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10.1073/pnas.2011802117 http://scihub22266oqcxt.onion/10.1073/pnas.2011802117 32820074!7486752!32820074     free     free     free Deprecated: Implicit conversion from float 209.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 209.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 209.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 209.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 209.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 209.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 243.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Proc+Natl+Acad+Sci+U+S+A 2020 ; 117 (36): 22430-22435 Nephropedia Template TP {{tp|p=32820074|t=2020. Characterizing superspreading events and age-specific infectiousness of SARS-CoV-2 transmission in Georgia, USA |pdf=|usr=}}{{32820074}} gab.com Text Characterizing superspreading events and age-specific infectiousness of SARS-CoV-2 transmission in Georgia, USA JO: Proc Natl Acad Sci U S A http://www.kidney.de/pget.php?&tw=1&pmid=32820074 #FOAvip It is imperative to advance our understanding of heterogeneities in the transmission of SARS-CoV-2 such as age-specific infectiousness and superspreading. 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 spatiotemporal mechanistic framework to integrate individual surveillance data with geolocation data and aggregate mobility data, enabling a more granular understanding of the transmission dynamics of SARS-CoV-2. We analyze reported cases, between March and early May 2020, in five (urban and rural) counties in the state of Georgia. First, our results show that the reproductive number reduced to below one in about 2 wk after the shelter-in-place order. Superspreading appears to be widespread across space and time, and it may have a particularly important role in driving the outbreak in rural areas and an increasing importance toward later stages of outbreaks in both urban and rural settings. Overall, about 2% of cases were directly responsible for 20% of all infections. We estimate that the infected nonelderly cases (<60 y) may be 2.78 [2.10, 4.22] times more infectious than the elderly, and the former tend to be the main driver of superspreading. Our results improve our understanding of the natural history and transmission dynamics of SARS-CoV-2. More importantly, we reveal the roles of age-specific infectiousness and characterize systematic variations and associated risk factors of superspreading. These have important implications for the planning of relaxing social distancing and, more generally, designing optimal control measures. Twit Text FOAVip Characterizing superspreading events and age-specific infectiousness of SARS-CoV-2 transmission in Georgia, USA ????Proc Natl Acad Sci U S A http://www.kidney.de/pget.php?&tw=1&pmid=32820074 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=32820074 #FOAvip English Wikipedia <ref>{{Cite pmid|32820074}}</ref> Characterizing superspreading events and age-specific infectiousness of SARS-CoV-2 transmission in Georgia, USA #MMPMID32820074 Lau MSY; Grenfell B; Thomas M; Bryan M; Nelson K; Lopman B Proc Natl Acad Sci U S A 2020[Sep]; 117 (36): 22430-22435 PMID32820074show ga It is imperative to advance our understanding of heterogeneities in the transmission of SARS-CoV-2 such as age-specific infectiousness and superspreading. 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 spatiotemporal mechanistic framework to integrate individual surveillance data with geolocation data and aggregate mobility data, enabling a more granular understanding of the transmission dynamics of SARS-CoV-2. We analyze reported cases, between March and early May 2020, in five (urban and rural) counties in the state of Georgia. First, our results show that the reproductive number reduced to below one in about 2 wk after the shelter-in-place order. Superspreading appears to be widespread across space and time, and it may have a particularly important role in driving the outbreak in rural areas and an increasing importance toward later stages of outbreaks in both urban and rural settings. Overall, about 2% of cases were directly responsible for 20% of all infections. We estimate that the infected nonelderly cases (<60 y) may be 2.78 [2.10, 4.22] times more infectious than the elderly, and the former tend to be the main driver of superspreading. Our results improve our understanding of the natural history and transmission dynamics of SARS-CoV-2. More importantly, we reveal the roles of age-specific infectiousness and characterize systematic variations and associated risk factors of superspreading. These have important implications for the planning of relaxing social distancing and, more generally, designing optimal control measures. |Basic Reproduction Number[MESH] |Betacoronavirus[MESH] |COVID-19[MESH] |Contact Tracing[MESH] |Coronavirus Infections/*epidemiology/prevention & control/*transmission[MESH] |Disease Transmission, Infectious/prevention & control/*statistics & numerical data[MESH] |Georgia/epidemiology[MESH] |Humans[MESH] |Pandemics/prevention & control[MESH] |Pneumonia, Viral/*epidemiology/prevention & control/*transmission[MESH] |Risk Factors[MESH]Characterizing superspreading events and age-specific infectiousness o(epmc).pdf DeepDyve Pubget Overpricing