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Mapping intra-urban malaria risk using high resolution satellite imagery: a case study of Dar es Salaam

Overview of attention for article published in International Journal of Health Geographics, July 2016
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  • Good Attention Score compared to outputs of the same age (65th percentile)
  • Above-average Attention Score compared to outputs of the same age and source (57th percentile)

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45 Dimensions

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172 Mendeley
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Title
Mapping intra-urban malaria risk using high resolution satellite imagery: a case study of Dar es Salaam
Published in
International Journal of Health Geographics, July 2016
DOI 10.1186/s12942-016-0051-y
Pubmed ID
Authors

Caroline W. Kabaria, Fabrizio Molteni, Renata Mandike, Frank Chacky, Abdisalan M. Noor, Robert W. Snow, Catherine Linard

Abstract

With more than half of Africa's population expected to live in urban settlements by 2030, the burden of malaria among urban populations in Africa continues to rise with an increasing number of people at risk of infection. However, malaria intervention across Africa remains focused on rural, highly endemic communities with far fewer strategic policy directions for the control of malaria in rapidly growing African urban settlements. The complex and heterogeneous nature of urban malaria requires a better understanding of the spatial and temporal patterns of urban malaria risk in order to design effective urban malaria control programs. In this study, we use remotely sensed variables and other environmental covariates to examine the predictability of intra-urban variations of malaria infection risk across the rapidly growing city of Dar es Salaam, Tanzania between 2006 and 2014. High resolution SPOT satellite imagery was used to identify urban environmental factors associated malaria prevalence in Dar es Salaam. Supervised classification with a random forest classifier was used to develop high resolution land cover classes that were combined with malaria parasite prevalence data to identify environmental factors that influence localized heterogeneity of malaria transmission and develop a high resolution predictive malaria risk map of Dar es Salaam. Results indicate that the risk of malaria infection varied across the city. The risk of infection increased away from the city centre with lower parasite prevalence predicted in administrative units in the city centre compared to administrative units in the peri-urban suburbs. The variation in malaria risk within Dar es Salaam was shown to be influenced by varying environmental factors. Higher malaria risks were associated with proximity to dense vegetation, inland water and wet/swampy areas while lower risk of infection was predicted in densely built-up areas. The predictive maps produced can serve as valuable resources for municipal councils aiming to shrink the extents of malaria across cities, target resources for vector control or intensify mosquito and disease surveillance. The semi-automated modelling process developed can be replicated in other urban areas to identify factors that influence heterogeneity in malaria risk patterns and detect vulnerable zones. There is a definite need to expand research into the unique epidemiology of malaria transmission in urban areas for focal elimination and sustained control agendas.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 172 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 <1%
Brazil 1 <1%
Unknown 170 99%

Demographic breakdown

Readers by professional status Count As %
Student > Master 31 18%
Researcher 22 13%
Student > Ph. D. Student 16 9%
Student > Doctoral Student 15 9%
Student > Bachelor 14 8%
Other 24 14%
Unknown 50 29%
Readers by discipline Count As %
Medicine and Dentistry 15 9%
Environmental Science 15 9%
Nursing and Health Professions 14 8%
Social Sciences 13 8%
Agricultural and Biological Sciences 11 6%
Other 36 21%
Unknown 68 40%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 4. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 05 December 2017.
All research outputs
#7,241,008
of 22,881,964 outputs
Outputs from International Journal of Health Geographics
#250
of 629 outputs
Outputs of similar age
#123,739
of 365,576 outputs
Outputs of similar age from International Journal of Health Geographics
#6
of 14 outputs
Altmetric has tracked 22,881,964 research outputs across all sources so far. This one has received more attention than most of these and is in the 67th percentile.
So far Altmetric has tracked 629 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 9.4. This one has gotten more attention than average, scoring higher than 58% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 365,576 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 65% of its contemporaries.
We're also able to compare this research output to 14 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 57% of its contemporaries.