Challenges of DHS and MIS to capture the entire pattern of malaria parasite risk and intervention effects in countries with different ecological zones: the case of Cameroon

Table 2 Posterior inclusion probabilities (%) of the climatic predictors and intervention coverage indicators obtained by the geostatistical variable selection applied to DHS and MIS data

Model	Variable	DHS			MIS
Model	Variable	Excluded	Continuous form	Categorical form	Excluded	Continuous form	Categorical form
Model 1, 2: cluster level	Rainfall	58	42	0	36	18	46
	NDVI^a	14	86	0	12	83	5
	LSTD	80	20	0	55	23	22
	EVI^a	56	32	12	16	17	67
	Distance to water body^a	41	33	26	23	25	52
	Altitude^a	0	0	100	1	96	3
	LSTN	43	10	47	54	29	17
	Forest^a	69	–	31	34	–	66
	Savana	58	–	42	69	–	31
	Cropland	82	–	18	72	–	28
Model 2: individual level	% population with access to an ITN in their household^a	17	83	–	42	58	–
	% households with at least one ITN	62	38	–	64	36	–
	% children slept under ITN previous night	61	39	–	36	64	–
	% of households with one ITN per two persons^a	52	48	–	33	67	–
	% of children with fever who received recommended anti-malarial drugs (ACT)^a	46	54	–	70	30	–

^aVariable with posterior inclusion probability (continuous or categorical) above 50%

ISSN: 1475-2875