Obtaining district-level health estimates using geographically masked location from Demographic and Health Survey data

Table 1 Number of primary survey clusters per district, per method, in increasing order of district area (km²) in 2000 and 2004

District	Malawi 2000 DHS			Malawi 2004 DHS				District Area (km²)
District	Method A*	Method B	Method C	Method A*	Method B	Method C	Validation	District Area (km²)
Chiradzulu	24	14	12	18	12	11	11	767
Phalombe	12	9	9	17	10	10	10	1394
Ntchisi	9	5	7	9	7	7	7	1655
Thyolo	43	32	33	48	33	36	36	1715
Nsanje	9	8	8	12	7	8	8	1942
Blantyre	43	35	36	46	36	36	36	2012
Mulanje	49	37	36	50	33	36	36	2056
Balaka	21	12	13	19	13	11	11	2193
Salima	37	32	36	36	32	35	35	2196
Mwanza	8	4	6	9	6	6	6	2259
Zomba	47	38	37	47	37	36	36	2541
Dowa	27	21	18	23	18	16	16	3041
Karonga	36	31	7	9	5	7	7	3355
Mchinji	18	14	15	16	15	13	13	3356
Ntcheu	21	16	14	18	13	15	15	3424
Dedza	26	24	22	26	22	20	20	3624
Machinga	31	34	34	40	34	36	36	3771
Nkhata Bay	11	8	6	8	5	6	6	4071
Nkhotakota	13	8	6	14	5	8	8	4259
Chitipa	5	5	5	5	5	5	5	4288
Chikwawa	17	16	16	21	16	14	14	4755
Rumphi	7	5	4	5	4	4	4	4769
Lilongwe	41	35	33	48	33	36	36	6159
Mangochi	40	36	36	44	33	36	36	6273
Kasungu	40	35	33	41	33	36	36	7878
Mzimba	41	36	37	39	37	36	36	10,430

*Method A accounts for survey clusters per district using two columns: a survey cluster’s maximum displacement area may be entirely within a district’s boundaries, or, a survey cluster may have more than one possible district of origin, in which case partial survey clusters are counted

ISSN: 1476-072X