Are hospital MERS outbreaks just like SARS?
Comparing hospital clusters, MERS and SARS both ignite via early super-spreaders then drop below R=1 within 3–5 generations; a >100-case outbreak is about twice as likely for SARS (2% vs 1%), while MERS transmission is more heterogeneous.
Source
Transmission characteristics of MERS and SARS in the healthcare setting: a comparative study
Study at a glance
- Design
- Computational / modelling — Comparative analysis of MERS vs SARS hospital outbreak trees plus 5,000 branching-process simulations per virus
- N
- N=8607 · 973 MERS and 7,634 SARS cases for HCW fractions; trees for Korea MERS n=186, Al-Hasa n=25, Singapore SARS n=188, Toronto n=90
- Population
- Laboratory-confirmed MERS and SARS cases in published hospital clusters (Saudi Arabia, South Korea, Singapore, Toronto, and other SARS sites)
- Outcome
- Exposure mix, reproduction number by generation, transmission heterogeneity, and probability of large nosocomial outbreaks
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Inspect source passages
Are hospital MERS outbreaks just like SARS?
These passages occur verbatim in the stored paper text. They support the points listed below; they do not verify every statement in the explanation.
Healthcare-linked MERS 43.5% to 100%.
ranging from 43.5 % for the nosocomial outbreak in Jeddah, Saudi Arabia, in 2014 to 100 %
>100-case probability 2% SARS vs 1% MERS.
Simulations indicate a 2-fold higher probability of occurrence of large outbreaks (>100 cases) for SARS than MERS (2 % versus 1 %)
What they did
Compiled exposure data and transmission trees for large MERS (South Korea 186; Al-Hasa 25; Jeddah) and SARS (Singapore 188; Toronto 90) hospital clusters, compared secondary-case distributions (negative binomial R and k), and simulated 5,000 outbreaks of each virus.
What they found
Healthcare-linked MERS ranged from 43.5% (Jeddah 2014) to 100% (Al-Hasa and Korea). Korea’s index patient infected 30 others; two second-generation patients infected 80 and 23. HCWs were 13.4–13.5% of MERS vs 19–57% of SARS. Probability of >100 cases: ~2% SARS vs ~1% MERS; >186 MERS cases ~1%.
The limits
What it doesn't show
Few fully resolved trees and reporting bias toward large clusters mean R and k are imprecise; simulations do not prove which infection-control rule would have stopped Korea 2015.
Key terms
- Super-spreading
- One case generating many secondary infections; Korea’s index MERS patient infected 30 people.
- Reproduction number R
- Mean secondary cases per case; in these hospitals it fell below 1 within three to five generations.
- Dispersion parameter k
- Negative-binomial heterogeneity; smaller k means more super-spreading. MERS looked more heterogeneous than SARS.
- Nosocomial
- Acquired in a healthcare setting; a large share of MERS cases were hospital-linked.
- Branching process
- Simulation that grows an outbreak from a distribution of secondary cases; 5,000 runs per virus here.
- MERS
- Middle East respiratory syndrome coronavirus; often subcritical in the community but amplifying in hospitals.
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Quiz yourself
Korea 2015 MERS cluster size:
Common questions
How large was the Korea cluster?
186 MERS infections linked to healthcare facilities.
Index patient’s secondary cases?
About 30.
Chance of >100 hospital cases?
About 2% for SARS vs 1% for MERS.
HCW share of MERS?
13.4% in Saudi Arabia vs 13.5% in Korea.
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