The University of Southampton
University of Southampton Institutional Repository

Associations between urbanicity and malaria at local scales in Uganda

Associations between urbanicity and malaria at local scales in Uganda
Associations between urbanicity and malaria at local scales in Uganda
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
urbanization, plasmodium falciparum, remote sensing, gis, urban malaria
1475-2875
1-12
Kigozi, Simon P.
c722d422-5dab-403a-a4c7-4d858f06ea8b
Pindolia, Deepa K.
f207589b-cc5b-4daa-8d17-ff674d73c046
Smith, David L.
5c918948-ded2-42d8-82c1-a746a4bc3b6e
Arinaitwe, Emmanuel
c7dd79d1-1777-48a0-8f1e-47d17dff9984
Katureebe, Agaba
e01a4695-1781-4480-9fb6-bd9f69201852
Kilama, Maxwell
506e69af-6dae-4d4f-97c8-1db151cfe6e8
Nankabirwa, Joaniter
29e63677-b199-40d2-a0c2-3c2209a58ee9
Lindsay, Steve W.
3084dbd3-bb5b-45e7-b877-00aca7c14c0f
Staedke, Sarah G.
3a6cb007-22e1-48a4-bbe5-de0741601767
Dorsey, Grant
9faa37f3-1165-426c-98fa-6af7a6b8f25f
Kamya, Moses R.
03387243-8e72-4459-a3d6-63b0998b3098
Tatem, Andrew J.
6c6de104-a5f9-46e0-bb93-a1a7c980513e
Kigozi, Simon P.
c722d422-5dab-403a-a4c7-4d858f06ea8b
Pindolia, Deepa K.
f207589b-cc5b-4daa-8d17-ff674d73c046
Smith, David L.
5c918948-ded2-42d8-82c1-a746a4bc3b6e
Arinaitwe, Emmanuel
c7dd79d1-1777-48a0-8f1e-47d17dff9984
Katureebe, Agaba
e01a4695-1781-4480-9fb6-bd9f69201852
Kilama, Maxwell
506e69af-6dae-4d4f-97c8-1db151cfe6e8
Nankabirwa, Joaniter
29e63677-b199-40d2-a0c2-3c2209a58ee9
Lindsay, Steve W.
3084dbd3-bb5b-45e7-b877-00aca7c14c0f
Staedke, Sarah G.
3a6cb007-22e1-48a4-bbe5-de0741601767
Dorsey, Grant
9faa37f3-1165-426c-98fa-6af7a6b8f25f
Kamya, Moses R.
03387243-8e72-4459-a3d6-63b0998b3098
Tatem, Andrew J.
6c6de104-a5f9-46e0-bb93-a1a7c980513e

Kigozi, Simon P., Pindolia, Deepa K., Smith, David L., Arinaitwe, Emmanuel, Katureebe, Agaba, Kilama, Maxwell, Nankabirwa, Joaniter, Lindsay, Steve W., Staedke, Sarah G., Dorsey, Grant, Kamya, Moses R. and Tatem, Andrew J. (2015) Associations between urbanicity and malaria at local scales in Uganda. Malaria Journal, 14 (1), 1-12. (doi:10.1186/s12936-015-0865-2).

Record type: Article

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 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

Text
s12936-015-0865-2.pdf - Version of Record
Available under License Creative Commons Attribution.
Download (1MB)

More information

Accepted/In Press date: 22 August 2015
Published date: 29 September 2015
Keywords: urbanization, plasmodium falciparum, remote sensing, gis, urban malaria
Organisations: Global Env Change & Earth Observation, WorldPop, Population, Health & Wellbeing (PHeW)

Identifiers

Local EPrints ID: 382036
URI: http://eprints.soton.ac.uk/id/eprint/382036
ISSN: 1475-2875
PURE UUID: 3de622d2-dd70-4850-bd0e-2ade209b4792
ORCID for Andrew J. Tatem: ORCID iD orcid.org/0000-0002-7270-941X

Catalogue record

Date deposited: 19 Oct 2015 12:33
Last modified: 15 Mar 2024 03:43

Export record

Altmetrics

Contributors

Author: Simon P. Kigozi
Author: Deepa K. Pindolia
Author: David L. Smith
Author: Emmanuel Arinaitwe
Author: Agaba Katureebe
Author: Maxwell Kilama
Author: Joaniter Nankabirwa
Author: Steve W. Lindsay
Author: Sarah G. Staedke
Author: Grant Dorsey
Author: Moses R. Kamya
Author: Andrew J. Tatem ORCID iD

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×