The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.
Middle East Respiratory Syndrome Coronavirus Outbreak in the Republic of Korea, 2015
Open accessAbstract
OBJECTIVES: The outbreak of Middle East respiratory syndrome coronavirus (MERS-CoV) infection in the Republic of Korea started from the index case who developed fever after returning from the Middle East. He infected 26 cases in Hospital C, and consecutive nosocomial transmission proceeded throughout the nation. We provide an epidemiologic description of the outbreak, as of July 2015. METHODS: Epidemiological research was performed by direct interview of the confirmed patients and reviewing medical records. We also analyzed the incubation period, serial interval, the characteristics of superspreaders, and factors associated with mortality. Full genome sequence was obtained from sputum specimens of the index patient. RESULTS: A total of 186 confirmed patients with MERS-CoV infection across 16 hospitals were identified in the Republic of Korea. Some 44.1% of the cases were patients exposed in hospitals, 32.8% were caregivers, and 13.4% were healthcare personnel. The most common presenting symptom was fever and chills. The estimated incubation period was 6.83 days and the serial interval was 12.5 days. A total of 83.2% of the transmission events were epidemiologically linked to five superspreaders, all of whom had pneumonia at presentation and contacted hundreds of people. Older age [odds ratio (OR) = 4.86, 95% confidence interval (CI) 1.90-12.45] and underlying respiratory disease (OR = 4.90, 95% CI 1.64-14.65) were significantly associated with mortality. Phylogenetic analysis showed that the MERS-CoV of the index case clustered closest with a recent virus from Riyadh, Saudi Arabia. CONCLUSION: A single imported MERS-CoV infection case imposed a huge threat to public health and safety. This highlights the importance of robust preparedness and optimal infection prevention control. The lessons learned from the current outbreak will contribute to more up-to-date guidelines and global health security.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
MAFFT Multiple Sequence Alignment Software Version 7: Improvements in Performance and Usability
Katoh, K., & Standley, D. M. (2013) · Molecular Biology and Evolution · doi:10.1093/molbev/mst010 · Cited by 46,209
Superspreading and the effect of individual variation on disease emergence
Lloyd-Smith, J. O., Schreiber, S. J., Kopp, P. E., & Getz, W. M. (2005) · Nature · doi:10.1038/nature04153 · Cited by 2,514
Super-spreaders in infectious diseases
Stein, R. A. (2011) · International Journal of Infectious Diseases · doi:10.1016/j.ijid.2010.06.020 · Cited by 388
Cited by
SARS and MERS: recent insights into emerging coronaviruses
de Wit, E., van Doremalen, N., Falzarano, D., & Munster, V. J. (2016) · Nature Reviews Microbiology · doi:10.1038/nrmicro.2016.81 · Cited by 3,510
Zimmermann, P., & Curtis, N. (2020) · Pediatric Infectious Disease Journal · doi:10.1097/inf.0000000000002660 · Cited by 1,077
Yuan, Y., Cao, D., Zhang, Y., Ma, J., Qi, J., Wang, Q., Lu, G., Wu, Y., Yan, J., Shi, Y., et al. (2017) · Nature Communications · doi:10.1038/ncomms15092 · Cited by 760
Hui, D. S., Azhar, E. I., Kim, Y.-J., Memish, Z. A., Oh, M.-D., & Zumla, A. (2018) · The Lancet Infectious Diseases · doi:10.1016/s1473-3099(18)30127-0 · Cited by 448
MERS transmission and risk factors: a systematic review
Park, J.-E., Jung, S., Kim, A., & Park, J.-E. (2018) · BMC Public Health · doi:10.1186/s12889-018-5484-8 · Cited by 285
Metadata
- Venue
- Osong Public Health and Research Perspectives
- Published
- 2015-08
- Volume
- 6
- Issue
- 4
- Pages
- 269-278
- ISSN
- 2210-9099 (ISSN-L)
- OpenAlex
- W2895727403
- Cited by
- 259
- References
- 3
- FWCI
- 27.95
- Type
- journal article
- Language
- en
- Open access
- diamond
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Middle East Respiratory Syndrome Coronavirus Outbreak in the Republic of Korea, 2015. https://app.cochat.ai/papers/10.1016/j.phrp.2015.08.006
- The paper
- Middle East Respiratory Syndrome Coronavirus Outbreak in the Republic of Korea, 2015. (2015). Osong Public Health and Research Perspectives. https://doi.org/10.1016/j.phrp.2015.08.006
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.