Associations between urbanicity and malaria at local scales in Uganda. (December 2015)

• Record Type: Journal Article
• Authors: Kigozi, Simon; Pindolia, Deepa; Smith, David; Arinaitwe, Emmanuel; Katureebe, Agaba; Kilama, Maxwell; Nankabirwa, Joaniter; Lindsay, Steve; Staedke, Sarah; Dorsey, Grant; Kamya, Moses; Tatem, Andrew
• Is Part Of: Malaria journal. Volume 14:Number 1(2015)
• Page Start: 1
• Page End: 12
• Publication Date: 2015-12
• Subjects: Urbanization -- Plasmodium falciparum -- Remote sensing -- GIS -- Urban malaria; Malaria -- Periodicals; 616.9362
• DOI: 10.1186/s12936-015-0865-2
• Languages: English
• ISSNs: 1475-2875

Abstract

Abstract Background Sub-Saharan Africa is expected to show the greatest rates of urbanization over the next 50 years. Urbanization has shown a substantial impact in reducing malaria transmission due to multiple factors, including unfavourable habitats forAnopheles mosquitoes, generally healthier human populations, better access to healthcare, and higher housing standards. Statistical relationships have been explored at global and local scales, but generally only examining the effects of urbanization on single malaria metrics. In this study, associations between multiple measures of urbanization and a variety of malaria metrics were estimated at local scales. Methods Cohorts of children and adults from 100 households across each of three contrasting sub-counties of Uganda (Walukuba, Nagongera and Kihihi) were followed for 24 months. Measures of urbanicity included density of surrounding households, vegetation index, satellite-derived night-time lights, land cover, and a composite urbanicity score. Malaria metrics included the household density of mosquitoes (number of femaleAnopheles mosquitoes captured), parasite prevalence and malaria incidence. Associations between measures of urbanicity and malaria metrics were made using negative binomial and logistic regression models. Results One site (Walukuba) had significantly higher urbanicity measures compared to the two rural sites. In Walukuba, all individual measures of higher urbanicity were significantly associated with a lower household density of mosquitoes. The higher composite urbanicity score in Walukuba was also associated with a lower household density of mosquitoes (incidence rate ratio = 0.28, 95 % CI 0.17–0.48, p < 0.001) and a lower parasite prevalence (odds ratio, OR = 0.44, CI 0.20–0.97, p = 0.04). In one rural site (Kihihi), only a higher density of surrounding households was associated with a lower parasite prevalence (OR = 0.15, CI 0.07–0.34, p < 0.001). And, in only one rural site (Nagongera) was living where NDVI ≤0.45 associated with higher incidence of malaria (IRR = 1.35, CI 1.35–1.70, p = 0.01). Conclusions Urbanicity has been shown previously to lead to a reduction in malaria transmission at large spatial scales. At finer scales, individual household measures of higher urbanicity were associated with lower mosquito densities and parasite prevalence only in the site that was generally characterized as being urban. The approaches outlined here can help better characterize urbanicity at the household level and improve targeting of control interventions.