↓ Skip to main content

Transmission characteristics of MERS and SARS in the healthcare setting: a comparative study

Overview of attention for article published in BMC Medicine, September 2015
Altmetric Badge

About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • One of the highest-scoring outputs from this source (#4 of 2,531)
  • High Attention Score compared to outputs of the same age (99th percentile)

Mentioned by

news
139 news outlets
blogs
3 blogs
twitter
21 tweeters

Citations

dimensions_citation
214 Dimensions

Readers on

mendeley
357 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
Transmission characteristics of MERS and SARS in the healthcare setting: a comparative study
Published in
BMC Medicine, September 2015
DOI 10.1186/s12916-015-0450-0
Pubmed ID
Authors

Gerardo Chowell, Fatima Abdirizak, Sunmi Lee, Jonggul Lee, Eunok Jung, Hiroshi Nishiura, Cécile Viboud

Abstract

The Middle East respiratory syndrome (MERS) coronavirus has caused recurrent outbreaks in the Arabian Peninsula since 2012. Although MERS has low overall human-to-human transmission potential, there is occasional amplification in the healthcare setting, a pattern reminiscent of the dynamics of the severe acute respiratory syndrome (SARS) outbreaks in 2003. Here we provide a head-to-head comparison of exposure patterns and transmission dynamics of large hospital clusters of MERS and SARS, including the most recent South Korean outbreak of MERS in 2015. To assess the unexpected nature of the recent South Korean nosocomial outbreak of MERS and estimate the probability of future large hospital clusters, we compared exposure and transmission patterns for previously reported hospital clusters of MERS and SARS, based on individual-level data and transmission tree information. We carried out simulations of nosocomial outbreaks of MERS and SARS using branching process models rooted in transmission tree data, and inferred the probability and characteristics of large outbreaks. A significant fraction of MERS cases were linked to the healthcare setting, ranging from 43.5 % for the nosocomial outbreak in Jeddah, Saudi Arabia, in 2014 to 100 % for both the outbreak in Al-Hasa, Saudi Arabia, in 2013 and the outbreak in South Korea in 2015. Both MERS and SARS nosocomial outbreaks are characterized by early nosocomial super-spreading events, with the reproduction number dropping below 1 within three to five disease generations. There was a systematic difference in the exposure patterns of MERS and SARS: a majority of MERS cases occurred among patients who sought care in the same facilities as the index case, whereas there was a greater concentration of SARS cases among healthcare workers throughout the outbreak. Exposure patterns differed slightly by disease generation, however, especially for SARS. Moreover, the distributions of secondary cases per single primary case varied highly across individual hospital outbreaks (Kruskal-Wallis test; P < 0.0001), with significantly higher transmission heterogeneity in the distribution of secondary cases for MERS than SARS. Simulations indicate a 2-fold higher probability of occurrence of large outbreaks (>100 cases) for SARS than MERS (2 % versus 1 %); however, owing to higher transmission heterogeneity, the largest outbreaks of MERS are characterized by sharper incidence peaks. The probability of occurrence of MERS outbreaks larger than the South Korean cluster (n = 186) is of the order of 1 %. Our study suggests that the South Korean outbreak followed a similar progression to previously described hospital clusters involving coronaviruses, with early super-spreading events generating a disproportionately large number of secondary infections, and the transmission potential diminishing greatly in subsequent generations. Differences in relative exposure patterns and transmission heterogeneity of MERS and SARS could point to changes in hospital practices since 2003 or differences in transmission mechanisms of these coronaviruses.

Twitter Demographics

The data shown below were collected from the profiles of 21 tweeters 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 357 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 357 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 56 16%
Researcher 55 15%
Student > Bachelor 46 13%
Student > Ph. D. Student 39 11%
Student > Postgraduate 21 6%
Other 68 19%
Unknown 72 20%
Readers by discipline Count As %
Medicine and Dentistry 111 31%
Agricultural and Biological Sciences 22 6%
Biochemistry, Genetics and Molecular Biology 20 6%
Engineering 17 5%
Nursing and Health Professions 17 5%
Other 81 23%
Unknown 89 25%

Attention Score in Context

This research output has an Altmetric Attention Score of 1125. 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 08 August 2020.
All research outputs
#5,424
of 16,164,211 outputs
Outputs from BMC Medicine
#4
of 2,531 outputs
Outputs of similar age
#66
of 241,798 outputs
Outputs of similar age from BMC Medicine
#1
of 1 outputs
Altmetric has tracked 16,164,211 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 99th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 2,531 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 37.6. This one has done particularly well, scoring higher than 99% 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 241,798 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 99% of its contemporaries.
We're also able to compare this research output to 1 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them