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10.1073/pnas.2015972118 http://scihub22266oqcxt.onion/10.1073/pnas.2015972118 33833080!8092384!33833080     free     free     free Warning: file_get_contents(https://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?dbfrom=pubmed&id=33833080&cmd=llinks): Failed to open stream: HTTP request failed! 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Time-dependent heterogeneity leads to transient suppression of the COVID-19 epidemic, not herd immunity |pdf=|usr=}}{{33833080}} gab.com Text Time-dependent heterogeneity leads to transient suppression of the COVID-19 epidemic, not herd immunity JO: Proc Natl Acad Sci U S A http://www.kidney.de/pget.php?&tw=1&pmid=33833080 #FOAvip Epidemics generally spread through a succession of waves that reflect factors on multiple timescales. On short timescales, superspreading events lead to burstiness and overdispersion, whereas long-term persistent heterogeneity in susceptibility is expected to lead to a reduction in both the infection peak and the herd immunity threshold (HIT). Here, we develop a general approach to encompass both timescales, including time variations in individual social activity, and demonstrate how to incorporate them phenomenologically into a wide class of epidemiological models through reparameterization. We derive a nonlinear dependence of the effective reproduction number [Formula: see text] on the susceptible population fraction S. We show that a state of transient collective immunity (TCI) emerges well below the HIT during early, high-paced stages of the epidemic. However, this is a fragile state that wanes over time due to changing levels of social activity, and so the infection peak is not an indication of long-lasting herd immunity: Subsequent waves may emerge due to behavioral changes in the population, driven by, for example, seasonal factors. Transient and long-term levels of heterogeneity are estimated using empirical data from the COVID-19 epidemic and from real-life face-to-face contact networks. These results suggest that the hardest hit areas, such as New York City, have achieved TCI following the first wave of the epidemic, but likely remain below the long-term HIT. Thus, in contrast to some previous claims, these regions can still experience subsequent waves. Twit Text FOAVip Time-dependent heterogeneity leads to transient suppression of the COVID-19 epidemic, not herd immunity ????Proc Natl Acad Sci U S A http://www.kidney.de/pget.php?&tw=1&pmid=33833080 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=33833080 #FOAvip English Wikipedia <ref>{{Cite pmid|33833080}}</ref> Time-dependent heterogeneity leads to transient suppression of the COVID-19 epidemic, not herd immunity #MMPMID33833080 Tkachenko AV; Maslov S; Elbanna A; Wong GN; Weiner ZJ; Goldenfeld N Proc Natl Acad Sci U S A 2021[Apr]; 118 (17): ä PMID33833080show ga Epidemics generally spread through a succession of waves that reflect factors on multiple timescales. On short timescales, superspreading events lead to burstiness and overdispersion, whereas long-term persistent heterogeneity in susceptibility is expected to lead to a reduction in both the infection peak and the herd immunity threshold (HIT). Here, we develop a general approach to encompass both timescales, including time variations in individual social activity, and demonstrate how to incorporate them phenomenologically into a wide class of epidemiological models through reparameterization. We derive a nonlinear dependence of the effective reproduction number [Formula: see text] on the susceptible population fraction S. We show that a state of transient collective immunity (TCI) emerges well below the HIT during early, high-paced stages of the epidemic. However, this is a fragile state that wanes over time due to changing levels of social activity, and so the infection peak is not an indication of long-lasting herd immunity: Subsequent waves may emerge due to behavioral changes in the population, driven by, for example, seasonal factors. Transient and long-term levels of heterogeneity are estimated using empirical data from the COVID-19 epidemic and from real-life face-to-face contact networks. These results suggest that the hardest hit areas, such as New York City, have achieved TCI following the first wave of the epidemic, but likely remain below the long-term HIT. Thus, in contrast to some previous claims, these regions can still experience subsequent waves. |*COVID-19/epidemiology/immunology/transmission[MESH] |*Epidemics[MESH] |*Immunity, Herd[MESH] |*Models, Immunological[MESH] |Humans[MESH] |SARS-CoV-2/*immunology[MESH]Time-dependent heterogeneity leads to transient suppression of the COV(epmc).pdf DeepDyve Pubget Overpricing