About: Characterizing super-spreading events and age-specific infectivity of COVID-19 transmission in Georgia, USA

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About: Characterizing super-spreading events and age-specific infectivity of COVID-19 transmission in Georgia, USA Goto Sponge NotDistinct Permalink

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

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type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
title	Characterizing super-spreading events and age-specific infectivity of COVID-19 transmission in Georgia, USA
Creator	Grenfell, Bryan Lopman, Ben Nelson, Kristin Sy Lau, Max
source	MedRxiv
abstract	As the current COVID-19 pandemic continues to impact countries around the globe, refining our understanding of its transmission dynamics and the effectiveness of interventions is imperative. In particular, it is essential to obtain a firmer grasp on the effect of social distancing, potential individual-level heterogeneities in transmission such as age-specific infectivity, and impact of super-spreading. To this end, it is important to exploit multiple data streams that are becoming abundantly available during the pandemic. In this paper, we formulate an individual-level spatio-temporal mechanistic framework to statistically integrate case data with geo-location data and aggregate mobility data, enabling a more granular understanding of the transmission dynamics of COVID-19. We analyze reported cases from surveillance data, between March and early May 2020, in five (urban and rural) counties in the State of Georgia USA. We estimate natural history parameters of COVID-19 and infer unobserved quantities including infection times and transmission paths using Bayesian data-augmentation techniques. First, our results show that the overall median reproductive number was 2.88 (with 95% C.I. [1.85, 4.9]) before the state-wide shelter-in-place order issued in early April, and the effective reproductive number was reduced to below 1 about two weeks by the order. Super-spreading appears to be widespread across space and time, and it may have a particularly important role in driving the outbreak in the rural area and increasing importance towards later stages of outbreaks in both urban and rural settings. Overall, about 2% of cases may have directly infected 20% of all infections. We estimate that the infected children and younger adults (<60 years old) may be 2.38 [1.30, 3.51] times more transmissible than infected elderly (>=60), and the former may be the main driver of super-spreading. Through the synthesis of multiple data streams using our transmission modelling framework, our results enforce and improve our understanding of the natural history and transmission dynamics of COVID-19. More importantly, we reveal the roles of age-specific infectivity and characterize systematic variations and associated risk factors of super-spreading. These have important implications for the planning of relaxing social distancing and, more generally, designing optimal control measures.
has issue date	2020-06-22(xsd:dateTime)
bibo:doi	10.1101/2020.06.20.20130476
has license	medrxiv
sha1sum (hex)	1b3ba5a373bb8a0bdf7fb6bcf3f1cc84ea6209e4
schema:url	https://doi.org/10.1101/2020.06.20.20130476
resource representing a document's title	Characterizing super-spreading events and age-specific infectivity of COVID-19 transmission in Georgia, USA
resource representing a document's body	covid:1b3ba5a373bb8a0bdf7fb6bcf3f1cc84ea6209e4#body_text
is schema:about of	named entity 'number' named entity 'improve' named entity 'transmissible' named entity 'impact' named entity 'May' »more»

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