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Spatio-temporal spillover risk of yellow fever in Brazil

Overview of attention for article published in Parasites & Vectors, August 2018
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  • 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 (94th percentile)

Mentioned by

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1 news outlet
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14 X users

Citations

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33 Dimensions

Readers on

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115 Mendeley
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Title
Spatio-temporal spillover risk of yellow fever in Brazil
Published in
Parasites & Vectors, August 2018
DOI 10.1186/s13071-018-3063-6
Pubmed ID
Authors

RajReni B. Kaul, Michelle V. Evans, Courtney C. Murdock, John M. Drake

Abstract

Yellow fever virus is a mosquito-borne flavivirus that persists in an enzoonotic cycle in non-human primates (NHPs) in Brazil, causing disease in humans through spillover events. Yellow fever (YF) re-emerged in the early 2000s, spreading from the Amazon River basin towards the previously considered low-risk, southeastern region of the country. Previous methods mapping YF spillover risk do not incorporate the temporal dynamics and ecological context of the disease, and are therefore unable to predict seasonality in spatial risk across Brazil. We present the results of a bagged logistic regression predicting the propensity for YF spillover per municipality (administrative sub-district) in Brazil from environmental and demographic covariates aggregated by month. Ecological context was incorporated by creating National and Regional models of spillover dynamics, where the Regional model consisted of two separate models determined by the regions' NHP reservoir species richness (high vs low). Of the 5560 municipalities, 82 reported YF cases from 2001 to 2013. Model accuracy was high for the National and low reservoir richness (LRR) models (AUC = 0.80), while the high reservoir richness (HRR) model accuracy was lower (AUC = 0.63). The National model predicted consistently high spillover risk in the Amazon, while the Regional model predicted strong seasonality in spillover risk. Within the Regional model, seasonality of spillover risk in the HRR region was asynchronous to the LRR region. However, the observed seasonality of spillover risk in the LRR Regional model mirrored the national model predictions. The predicted risk of YF spillover varies with space and time. Seasonal trends differ between regions indicating, at times, spillover risk can be higher in the urban coastal regions than the Amazon River basin which is counterintuitive based on current YF risk maps. Understanding the spatio-temporal patterns of YF spillover risk could better inform allocation of public health services.

X Demographics

X Demographics

The data shown below were collected from the profiles of 14 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 115 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 115 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 16 14%
Student > Master 16 14%
Student > Bachelor 14 12%
Researcher 9 8%
Student > Doctoral Student 8 7%
Other 21 18%
Unknown 31 27%
Readers by discipline Count As %
Agricultural and Biological Sciences 30 26%
Veterinary Science and Veterinary Medicine 6 5%
Immunology and Microbiology 6 5%
Medicine and Dentistry 6 5%
Nursing and Health Professions 5 4%
Other 21 18%
Unknown 41 36%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 18. 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 20 October 2023.
All research outputs
#2,086,311
of 25,826,146 outputs
Outputs from Parasites & Vectors
#351
of 6,083 outputs
Outputs of similar age
#41,480
of 345,741 outputs
Outputs of similar age from Parasites & Vectors
#7
of 117 outputs
Altmetric has tracked 25,826,146 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 91st percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 6,083 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.2. This one has done particularly well, scoring higher than 94% 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 345,741 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 117 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 94% of its contemporaries.