About: Distinctive trajectories of COVID-19 epidemic by age and gender: a retrospective modeling of the epidemic in South Korea

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About: Distinctive trajectories of COVID-19 epidemic by age and gender: a retrospective modeling of the epidemic in South Korea Goto Sponge NotDistinct Permalink

An Entity of Type : schema:ScholarlyArticle, within Data Space : covidontheweb.inria.fr associated with source document(s)

Attributes	Values
type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
has title	Distinctive trajectories of COVID-19 epidemic by age and gender: a retrospective modeling of the epidemic in South Korea
Creator	Jiang, Yu Zhang, Hongmei Duan, Jiasong Yu, Xinhua
Source	Elsevier; Medline; PMC
abstract	OBJECTIVES: Elderly people had suffered disproportional burden of COVID-19. We hypothesized that males and females in different age groups might have different epidemic trajectories. METHODS: Using publicly available data from South Korea, daily new COVID-19 cases were fitted with generalized additive models, assuming Poisson and negative binomial distributions. Epidemic dynamics by age and gender groups were explored with interactions between smoothed time terms and age and gender. RESULTS: A negative binomial distribution fitted the daily case counts best. Interaction between the dynamic patterns of daily new cases and age groups was statistically significant (p < 0.001), but not with gender group. People aged 20-39 years led the epidemic processes in the society with two peaks: one major peak around March 1 and a smaller peak around April 7, 2020. The epidemic process among people aged 60 or above was trailing behind that of younger people with smaller magnitude. After March 15, there was a consistent decline of daily new cases among elderly people, despite large fluctuations of case counts among young adults. CONCLUSIONS: Although young people drove the COVID-19 epidemic in the whole society with multiple rebounds, elderly people could still be protected from virus infection after the peak of epidemic.
has issue date	2020-07-02(xsd:dateTime)
bibo:doi	10.1016/j.ijid.2020.06.101
bibo:pmid	32623081
has license	no-cc
sha1sum (hex)	94c5f04017af2e74bf554500e8afc889572019c4
schema:url	https://doi.org/10.1016/j.ijid.2020.06.101
resource representing a document's title	Distinctive trajectories of COVID-19 epidemic by age and gender: a retrospective modeling of the epidemic in South Korea
has PubMed Central identifier	PMC7330572
has PubMed identifier	32623081
schema:publication	Int J Infect Dis
resource representing a document's body	covid:94c5f04017af2e74bf554500e8afc889572019c4#body_text
is schema:about of	named entity 'COVID-19' named entity 'epidemic' named entity 'gender' named entity 'Journal' named entity 'trajectories' named entity 'SOUTH KOREA' named entity 'COVID-19 EPIDEMIC' named entity 'suffered' named entity 'retrospective' named entity 'retrospective' named entity 'COVID-19' named entity 'epidemic' named entity 'epidemic' named entity 'South Korea' named entity 'COVID' named entity 'Institutional Review Board' named entity 'Wuhan' named entity 'epidemic' named entity 'Poisson' named entity 'Daegu' named entity 'epidemic' named entity 'epidemic' named entity 'disease burden' named entity 'contact tracing' named entity 'pneumonia' named entity 'Elderly people' named entity 'epidemic' named entity 'epidemic' named entity 'virus' named entity 'epidemic' named entity 'epidemic' named entity 'epidemic' named entity 'epidemic' named entity 'virus' named entity 'infectious diseases' named entity 'human subjects' named entity 'vector' named entity 'COVID-19' named entity 'KCDC' named entity 'epidemic' named entity 'exponential growth' named entity 'continuous variable' named entity 'basis function' named entity 'epidemic' named entity 'elderly people' named entity 'GAM' named entity 'elderly people' named entity 'seasonal flu' named entity 'COVID' named entity 'Wuhan' named entity 'epidemic' named entity 'count data' named entity 'IHME' named entity 'contact tracing' named entity 'incubation period' named entity 'South Korea' named entity 'epidemic' named entity 'epidemic' named entity 'COVID-19' named entity 'COVID' named entity 'epidemic' named entity 'SARS-CoV-2' named entity 'Negative Binomial' named entity 'transmissibility' named entity 'COVID' named entity 'statistical methods' named entity 'KCDC' named entity 'epidemic' named entity 'epidemic' named entity 'March 1' named entity 'Singapore' named entity 'epidemics' named entity 'epidemic' named entity 'time series' named entity 'China' named entity 'basic reproduction number' named entity 'attack rate' named entity 'empirical evidence'

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