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Consensus and conflict among ecological forecasts of Zika virus outbreaks in the United States

Overview of attention for article published in Scientific Reports, March 2018
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (87th percentile)
  • High Attention Score compared to outputs of the same age and source (86th percentile)

Mentioned by

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32 X users
facebook
1 Facebook page

Citations

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51 Dimensions

Readers on

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90 Mendeley
Title
Consensus and conflict among ecological forecasts of Zika virus outbreaks in the United States
Published in
Scientific Reports, March 2018
DOI 10.1038/s41598-018-22989-0
Pubmed ID
Authors

Colin J. Carlson, Eric Dougherty, Mike Boots, Wayne Getz, Sadie J. Ryan

Abstract

Ecologists are increasingly involved in the pandemic prediction process. In the course of the Zika outbreak in the Americas, several ecological models were developed to forecast the potential global distribution of the disease. Conflicting results produced by alternative methods are unresolved, hindering the development of appropriate public health forecasts. We compare ecological niche models and experimentally-driven mechanistic forecasts for Zika transmission in the continental United States. We use generic and uninformed stochastic county-level simulations to demonstrate the downstream epidemiological consequences of conflict among ecological models, and show how assumptions and parameterization in the ecological and epidemiological models propagate uncertainty and produce downstream model conflict. We conclude by proposing a basic consensus method that could resolve conflicting models of potential outbreak geography and seasonality. Our results illustrate the usually-undocumented margin of uncertainty that could emerge from using any one of these predictions without reservation or qualification. In the short term, ecologists face the task of developing better post hoc consensus that accurately forecasts spatial patterns of Zika virus outbreaks. Ultimately, methods are needed that bridge the gap between ecological and epidemiological approaches to predicting transmission and realistically capture both outbreak size and geography.

X Demographics

X Demographics

The data shown below were collected from the profiles of 32 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 90 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 90 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 22 24%
Researcher 15 17%
Student > Master 10 11%
Professor 7 8%
Student > Doctoral Student 5 6%
Other 10 11%
Unknown 21 23%
Readers by discipline Count As %
Agricultural and Biological Sciences 19 21%
Environmental Science 6 7%
Medicine and Dentistry 6 7%
Social Sciences 5 6%
Engineering 4 4%
Other 19 21%
Unknown 31 34%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 19. 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 25 June 2020.
All research outputs
#1,943,127
of 25,358,192 outputs
Outputs from Scientific Reports
#17,848
of 139,577 outputs
Outputs of similar age
#40,922
of 338,737 outputs
Outputs of similar age from Scientific Reports
#494
of 3,541 outputs
Altmetric has tracked 25,358,192 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 92nd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 139,577 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 18.7. This one has done well, scoring higher than 87% 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 338,737 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 87% of its contemporaries.
We're also able to compare this research output to 3,541 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 86% of its contemporaries.