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Routine mortality surveillance to identify the cause of death pattern for out-of-hospital adult (aged 12+ years) deaths in Bangladesh: introduction of automated verbal autopsy

Overview of attention for article published in BMC Public Health, March 2021
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (71st percentile)
  • Above-average Attention Score compared to outputs of the same age and source (57th percentile)

Mentioned by

policy
1 policy source
wikipedia
2 Wikipedia pages

Readers on

mendeley
35 Mendeley
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Title
Routine mortality surveillance to identify the cause of death pattern for out-of-hospital adult (aged 12+ years) deaths in Bangladesh: introduction of automated verbal autopsy
Published in
BMC Public Health, March 2021
DOI 10.1186/s12889-021-10468-7
Pubmed ID
Authors

Md. Toufiq Hassan Shawon, Shah Ali Akbar Ashrafi, Abul Kalam Azad, Sonja M. Firth, Hafizur Chowdhury, Robert G. Mswia, Tim Adair, Ian Riley, Carla Abouzahr, Alan D. Lopez

Abstract

In Bangladesh, a poorly functioning national system of registering deaths and determining their causes leaves the country without important information on which to inform health programming, particularly for the 85% of deaths that occur in the community. In 2017, an improved death registration system and automated verbal autopsy (VA) were introduced to 13 upazilas to assess the utility of VA as a routine source of policy-relevant information and to identify leading causes of deaths (COD) in rural Bangladesh. Data from 22,535 VAs, collected in 12 upazilas between October 2017 and August 2019, were assigned a COD using the SmartVA Analyze 2.0 computer algorithm. The plausibility of the VA results was assessed using a series of demographic and epidemiological checks in the Verbal Autopsy Interpretation, Performance and Evaluation Resource (VIPER) software tool. Completeness of community death reporting was 65%. The vast majority (85%) of adult deaths were due to non-communicable diseases, with ischemic heart disease, stroke and chronic respiratory disease comprising about 60% alone. Leading COD were broadly consistent with Global Burden of Disease study estimates. Routine VA collection using automated methods is feasible, can produce plausible results and provides critical information on community COD in Bangladesh. Routine VA and VIPER have potential application to countries with weak death registration systems.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 35 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 35 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 3 9%
Student > Postgraduate 3 9%
Student > Bachelor 2 6%
Other 2 6%
Unspecified 2 6%
Other 4 11%
Unknown 19 54%
Readers by discipline Count As %
Nursing and Health Professions 5 14%
Social Sciences 3 9%
Unspecified 2 6%
Medicine and Dentistry 2 6%
Computer Science 1 3%
Other 2 6%
Unknown 20 57%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 6. 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 September 2023.
All research outputs
#5,402,332
of 25,286,324 outputs
Outputs from BMC Public Health
#6,182
of 16,927 outputs
Outputs of similar age
#123,094
of 429,692 outputs
Outputs of similar age from BMC Public Health
#179
of 417 outputs
Altmetric has tracked 25,286,324 research outputs across all sources so far. Compared to these this one has done well and is in the 75th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 16,927 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 14.5. This one has gotten more attention than average, scoring higher than 62% 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 429,692 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 71% of its contemporaries.
We're also able to compare this research output to 417 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.