Dataset Information

Microevolution of Outbreak-Associated Middle East Respiratory Syndrome Coronavirus, South Korea, 2015.

ABSTRACT: During the 2015 Middle East respiratory syndrome coronavirus outbreak in South Korea, we sequenced full viral genomes of strains isolated from 4 patients early and late during infection. Patients represented at least 4 generations of transmission. We found no evidence of changes in the evolutionary rate and no reason to suspect adaptive changes in viral proteins.

SUBMITTER: Seong MW

PROVIDER: S-EPMC4734539 | biostudies-literature | 2016 Feb

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Microevolution of Outbreak-Associated Middle East Respiratory Syndrome Coronavirus, South Korea, 2015.

Seong Moon-Woo MW Kim So Yeon SY Corman Victor Max VM Kim Taek Soo TS Cho Sung Im SI Kim Man Jin MJ Lee Seung Jun SJ Lee Jee-Soo JS Seo Soo Hyun SH Ahn Ji Soo JS Yu Byeong Su BS Park Nare N Oh Myoung-don MD Park Wan Beom WB Lee Ji Yeon JY Kim Gayeon G Joh Joon Sung JS Jeong Ina I Kim Eui Chong EC Drosten Christian C Park Sung Sup SS

Emerging infectious diseases 20160201 2

During the 2015 Middle East respiratory syndrome coronavirus outbreak in South Korea, we sequenced full viral genomes of strains isolated from 4 patients early and late during infection. Patients represented at least 4 generations of transmission. We found no evidence of changes in the evolutionary rate and no reason to suspect adaptive changes in viral proteins. ...[more]

PMID: 26814649

Similar Datasets

Project description:Background. Since the emergence of Middle East Respiratory Syndrome Coronavirus (MERS-CoV) in 2012, more than 1,300 laboratory confirmed cases of MERS-CoV infections have been reported in Asia, North Africa, and Europe by July 2015. The recent MERS-CoV nosocomial outbreak in South Korea quickly became the second largest such outbreak with 186 total cases and 36 deaths in a little more than one month, second only to Saudi Arabia in country-specific number of reported cases. Methods. We use a simple mathematical model, the Richards model, to trace the temporal course of the South Korea MERS-CoV outbreak. We pinpoint its outbreak turning point and its transmissibility via basic reproduction number R 0 in order to ascertain the occurrence of this nosocomial outbreak and how it was quickly brought under control. Results. The estimated outbreak turning point of ti = 23.3 days (95% CI [22.6-24.0]), or 23-24 days after the onset date of the index case on May 11, pinpoints June 3-4 as the time of the turning point or the peak incidence for this outbreak by onset date. R 0 is estimated to range between 7.0 and 19.3. Discussion and Conclusion. The turning point of the South Korea MERS-CoV outbreak occurred around May 27-29, when control measures were quickly implemented after laboratory confirmation of the first cluster of nosocomial infections by the index patient. Furthermore, transmissibility of MERS-CoV in the South Korea outbreak was significantly higher than those reported from past MERS-CoV outbreaks in the Middle East, which is attributable to the nosocomial nature of this outbreak. Our estimate of R 0 for the South Korea MERS-CoV nosocomial outbreak further highlights the importance and the risk involved in cluster infections and superspreading events in crowded settings such as hospitals. Similar to the 2003 SARS epidemic, outbreaks of infectious diseases with low community transmissibility like MERS-CoV could still occur initially with large clusters of nosocomial infections, but can be quickly and effectively controlled with timely intervention measures.

Project description:BackgroundEpidemiologic parameters are important in planning infection control policies during the outbreak of emerging infections. Korea experienced an outbreak of Middle East Respiratory Syndrome coronavirus (MERS-CoV) infection in 2015, which was characterized by superspreading events in healthcare settings. We aimed to estimate the epidemiologic parameters over time during the outbreak to assess the effectiveness of countermeasures.Materials and methodsPublicly available data pertaining to the MERS outbreak in Korea were collected. We estimated the incubation periods of 162 cases whose sources of exposure were identified and the temporal trend was evaluated. Factors influencing incubation duration were analyzed. The generational reproduction number (Rg ) and case reproduction number (R(c) ) were estimated over time.ResultsThe estimated median incubation period was 7.4 days (95% CI, 6.9-8.0). Median incubation periods tended to be longer over time as the disease generation progressed: 6.16 days (95% CI, 5.38-6.97), 7.68 days (95% CI, 7.04-8.44), and 7.95 days (95% CI, 6.25-9.88) in the first, second, and third generations, respectively. The number of days of illness in the source cases at the time of exposure inversely correlated with the incubation periods in the receiving cases (HR 0.91 [95% CI, 0.84-0.99] per one illness day increase; P=0.026). This relationship was consistent (HR 0.83 [95% CI, 0.74-0.93] per one illness day increase) in the multivariable analysis incorporating clinical characteristics, the order of generation, and a link to superspreaders. Because the third generation cases were exposed to their source cases in the early stage (median one day) compared to the second generation cases (median 6 days), the temporal trend of incubation periods appears to be influenced by early isolation of symptomatic cases and reduction of potential exposure to source cases in the later stage. Rg declined rapidly from 28 to 0.23 in two generations. R(c) dropped below the epidemic threshold at one on May 31, 2015, which approximately coincided with the initiation of the stringent countermeasures.ConclusionsDespite the initial delay, the stringent countermeasures targeted towards second generation cases appeared to effectively contain the MERS outbreak in Korea as suggested by the decline of R(c) shortly after implementation. Except for superspreading events, the transmission potential for MERS-CoV seems to be low. Further research should be focused on characterizing superspreaders in comparison to non-transmitting cases with regard to environmental, behavioral, and virologic and host genetic factors in order to better prepare for future outbreaks of MERS-CoV.

Dataset Information

Microevolution of Outbreak-Associated Middle East Respiratory Syndrome Coronavirus, South Korea, 2015.

Publications

Microevolution of Outbreak-Associated Middle East Respiratory Syndrome Coronavirus, South Korea, 2015.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets