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Mapping Zika virus disease incidence in Valle del Cauca

Overview of attention for article published in Infection, October 2016
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (51st percentile)
  • Good Attention Score compared to outputs of the same age and source (76th percentile)

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4 X users
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2 Facebook pages

Citations

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21 Dimensions

Readers on

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72 Mendeley
Title
Mapping Zika virus disease incidence in Valle del Cauca
Published in
Infection, October 2016
DOI 10.1007/s15010-016-0948-1
Pubmed ID
Authors

Alfonso J. Rodriguez-Morales, Maria Leonor Galindo-Marquez, Carlos Julian García-Loaiza, Juan Alejandro Sabogal-Roman, Santiago Marin-Loaiza, Andrés F. Ayala, Guillermo J. Lagos-Grisales, Carlos O. Lozada-Riascos, Esteban Parra-Valencia, Jorge H. Rojas-Palacios, Eduardo López, Pío López, Martin P. Grobusch

Abstract

Geographical information systems (GIS) use for development of epidemiological maps in tropical diseases is increasingly frequently utilized. Here, we apply this technique to map the current Zika virus (ZIKV) outbreak in Colombia. Surveillance cases data of the ongoing epidemic of ZIKV in Valle del Cauca department and its capital, Cali (2015-2016), were used to estimate cumulated incidence rates (cases/100,000 population) to develop the first maps in the department and it municipalities. The GIS software used was Kosmo Desktop 3.0RC1(®). Three thematic incidence rate maps were developed. Up to April 2, 2016, 9,825 cases of ZIKV were reported (15.15 % of the country cases). The burden of ZIKV infection has been concentrated in the North of the department. Valle del Cauca borders with other departments with incidence of ZIKV infection, such as Quindío (173 cases) and Risaralda (687 cases). Eleven municipalities of Valle del Cauca had cases in the range between 250 and 499 cases/100,000, all in the North and East of the department. Cali, the capital concentrates more than a third of the reported cases of ZIKV in Valle del Cauca. Use of GIS-based epidemiological maps allows to guide decision-making for prevention and control of diseases that constitute significant public health problems in the region and the country, such as exemplified by the emergence of ZIKV infection, particularly in departments such as Valle del Cauca with a high disease incidence.

X Demographics

X Demographics

The data shown below were collected from the profiles of 4 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 72 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Netherlands 1 1%
Unknown 71 99%

Demographic breakdown

Readers by professional status Count As %
Researcher 15 21%
Student > Master 12 17%
Student > Bachelor 9 13%
Student > Doctoral Student 5 7%
Student > Ph. D. Student 5 7%
Other 14 19%
Unknown 12 17%
Readers by discipline Count As %
Medicine and Dentistry 25 35%
Social Sciences 7 10%
Agricultural and Biological Sciences 5 7%
Nursing and Health Professions 4 6%
Arts and Humanities 3 4%
Other 12 17%
Unknown 16 22%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 19 October 2016.
All research outputs
#12,674,864
of 22,893,031 outputs
Outputs from Infection
#816
of 1,403 outputs
Outputs of similar age
#154,561
of 319,861 outputs
Outputs of similar age from Infection
#3
of 13 outputs
Altmetric has tracked 22,893,031 research outputs across all sources so far. This one is in the 44th percentile – i.e., 44% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,403 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.5. This one is in the 41st percentile – i.e., 41% 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 319,861 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 51% of its contemporaries.
We're also able to compare this research output to 13 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 76% of its contemporaries.