scholarly journals Temporal changes in the risk of superspreading events of coronavirus disease 2019

Author(s):  
Jun-Sik Lim ◽  
Eunbi Noh ◽  
Eunha Shim ◽  
Sukhyun Ryu

In order to identify the temporal change in the possible risk of superspreading events (SSE), we estimated the overdispersion parameter in two different periods of COVID-19 pandemic. We identified the possible risk of SSE was reduced 34% during the second epidemic period in South Korea.

Author(s):  
Jun-Sik Lim ◽  
Eunbi Noh ◽  
Eunha Shim ◽  
Sukhyun Ryu

Abstract In order to identify the temporal change in the possible risk of superspreading events (SSE), we estimated the overdispersion parameter in two different periods of COVID-19 pandemic. We identified the possible risk of SSE was reduced 90% during the second epidemic period in South Korea.


2014 ◽  
Vol 86 (1-2) ◽  
pp. 547-554 ◽  
Author(s):  
Nam Sook Kim ◽  
Sang Hee Hong ◽  
Un Hyuk Yim ◽  
Kyung-Hoon Shin ◽  
Won Joon Shim

2020 ◽  
Author(s):  
Yoshihiro Ito ◽  
Miyuu Uemura ◽  
Spahr C. Webb ◽  
Kimihiro Mochizuki ◽  
Stuart Henrys

<p>The interactions of wind with the ocean surface, ocean wave with acoustic wave, acoustic wave with seismic wave below the sea bottom, and the interplay among them drive important energy flows from the atmosphere to the lithosphere. Uncertainty remains regarding the origin of wind-related noise in the ocean and its coupling to seismic noise below the sea floor. Seismic interferometry is a powerful tool that uses microseisms, or ambient noise within solid earth, to monitor temporal seismic velocity change by referring to the auto/cross-correlation as a Green’s function at the sites, and its temporal change. The most important assumption when detecting seismic velocity changes with seismic interferometry is that mutually uncorrelated noise sources are distributed randomly in space and time without any temporal changes in their density and intensity in a fully diffuse wave field. An effect of temporal variation on the ambit noise field to the retrieval of Green’s function is, however, not fully understood, nor is how reliable temporal changes in interferogram noise are, especially when accompanied by large earthquakes and slow slip events. Here, we show relationships among the temporal changes of sea surface wave, acoustic wave, and seismic wave fields, which are observed in ocean bottom pressure gauges and seismometer arrays installed in New Zealand. The temporal variation in the power spectrum obtained from continuous ocean bottom seismometer and pressure records near 200 mHz correlates with the temporal variation in wind speed above the sites, particularly during wind turbulence of more than 5 m/s. The temporal fluctuation in the ocean bottom pressure caused by the ocean surface wave field correlates to that of a microseism near 200 mHz. The temporal variations in the power spectrum from both continuous ocean bottom pressures and microseisms in the 200–800 mHz range show a positive correlation. After calculating the auto/cross-correlation functions (ACF/CCF) from ambient noise in a 200–800 mHz pass band every 6 h, the temporal variation in the correlation between the ACF/CCFs is investigated every 6 h. The temporal variation in the ACF/CCFs correlates with the time derivative of the temporal changes in the power spectrum amplitude of both the bottom pressure and the microseism rather than the temporal changes in the amplitude of the power spectrum. This suggests that the temporal change that occurs in the seismic interferogram owing to ambient noise, is mostly controlled by the temporal change in the ocean wave field undergoing fluctuations by the atmospheric turbulence over the sea surface. The temporal variations in the noise field in space and time may break the assumption on seismic interferometry, and eventually make the apparent temporal change in interferogram noise.</p>


2015 ◽  
Vol 58 (7) ◽  
pp. 713-723 ◽  
Author(s):  
Kijun Nam ◽  
Woo-Kyun Lee ◽  
Moonil Kim ◽  
Doo-Ahn Kwak ◽  
Woo-Hyuk Byun ◽  
...  

2019 ◽  
Author(s):  
Anne Mimet ◽  
Robert Buitenwerf ◽  
Brody Sandel ◽  
Jens-Christian Svenning ◽  
Signe Normand

AbstractAimTheory suggests that increasing productivity and climate stability toward the tropics can explain the latitudinal richness gradient by favouring specialization. A positive relationship between species richness and specialization should thus emerge as a fundamental biogeographic pattern. However, land use and climate change disproportionally increase the local extirpation risk for specialists, potentially impacting this pattern. Here, we empirically quantify the richness-specialization prediction and test how 50 years of climate and land use change has affected the richness-specialization relationship.LocationUSATime period1966-2015Major taxa studiedBirdsMethodsWe used the North American breeding bird survey to quantify bird community richness and specialization to habitat and climate. We assess i) temporal change in the slope of the richness-specialization relationship, using a Generalized Mixed Model; ii) temporal change in spatial covariation of richness and specialization as driven by local environmental conditions, using Generalized Additive Models; and iii) land use, climate and topographic drivers of the spatio-temporal changes in the relationship, using a multivariate method.ResultsWe found evidence for a positive richness-specialization relationship in bird communities. However, the slope of the relationship declined strongly over time. Richness spatially covaried with specialization following a unimodal pattern. The peak of the unimodal pattern shifted toward less specialized communities over time. These temporal changes were associated with precipitation change, decreasing temperature stability and land use.Main conclusionsRecent climate and land use changes induced two antagonist types of community responses. In human-dominated areas, the decoupling of richness and specialization drove a general biotic homogenization trend. In human-preserved areas under increasing climate harshness, specialization increased while richness decreased in a “specialization” trend. Our results offer new support for specialization as a key driver of macroecological diversity patterns, and show that global changes are erasing this fundamental macroecological pattern.BiosketchAnne Mimet is a postdoctoral researcher interested in the understanding of human impacts on biodiversity through land use and climate changes, at various spatio-temporal scales. She is interested in embracing the complexity of socio-ecological systems, and in the understanding of biodiversity trends in a human-dominated world in the context of the general theories of ecology.


2019 ◽  
Vol 128 ◽  
pp. 309-317 ◽  
Author(s):  
Jinmo Ahn ◽  
Won-Seok Kim ◽  
Jin-Beak Park ◽  
Arokiasamy J. Francis ◽  
Wooyong Um

2019 ◽  
Vol 37 (3) ◽  
pp. 426-432
Author(s):  
Sei-Woong Choi ◽  
Nang-Hee Kim ◽  
Bora Shin ◽  
Jae-Young Lee ◽  
Beom-Jun Jang

2018 ◽  
Vol 28 (2) ◽  
pp. 65-77 ◽  
Author(s):  
Jiyoung Lee ◽  
Jae-Hyun Lim ◽  
Junhyung Park ◽  
Il-Nam Kim

Microbial communities play an essential role in marine biogeochemical cycles. Physical and biogeochemical changes in Jinhae Bay, the most anthropogenically eutrophied bay on the coasts of South Korea, are well described, but less is known about the associated changes in microbial communities. Temporal and vertical variation in microbial communities at three depths (surface, middle, and bottom) at seven time points (June to December) at the J1 sampling site were investigated on the MiSeq platform based on the 16S rRNA gene. Overall, the microbial community was dominated by Proteobacteria, Cyanobacteria, and Bacteroidetes from June to November, whereas Firmicutes were dominant in December, especially in the middle and bottom layers. The results indicate that the microbial community composition strongly varied with temporal changes in the physicochemical water properties. Moreover, the community composition differed markedly between the surface and middle layers and the bottom layer in the summer, when the water column was strongly stratified and bottom water hypoxia developed. A redundancy analysis suggested a significant correlation between physicochemical variables (i.e., temperature, salinity, and oxygen concentration) and microbial community composition. This study indicates that temporal changes in water conditions and eutrophication-induced hypoxia effectively shape the structure of the microbial community.


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