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10.1073/pnas.2016623118 http://scihub22266oqcxt.onion/10.1073/pnas.2016623118 33741734!8040586!33741734     free     free     free Warning: file_get_contents(https://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?dbfrom=pubmed&id=33741734&cmd=llinks): Failed to open stream: HTTP request failed! 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Overdispersion in COVID-19 increases the effectiveness of limiting nonrepetitive contacts for transmission control |pdf=|usr=}}{{33741734}} gab.com Text Overdispersion in COVID-19 increases the effectiveness of limiting nonrepetitive contacts for transmission control JO: Proc Natl Acad Sci U S A http://www.kidney.de/pget.php?&tw=1&pmid=33741734 #FOAvip Increasing evidence indicates that superspreading plays a dominant role in COVID-19 transmission. Recent estimates suggest that the dispersion parameter k for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is on the order of 0.1, which corresponds to about 10% of cases being the source of 80% of infections. To investigate how overdispersion might affect the outcome of various mitigation strategies, we developed an agent-based model with a social network that allows transmission through contact in three sectors: "close" (a small, unchanging group of mutual contacts as might be found in a household), "regular" (a larger, unchanging group as might be found in a workplace or school), and "random" (drawn from the entire model population and not repeated regularly). We assigned individual infectivity from a gamma distribution with dispersion parameter k We found that when k was low (i.e., greater heterogeneity, more superspreading events), reducing random sector contacts had a far greater impact on the epidemic trajectory than did reducing regular contacts; when k was high (i.e., less heterogeneity, no superspreading events), that difference disappeared. These results suggest that overdispersion of COVID-19 transmission gives the virus an Achilles' heel: Reducing contacts between people who do not regularly meet would substantially reduce the pandemic, while reducing repeated contacts in defined social groups would be less effective. Twit Text FOAVip Overdispersion in COVID-19 increases the effectiveness of limiting nonrepetitive contacts for transmission control ????Proc Natl Acad Sci U S A http://www.kidney.de/pget.php?&tw=1&pmid=33741734 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=33741734 #FOAvip English Wikipedia <ref>{{Cite pmid|33741734}}</ref> Overdispersion in COVID-19 increases the effectiveness of limiting nonrepetitive contacts for transmission control #MMPMID33741734 Sneppen K; Nielsen BF; Taylor RJ; Simonsen L Proc Natl Acad Sci U S A 2021[Apr]; 118 (14): ä PMID33741734show ga Increasing evidence indicates that superspreading plays a dominant role in COVID-19 transmission. Recent estimates suggest that the dispersion parameter k for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is on the order of 0.1, which corresponds to about 10% of cases being the source of 80% of infections. To investigate how overdispersion might affect the outcome of various mitigation strategies, we developed an agent-based model with a social network that allows transmission through contact in three sectors: "close" (a small, unchanging group of mutual contacts as might be found in a household), "regular" (a larger, unchanging group as might be found in a workplace or school), and "random" (drawn from the entire model population and not repeated regularly). We assigned individual infectivity from a gamma distribution with dispersion parameter k We found that when k was low (i.e., greater heterogeneity, more superspreading events), reducing random sector contacts had a far greater impact on the epidemic trajectory than did reducing regular contacts; when k was high (i.e., less heterogeneity, no superspreading events), that difference disappeared. These results suggest that overdispersion of COVID-19 transmission gives the virus an Achilles' heel: Reducing contacts between people who do not regularly meet would substantially reduce the pandemic, while reducing repeated contacts in defined social groups would be less effective. |*Models, Statistical[MESH] |*Pandemics[MESH] |*Physical Distancing[MESH] |Age Factors[MESH] |COVID-19/*epidemiology/prevention & control/*transmission/virology[MESH] |Computer Simulation[MESH] |Contact Tracing/*statistics & numerical data[MESH] |Humans[MESH] |Quarantine/statistics & numerical data[MESH] |SARS-CoV-2/pathogenicity/physiology[MESH]Overdispersion in COVID-19 increases the effectiveness of limiting non(epmc).pdf DeepDyve Pubget Overpricing