May 2016 consolidation
New data
- Infrastructure - electricity - Energy Information Administration (EIA) - 1 series, preprocessor - pulled by Ryan, vetted by Brandon
| SeriesEnElecTotalCapacityEIA |
- Infrastructure - electricity - World Development Indicators (WDI) - 3 series, all preprocessor - pulled by Kanishka, vetted by Joel
| SeriesEnElecAccess%National |
| SeriesEnElecAccess%Rural |
| SeriesEnElecAccess%Urban |
- Health - Diabetes - International Diabetes Federation (IDF) - 2 series, both preprocessor - pulled by Joel, vetted by Brandon
| SeriesHealthDiabetesPrev% |
| SeriesHealthIGTPrev% |
- Health - HIV - UNAIDS - 6 series, all preprocessor - pulled by Joel, vetted by Brandon
| SeriesHealthUNAIDSDeathsHighEst |
| SeriesHealthUNAIDSDeathsLowEst |
| SeriesHealthUNAIDSDeathsMidEst |
| SeriesHealthUNAIDSTotalHIVHighEst |
| SeriesHealthUNAIDSTotalHIVLowEst |
| SeriesHealthUNAIDSTotalHIVMidEst |
- Water - AQUASTAT - 50 series, many preprocessor - pulled by Kristen, vetted by Joel
| SeriesDesalinatedWater |
| SeriesIrrigatedCropIntensity |
| SeriesIrWaterReq |
| SeriesIrWaterWith |
| SeriesLandCultivatedArea |
| SeriesLandEquipIrActual |
| SeriesLandEquipIrFullControl |
| SeriesLandEquipIrFullControlActual |
| SeriesLandIr%Grain |
| SeriesLandIrAreaSalinized |
| SeriesLandIrEquipDrained |
| SeriesLandIrEquipGround |
| SeriesLandIrHarvestedCropArea |
| SeriesLandIrWaterLogged |
| SeriesTotalDamCapacity |
| SeriesWasterwaterTreated |
| SeriesWasteWaterDirectNotTreated |
| SeriesWastewaterIrDirectTreated |
| SeriesWasteWaterLandEquipDirectNotTreated |
| SeriesWasteWaterLandEquipDirectTreated |
| SeriesWastewaterProduced |
| SeriesWastewaterTreatedReused |
| SeriesWaterDependencyRatio |
| SeriesWaterDesalinated |
| SeriesWaterGroundEntering |
| SeriesWaterGroundLeaving |
| SeriesWaterGroundProdInternal |
| SeriesWaterGroundTotal |
| SeriesWaterGroundWithD |
| SeriesWaterResExploitGround |
| SeriesWaterResExploitSurface |
| SeriesWaterResOverlap |
| SeriesWaterResTotalExploit |
| SeriesWaterResTotalRenew |
| SeriesWaterResTotalRenewGround |
| SeriesWaterResTotalRenewSurface |
| SeriesWaterSurfaceWithD |
| SeriesWaterTotalRenewPC |
| SeriesWaterTotalWithd |
| SeriesWaterTotalWithdPC |
| SeriesWaterTotalWithdSector |
| SeriesWaterTotalWithdSources |
| SeriesWaterWith%Agric |
| SeriesWaterWith%Fresh |
| SeriesWaterWith%Household |
| SeriesWaterWith%Ind |
| SeriesWaterWithAgr%FreshAquastat |
| SeriesWaterWithdAgriculture |
| SeriesWaterWithdIndustrial |
| SeriesWaterWithdMunicipal |
Affected modules
Infrastructure
Electricity capacity
The countries with the largest relative changes were mostly small island countries because previously we had little or no data for these countries. The countries with the largest relative increases in electrical capacity are Equatorial Guinea, Comoros, and Benin. The largest relative decreases occur in Timor-Leste and Seychelles.
Electricity access
Global access to electricity is now initialized at 85.3345% in 2015 rather than 84.2006%. The countries with the largest relative increase in access to electricity are Comoros, Somalia, Sierra Leone, Guinea-Bissau, and Rwanda. This is because there was previously either very old data for these countries or no data at all. The largest relative decreases occur in South Sudan, Seychelles, and St. Vincent and the Grenadines, for the same reason.
Note:This variable is used to fill holes for the portion of the population using solid fuels (CENSOLFUEL in DataInfra.bas and DataEnv.bas). That equation: "Percent of People using Primarily Solid Fuels (Full Model 2010)"was last updated on 12/18/2013 at 7:26:28 PM and should be reestimated with this new data. It also uses GDPPCP and PopUrban% as independent variables.
Health
Diabetes
The countries with the biggest absolute increases in DALYs from diabetes are: India, South Africa, Kenya, Tanzania, and Uganda. The countries with the largest absolute decreases in DALYs are Indonesia, China, and South Sudan. The countries with the largest relative increases are Lesotho, Zambia, and Kenya. The countries with the largest relative decreases are South Sudan, Sao Tome and Principe and the Bahamas.
Note:If impaired glucose intolerance (HelathIGTPrev%) is null it is estimated using the following equation: "GDP/Capita (PPP 2000) Versus Impaired Glucose Tolerance (2003) Log". This needs to be updated - unknown when it was last updated.
The same goes for filling holes in diabetes prevalence in the preprocessor. Holes are filled using: "GDP/Capita (PPP 2000) Versus Diabetes Prevalence (2003) Log". Unknown when this was last updated.
Also, these are initialized as CHLDIABIGT(ICount%) and CHLDIABPREV(ICount%) but I do not believe the data is for children. This needs to be investigated.
HIV
Global HIV prevalence is initialized higher after this data update. Global HIV prevalence is initialized at .472% in 2014 - it was initialized at .458% in 2014 before this data update. HIV prevalence in Africa is now initialized (2014) at 2.226% rather than 1.987% before this update.
The largest increases are in Botswana, Namibia, Zimbabwe, Uganda, and Swaziland. The largest decreases are in Kenya, CAR, and Sudan.
Note: HIV prevalence is heavily influenced by peak year, peak prevalence, and an initial growth rate (CHIVINCR(ICount%)). This growth rate is initialized as the square root of the ratio of 2006 data to 2004 data: CHIVINCR(ICount%) = (CHIVRATE06 / CHIVRATE04) ^ (1 / 2) - 1. We can update this using more recent data.
Also, the peak year and peak prevalence data are read from SeriesHIVPeaks which was updated in 2013. This table has both the year of peak and the prevalence of HIV in that year. BUT, the code is reading the columns "Peak Year" and "Peak Prevalence", which do not necessarily align with the most recent data.
Bugs and issues
- The "infrastructure overview" category produces a "Run -ime error 3021: No current record" error when clicked