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10.1098/rsos.210506 http://scihub22266oqcxt.onion/10.1098/rsos.210506 34295529!8261230!34295529     free     free     free Warning: file_get_contents(https://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?dbfrom=pubmed&id=34295529&cmd=llinks): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 215       R+Soc+Open+Sci 2021 ; 8 (7): 210506 Nephropedia Template TP {{tp|p=34295529|t=2021. June: open-source individual-based epidemiology simulation |pdf=|usr=}}{{34295529}} gab.com Text June: open-source individual-based epidemiology simulation JO: R Soc Open Sci http://www.kidney.de/pget.php?&tw=1&pmid=34295529 #FOAvip We introduce June, an open-source framework for the detailed simulation of epidemics on the basis of social interactions in a virtual population constructed from geographically granular census data, reflecting age, sex, ethnicity and socio-economic indicators. Interactions between individuals are modelled in groups of various sizes and properties, such as households, schools and workplaces, and other social activities using social mixing matrices. June provides a suite of flexible parametrizations that describe infectious diseases, how they are transmitted and affect contaminated individuals. In this paper, we apply June to the specific case of modelling the spread of COVID-19 in England. We discuss the quality of initial model outputs which reproduce reported hospital admission and mortality statistics at national and regional levels as well as by age strata. Twit Text FOAVip June: open-source individual-based epidemiology simulation ????R Soc Open Sci http://www.kidney.de/pget.php?&tw=1&pmid=34295529 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=34295529 #FOAvip English Wikipedia <ref>{{Cite pmid|34295529}}</ref> June: open-source individual-based epidemiology simulation #MMPMID34295529 Aylett-Bullock J; Cuesta-Lazaro C; Quera-Bofarull A; Icaza-Lizaola M; Sedgewick A; Truong H; Curran A; Elliott E; Caulfield T; Fong K; Vernon I; Williams J; Bower R; Krauss F R Soc Open Sci 2021[Jul]; 8 (7): 210506 PMID34295529show ga We introduce June, an open-source framework for the detailed simulation of epidemics on the basis of social interactions in a virtual population constructed from geographically granular census data, reflecting age, sex, ethnicity and socio-economic indicators. Interactions between individuals are modelled in groups of various sizes and properties, such as households, schools and workplaces, and other social activities using social mixing matrices. June provides a suite of flexible parametrizations that describe infectious diseases, how they are transmitted and affect contaminated individuals. In this paper, we apply June to the specific case of modelling the spread of COVID-19 in England. We discuss the quality of initial model outputs which reproduce reported hospital admission and mortality statistics at national and regional levels as well as by age strata. ?June: open-source individual-based epidemiology simulation (epmc).pdf DeepDyve Pubget Overpricing