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A.4. Country-specific documentation

This appendix lists the data sources used to estimatethe population figures in the GIS database and other relevantinformation pertaining to the demographic estimates and GIS datasets. The data for the nineteen West African countries have beenestimated by Benoit Ninnin for the West Africa Long Term PerspectiveStudy (WALTPS) carried out by the Club du Sahel/OECD (see Ninnin1994). All other figures have been estimated by the author atNCGIA. Unless otherwise stated the administrative boundariesare the same as those in the African Data Sampler (WRI 1995) orin the WALTPS database (see Brunner et al 1995).

Rwanda
  1. United Nations (1973), Demographic Yearbook 1973,Department for Economic and Social Information and Policy Analysis,New York
  2. Republique Rwandaise (19XX), Atlas du Rwanda,
  3. Republique Rwandaise (1991), Recensement Generalde la Population et de l'Habitat Au 15 Aout 1991, ResultatsProvisoires, Service National de Recensement, Kigali
  4. Michigan State University (undated), Rwanda DistrictLevel Administrative Unit GIS Coverage Department of Geography,East Lansing.

District level population was available for 1978and 1991. Only prefecture population was available for 1970. P80 and P90 calculated from R7891. P70 estimated assuming constantgrowth within each prefecture. P60 estimated using P70P78 ratesby prefecture. Exception: Kigali (Nyarugenge) figures for 60and 70 were available from UNSTAT urban database.

Sao Tome

  1. Republica Democratica des Sao Tome e Principe(1978), Censo de 1970, Resultados de 1970.

P60, 80 and 90 estimated by distributing countrylevel totals from the UN World Pop Prospects to the two islandsaccording to 1970 proportions.

Senegal

WALTPS pop estimates based on:

  1. Etude d'une Image à Long Terme de l'Afrique.
  2. Direction de la Prévision et de la Statistique:les principaux résultats provisoires du recensement dela Population et de l'Habitat du Sénégal 1985: Dakar,1989.
  3. CERPOD: Migration et urbanisation au Sénégal,Ba A. et I. Sarr: Rapport de recherche.
  4. Lopez-Escartin N.: Données de base surla population, Sénégal: CEPED, No. 7, Paris, Août1991.
  5. Direction de la prévision et de la statistique:Répertoire des villages, dix volumes, Transfert editions.

Boundary data set produced by USGS/EDC USAID/FEWS

Sierra Leone

WALTPS pop estimates based on:

  1. Etude d'une Image à Long Terme de l'Afrique.
  2. Sesay I.M.: Population distribution and migration,1992.
  3. Kaindaneh D.E et J.L.K. Muana: Population andenvironment.
  4. Sierra Leone: National Report on Population andDevelopment Inter-relationships.

Seychelles

Only two polygons representing Mahe and Praslin Islandsfor which separate population figures were available in the 1973and 1988 UN Demographic Yearbooks for 1971 and 1977. By far thelargest part of the population lives on Mahe Island.

The total country population from the UN World PopulationProspects was split to the two islands using the proportions of1971 for P60 and P70 and those for 1977 for P80 and P90.

Somalia

  1. Somalia Statistical Division, 1975 Census, StatisticalAbstract, Central Statistical Department, Mogadishu.
  2. Somali Democratic Republic (1982), StatisticalAbstract, Central Statistical Department, Mogadishu.

Very little information on the population distributionof Somalia is available. The only available census informationat the 2nd subnational level was for 1975. However, the districtlevel data from 1) did not match the province level totals for2. They were thus adjusted uniformly to match the province level population for 1975. The 1980 province population estimatesfrom 2) were then distributed over the

districts in the province using the same proportionsas in 1975; this assumes constant growth rates in each province. The 75-80 growth rates were then used to estimate P60-90. Thesehad to be adjusted again to match the UN estimated national totalswhich were considerably higher. The adjustment was again uniform.

The resulting district level estimates are obviouslyhighly unreliable. Considering the recent developments in Somalia,they can be considered only a rough proxy of the true currentpopulation distribution.

The names of the second administrative level unitsin the coverage did not match those in the census listing in alarge number of cases. The names from the coverage were retained,but those from the census listing are indicated in parenthesesin several cases.

South Africa

  1. Republic of South Africa (1992), 1992 South AfricanStatistics, Central Statistical Service, Pretoria.
  2. Republic of South Africa (1991), Population Census1991. Adjustment for undercount, Central Statistical Service,Pretoria.
  3. Zietsman, H. L. and I.J. van der Merwe (1986),Population census atlas of South Africa I.J. van der Merwe, StellenboschInstitute for Cartographic Analysis, University of Stellenbosch.
  4. Ciskei (1988), Statistical abstract of Ciskei1988, No.1., Ciskei Central Statistical Service.
  5. Republic of South Africa (1982), South AfricanStatistics 1982, Department of Statistics, Pretoria.
  6. Republic of South Africa (1978), South AfricanStatistics 1978, Department of Statistics, Pretoria.
  7. Republic of South Africa (1968), South AfricanStatistics 1968, Department of Statistics, Pretoria.
  8. Republic of South Africa (1951), 1951 Populationcensus, Vol. 1, Department of Statistics, Pretoria.
  9. Christopher, A. J. (1994) The atlas of apartheid. New York/London, Routledge; Johannesburg, South Africa : WitwatersrandUniversity Press.

Several circumstances make it very difficult to estimateconsistent temporal data series for South Africa despite the well-developedcensus taking system in the country. Apart from changes in districtboundaries between censuses, the creation of homelands and "independent

states" cause sudden, drastic changes in districtpopulations that are difficult to reconcile. Even at the provincelevel, population figures for the 1960-90 period fluctuate widely,since population numbers for

the homelands are subtracted at various points intime and compiled for separate units.

In addition, from the available source data it wasunclear whether the figures represented adjusted or unadjustedcounts. Adjustments for under-enumeration are up to 20% for theblack population.

The P60-90 estimates are primarily based on the 1991population figures compiled from 1) and 2) above. For 1980 onlydata for approximately 80 statistical regions were available. These regions usually consist of 3-4 districts. The proportionof district population within each statistical area was assumedto remain constant between 1980 and 1991. Additionally, districttotals for 1951 were used (after adjusting for disaggregationof boundaries) as well as province level totals for 1960

and 1970. Considerable adjustments and judgementwere necessary in some cases - especially for the "independenthomelands" and for Natal, where the creation of a large numberof small administrative units belonging to Kwazulu homeland causedthe listed 1980 pop figures to be significantly larger in mostcases than the 1991 figures.

The final estimates were adjusted using nationalUN estimates to compensate for an apparent underestimation ofabout 5%.

Since the end of apartheid, the administrative boundariesin South Africa have changed considerably in an ongoing processof revisions.

Even though an updated boundary data set was availablefrom SADCC, the older boundaries matching the 1980 and 1990 censuseshave been used, since no pop estimates matching the new boundarieswere available.

Sudan

  1. Central Bureau of Statistics (1993), Populationcensus of Sudan 1993, Census Office, Khartoum. Incomplete dueto partial enumeration in Southern Sudan. Boundaries seemed tohave changed somewhat between '83 and '93, but no map was available.
  2. Population Studies Center (1983), Populationof Sudan and its regions, Project Document 1, 1983 census: Totalpopulations by region, province and district, University of Gezirajointly with Department of Statistics, Census Office.
  3. Republic of Sudan (1961), First population censusof Sudan 1955/56, Final report, Vol 1, Khartoum.
  4. Nelson, H.D. (1982), Sudan - A country study,Area Handbook Series, Federal Research Division of the Libraryof Congress.
  5. Ertur, O.S. and W.J. House (1994), Populationand human resources development in the Sudan, Compiled in cooperationwith UNFPA and ILO, Iowa State University Press, Ames.

4) and 5) list figures for 1973 by region.

Boundaries changed significantly between the threecensuses, so data had to be aggregated or split to match the availableboundary data set. The boundaries match the 1983 census althoughsome of the unit names are

different in the coverage and the census publications.

P90 is based on the intercensal 83-93 growth ratefor the districts (third level units) where available. Else theyare based on region level growth rates for the areas not enumerated.For these, only 1993 estimates were available.

Since matching of the 1956 and 73 units was verydifficult due to numerous boundary changes at the lower levels,P80 is based on regional level growth rates 73-83, and P60 andP70 are based on region level growth rates for 56-73.

Swaziland

  1. Swaziland Government (1986), 1986 Swaziland populationcensus, Vol. 1, Statistical Tables, Central Statistical Office,Mbabane.
  2. UN Demographic Yearbooks.

Pop data available from the 1966, 76, and 86 censuses.

Tanzania

  1. United Republic of Tanzania (1969), 1967 PopulationCensus. Vol. 1, Statistics for Enumeration Areas, Bureau ofStatistics, Dar-Es-Salaam.
  2. United Republic of Tanzania (1989), StatisticalAbstract of Tanzania 1987, Bureau of Statistics, Dar-Es-Salaam.
  3. United Republic of Tanzania (1989), Sensa 1988- The 1988 Population Census, Preliminary Results, Bureau of Statistics,Ministry of Finance, Economic Affairs and Planning, Dar-Es-Salaam.

District population figures were available for 1988- from 3. and for 1967 fro 1. Where district boundaries changedand the changes could not be reconstructed, district figures wereestimated assuming constant growth rates in the region; if itwas clear which regions were split, proportional adjustment wasused.1978 district totals: based on POP67 and growth rate 67-88. The resulting figures were uniformly adjusted to match the publishedregion totals for 1978.

P60-90 calculated by using the resulting intercensalgrowth rates for 66-78 and 78-88.

Boundaries were produced by the International Centerfor Research in Agroforestry (ICRAF)

Togo

WALTPS pop estimates based on:

  1. Etude d'une Image à Long Terme de l'Afrique.
  2. Lopez-Escartin N.: Données de base surla population, Togo: CEPED, No. 4, Paris, Août 1991.

Tunisia

  1. Direction General du Plan, Service des StatistiqueDemographiques (1966), Recensement General de la Population etdes Logements 3 Mai 1966, Ministere du Plan, Tunis
  2. Institut National de la Statistique (1975), RecensementGeneral de la Population et des Logements 8 Mai 1975, Ministeredu Plan, Tunis.
  3. Institut National de la Statistique (1984), recensementGeneral de la Population et de l'Habitat, Ministere du Plan, Tunis.

P60-90 based on inter-censal growth rates 66-75 and75-84. Some governates split between the 66 and 75 and betweenthe 75 and 84 census. For the resulting governates, constant growthrates were assumed - i.e., the population in the previous censuswas split in proportion to the population for the new governatesin the later census.

NAME1 is the region number

NAME2 is the governate

Uganda

  1. Republic of Uganda (1992), Provisional resultsof the 1991 Population and Housing Census, Statistics Department,Ministry of Finance and Economic Planning, Entebbe, Uganda
  2. Republic of Uganda (1992), The 1991 Populationand Housing Census, District Summary Series, Statistics Department,Ministry of Finance and Economic Planning, Entebbe, Uganda
  3. Republic of Uganda (1993), The 1991 Populationand Housing Census: Preliminary Estimates of Fertility and Mortality,1993, Statistics Department, Ministry of Finance and EconomicPlanning, Entebbe, Uganda

1980 and 1991 county figures from publications. 1969 county population based on district level growth rates 1969-80. Exception: the data for urban municipalities was available fromRoU (1992) and were considered explicitly. District growth rateswere calculated after subtracting the known municipality figuresfrom the 69 and 80 district totals.

P60-90 were calculated from resulting 69-80 and 80-90county growth rates.

Boundary data were produced by the National StatisticalOffice in collaboration with the UN Statistics Division's SoftwareDevelopment Project.

Zaire

  1. Romaniuk, A. (1968), The Demography of the DemographicRepublic of the Congo, in W. Brass et al (eds), The Demographyof Tropical Africa, Princeton University Press, Princeton
  2. Atlas des collectivites, de Saint-Moulin, Kinshasa1976
  3. Republique du Zaire (1984), Combien Sommes-Nous,Resultats Provisoires, Institut National de la Statistique, Kinshasa
  4. Republique du Zaire (undated), Zaire RecensementScientifique de la Population 1984, Totaux Definitifs, InstitutNational de la Statistique, Kinshasa [ contains pop figures downto cite/col level ]
  5. Groupe de Demographie Africaine (1986), Populationsize in African countries, IDP-INEP-INSEE-MICOOP-ORSTOM, Paris

GIS database produced by the Universitè Louvain,Belgium and obtained from the Department of Geography, Universityof Maryland. This database also includes population figures for1958, 70 and 84. These data had to be reconciled since boundarychanges occurred between the enumerations. All available sourcesand maps were used for this purpose.

Zambia

  1. Republic of Zambia (1973), Statistical Yearbook1971, Central Statistics Office, Lusaka
  2. Republic of Zambia (1989), Monthly Digest ofStatistics, January-June 1989, Central Statistics Office, Lusaka
  3. Republic of Zambia (1990), 1990 Census of Population,Housing, and Agriculture, Preliminary Report, Central StatisticsOffice, Lusaka

P60-90 based on censuses for 1963, 1969, 1980 and1990. In cases where districts were split between the 63 and69 censuses, the 63 population was distributed proportional tothe 69 figures.

Kalengwa Township data for 1990 was redistributedfrom Mufumbwe to Kasempa District to be consistent with priordata and boundaries.

Boundary data set was updated using maps in the censuspublications.

Zimbabwe

  1. Central Statistical Office (1969), Census ofPopulation 1969, Salisbury
  2. Central Statistical Office (1984), 1982 PopulationCensus. A preliminary assessment, Harare.
  3. Central Statistical Office (1992), 1992 PopulationCensus. Preliminary Report, Harare.

P60-90 based on published figures for 1961, 1969,1982 and 1992.

Listings for 1969 and 81 did not match 1992 listingswell. Unit names were matched and aggregated to the districtlevel using maps and the ward level GIS coverage obtained throughILRI as a reference. Missing values were estimated using averageprovince level growth rates.

Even though ward level boundaries were available,data were estimated only at the district level, since matchingof population census figures for smaller units would have beendifficult, if not impossible without more information from theNational Statistical Office.

GIS boundaries derived by dissolving the ward boundariesin the data set obtained from the International Livestock ResearchInstitute (ILRI) to the district level.

[ Country-specific documentation | African Population Distribution Database]

<URL: http://grid2.cr.usgs.gov/globalpop/africa/country-specific/r_z.htm>
Last modified: 21 February 1997.
Please address any comments or suggestions to uwe@ncgia.ucsb.edu. African Population Database Documentation : A.4.