Note related to winterization: Data set and projections of target population Table of Contents Main findings .......................................................................................................................................... 1 Method of calculation ............................................................................................................................ 1 Non-Food Items ...................................................................................................................................... 3 Shoes indicator: .................................................................................................................................. 3 Winter jacket indicator: ...................................................................................................................... 4 Blanket indicator: ............................................................................................................................... 5 Thermal underwear indicator: ........................................................................................................... 6 Socks indicator: ................................................................................................................................... 7 Mattresses indicator:.......................................................................................................................... 8 Fuel and heater....................................................................................................................................... 9 Projection of target population- frontline Luhansk.............................................................................. 10 Clustered raion district names ............................................................................................................. 11 Main findings Despite the difficulty to know the exact population baseline and need assessments, the winterization is targeting between 7.2% to 13.3% of IDP registered population1 depending on type of items and location. Part of the population of concern is actually living in NGCA but realistic projection could not be included in this document. Method of calculation The registered population in 2015 is over 1.4 million IDPs who registered due to displacement and also for other considerations. In parallel, an extract from MoSP database2 and based on renewal/extension of IDPs’ certificates has shown that 753,759 individuals are registered, a figure used here for triangulation of population baseline. The triangulation was done on very conservative manner in order to not mislead and create fake needs and potential duplication. 1 Based on Ministry of Social Policy of Ukraine official IDP registered population of 1.4 million. 2 Potentially the extract is not reflecting the entire population baseline and the exact confirmed IDPs population is higher. In same time cluster partners reported in Kharkiv that around 70% of interviewees (out of pensioner caseload) did confirm their stay in Kharkiv and Kharkiv oblast. Note on winterization: data set & projections Page 1 In parallel, winterization should also, in general, take account of feasibility in terms of capacity for distribution and also data collection/beneficiaries identification. Such statement leads to get a disaggregation of population between in GCA and NGCA3. In NGCA and due to the tremendous challenge for security and access, no educated guess could be done realistically feasible until now. For GCA, the following paragraphs aimed at summarizing key figures for IDP targeting especially focusing on Northern Donbas subnational cluster area of intervention. Calculation of need has been made using the Shelter Cluster/REACH Shelter Assessment, data for which was collected May-June 2015. Key indicators of reported need for non-food items relating to winter and access to fuel and sufficient heating are used here to project % and therefore numbers of displaced families in need of winter assistance. Data is broken down to a ‘clustered raion’ level to assist with targeting of localities, given disparities of need between areas. 3 In GCA, usually IDPs are the population of concern, where in NGCA population of concern could also include returning IDPs and also affected population. Note on winterization: data set & projections Page 2 Projection of target population- IDP families Non-Food Items Shoes indicator: Household indicator: “Do you have at least one per person of shoes?” Total 121 788 Northern Donbas 63 218 RURAL 59 052 Rural Donetsk 32 948 Rural Luhansk 10 048 URBAN 62 736 Urban Donetsk 11 123 Urban Luhansk 9 099 Theoretical % of Triangulated Needs projected, Rural Need population confirmed population individuals Rural Dnipropetrovsk #1 30,71% 4993 58,04% 2897 889 Rural Dnipropetrovsk #2 38,37% 5666 58,04% 3288 1261 Rural Dnipropetrovsk #3 15,75% 1521 58,04% 882 138 Rural Dnipropetrovsk #4 9,25% 13273 58,04% 7703 712 Rural Donetsk #1 27,88% 29448 54,18% 15953 4448 Rural Donetsk #2 15,74% 29448 54,18% 15953 2510 Rural Donetsk #3 54,45% 57999 54,18% 31421 17109 Rural Donetsk #4 29,89% 54859 54,18% 29720 8881 Rural Kharkiv #1 20,00% 8026 46,33% 3718 743 Rural Kharkiv #2 33,62% 7834 46,33% 3629 1220 Rural Kharkiv #3 23,33% 6901 46,33% 3197 745 Rural Kharkiv #4 32,69% 16526 46,33% 7656 2502 Rural Kharkiv #5 15,08% 14463 46,33% 6700 1010 Rural Luhansk #1 35,67% 23396 67,42% 15774 5626 Rural Luhansk #2 8,56% 67021 67,42% 45188 3866 Rural Luhansk #3 11,46% 1184 67,42% 798 91 Rural Luhansk #4 7,37% 9366 67,42% 6314 465 Rural Zaporizhia #1 44,62% 12245 40,38% 4944 2206 Rural Zaporizhia #2 62,02% 18491 40,38% 7467 4630 Urban Berdiansk 66,94% 14118 40,38% 5701 3816 Dniprodzerzhynsk 44,58% 4221 58,04% 2449 1091 Dnipropetrovsk 39,27% 28149 58,04% 16336 6415 Dymytrov / Krasnoarmiisk 8,84% 69165 54,18% 37470 3310 Dzerzhynsk / Kostiantynivka 14,29% 55101 54,18% 29851 4264 Izium 7,51% 23118 46,33% 10710 804 Kharkiv 43,56% 80949 46,33% 37505 16338 Kramatorsk / Druzhkivka 2,90% 53499 54,18% 28983 840 Kryvyi Rih 41,08% 7449 46,33% 3451 1417 Mariupol 12,24% 62312 54,18% 33758 4130 Melitopol 29,86% 3798 40,38% 1533 457 Nikopol 59,15% 1975 46,33% 915 541 Pavlohrad 8,29% 5571 46,33% 2581 214 Severodonetsk 24,77% 54482 67,42% 36733 9099 Sloviansk 16,89% 29613 54,18% 16043 2709 Zaporizhia 48,89% 36936 40,38% 14915 7291 Note on winterization: data set & projections Page 3 Winter jacket indicator: Household indicator: “Do you have at least one per person of winter jackets?” Total 136 313 Northern Donbas 74 509 RURAL 59 209 Rural Donetsk 26 909 Rural Luhansk 17 054 URBAN 77 104 Urban Donetsk 20 268 Urban Luhansk 10 278 Theoretical % of Triangulated projected need Rural REACH population confirmed population in individual Rural Dnipropetrovsk #1 23,57% 4993 58,04% 2897 682 Rural Dnipropetrovsk #2 24,42% 5666 58,04% 3288 802 Rural Dnipropetrovsk #3 24,80% 1521 58,04% 882 218 Rural Dnipropetrovsk #4 16,76% 13273 58,04% 7703 1291 Rural Donetsk #1 13,94% 29448 54,18% 15953 2224 Rural Donetsk #2 9,84% 29448 54,18% 15953 1569 Rural Donetsk #3 40,41% 57999 54,18% 31421 12697 Rural Donetsk #4 35,06% 54859 54,18% 29720 10419 Rural Kharkiv #1 24,00% 8026 46,33% 3718 892 Rural Kharkiv #2 39,30% 7834 46,33% 3629 1426 Rural Kharkiv #3 27,78% 6901 46,33% 3197 888 Rural Kharkiv #4 26,15% 16526 46,33% 7656 2002 Rural Kharkiv #5 12,30% 14463 46,33% 6700 824 Rural Luhansk #1 30,67% 23396 67,42% 15774 4837 Rural Luhansk #2 22,99% 67021 67,42% 45188 10390 Rural Luhansk #3 29,17% 1184 67,42% 798 232 Rural Luhansk #4 25,26% 9366 67,42% 6314 1595 Rural Zaporizhia #1 31,01% 12245 40,38% 4944 1533 Rural Zaporizhia #2 62,79% 18491 40,38% 7467 4688 Urban REACH Berdiansk 63,67% 14118 40,38% 5701 3630 Dniprodzerzhynsk 20,00% 4221 58,04% 2449 489 Dnipropetrovsk 29,15% 28149 58,04% 16336 4761 Dymytrov / Krasnoarmiisk 14,46% 69165 54,18% 37470 5417 Dzerzhynsk / Kostiantynivka 20,71% 55101 54,18% 29851 6183 Izium 4,23% 23118 46,33% 10710 452 Kharkiv 50,50% 80949 46,33% 37505 18938 Kramatorsk / Druzhkivka 18,84% 53499 54,18% 28983 5460 Kryvyi Rih 25,41% 7449 46,33% 3451 876 Mariupol 31,65% 62312 54,18% 33758 10682 Melitopol 36,65% 3798 40,38% 1533 561 Nikopol 52,44% 1975 46,33% 915 479 Pavlohrad 12,44% 5571 46,33% 2581 321 Severodonetsk 27,98% 54482 67,42% 36733 10278 Sloviansk 20,00% 29613 54,18% 16043 3208 Zaporizhia 36,00% 36936 40,38% 14915 5369 Note on winterization: data set & projections Page 4 Blanket indicator: Household indicator: “Do you have at least one per person of blankets?” Total 77 483 Northern Donbas 31 967 RURAL 29 500 Rural Donetsk 12 951 Rural Luhansk 3 816 URBAN 47 983 Urban Donetsk 11 302 Urban Luhansk 3 898 Needs Theoretical % of Triangulated projected, Rural Need population confirmed population individuals Rural Dnipropetrovsk #1 13,21% 4993 58,04% 2897 382 Rural Dnipropetrovsk #2 19,19% 5666 58,04% 3288 630 Rural Dnipropetrovsk #3 14,17% 1521 58,04% 882 125 Rural Dnipropetrovsk #4 6,94% 13273 58,04% 7703 534 Rural Donetsk #1 15,87% 29448 54,18% 15953 2531 Rural Donetsk #2 6,23% 29448 54,18% 15953 993 Rural Donetsk #3 23,29% 57999 54,18% 31421 7317 Rural Donetsk #4 2,87% 54859 54,18% 29720 854 Rural Kharkiv #1 18,86% 8026 46,33% 3718 701 Rural Kharkiv #2 30,13% 7834 46,33% 3629 1093 Rural Kharkiv #3 15,56% 6901 46,33% 3197 497 Rural Kharkiv #4 7,31% 16526 46,33% 7656 559 Rural Kharkiv #5 13,10% 14463 46,33% 6700 877 Rural Luhansk #1 17,67% 23396 67,42% 15774 2786 Rural Luhansk #2 2,67% 67021 67,42% 45188 1208 Rural Luhansk #3 7,81% 1184 67,42% 798 62 Rural Luhansk #4 3,68% 9366 67,42% 6314