    Rural areas7,637Bilaterals0KfW (new)Rural areas100.0%

    Investment in rehabilitation6,044HIPIC (water for debt swaps)HIPIC/PRSP

    Multilaterals I

    Total investment cost25,874Multilaterals II (IDA)

    Investment assumptionsAfrican economy & W&S

    Reform costsPercapita investments costs in:National economy%

    Urban centers > 500,00080GDP average growth3.50%

    Pending of financing19,327Urban centers < 500,00060Contribution.as % of GDP0.10%

    Rural areas40Contribution.as % of PE

    Total investment in water25,874Total fuentes25,874

    Total investment as % GDP0.40%Productive efficiency in W&S

    UFW:Collection efficiencyTech. Efficiency

    Other country specific assumptions II2000200120022003200420052006200720082009201020112012

    Other country specific assumptions III

    Other country specific assumptions IIII

    Other country assumptions

    13131313131313131313131313

    Model II

    WATER AND SANITATION MILLENNIUM DEVELOPMENT GOALS FINANCING POLICY MODEL

    MDG related Investments and financing optionsAssumptions on financing policyAssumptions on MDGs

    Investments (US$ millions)Sources of financing (US$ millions)Main assumption on financing sources

    Investments in:Compliance with Water MDG:

    Water Access facilitiesOwn country resources6,547

    Countries pop 500,000100.0%

    Countries 2M 500,00080GDP average growth3.50%

    Pending of financing19,327Urban centers < 500,00060Contribution.as % of GDP0.10%

    Rural areas40Contribution.as % of PE

    Total investment in water25,874Total fuentes25,874

    -0.00

    Total investment as % GDP0.40%Productive efficiency in W&S

    UFW:Collection efficiencyTech. Efficiency

    Other country specific assumptions II2000200120022003200420052006200720082009201020112012

    Other country specific assumptions III

    Other country specific assumptions IIII

    Other country assumptions

    13131313131313131313131313

    Model III

    WATER AND SANITATION MILLENNIUM DEVELOPMENT GOALS FINANCING POLICY MODEL

    MDG related Investments and financing optionsAssumptions on financing policyAssumptions on MDGs

    Investments (US$ millions)Sources of financing (US$ millions)Main assumption on financing sources

    Investments in:Compliance with Water MDG:

    Water Access facilitiesOwn country resources6,547

    Countries with advanced reform5,992DonorsEuropean UnionGrant fundingUrban Centers > 500,000100.0%

    Countries entering reform process6,200UNICEFCredit fundingUrban Centers < 500,000100.0%

    Countries not interested in RP7,637Bilaterals0KfW (new)Rural areas100.0%

    HIPIC (water for debt swaps)HIPIC/PRSP

    Multilaterals I

    Total investment cost19,829Multilaterals II (IDA)

    Investment assumptionsAfrican economy & W&S

    Investments in rehabilitation6,044Percapita investments costs in:National economy%

    Reform costsUrban centers > 500,00080GDP average growth3.50%

    Pending of financing19,327Urban centers < 500,00060Contribution.as % of GDP0.10%

    Rural areas40Contribution.as % of PE

    Total investment in water25,874Total fuentes25,874

    Total investment as % GDP0.40%Productive efficiency in W&S

    UFW:Collection efficiencyTech. Efficiency

    Sixto Requena:Not finished yet

    Sixto Requena:

    Sixto Requena:Not finished yet

    Summary

    Year 2000AnnualYear 2015AdditionalInvestments needed

    PopulationAccess to safe watergrowth ratePopulationAccess to safe waterpeople withUS$Period

    millions%Millions%00 - 15Millions%MDG%accessper capita00 - 15Annual

    Big urban conglomarates8714%7587%4.2%16118%15093.1%75805,993400

    Cities < 500 th and towns12820%10178%4.0%23025%20488.8%103606,199413

    Rural areas41166%17442%1.6%51757%36570.6%191407,637509

    Total625100%35056%2.5%908100%71979.2%36919,8301,322

    Year 2000AnnualYear 2015AdditionalInvestments needed

    PopulationAccess to safe watergrowth ratePopulationAccess to safe waterpeople withUS$Period

    millions%Millions%00 - 15Millions%MDG%accessper capita00 - 15Annual

    Big urban conglomarates8714%7587%4.2%16118%15093.1%75805,992399

    Cities < 500 th and towns12820%10178%4.0%23025%20488.8%103606,200413

    Rural areas41166%17442%1.6%51757%36570.6%191407,637509

    Total625100%35056%2.5%908100%00.0%36919,8291,322

    Very small countries:Cape Verde, Eq. Guinea, Djibouti, Comoros, Mauritius, G. Bissau, Gabon, and Gambia

    Year 2000AnnualYear 2015AdditionalInvestments needed

    PopulationAccess to safe watergrowth ratePopulationAccess to safe waterpeople withUS$Period

    millions%Millions%00 - 15Millions%MDG%accessper capita00 - 15Annual

    Big urban conglomarates0.57%0.487%3.2%18%0.792.5%0.380242

    Cities < 500 th and towns3.041%2.276%3.3%550%4.185.7%1.9601127

    Rural areas3.752%2.670%0.6%442%3.484.7%0.840342

    Total7.1100%5.273%2.0%10100%8.285.8%3.017011

    Small countries: Botswana, Namibia, Lesotho, Mauritania, Congo, CRA, Eritrea, and Togo

    Year 2000AnnualYear 2015AdditionalInvestments needed

    PopulationAccess to safe watergrowth ratePopulationAccess to safe waterpeople withUS$Period

    millions%Millions%00 - 15Millions%MDG%accessper capita00 - 15Annual

    Big urban conglomarates3.415%3.087%4.4%6.520%6.193.1%3.18024716

    Cities < 500 th and towns5.624%3.766%3.4%9.429%7.680.9%3.86023015

    Rural areas14.161%7.050%0.9%16.351%12.073.8%5.04020013

    Total23.2100%13.759%2.2%32.2100%25.779.8%11.967745

    Medium size countries: Sierra Leone, Benin, Burundi, Guinea, Chad, Rwanda, Zambia, and Senegal

    Year 2000AnnualYear 2015AdditionalInvestments needed

    PopulationAccess to safe watergrowth ratePopulationAccess to safe waterpeople withUS$Period

    millions%Millions%00 - 15Millions%MDG%accessper capita00 - 15Annual

    Big urban conglomarates6.811%5.987%4.5%13.115%12.293.1%6.38050634

    Cities < 500 th and towns11.119%7.063%4.0%19.922%16.080.7%9.16054536

    Rural areas41.370%18.846%2.0%55.963%40.672.6%21.74086958

    Total59.1100%31.754%2.8%88.9100%68.877.4%37.11,920128

    Niger, Malawi, Mali, Zimbawe, Burkina Faso, Angola, Cote d'Ivoire, Cameroun

    Year 2000AnnualYear 2015AdditionalInvestments needed

    PopulationAccess to safe watergrowth ratePopulationAccess to safe waterpeople withUS$Period

    millions%Millions%00 - 15Millions%MDG%accessper capita00 - 15Annual

    Big urban conglomarates12.813%11.187%4.7%25.417%23.693.1%12.58099867

    Cities < 500 th and towns20.421%15.274%3.5%34.423%29.385.2%14.16084756

    Rural areas65.866%36.055%2.1%89.560%69.277.3%33.1401,32588

    Total99.1100%62.463%2.8%149.2100%122.181.8%59.73,169211

    Madagascar, Mozambique, Ghana, Uganda, Sudan, Kenya, Tanzania South Africa

    Year 2000AnnualYear 2015AdditionalInvestments needed

    PopulationAccess to safe watergrowth ratePopulationAccess to safe waterpeople withUS$Period

    millions%Millions%00 - 15Millions%MDG%accessper capita00 - 15Annual

    Big urban conglomarates32.415%28.187%3.7%55.819%52.093.1%23.9801,909127

    Cities < 500 th and towns43.020%37.086%3.9%76.526%70.892.6%33.8602,028135

    Rural areas135.664%69.151%1.0%156.854%116.974.6%47.8401,911127

    Total211.1100%134.364%2.1%289.1100%239.782.9%105.45,848390

    Republic Democratic of Congo, Ethiopia, Nigeria

    Year 2000AnnualYear 2015AdditionalInvestments needed

    PopulationAccess to safe watergrowth ratePopulationAccess to safe waterpeople withUS$Period

    millions%Millions%00 - 15Millions%MDG%accessper capita00 - 15Annual

    Big urban conglomarates30.814%26.787%4.5%59.718%55.693.1%28.9802,309154

    Cities < 500 th and towns45.020%35.479%4.3%84.825%76.189.7%40.6602,437162

    Rural areas150.066%40.427%1.8%194.757%122.963.1%82.5403,299220

    Total225.7100%102.645%2.8%339.1100%254.575.1%152.08,045536

    Water

    % people in cities < 500 th and townsCountryPopulation (000), 2000People with accessCoverage, 2000Non covered 2000Population (000) 2015With access according to MDGNon covered 2015 (MDG)Persons added during 2000-2015cities < 500 & townsInvestment required (US$ M)UrbanGNP 2000200120022003200420052006200720082009201020112012201320142015

    20002015UrbanRuralTotalUrbanRuralTotalUrbanRuralTotalUrbanRuralTotalUrbanRuralTotalUrbanRuralTotalUrbanRuralUrbanRuralTotal2000201520002015Add 00-15rate of coverageAddedUrbanRuralTotalPop growthBillion

    Cape Verde68.160.6Cape Verde26616242817014431464%89%73%36%11%27%41715056734214248418%6%172-2169369,168100%43100%100%2664171510.50213487757612.20.012.23.0%0.5880.60840148320.62969553510.65173487880.67454559960.69815469560.72259010990.74788076380.77405659050.80114857120.82918877120.85821037820.88824774140.91933641230.95151318680.9848161483

    Equatorial Guinea ..............................51.750.3Eq Guinea218234452989819645%42%43%55%58%57%42526769230819049828%29%21091301368,999100%42100%100%2184252070.681622718114114.03.717.64.6%0.3630.37612095410.38928518750.4029101690.4170120250.43160744580.44671370640.46234868620.47853089020.49527947130.51261425280.53055575170.5491252030.56834458510.58823664560.6088249282

    Djibouti61.463.8Djibouti531106637531106637100%100%100%0%0%0%61092702610927020%0%79-1465368,697100%41100%100%531610790.1295081967106.10.06.10.9%0.5530.57285398590.59290387540.61365551110.6351334540.65736312480.68037083420.70418381340.72883024690.75433930550.78074118120.80806712260.83634947180.86562170340.8959184630.9272756092

    Comoros61.463.8Comoros23146469522644166798%95%96%2%5%4%4556121,0674505971,0471%3%224156380368,632100%40100%100%2314552240.497435897411115.76.221.94.6%0.2120.21973497120.22742569520.23538559450.24362409030.25215093350.26097621620.27011038370.27956424720.28934899580.29947621070.3099578780.32080640380.33203462790.34365583990.3556837943

    Mauritius61.463.8Mauritius4786801,1584786801,158100%100%100%0%0%0%6326691,3016326691,3010%0%154-11143368,252100%39100%100%4786321540.24367088613811.60.011.61.9%1.1861.22765491.27062282151.31509462031.3611229321.40876223461.45806891281.50910132471.56191987111.61658706661.67316761391.73172848041.79233897721.85507084141.91999832091.9871982621

    Guinea-Bissau61.460.6G Bissau2889251,2138450959229%55%49%71%45%51%7439841,7274797631,24236%23%396254650368,109100%38100%100%2887434550.825722244837624.110.234.36.5%0.2170916960.22468990540.2325540520.24069344390.24911771440.25783683440.26686112360.27620126290.28586830710.29587369790.30622927730.3169473020.32804045760.33952187360.35140513920.3637043191

    Gabon ................................................51.750.3Gabon9982281,22672912585473%55%70%27%45%30%1,5631951,7581,3521511,50314%23%62326649367,460100%3752%50%5167862700.461137060412547.41.048.43.0%3.9279311364.06540872584.20769803124.35496746234.50739132344.66515001984.82843027044.99742532995.17233521655.3533669495.54073479225.734660515.93537362786.14311170486.35812061456.580654836

    Gambia68.160.6Gambia4248821,30633946780780%53%62%20%47%38%7211,0611,7826498121,46110%24%310344654366,81199%36100%100%4247212970.477269224814221.913.835.73.6%0.4395792640.45496453820.47088829710.48736938750.5044273160.52208227210.54035515160.55926758190.57884194730.59910141550.6200699650.64177241380.66423444820.68748265390.71154454680.736448606

    Botswana49.245.8Botswana8158071,6228157341,549100%91%96%0%9%4%9487451,6939487111,6590%5%133-23110366,15799%35100%100%8159481330.14029535861910.30.010.31.0%5.2797711365.46456312585.65582283525.85377663446.05865881666.27071187526.49018679086.71734332856.9524503457.19578610717.44763862087.70830597257.97809668168.25733006548.54633661778.8454583993

    Namibia68.145.8Namibia5331,1931,7265337991,332100%67%77%0%33%23%9121,4012,3139121,1702,0820%17%379371750366,04799%3468%56%3635111480.41557017546129.114.843.93.6%3.5694254083.69435529733.82365773273.95748575334.09599775474.23935767614.38773519484.54130592664.7002516344.86476044125.03502705675.21125300365.39364685885.58242449885.77780935635.9800326837

    Lesotho68.145.8Lesotho6021,5512,1535901,3651,95598%88%91%2%12%9%8331,3082,1418251,2302,0541%6%235-13599365,29799%3368%56%410466570.2846108141618.50.018.52.2%1.1806766081.22200028931.26477029941.30903725991.3548535641.40227343871.45135300911.50215036441.55472562711.60914102411.66546095991.72375209351.78408341681.84652633641.91115475821.9780451747

    Mauritania61.460.6Mauritania1,5411,1282,66952445197534%40%37%66%60%63%3,0301,0764,1062,0307532,78333%30%1,5063021,808365,19899%3261%61%9461,8368900.7419141914660107.312.1119.44.6%0.9780698241.01230226781.04773284721.08440349691.12235761931.16164013591.20229754071.24437795461.2879311831.33300877441.37966408151.42795232441.47793065571.52965822871.58319626671.638608136

    Congo51.750.3Congo1,8411,1032,9441,3071881,49571%17%51%29%83%49%3,4321,2984,7302,9347593,69415%42%1,6275722,199363,39098%3152%50%9521,7267740.5545502256429121.622.9144.54.2%1.7345130241.79522097981.85805371411.92308559411.99039358992.06005736562.13215937342.20678495142.28402242472.36396320962.44670192192.53233648922.62096826632.71270215562.80764673112.9059143667

    Central African Republic ....................51.750.3CAR1,4892,1263,6151,1919782,16980%46%60%20%54%40%2,4242,4534,8772,1821,7913,97210%27%9908131,803361,19198%3052%50%7701,2194490.453978731220475.232.5107.73.3%1.0309463681.06702949091.10437552311.14302866641.18303466971.22444088311.2672963141.3116516851.3575594941.40507407631.4542516691.50515047741.55783074411.61235482011.66878723881.7271947922

    Eritrea61.463.8Eritrea7223,1293,8514551,3141,76963%42%46%37%58%54%1,4974,2245,7211,2202,9994,21919%29%7651,6852,450359,38797%2961%64%4439555120.627180741932154.867.4122.25.0%0.6962369920.72060528670.74582647180.77193039830.79894796220.82691114090.85585303080.88580788690.91681116290.94889955360.9821110381.01648492431.05206189671.08888406311.12699500531.1664398305

    Togo ..................................................61.460.6Togo1,5403,0894,6291,3091,1742,48385%38%54%15%62%46%2,8053,7716,5762,5952,6025,1978%31%1,2861,4282,714356,93797%2861%61%9461,7007540.495495495537495.457.1152.54.1%1.3177735681.36389564291.41163199041.461039111.51217547891.56510162071.61988017741.67657598361.7352561431.7959901081.85884976181.92390950351.99124633612.06093995782.13307285642.2077304063

    Sierra Leone ......................................61.460.6Sierra Leone1,7793,0764,8554099541,36323%31%28%77%69%72%3,3223,7927,1142,0432,4844,52739%35%1,6341,5303,164354,22496%2761%61%1,0922,0139210.7997239394736116.061.2177.24.3%0.6465260160.66915442660.69257483150.71681495060.74190347390.76787009540.79474554880.8225616430.85135130050.8811485960.91198879690.94390840480.97694519891.01113828091.04652812071.083156605

    Benin68.160.6Benin2,5773,5206,0971,9071,9363,84374%55%63%26%45%37%5,0044,4459,4494,3533,4457,79813%23%2,4471,5093,955351,05995%2668%61%1,7553,0321,2770.5619642217718181.460.4241.74.5%2.3448007682.42686879492.51180920272.59972252482.69071281322.78488776162.88235883332.98324139243.08765484123.19572276063.30757305723.42333811423.54315494823.66716537143.79551615943.928359225

    Burundi61.463.8Burundi6006,0956,6955763,8404,41696%63%66%4%37%34%1,4288,4079,8351,3996,8528,2512%19%8233,0123,835347,10494%2561%64%3689115430.588406791331959.5120.5180.06.0%0.732333440.75796511040.78449388930.81195117540.84036946650.86978239790.90022478180.93173264910.96434329190.99809530711.03302864281.06918464531.10660610791.14533732171.18542412791.2269139724

    Guinea68.160.6Guinea2,4354,9957,4301,7531,7983,55172%36%48%28%64%52%4,0077,29311,3003,4464,9598,40514%32%1,6933,1614,854343,26993%2468%61%1,6582,4287700.4912391687378127.9126.4254.33.4%3.302705923.41830062723.53794114923.66176908943.78993100753.92257859284.05986884354.2019642534.34903300194.5012491574.65879287744.82185062824.99061540015.16528693915.3460719825.5331845014

    Chad51.750.3Chad1,8205,8317,6515641,5162,08031%26%27%69%74%73%3,8278,54912,3762,5075,3867,89335%37%1,9423,8705,812338,41592%2352%50%9411,9259840.7749218589763140.1154.8294.95.1%1.5413936641.59534244221.65117942771.70897070771.76878468251.83069214631.89476637151.96108319452.02972110632.1007613452.17428799212.25038807182.32915165432.41067196222.49504548092.5823720727

    Rwanda51.763.8Rwanda4767,2577,7332862,9033,18860%40%41%40%60%59%9369,56810,5047496,6987,44620%30%4633,7954,258332,60390%2252%64%2465973510.618589743621732.7151.8184.54.6%1.9876829442.0572518472.12925566172.20377960982.28091189622.36074381262.4433698462.52888779062.61739886332.70900782352.80382309732.90195690573.00352539743.10864878633.21745149393.3300622961

    Zambia ..............................................61.463.8Zambia3,6325,5379,1693,1962,6585,85488%48%64%12%52%36%6,6898,10714,7966,2885,99912,2876%26%3,0923,3416,433328,34589%2161%64%2,2304,2682,0380.4916773491,002227.3133.7360.94.2%3.0261967363.13211362183.24173759853.35519841453.4726303593.59417242153.71996845633.85016735233.98492320964.12439552194.26874936524.4181555934.57279103874.73283872514.89848808055.0699351633

    Senegal61.460.6Senegal4,4984,9839,4814,1383,2397,37792%65%78%8%35%22%7,7595,75713,5167,4494,75012,1984%18%3,3101,5114,821321,91287%2061%61%2,7624,7021,9400.4444408644862247.660.4308.03.7%4.714378244.87938147845.05015983015.22691542425.4098574645.59920247535.79517456195.99800567166.20793587016.42521362556.65009610246.8828494667.12374919737.37308041927.63113823397.8982280721

    Niger68.160.6Niger2,2078,52310,7301,5454,7736,31870%56%59%30%44%41%5,38713,09418,4814,57910,21314,79215%22%3,0345,4408,474317,09186%1968%61%1,5033,2651,7620.66260823991,167219.4217.6437.06.1%1.9391823362.00705371782.07730059792.15000611882.2252563332.30314030462.38375021532.46718147282.55353282442.64290647322.73540819982.83114748682.93023764883.03279596653.13894382533.2488068592

    Malawi68.163.8Malawi2,7238,02010,7432,5873,5296,11695%44%57%5%56%43%3,33012,32615,6563,2478,87512,1213%28%6605,3466,006308,61684%1868%64%1,8542,1252700.20324940325551.7213.8265.51.4%1.7443631361.80541584581.86860540041.93400658942.001696822.07175620872.1442676762.21931704472.29699314122.37738790122.46059647772.54671735442.63585246182.7281072982.82359105342.9224167403

    Mali68.160.6Mali3,3757,85911,2342,4984,7947,29174%61%65%26%39%35%7,19410,46317,6576,2598,42314,68113%20%3,7613,6297,390302,61082%1768%61%2,2984,3602,0610.60096057061,239276.1145.1421.35.2%2.548296962.63748735362.7297994112.82534239042.9242293743.02657740213.13250761123.24214537763.35562046583.47306718213.59462453353.72043639213.85065166593.98542447424.12491433084.2692863323

    Zimbabwe ..........................................61.463.8Zimbabwe4,1217,54811,6694,1215,8129,933100%77%85%0%23%15%7,5088,86016,3687,5087,84115,3490%12%3,3872,0295,416295,22080%1661%64%2,5304,7902,2600.45111880661,019250.681.2331.74.1%5.850600966.05537199366.26731001346.48666586386.71369916916.948678647.19188239247.44359827617.70412421587.97376856338.25285046318.54170022938.84065973739.15008282819.47033572719.8017974775

    Burkina68.160.6Burkina2,2049,73311,9371,8515,3537,20584%55%60%16%45%40%4,26814,24018,5083,92711,03614,9638%23%2,0755,6837,758289,80479%1568%61%1,5012,5861,0850.528503321574154.5227.3381.94.5%2.4219133442.5066803112.59441412192.68521861622.77920126782.87647331212.97714987813.08135012383.18919737813.30081928643.41634796143.535920143.65967734493.7877660523.92033786384.0575496891

    Angola51.750.3Angola4,4048,47412,8781,4973,3904,88734%40%38%66%60%62%9,17411,62220,7966,1478,13514,28233%30%4,6494,7469,395282,04676%1452%50%2,2774,6152,3380.75639135911,768336.6189.8526.45.0%3.8469137923.98155577474.12091022684.26514208484.41442205774.56892682984.72883926884.89434864325.06565084575.24294862535.42645182725.61637764125.81295085866.01640413876.22697828356.4449225234

    Cte d'Ivoire68.160.6Cote d'Ivoire6,8547,93214,7866,1695,15611,32490%65%77%10%35%23%10,95410,57521,52910,4068,72419,1315%18%4,2383,5697,806272,65174%1368%61%4,6686,6381,9710.4072244698802323.0142.7465.73.2%9.59109129.92677939210.274216670710.633814254211.005997753111.391207674511.789899943112.202546441112.629635566513.071672811313.529181359714.002702707314.492797302115.000045207615.525046789916.0684234276

    Cameroon ..........................................51.750.3Cameroun7,3797,70615,0856,0513,2379,28782%42%62%18%58%38%11,9058,32120,22610,8345,90816,7419%29%4,7832,6717,454264,84572%1252%50%3,8155,9882,1730.441477632959363.4106.9470.33.2%8.6444533768.94700924429.26015456779.58425997769.919709076810.266898894510.626240355810.998158768211.383094325111.781502626512.193855218412.620640151113.062362556413.519545245813.992729329414.482474856

    Madagascar61.463.8Madagascar4,72111,22115,9424,0133,4797,49185%31%47%15%69%53%9,49414,57824,0728,7829,54918,3318%35%4,7696,07010,839257,39170%1161%64%2,8996,0573,1580.54305706591,715347.2242.8590.04.8%3.8687759364.00418309384.1443295024.28938103464.43950937084.59489219884.75571342584.92216339575.09443911455.27274448355.45729054045.64829570945.84598605926.05059557136.26236641636.4815492408

    Mozambique49.263.8Mozambique7,91711,76419,6816,8096,23513,04486%53%66%14%47%34%11,33812,18823,52610,5449,32419,8687%24%3,7363,0896,825246,55267%1049%64%3,8957,2343,3380.35428675481,183275.2123.6398.82.4%3.7463152643.87743629824.01314656874.15360669864.2989829334.44944733574.60517799244.76635922224.93318179495.10584315785.28454766835.46950683675.6609395765.85907246116.06413999736.2763848972

    Ghana68.160.6Ghana7,75312,46020,2136,7456,10512,85187%49%64%13%51%36%11,18215,19626,37810,45511,32121,7767%26%3,7105,2168,926239,72765%968%61%5,2806,7761,4960.3548541057531286.2208.6494.82.5%6.5938365446.8246208237.06348255187.31070444127.56657909667.8314093658.10550869288.3892014978.68282354948.98672237369.30125765679.62680167479.963739733310.31247062410.673407095811.0469763442

    Uganda61.463.8Uganda3,08318,69521,7782,2208,60010,81972%46%50%28%54%50%8,01430,72538,7396,89222,42929,32114%27%4,67213,83018,502230,80163%861%64%1,8935,1293,2360.67792409792,194329.9553.2883.16.6%6.6988282886.93328727817.17595233287.42711066457.68705953777.95610662158.23457035338.52278031578.82107762679.12981534369.44935888079.780086441510.122389466910.476673098310.843356656711.2228741397

    Sudan ................................................49.253.1Sudan10,65218,83829,4909,16112,99822,15986%69%75%14%31%25%20,65721,77642,43319,21118,40137,6127%16%10,0505,40315,453212,29958%749%53%5,24110,9695,7280.52315260882,997744.1216.1960.24.5%9.5994818569.93546372110.283204951210.643117124511.015626223811.401173141711.800214201612.213221698712.640684458113.083108414213.541017208714.01495281114.505476159415.013167824915.538628698816.0824807033

    Kenya49.263.8Kenya9,95720,12330,0808,6636,23814,90187%31%50%13%69%50%18,86721,13440,00117,64113,84331,4837%35%8,9787,60516,583196,84753%649%64%4,89912,0377,1380.50894142483,633645.6304.2949.84.4%10.609971210.98132019211.365666398711.763464722712.17518598812.601317497513.0423636113.498846336313.971305958114.460301666614.966412224915.490236652816.032394935716.593528758417.17430226517.7754028442

    Tanzania68.163.8Tanzania11,02122,49633,5178,8179,44818,26580%42%54%20%58%46%22,78526,55949,34420,50718,85739,36310%29%11,6909,40921,098180,26449%568%64%7,50514,5377,0320.57004852124,008855.0376.31231.45.0%9.0132152329.32867776519.65518148699.993112838910.342871788310.704872300911.079542831411.467326830511.868683269612.28408718412.714030235513.159021293713.61958703914.096272585414.589642125815.1002796002

    South56.245.8South Africa20,33020,04740,37718,70416,03834,74192%80%86%8%20%14%29,96114,65544,61628,76313,19041,9524%10%10,059-2,8487,211159,16643%456%46%11,42513,7222,2970.3497240858803788.70.0788.72.6%129.170948096133.6919312794138.3711488741143.2141390847148.2266339527153.414566141158.784075956164.3415186144170.0934717659176.0467432778182.2083792925188.5856725677195.1861711076202.0176870963209.0883061447216.4063968598

    Democratic51.750.3RDC15,64136,01451,65513,9209,36423,28489%26%45%11%74%55%33,00851,03784,04531,19332,15363,3466%37%17,27222,79040,062151,95541%352%50%8,08616,6038,5170.55372402914,7161287.4911.62199.05.1%15.284415.81935416.3730313916.946087488617.539200550818.1530725718.7884301119.446025163820.126636044620.831068306121.560155696822.314761146223.095777786323.904130008924.740774559225.6067016687

    Ethiopia61.463.8Ethiopia11,04251,52362,5658,5026,69815,20077%13%24%23%87%76%19,73870,02789,76517,46839,56557,03312%44%8,96632,86741,833111,89330%261%64%6,78012,5935,8130.51326558712,984657.61314.71972.33.9%6.7374530566.9732639137.21732814997.46993463527.73138234748.00198072958.28205005518.5719218078.87193907039.18245693779.50384293059.836477433110.180754143310.537080538310.905878357111.2875840996

    Nigeria61.460.6Nigeria49,05062,456111,50639,73124,35864,08881%39%57%19%61%43%91,69173,623165,31482,98051,168134,14810%31%43,25026,81070,06070,06019%161%61%30,11755,56525,4480.521205952913,2643194.71072.44267.14.3%32.70498508833.849659566135.034397650936.260601568737.529722623638.843262915440.202777117441.609874316643.066219917644.573537614746.133611431347.748287831449.419477905551.149159632152.939380219354.7922585269

    214,768410,533625,301175,810174,020349,83182%42%56%44%390,874517,223908,097354,043364,956718,998178,232190,936369,168128,115229,615101,50013184.38792890267758.777220943.16512890264.1%312.186214256323.112731755334.4216773664346.1264360742358.2408613368370.7792914836383.7565666855397.1880465195411.0896281477425.4777651329440.3694869125455.7824189545471.7348036179488.2455217445505.3341150055523.02080903076546.8663740231

    91%71%0.31218621430.32311273180.33442167740.34612643610.35824086130.37077929150.38375656670.39718804650.41108962810.42547776510.44036948690.4557824190.47173480360.48824552170.5053341150.523020809

    Additional served per year24,61136,831152,267517

    Out of which urban11,882389

    Out of which rural12,729-189906

    Investement US$ percapita Urban70Cities < 500,00060Urban > 500,00080

    Investement US$ percapita rural40

    Annual investment urban831,751

    Annual investment Rural509,162

    Total annual investment1,340,912

    20113686.1

    Liberia, Saint Helena, Sao Tome, Seychelles, Somalia, and Swaziland are not included because they do not have information

    Combined population of Liberia, Saint Helena, Sao Tome, Seychelles, Somalia, and Swaziland is14.338

    Rural 2000Urban 2000Total 2000Rural 2015Urban 2015Total 2015

    Served 2000175175350175175350

    Added 2000-2015190178368

    Not Served2354027515236188

    Water

    000

    000

    000

    000

    000

    000

    Served 2000

    Added 2000-2015

    Not Served

    Population (million)

    Water Supply Coverage in Africa

    Sanitation

    SANITATION

    Population, 2000CoveragePop. ServedCoveragePop. Served

    CountryUrbanRuralTotalUrbanRuralTotalUrbanRuralTotalUrbanRuralTotalUrbanRuralTotal

    Cape Verde26616242864%89%73%17014431495%32%71%25352305

    Eq Guinea21823445245%42%43%989819660%46%53%131108238

    Djibouti531106637100%100%100%53110663799%50%91%52653579

    Comoros23146469598%95%96%22644166798%98%98%226455681

    Mauritius4786801,158100%100%100%4786801,158100%99%99%4786731,151

    G Bissau2889251,21329%55%49%8450959288%34%47%253315568

    Gabon9982281,22673%55%70%72912585425%4%21%2509259

    Gambia4248821,30680%53%62%33946780741%35%37%174309483

    Botswana8158071,622100%91%96%8157341,54984%44%64%6853551,040

    Namibia5331,1931,726100%67%77%5337991,33296%17%41%512203714

    Lesotho6021,5512,15398%88%91%5901,3651,95592%92%92%5541,4271,981

    Mauritania1,5411,1282,66934%40%37%52445197544%19%33%678214892

    Congo1,8411,1032,94471%17%51%1,3071881,49514%9%2580258

    CAR1,4892,1263,61580%46%60%1,1919782,16943%23%31%6404891,129

    Eritrea7223,1293,85163%42%46%4551,3141,76966%1%13%47731508

    Togo1,5403,0894,62985%38%54%1,3091,1742,48369%17%34%1,0635251,588

    Sierra Leone1,7793,0764,85523%31%28%4099541,36323%31%28%4099541,363

    Benin2,5773,5206,09774%55%63%1,9071,9363,84346%6%23%1,1852111,397

    Burundi6006,0956,69596%63%66%5763,8404,41679%12%18%4747311,205

    Guinea2,4354,9957,43072%36%48%1,7531,7983,55194%41%58%2,2892,0484,337

    Chad1,8205,8317,65131%26%27%5641,5162,08081%13%29%1,4747582,232

    Rwanda4767,2577,73360%40%41%2862,9033,18812%6%6%57435493

    Zambia3,6325,5379,16988%48%64%3,1962,6585,85499%64%78%3,5963,5447,139

    Senegal4,4984,9839,48192%65%78%4,1383,2397,37794%49%70%4,2282,4426,670

    Niger2,2078,52310,73070%56%59%1,5454,7736,31879%5%20%1,7444262,170

    Malawi2,7238,02010,74395%44%57%2,5873,5296,11696%70%77%2,6145,6148,228

    Mali3,3757,85911,23474%61%65%2,4984,7947,29193%50%63%3,1393,9307,068

    Zimbabwe4,1217,54811,669100%77%85%4,1215,8129,93399%51%68%4,0803,8497,929

    Burkina2,2049,73311,93784%55%60%1,8515,3537,20588%16%29%1,9401,5573,497

    Angola4,4048,47412,87834%40%38%1,4973,3904,88770%30%44%3,0832,5425,625

    Cote d'Ivoire6,8547,93214,78690%65%77%6,1695,15611,32478%30%52%5,3462,3807,726

    Cameroun7,3797,70615,08582%42%62%6,0513,2379,28799%85%92%7,3056,55013,855

    Madagascar4,72111,22115,94285%31%47%4,0133,4797,49170%30%42%3,3053,3666,671

    Mozambique7,91711,76419,68186%53%66%6,8096,23513,04469%29%45%5,4633,4128,874

    Ghana7,75312,46020,21387%49%64%6,7456,10512,85162%64%63%4,8077,97412,781

    Uganda3,08318,69521,77872%46%50%2,2208,60010,81996%82%84%2,96015,33018,290

    Sudan10,65218,83829,49086%69%75%9,16112,99822,15987%48%62%9,2679,04218,309

    Kenya9,95720,12330,08087%31%50%8,6636,23814,90196%81%86%9,55916,30025,858

    Tanzania11,02122,49633,51780%42%54%8,8179,44818,26598%86%90%10,80119,34730,147

    South Africa20,33020,04740,37792%80%86%18,70416,03834,74199%72%86%20,12714,43434,561

    RDC15,64136,01451,65589%26%45%13,9209,36423,28452%6%20%8,1332,16110,294

    Ethiopia11,04251,52362,56577%13%24%8,5026,69815,20058%6%15%6,4043,0919,496

    Nigeria49,05062,456111,50681%39%57%39,73124,35864,08885%45%63%41,69328,10569,798

    214,768410,533625,301175,810174,020349,83180%40%54%172,635165,750338,386

    List of excluded countries

    Liberia, Saint Helena, Sao Tome, Seychelles, Somalia, and Swaziland are not included because they do not have information

    Population, 2000CoveragePop. ServedCoveragePop. Served

    CountryUrbanRuralTotalUrbanRuralTotalUrbanRuralTotalUrbanRuralTotalUrbanRuralTotal

    Liberia1,4161,7383,1540%0000%000

    Sao Tome69781470%0000%000

    Seychelles4928770%0000%000

    Somalia2,7767,32110,0970%0000%000

    Swaziland2667421,0080%0000%000

    Sheet3

    2013201420152016

    13131313

    *

    Manque dAEP = Une dimension centrale de la pauvretODMs: Ou en sommes nous?

    *

    3 paramtres fondamentaux pour latteinte des ODMs en AfriqueREFORMES INSTITUTIONNELLES EN COURS DANS 39 PAYS Amlioration de la gouvernance : NEPAD, PPP, secteur priv local, socit civile, dcentralisation, intgration rgionaleNcessaire dencourager et de prenniser les reformes

    SYSTEMES DE FINANCEMENTS SONT FONDAMENTAUXMcanismes financiers non viables, dpendant fortement de laide extrieure (>80%)Nouvelles orientations de laide: Accent mis sur la rduction de la pauvret; ncessit de restaurer les institutions avant de faire des investissements; annulation de dette, soutien budgtaire; recherche de nouvelles sources.Les stratgies de financement des ODM ncessitent de linnovation

    CAPACITES SONT LA CLE DE LA PERFORMANCEFaiblesse du secteur publique, tat providenceApproche programme, dcentralisation, participation PME et SPD, et consultation des consommateurs et usagers sont des opportunits de dveloppement des capacitsOpportunits pour soutenir lapproche programme, et renforcer lutilisation du secteur priv et les capacits des consommateurs

    *

    Raisons pour sengager dans des reformesManque dautonomieManque de capacitsDifficults de mobilisation des investissementsOptimisation des investissementsGestion des pertes et de la demandeAmlioration

    *

    Manque dautonomie dans la gestion quotidienneDifficults dtablir des tarifs adquatsDifficults de recouvrement des factures de lAdministration et des communesManque de moyens financiers pour raliser les investissementsContraintes institutionnelles

    *

    Objectifs de la reformeAssurer la viabilit financire du secteur en amliorant la gestion, la tarification et le recouvrement des factures

    Rduction de la pauvret et amlioration de la sant des populations dfavorises des zones pri urbaines par un accs leau potable et un assainissement adquat

    *

    Objectifs de la reformeParticipation du secteur priv dans la gestion du service deau en milieu urbain pour amliorer les performances techniques et commerciales

    Renforcement des capacits institutionnelles des acteurs chargs de la mise en uvre de cette rforme

    *

    Ncessit des reformes est largement reconnuePlutt Comment? que Pourquoi?Une majorit ont impliqu le PPPSparer la gestion du service des fonctions de rgulationRenforcement de lautonomie de gestionCrer les conditions de viabilit financireContexte africain

    *

    RgulationInvestissements et dvt des infrastructuresGestion du service,exploitation et maintenanceGouvernement CentralMunicipalitSocit publiquePublicPrivContrat de gestion AffermageConcessionPolitique sectorielle

    *

    Sharing the experience of reformArrangements institutionnels pour la gestion du service

    *

    Ghana, Botswana, Maurice, Togo, Congo (B), DRC, RCA., Cameroun, Tchad, TunisieMalawiGhanaOuganda, Burkina Faso, Swaziland, Lesotho, Liberia, Sierra Leone, LybieKenya, Zimbabwe, Afrique du Sud, Namibie, Zambie, EgypteZambieNiger, Cote dIvoire, Sngal, Cap VertMozambiqueGabon, MarocMaliTanzanieSocit publiquesCompagnies NationaleRgulateurVille or RgionaleEau - AssainissementParticipation du secteur privEauEau - ElectricitBenin, RCA, MauritanieEauEau - Electricit

    *

    Les difficults de la rgulationOrientations: Diffrentes approches de rgulation Agent de circulation ou police de quartier?Finances: Qui finance le rgulateur, et quelles sont les implications?Indpendance du politique: Non assure quand le politique utilise le rgulateur comme couverture.Indpendance du gestionnaire: Non assure quand le rgulateur dpend de la socit de services.Information: Maintenir un rgulateur inform des dtails du secteur par des changes rguliers avec la socit, sans compromettre son indpendance.

    *

    Ralentissement des PSP en Afrique Sub-Saharienne (La demande est passe des aspects contractuels aux cadres de rgulation et a la stimulation des marchs, et loffre sest affaiblie)Le PSP nest pas une fin en soi (Cest un outil sintgrant dans les Documents Stratgiques de Rduction de la Pauvret pour (i) croissance et emploi, et (ii) favoriser laccs aux marches et aux services de base, leau tant de plus en plus intgre aux PRSP, avec la dfinition de plans ODM associant reformes, investissements progressifs, et renforcement de capacits)Les leons des annes 1990

    *

    Leons sur la mise en uvre, mais aussi sur la prennit (Importance des reformes structurelles avant le PPP, (re)construction des capacit du secteur public pour la supervision, la gestion et le suivi des contrats, participation de toutes les partie prenantes, intgration dobjectifs pour amliorer les services aux populations dfavorises)Services aux pauvres est le point dattaque des PPP (Politiques, socit civile et perception du secteur prive ont joue un rle central dans les checs)Les leons des annes 1990

    *

    Stratgies pour les services aux pauvres est devenu critique (Cot lev des services alternatifs, rle les petits oprateurs, ncessite de lier loprateur central aux autres oprateurs, ncessite davoir des programmes a grande chelle)Problmatique de lassainissement urbain (plus large que le mandat des socits deau, ncessite de dvelopper des stratgies et approches spcifiques)Les leons des annes 1990

  • MERCI

    A Delegated Management Model to Improve Water Supply Delivery within Informal Settlements:Lessons from Nyalenda - KisumuOn prioritization: The UN Convention states that special regard should be given to the requirements of vital human needs.

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