2021 Socio Economic Impact Assessment of COVID-19 on Households in Zambia
1st Edition
Zambia, 2021
Get Microdata
Reference ID
ZMB-ZSA-SEIA-2021-V1.0
Producer(s)
Zambia Statistics Agency,
Metadata
Created on
Jan 16, 2026
Last modified
Jan 17, 2026
Page views
3687
Downloads
12
District (DIST)
Data file: HouseholdRoster_A
Overview
Valid:
48560
Invalid:
0
Minimum:
101
Maximum:
1016
Type:
Continuous
Decimal:
0
Width:
4
Range:
101 - 1016
Format:
Numeric
Questions and instructions
Categories
| Value | Category | Cases | |
|---|---|---|---|
| 101 | Chibombo | 687 |
1.4%
|
| 102 | Chisamba | 313 |
0.6%
|
| 103 | Chitambo | 87 |
0.2%
|
| 104 | Itezhi-tezhi | 224 |
0.5%
|
| 105 | Kabwe | 1046 |
2.2%
|
| 106 | Kapiri Mposhi | 556 |
1.1%
|
| 107 | Luano | 95 |
0.2%
|
| 108 | Mkushi | 343 |
0.7%
|
| 109 | Mumbwa | 534 |
1.1%
|
| 110 | Ngabwe | 105 |
0.2%
|
| 111 | Serenje | 292 |
0.6%
|
| 201 | Chililabombwe | 325 |
0.7%
|
| 202 | Chingola | 518 |
1.1%
|
| 203 | Kalulushi | 444 |
0.9%
|
| 204 | Kitwe | 1255 |
2.6%
|
| 205 | Luanshya | 575 |
1.2%
|
| 206 | Lufwanyama | 334 |
0.7%
|
| 207 | Masaiti | 411 |
0.8%
|
| 208 | Mpongwe | 495 |
1%
|
| 209 | Mufulira | 448 |
0.9%
|
| 210 | Ndola | 1213 |
2.5%
|
| 301 | Chadiza | 114 |
0.2%
|
| 302 | Chipata | 1829 |
3.8%
|
| 303 | Katete | 607 |
1.3%
|
| 304 | Lundazi | 998 |
2.1%
|
| 305 | Mambwe | 149 |
0.3%
|
| 306 | Nyimba | 225 |
0.5%
|
| 307 | Petauke | 927 |
1.9%
|
| 308 | Sinda | 613 |
1.3%
|
| 309 | Vubwi | 123 |
0.3%
|
| 401 | Chembe | 188 |
0.4%
|
| 402 | Chiengi | 455 |
0.9%
|
| 403 | Chipili | 135 |
0.3%
|
| 404 | Kawambwa | 525 |
1.1%
|
| 405 | Lunga | 137 |
0.3%
|
| 406 | Mansa | 1100 |
2.3%
|
| 407 | Milenge | 144 |
0.3%
|
| 408 | Mwansabombwe | 254 |
0.5%
|
| 409 | Mwense | 502 |
1%
|
| 410 | Nchelenge | 965 |
2%
|
| 411 | Samfya | 748 |
1.5%
|
| 501 | Chilanga | 451 |
0.9%
|
| 502 | Chirundu | 103 |
0.2%
|
| 503 | Chongwe | 618 |
1.3%
|
| 504 | Kafue | 440 |
0.9%
|
| 505 | Luangwa | 113 |
0.2%
|
| 506 | Lusaka | 3713 |
7.6%
|
| 507 | Rufunsa | 252 |
0.5%
|
| 508 | Shibuyungi | 109 |
0.2%
|
| 601 | Chama | 481 |
1%
|
| 602 | Chinsali | 502 |
1%
|
| 603 | Isoka | 399 |
0.8%
|
| 604 | Mafinga | 170 |
0.4%
|
| 605 | Mpika | 1087 |
2.2%
|
| 606 | Nakonde | 645 |
1.3%
|
| 607 | Shiwangandu | 204 |
0.4%
|
| 701 | Chilubi | 375 |
0.8%
|
| 702 | Kaputa | 442 |
0.9%
|
| 703 | Kasama | 1064 |
2.2%
|
| 704 | Luwingu | 580 |
1.2%
|
| 705 | Mbala | 740 |
1.5%
|
| 706 | Mporokoso | 345 |
0.7%
|
| 707 | Mpulungu | 720 |
1.5%
|
| 708 | Mungwi | 486 |
1%
|
| 709 | Nsama | 110 |
0.2%
|
| 801 | Chavuma | 257 |
0.5%
|
| 802 | Ikelenge | 121 |
0.2%
|
| 803 | Kabompo | 391 |
0.8%
|
| 804 | Kasempa | 217 |
0.4%
|
| 805 | Manyinga | 402 |
0.8%
|
| 806 | Mufumbwe | 230 |
0.5%
|
| 807 | Mwinilunga | 565 |
1.2%
|
| 808 | Solwezi | 1338 |
2.8%
|
| 809 | Zambezi | 263 |
0.5%
|
| 901 | Chikankata | 144 |
0.3%
|
| 902 | Choma | 629 |
1.3%
|
| 903 | Gwembe | 117 |
0.2%
|
| 904 | Kalomo | 684 |
1.4%
|
| 905 | Kazungula | 343 |
0.7%
|
| 906 | Livingstone | 909 |
1.9%
|
| 907 | Mazabuka | 351 |
0.7%
|
| 908 | Monze | 804 |
1.7%
|
| 909 | Namwala | 277 |
0.6%
|
| 910 | Pemba | 147 |
0.3%
|
| 911 | Siavonga | 277 |
0.6%
|
| 912 | Sinazongwe | 227 |
0.5%
|
| 913 | Zimba | 461 |
0.9%
|
| 1001 | Kalabo | 501 |
1%
|
| 1002 | Kaoma | 289 |
0.6%
|
| 1003 | Limulunga | 312 |
0.6%
|
| 1004 | Luampa | 133 |
0.3%
|
| 1005 | Lukulu | 376 |
0.8%
|
| 1006 | Mitete | 105 |
0.2%
|
| 1007 | Mongu | 646 |
1.3%
|
| 1008 | Mulobezi | 130 |
0.3%
|
| 1009 | Mwandi | 104 |
0.2%
|
| 1010 | Nalolo | 259 |
0.5%
|
| 1011 | Nkeyema | 272 |
0.6%
|
| 1012 | Senanga | 426 |
0.9%
|
| 1013 | Sesheke | 115 |
0.2%
|
| 1014 | Shang'ombo | 216 |
0.4%
|
| 1015 | Sikongo | 208 |
0.4%
|
| 1016 | Sioma | 127 |
0.3%
|
Warning: these figures indicate the number of cases found in the data file. They cannot be interpreted as summary statistics of the population of interest.