Publication details for Prof Steve LindsayKigozi, S.P., Pindolia, D.K., Smith, D.L., Arinaitwe, E., Katureebe, A., Kilama, M., Nankabirwa, J., Lindsay, S.W., Staedke, S.G., Dorsey, G., Kamya, M.R. & Tatem, A.J. (2015). Associations between urbanicity and malaria at local scales in Uganda. Malaria Journal 14(1): 374.
- Publication type: Journal Article
- ISSN/ISBN: 1475-2875 (electronic)
- DOI: 10.1186/s12936-015-0865-2
- Further publication details on publisher web site
- Durham Research Online (DRO) - may include full text
Author(s) from Durham
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 for Anopheles 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 female Anopheles 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.