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X Demographics
Mendeley readers
Attention Score in Context
| Title |
A novel method for mapping village-scale outdoor resting microhabitats of the primary African malaria vector, Anopheles gambiae
|
|---|---|
| Published in |
Malaria Journal, September 2016
|
| DOI | 10.1186/s12936-016-1534-9 |
| Pubmed ID | |
| Authors |
Julius R. Dewald, Douglas O. Fuller, Günter C. Müller, John C. Beier |
| Abstract |
Knowledge of Anopheles resting habitats is needed to advance outdoor malaria vector control. This study presents a technique to map locations of resting habitats using high-resolution satellite imagery (world view 2) and probabilistic Dempster-Shafer (D-S) modelling, focused on a rural village in southern Mali, West Africa where field sampling was conducted to determine outdoor habitat preferences of Anopheles gambiae, the main vector in the study area. A combination of supervised and manual image classification was used to derive an accurate land-cover map from the satellite image that provided classes (i.e., photosynthetically active vegetation, water bodies, wetlands, and buildings) suitable for habitat assessment. Linear fuzzy functions were applied to the different image classes to scale resting habitat covariates into a common data range (0-1) with fuzzy breakpoints parameterized experimentally through comparison with mosquito outdoor resting data. Fuzzy layers were entered into a Dempster-Shafer (D-S) weight-of-evidence model that produced pixel-based probability of resting habitat locations. The D-S model provided a highly detailed suitability map of resting locations. The results indicated a significant difference (p < 0.001) between D-S values at locations positive for An. gambiae and a set of randomly sampled points. Further, a negative binomial regression indicated that although the D-S estimates did not predict abundance (p > 0.05) subsequent analysis suggested that the D-S modelling approach may provide a reasonable estimate locations of low-to-medium An. gambiae density. These results suggest that that D-S modelling performed well in identifying presence points and specifically resting habitats. The use of a D-S modelling framework for predicting the outdoor resting habitat locations provided novel information on this little-known aspect of anopheline ecology. The technique used here may be applied more broadly at different geographic scales using Google Earth, Landsat or other remotely-sensed imagery to assess the malaria vector resting habitats where outdoor control measures can reduce the burden of the disease in Africa and elsewhere. |
X Demographics
The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 1 | 50% |
| Unknown | 1 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 1 | 50% |
| Members of the public | 1 | 50% |
Mendeley readers
The data shown below were compiled from readership statistics for 59 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 59 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 10 | 17% |
| Student > Doctoral Student | 8 | 14% |
| Researcher | 6 | 10% |
| Student > Master | 6 | 10% |
| Student > Bachelor | 5 | 8% |
| Other | 13 | 22% |
| Unknown | 11 | 19% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 13 | 22% |
| Medicine and Dentistry | 10 | 17% |
| Environmental Science | 7 | 12% |
| Engineering | 3 | 5% |
| Nursing and Health Professions | 2 | 3% |
| Other | 7 | 12% |
| Unknown | 17 | 29% |
Attention Score in Context
This research output has an Altmetric Attention Score of 2. 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 09 August 2017.
All research outputs
#15,392,095
of 24,400,706 outputs
Outputs from Malaria Journal
#4,179
of 5,827 outputs
Outputs of similar age
#189,464
of 326,413 outputs
Outputs of similar age from Malaria Journal
#72
of 118 outputs
Altmetric has tracked 24,400,706 research outputs across all sources so far. This one is in the 34th percentile – i.e., 34% of other outputs scored the same or lower than it.
So far Altmetric has tracked 5,827 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 7.0. This one is in the 24th percentile – i.e., 24% of its peers scored the same or lower than it.
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 326,413 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 39th percentile – i.e., 39% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 118 others from the same source and published within six weeks on either side of this one. This one is in the 32nd percentile – i.e., 32% of its contemporaries scored the same or lower than it.