Advanced search
1 file | 3.08 MB Add to list

Can we use local climate zones for predicting malaria prevalence across sub-Saharan African cities?

Author
Organization
Abstract
Malaria burden is increasing in sub-Saharan cities because of rapid and uncontrolled urbanization. Yet very few studies have studied the interactions between 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 modeling malaria prevalence rate (PfPR$_{2-10}$) 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 modeling 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%–30%) than rural areas (15%–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$_{2-10}$. 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 modeling in urban malaria studies.
Keywords
Renewable Energy, Sustainability and the Environment, Public Health, Environmental and Occupational Health, General Environmental Science, malaria, sub-Saharan africa, local climate zones, urban malaria modeling, random forest modeling, urban health, WUDAPT, OUTDOOR THERMAL COMFORT, DAR-ES-SALAAM, PLASMODIUM-FALCIPARUM, URBAN AGRICULTURE, TRANSMISSION, INEQUALITY, MANAGEMENT, INFECTION, MOSQUITOS, KAMPALA

Downloads

  • published.pdf
    • full text (Published version)
    • |
    • open access
    • |
    • PDF
    • |
    • 3.08 MB

Citation

Please use this url to cite or link to this publication:

MLA
Brousse, O., et al. “Can We Use Local Climate Zones for Predicting Malaria Prevalence across Sub-Saharan African Cities?” ENVIRONMENTAL RESEARCH LETTERS, vol. 15, no. 12, 2020, doi:10.1088/1748-9326/abc996.
APA
Brousse, O., Georganos, S., Demuzere, M., Dujardin, S., Lennert, M., Linard, C., … van Lipzig, N. P. M. (2020). Can we use local climate zones for predicting malaria prevalence across sub-Saharan African cities? ENVIRONMENTAL RESEARCH LETTERS, 15(12). https://doi.org/10.1088/1748-9326/abc996
Chicago author-date
Brousse, O., S. Georganos, Matthias Demuzere, S. Dujardin, M. Lennert, C. Linard, R. W. Snow, W. Thiery, and N. P. M. van Lipzig. 2020. “Can We Use Local Climate Zones for Predicting Malaria Prevalence across Sub-Saharan African Cities?” ENVIRONMENTAL RESEARCH LETTERS 15 (12). https://doi.org/10.1088/1748-9326/abc996.
Chicago author-date (all authors)
Brousse, O., S. Georganos, Matthias Demuzere, S. Dujardin, M. Lennert, C. Linard, R. W. Snow, W. Thiery, and N. P. M. van Lipzig. 2020. “Can We Use Local Climate Zones for Predicting Malaria Prevalence across Sub-Saharan African Cities?” ENVIRONMENTAL RESEARCH LETTERS 15 (12). doi:10.1088/1748-9326/abc996.
Vancouver
1.
Brousse O, Georganos S, Demuzere M, Dujardin S, Lennert M, Linard C, et al. Can we use local climate zones for predicting malaria prevalence across sub-Saharan African cities? ENVIRONMENTAL RESEARCH LETTERS. 2020;15(12).
IEEE
[1]
O. Brousse et al., “Can we use local climate zones for predicting malaria prevalence across sub-Saharan African cities?,” ENVIRONMENTAL RESEARCH LETTERS, vol. 15, no. 12, 2020.
@article{8692387,
  abstract     = {{Malaria burden is increasing in sub-Saharan cities because of rapid and uncontrolled urbanization. Yet very few studies have studied the interactions between 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 modeling malaria prevalence rate (PfPR$_{2-10}$) 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 modeling 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%–30%) than rural areas (15%–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$_{2-10}$. 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 modeling in urban malaria studies.}},
  articleno    = {{124051}},
  author       = {{Brousse, O. and Georganos, S. and Demuzere, Matthias and Dujardin, S. and Lennert, M. and Linard, C. and Snow, R. W. and Thiery, W. and van Lipzig, N. P. M.}},
  issn         = {{1748-9326}},
  journal      = {{ENVIRONMENTAL RESEARCH LETTERS}},
  keywords     = {{Renewable Energy,Sustainability and the Environment,Public Health,Environmental and Occupational Health,General Environmental Science,malaria,sub-Saharan africa,local climate zones,urban malaria modeling,random forest modeling,urban health,WUDAPT,OUTDOOR THERMAL COMFORT,DAR-ES-SALAAM,PLASMODIUM-FALCIPARUM,URBAN AGRICULTURE,TRANSMISSION,INEQUALITY,MANAGEMENT,INFECTION,MOSQUITOS,KAMPALA}},
  language     = {{eng}},
  number       = {{12}},
  pages        = {{15}},
  title        = {{Can we use local climate zones for predicting malaria prevalence across sub-Saharan African cities?}},
  url          = {{http://dx.doi.org/10.1088/1748-9326/abc996}},
  volume       = {{15}},
  year         = {{2020}},
}

Altmetric
View in Altmetric
Web of Science
Times cited: