Journal article
Can we use local climate zones for predicting malaria prevalence across sub-Saharan African cities?
- Abstract:
- Malaria burden is increasing in sub-Saharan cities because of their rapid and uncontrolled urbanization. Yet very few studies have studied the interactions between the urban environments and malaria. Additionally, no standardized urban land-use/land-cover has been defined for urban malaria studies. Here, we demonstrate the potential of Local Climate Zones (LCZs) for modelling malaria (PfPR 2-10) prevalence and studying malaria prevalence in urban settings across nine sub-Saharan African cities. Using a random forest classification algorithm over a set of 365 malaria surveys we: (i) identify a suitable set of covariates derived from open-source earth observations; and (ii) depict the best buffer size at which to aggregate them for modelling PfPR 2-10. Our results demonstrate that geographical models can learn from LCZ over a set of cities and be transferred over a city of choice that has few or no malaria surveys. In particular, we find that urban areas systematically have lower PfPR 2-10 (5 % to 30 %) than rural areas (15 % to 40 %). The PfPR 2-10 urban-to-rural gradient is dependent on the climatic environment in which the city is located. Further, LCZs show that more open urban environments located close to wetlands have higher PfPR 2-10. We also find that informal settlements -- represented by the LCZ~7 (lightweight lowrise) -- have higher malaria prevalence than other densely built-up residential areas with a mean prevalence of 11.11 %. Overall, we suggest the applicability of LCZs for more exploratory modelling in urban malaria studies.
- Publication status:
- Published
- Peer review status:
- Peer reviewed
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(Preview, Version of record, pdf, 2.9MB, Terms of use)
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- Publisher copy:
- 10.1088/1748-9326/abc996
Authors
- Publisher:
- IOP Publishing
- Journal:
- Environmental Research Letters More from this journal
- Volume:
- 15
- Issue:
- 12
- Article number:
- 124051
- Publication date:
- 2020-12-14
- Acceptance date:
- 2020-11-11
- DOI:
- EISSN:
-
1748-9326
- Language:
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English
- Keywords:
- Pubs id:
-
1145510
- Local pid:
-
pubs:1145510
- Deposit date:
-
2020-11-16
- ARK identifier:
Terms of use
- Copyright holder:
- Brousse et al.
- Copyright date:
- 2020
- Rights statement:
- ©2020 The Author(s). Published by IOP Publishing Ltd
- Notes:
- Original Content from this work may be used under the terms of the Creative Commons Attribution 4.0 licence. Any further distribution of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI.
- Licence:
- CC Attribution (CC BY)
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