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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Assessing the social and environmental determinants of pertussis epidemics in Queensland, Australia: a Bayesian spatio-temporal analysis
|
|---|---|
| Published in |
Epidemiology & Infection, January 2017
|
| DOI | 10.1017/s0950268816003289 |
| Pubmed ID | |
| Authors |
X. HUANG, S. LAMBERT, C. LAU, R. J. SOARES MAGALHAES, J. MARQUESS, M. RAJMOKAN, G. MILINOVICH, W. HU |
| Abstract |
Pertussis epidemics have displayed substantial spatial heterogeneity in countries with high socioeconomic conditions and high vaccine coverage. This study aims to investigate the relationship between pertussis risk and socio-environmental factors on the spatio-temporal variation underlying pertussis infection. We obtained daily case numbers of pertussis notifications from Queensland Health, Australia by postal area, for the period January 2006 to December 2012. A Bayesian spatio-temporal model was used to quantify the relationship between monthly pertussis incidence and socio-environmental factors. The socio-environmental factors included monthly mean minimum temperature (MIT), monthly mean vapour pressure (VAP), Queensland school calendar pattern (SCP), and socioeconomic index for area (SEIFA). An increase in pertussis incidence was observed from 2006 to 2010 and a slight decrease from 2011 to 2012. Spatial analyses showed pertussis incidence across Queensland postal area to be low and more spatially homogeneous during 2006-2008; incidence was higher and more spatially heterogeneous after 2009. The results also showed that the average decrease in monthly pertussis incidence was 3·1% [95% credible interval (CrI) 1·3-4·8] for each 1 °C increase in monthly MIT, while average increase in monthly pertussis incidences were 6·2% (95% CrI 0·4-12·4) and 2% (95% CrI 1-3) for SCP periods and for each 10-unit increase in SEIFA, respectively. This study demonstrated that pertussis transmission is significantly associated with MIT, SEIFA, and SCP. Mapping derived from this work highlights the potential for future investigation and areas for focusing future control strategies. |
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 % |
|---|---|---|
| Australia | 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 40 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 1 | 3% |
| Unknown | 39 | 98% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 6 | 15% |
| Researcher | 6 | 15% |
| Student > Master | 5 | 13% |
| Student > Bachelor | 3 | 8% |
| Professor > Associate Professor | 3 | 8% |
| Other | 6 | 15% |
| Unknown | 11 | 28% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 16 | 40% |
| Nursing and Health Professions | 4 | 10% |
| Agricultural and Biological Sciences | 2 | 5% |
| Immunology and Microbiology | 2 | 5% |
| Environmental Science | 1 | 3% |
| Other | 2 | 5% |
| Unknown | 13 | 33% |
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 17 February 2017.
All research outputs
#22,793,536
of 25,411,814 outputs
Outputs from Epidemiology & Infection
#4,400
of 4,683 outputs
Outputs of similar age
#363,376
of 422,337 outputs
Outputs of similar age from Epidemiology & Infection
#43
of 49 outputs
Altmetric has tracked 25,411,814 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 4,683 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.4. This one is in the 1st percentile – i.e., 1% 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 422,337 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 49 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.