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Estimating the spatial risk of tuberculosis distribution in Gurage zone, southern Ethiopia: a geostatistical kriging approach

Overview of attention for article published in BMC Public Health, June 2018
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  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (75th percentile)
  • Average Attention Score compared to outputs of the same age and source

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1 blog
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Title
Estimating the spatial risk of tuberculosis distribution in Gurage zone, southern Ethiopia: a geostatistical kriging approach
Published in
BMC Public Health, June 2018
DOI 10.1186/s12889-018-5711-3
Pubmed ID
Authors

Sebsibe Tadesse, Fikre Enqueselassie, Seifu Hagos Gebreyesus

Abstract

In low-income countries it is difficult to obtain complete data that show spatial heterogeneity in the risk of tuberculosis within-and-between smaller administrative units. This may contribute to the partial effectiveness of tuberculosis control programs. The aim of this study was to estimate the spatial risk of tuberculosis distribution in Gurage Zone, Southern Ethiopia using limited spatial datasets. A total of 1601 patient data that were retrieved from unit tuberculosis registers were included in the final analyses. The population and geo-location data were obtained from the Central Statistical Agency of Ethiopia. Altitude data were extracted from ASTER Global Digital Elevation Model Version 2. Aggregated datasets from sample of 169(40%), 254(60%) and 338(80%) kebeles were used to estimate the spatial risk of TB distribution in the Gurage Zone by using a geostatistical kriging approach. The best set of input parameters were decided based on the lowest prediction error criteria of the cross-validation technique. ArcGIS 10.2 was used for the spatial data analyses. The best semivariogram models were the Pentaspherical, Rational Quadratic, and K-Bessel for the 40, 60 and 80% spatial datasets, respectively. The predictive accuracies of the models have improved with the true anisotropy, altitude and latitude covariates, the change in detrending pattern from local to global, and the increase in size of spatial dataset. The risk of tuberculosis was estimated to be higher at western, northwest, southwest and southeast parts of the study area, and crossed between high and low at west-central parts. This study has underlined that the geostatistical kriging approach can be applied to estimate the spatial risk of tuberculosis distribution in data limited settings. The estimation results may help local public health authorities measure burden of the disease at all locations, identify geographical areas that require more attention, and evaluate the impacts of intervention programs.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 46 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 46 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 7 15%
Researcher 6 13%
Student > Master 6 13%
Lecturer 4 9%
Student > Bachelor 2 4%
Other 3 7%
Unknown 18 39%
Readers by discipline Count As %
Medicine and Dentistry 10 22%
Nursing and Health Professions 6 13%
Computer Science 4 9%
Pharmacology, Toxicology and Pharmaceutical Science 3 7%
Business, Management and Accounting 1 2%
Other 4 9%
Unknown 18 39%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 8. 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 27 June 2018.
All research outputs
#4,137,050
of 23,092,602 outputs
Outputs from BMC Public Health
#4,604
of 15,054 outputs
Outputs of similar age
#80,293
of 328,981 outputs
Outputs of similar age from BMC Public Health
#158
of 324 outputs
Altmetric has tracked 23,092,602 research outputs across all sources so far. Compared to these this one has done well and is in the 81st percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 15,054 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 14.0. This one has gotten more attention than average, scoring higher than 69% 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 328,981 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 75% of its contemporaries.
We're also able to compare this research output to 324 others from the same source and published within six weeks on either side of this one. This one is in the 48th percentile – i.e., 48% of its contemporaries scored the same or lower than it.