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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Improving estimates of the burden of severe acute malnutrition and predictions of caseload for programs treating severe acute malnutrition: experiences from Nigeria
|
|---|---|
| Published in |
Archives of Public Health, November 2017
|
| DOI | 10.1186/s13690-017-0234-4 |
| Pubmed ID | |
| Authors |
Assaye Bulti, André Briend, Nancy M. Dale, Arjan De Wagt, Faraja Chiwile, Stanley Chitekwe, Chris Isokpunwu, Mark Myatt |
| Abstract |
The burden of severe acute malnutrition (SAM) is estimated using unadjusted prevalence estimates. SAM is an acute condition and many children with SAM will either recover or die within a few weeks. Estimating SAM burden using unadjusted prevalence estimates results in significant underestimation. This has a negative impact on allocation of resources for the prevention and treatment of SAM. A simple method for adjusting prevalence estimates intended to improve the accuracy of burden estimates and caseload predictions has been proposed. This method employs an incidence correction factor. Application of this method using the globally recommended incidence correction factor has led to programs underestimating burden and caseload in some settings. A method for estimating a locally appropriate incidence correction factor from prevalence, population size, program caseload, and program coverage was developed and tested using data from the Nigerian national SAM treatment program. Applying the developed method resulted in errors in caseload prediction of about 10%. This is a considerable improvement upon the current method, which resulted in a 79.5% underestimate. Methods for improving the precision of estimates are proposed. It is possible to considerably improve predictions of caseload by applying a simple model to data that are readily available to program managers. This implies that more accurate estimates of burden may also be made using the same methods and data. |
X Demographics
The data shown below were collected from the profiles of 6 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Pakistan | 2 | 33% |
| Unknown | 4 | 67% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 4 | 67% |
| Scientists | 1 | 17% |
| Practitioners (doctors, other healthcare professionals) | 1 | 17% |
Mendeley readers
The data shown below were compiled from readership statistics for 47 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 47 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 8 | 17% |
| Student > Bachelor | 4 | 9% |
| Researcher | 4 | 9% |
| Student > Ph. D. Student | 3 | 6% |
| Lecturer | 2 | 4% |
| Other | 6 | 13% |
| Unknown | 20 | 43% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 9 | 19% |
| Nursing and Health Professions | 8 | 17% |
| Environmental Science | 2 | 4% |
| Agricultural and Biological Sciences | 2 | 4% |
| Economics, Econometrics and Finance | 2 | 4% |
| Other | 3 | 6% |
| Unknown | 21 | 45% |
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 03 October 2019.
All research outputs
#4,707,742
of 25,382,440 outputs
Outputs from Archives of Public Health
#312
of 1,144 outputs
Outputs of similar age
#79,539
of 342,671 outputs
Outputs of similar age from Archives of Public Health
#9
of 21 outputs
Altmetric has tracked 25,382,440 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 1,144 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 7.1. This one has gotten more attention than average, scoring higher than 72% 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 342,671 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 76% of its contemporaries.
We're also able to compare this research output to 21 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.