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Fig. 7 | BMC Public Health

Fig. 7

From: Geo-visual integration of health outcomes and risk factors using excess risk and conditioned choropleth maps: a case study of malaria incidence and sociodemographic determinants in Ghana

Fig. 7

a, b Malaria incidence conditional on basic education and (a) employment-to-population ratio (b) no/other religion where districts with relatively high rates due to co-location of the two risk factors were indicated in the different intensities of the brown colour. Numbers in the brackets indicate the number of districts for the rate as influenced by the two predictor variables. The maps were generated using GeoDa statistical software version 1.12. c, d Malaria incidence conditioned on urban and (c) employment-to-population ratio, and (d) no/other religion where districts with relatively high rates due to co-location of the two risk factors were indicated by the different intensities of the brown colour. Numbers in the brackets indicate the number of districts for the rate as influenced by the two predictor variables. The maps were generated using GeoDa statistical software version 1.12. e, f, g Malaria rate conditional on intermigration and (e) intramigration, (f) no/other religion (g) agric households where districts with relatively high rates due to co-location of the two risk factors were indicated by the different intensities of the brown colour. Numbers in the brackets indicate the number of districts for the rate as influenced by the two predictor variables. The maps were generated using GeoDa statistical software version 1.12. h, i Malaria rate conditional on Intramigration and (h) No/other religion and (i) Agric households where districts with relatively high rates due to co-location of the two risk factors were indicated by the different intensities of the brown colour. Numbers in the brackets indicate the number of districts for the rate as influenced by the two predictor variables. The maps were generated using GeoDa statistical software version 1.12. j, k Malaria rate conditional on no/other religion and (j) Employment-to-population ratio (k) Agric household where districts with relatively high rates due to co-location of the two risk factors were indicated by the different intensities of the brown colour. Numbers in the brackets indicate the number of districts for the rate as influenced by the two predictor variables. The maps were generated using GeoDa statistical software version 1.12

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