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Modelling the Effects of Seasonality and Socioeconomic Impact on the Transmission of Rift Valley Fever Virus

Overview of attention for article published in PLoS Neglected Tropical Diseases, January 2015
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Title
Modelling the Effects of Seasonality and Socioeconomic Impact on the Transmission of Rift Valley Fever Virus
Published in
PLoS Neglected Tropical Diseases, January 2015
DOI 10.1371/journal.pntd.0003388
Pubmed ID
Authors

Yanyu Xiao, John C. Beier, Robert Stephen Cantrell, Chris Cosner, Donald L. DeAngelis, Shigui Ruan

Abstract

Rift Valley fever (RVF) is an important mosquito-borne viral zoonosis in Africa and the Middle East that causes human deaths and significant economic losses due to huge incidences of death and abortion among infected livestock. Outbreaks of RVF are sporadic and associated with both seasonal and socioeconomic effects. Here we propose an almost periodic three-patch model to investigate the transmission dynamics of RVF virus (RVFV) among ruminants with spatial movements. Our findings indicate that, in Northeastern Africa, human activities, including those associated with the Eid al Adha feast, along with a combination of climatic factors such as rainfall level and hydrological variations, contribute to the transmission and dispersal of the disease pathogen. Moreover, sporadic outbreaks may occur when the two events occur together: 1) abundant livestock are recruited into areas at risk from RVF due to the demand for the religious festival and 2) abundant numbers of mosquitoes emerge. These two factors have been shown to have impacts on the severity of RVF outbreaks. Our numerical results present the transmission dynamics of the disease pathogen over both short and long periods of time, particularly during the festival time. Further, we investigate the impact on patterns of disease outbreaks in each patch brought by festival- and seasonal-driven factors, such as the number of livestock imported daily, the animal transportation speed from patch to patch, and the death rate induced by ceremonial sacrifices. In addition, our simulations show that when the time for festival preparation starts earlier than usual, the risk of massive disease outbreaks rises, particularly in patch 3 (the place where the religious ceremony will be held).

Twitter Demographics

The data shown below were collected from the profile of 1 tweeter who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 61 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 2%
Unknown 60 98%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 11 18%
Researcher 9 15%
Student > Master 9 15%
Professor > Associate Professor 4 7%
Student > Bachelor 4 7%
Other 17 28%
Unknown 7 11%
Readers by discipline Count As %
Agricultural and Biological Sciences 13 21%
Medicine and Dentistry 12 20%
Veterinary Science and Veterinary Medicine 7 11%
Biochemistry, Genetics and Molecular Biology 2 3%
Immunology and Microbiology 2 3%
Other 12 20%
Unknown 13 21%

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 09 January 2015.
All research outputs
#7,556,427
of 12,091,691 outputs
Outputs from PLoS Neglected Tropical Diseases
#4,228
of 5,486 outputs
Outputs of similar age
#142,952
of 275,543 outputs
Outputs of similar age from PLoS Neglected Tropical Diseases
#110
of 168 outputs
Altmetric has tracked 12,091,691 research outputs across all sources so far. This one is in the 23rd percentile – i.e., 23% of other outputs scored the same or lower than it.
So far Altmetric has tracked 5,486 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 12.1. This one is in the 17th percentile – i.e., 17% 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 275,543 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 37th percentile – i.e., 37% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 168 others from the same source and published within six weeks on either side of this one. This one is in the 27th percentile – i.e., 27% of its contemporaries scored the same or lower than it.