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10.1073/pnas.2016623118

http://scihub22266oqcxt.onion/10.1073/pnas.2016623118
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33741734!8040586!33741734
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suck abstract from ncbi


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pmid33741734      Proc+Natl+Acad+Sci+U+S+A 2021 ; 118 (14): ä
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  • 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]


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