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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Mobile population dynamics and malaria vulnerability: a modelling study in the China-Myanmar border region of Yunnan Province, China
|
|---|---|
| Published in |
Infectious Diseases of Poverty, April 2018
|
| DOI | 10.1186/s40249-018-0423-6 |
| Pubmed ID | |
| Authors |
Tian-Mu Chen, Shao-Sen Zhang, Jun Feng, Zhi-Gui Xia, Chun-Hai Luo, Xu-Can Zeng, Xiang-Rui Guo, Zu-Rui Lin, Hong-Ning Zhou, Shui-Sen Zhou |
| Abstract |
The China-Myanmar border region presents a great challenge in malaria elimination in China, and it is essential to understand the relationship between malaria vulnerability and population mobility in this region. A community-based, cross-sectional survey was performed in five villages of Yingjiang county during September 2016. Finger-prick blood samples were obtained to identify asymptomatic infections, and imported cases were identified in each village (between January 2013 and September 2016). A stochastic simulation model (SSM) was used to test the relationship between population mobility and malaria vulnerability, according to the mechanisms of malaria importation. Thirty-two imported cases were identified in the five villages, with a 4-year average of 1 case/year (range: 0-5 cases/year). No parasites were detected in the 353 blood samples from 2016. The median density of malaria vulnerability was 0.012 (range: 0.000-0.033). The average proportion of mobile members of the study population was 32.56% (range: 28.38-71.95%). Most mobile individuals lived indoors at night with mosquito protection. The SSM model fit the investigated data (χ2 = 0.487, P = 0.485). The average probability of infection in the members of the population that moved to Myanmar was 0.011 (range: 0.0048-0.1585). The values for simulated vulnerability increased with greater population mobility in each village. A high proportion of population mobility was associated with greater malaria vulnerability in the China-Myanmar border region. Mobile population-specific measures should be used to decrease the risk of malaria re-establishment in China. |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| India | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 64 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 64 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 15 | 23% |
| Student > Ph. D. Student | 8 | 13% |
| Student > Bachelor | 6 | 9% |
| Student > Master | 5 | 8% |
| Student > Postgraduate | 3 | 5% |
| Other | 11 | 17% |
| Unknown | 16 | 25% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 17 | 27% |
| Social Sciences | 6 | 9% |
| Nursing and Health Professions | 4 | 6% |
| Biochemistry, Genetics and Molecular Biology | 3 | 5% |
| Mathematics | 3 | 5% |
| Other | 13 | 20% |
| Unknown | 18 | 28% |
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 30 April 2018.
All research outputs
#17,730,887
of 25,988,468 outputs
Outputs from Infectious Diseases of Poverty
#135
of 184 outputs
Outputs of similar age
#222,766
of 342,948 outputs
Outputs of similar age from Infectious Diseases of Poverty
#2
of 3 outputs
Altmetric has tracked 25,988,468 research outputs across all sources so far. This one is in the 21st percentile – i.e., 21% of other outputs scored the same or lower than it.
So far Altmetric has tracked 184 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 7.8. This one is in the 27th percentile – i.e., 27% 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 342,948 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 26th percentile – i.e., 26% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 3 others from the same source and published within six weeks on either side of this one.