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Could the Recent Zika Epidemic Have Been Predicted?

Overview of attention for article published in Frontiers in Microbiology, July 2017
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  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (96th percentile)
  • High Attention Score compared to outputs of the same age and source (97th percentile)

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6 news outlets
blogs
1 blog
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25 X users
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1 Facebook page

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160 Mendeley
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Title
Could the Recent Zika Epidemic Have Been Predicted?
Published in
Frontiers in Microbiology, July 2017
DOI 10.3389/fmicb.2017.01291
Pubmed ID
Authors

Ángel G. Muñoz, Madeleine C. Thomson, Anna M. Stewart-Ibarra, Gabriel A. Vecchi, Xandre Chourio, Patricia Nájera, Zelda Moran, Xiaosong Yang

Abstract

Given knowledge at the time, the recent 2015-2016 zika virus (ZIKV) epidemic probably could not have been predicted. Without the prior knowledge of ZIKV being already present in South America, and given the lack of understanding of key epidemiologic processes and long-term records of ZIKV cases in the continent, the best related prediction could be carried out for the potential risk of a generic Aedes-borne disease epidemic. Here we use a recently published two-vector basic reproduction number model to assess the predictability of the conditions conducive to epidemics of diseases like zika, chikungunya, or dengue, transmitted by the independent or concurrent presence of Aedes aegypti and Aedes albopictus. We compare the potential risk of transmission forcing the model with the observed climate and with state-of-the-art operational forecasts from the North American Multi Model Ensemble (NMME), finding that the predictive skill of this new seasonal forecast system is highest for multiple countries in Latin America and the Caribbean during the December-February and March-May seasons, and slightly lower-but still of potential use to decision-makers-for the rest of the year. In particular, we find that above-normal suitable conditions for the occurrence of the zika epidemic at the beginning of 2015 could have been successfully predicted at least 1 month in advance for several zika hotspots, and in particular for Northeast Brazil: the heart of the epidemic. Nonetheless, the initiation and spread of an epidemic depends on the effect of multiple factors beyond climate conditions, and thus this type of approach must be considered as a guide and not as a formal predictive tool of vector-borne epidemics.

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X Demographics

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 160 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 160 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 28 18%
Researcher 23 14%
Student > Master 22 14%
Student > Bachelor 16 10%
Student > Doctoral Student 9 6%
Other 30 19%
Unknown 32 20%
Readers by discipline Count As %
Medicine and Dentistry 17 11%
Agricultural and Biological Sciences 15 9%
Environmental Science 15 9%
Social Sciences 10 6%
Nursing and Health Professions 9 6%
Other 53 33%
Unknown 41 26%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 69. 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 06 August 2020.
All research outputs
#547,265
of 23,460,553 outputs
Outputs from Frontiers in Microbiology
#273
of 25,869 outputs
Outputs of similar age
#12,520
of 313,600 outputs
Outputs of similar age from Frontiers in Microbiology
#14
of 545 outputs
Altmetric has tracked 23,460,553 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 97th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 25,869 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.4. This one has done particularly well, scoring higher than 98% 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 313,600 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 96% of its contemporaries.
We're also able to compare this research output to 545 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 97% of its contemporaries.