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Attention Score in Context
| Title |
Describing interaction effect between lagged rainfalls on malaria: an epidemiological study in south–west China
|
|---|---|
| Published in |
Malaria Journal, January 2017
|
| DOI | 10.1186/s12936-017-1706-2 |
| Pubmed ID | |
| Authors |
Yunyun Wu, Zhijiao Qiao, Nan Wang, Hongjie Yu, Zijian Feng, Xiaosong Li, Xing Zhao |
| Abstract |
When discussing the relationship between meteorological factors and malaria, previous studies mainly focus on the interaction between different climatic factors, while the possible interaction within one particular climatic predictor at different lag periods has been largely neglected. In this study, this issue was investigated by exploring the interaction of lagged rainfalls and its impact on malaria epidemics, which is a typical example of those meteorological variables. The weekly data of malaria cases and three climatic variables of 30 counties in southwest China from 2004 to 2009 were analysed with the varying coefficient-distributed lag non-linear model. The correlation patterns of the 6th, 9th and 12th week lags would vary over different rainfall levels at the 4th-week lag. The non-linear patterns for rainfall at different rainfall levels are distinct from each other. In the low rainfall level at the 4th week lag, the increasing rainfall may promote the transmission of malaria. However, for the high rainfall level at the 4th week lag, evidence shows that the excessive rainfall decreases the risk of malaria. This study reports for the first time that the interaction effect between lagged rainfalls on malaria exists, and highlights the importance of integrating the interaction between lagged predictors in relevant studies, which could help to better understand and predict malaria transmission. |
X Demographics
The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 2 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Science communicators (journalists, bloggers, editors) | 2 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 60 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 1 | 2% |
| Australia | 1 | 2% |
| Unknown | 58 | 97% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 16 | 27% |
| Researcher | 11 | 18% |
| Student > Master | 6 | 10% |
| Student > Bachelor | 5 | 8% |
| Student > Doctoral Student | 4 | 7% |
| Other | 8 | 13% |
| Unknown | 10 | 17% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 10 | 17% |
| Agricultural and Biological Sciences | 9 | 15% |
| Nursing and Health Professions | 6 | 10% |
| Social Sciences | 4 | 7% |
| Environmental Science | 3 | 5% |
| Other | 13 | 22% |
| Unknown | 15 | 25% |
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 31 January 2017.
All research outputs
#15,440,760
of 22,950,943 outputs
Outputs from Malaria Journal
#4,493
of 5,585 outputs
Outputs of similar age
#256,701
of 420,210 outputs
Outputs of similar age from Malaria Journal
#96
of 117 outputs
Altmetric has tracked 22,950,943 research outputs across all sources so far. This one is in the 22nd percentile – i.e., 22% of other outputs scored the same or lower than it.
So far Altmetric has tracked 5,585 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.8. This one is in the 12th percentile – i.e., 12% 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 420,210 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 30th percentile – i.e., 30% of its contemporaries scored the same or lower than it.
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 is in the 4th percentile – i.e., 4% of its contemporaries scored the same or lower than it.