PMC:7001239 / 3330-4246 JSONTXT

{"project":"LitCovid-PD-CLO","denotations":[{"id":"T32","span":{"begin":3,"end":4},"obj":"http://purl.obolibrary.org/obo/CLO_0001020"},{"id":"T33","span":{"begin":130,"end":131},"obj":"http://purl.obolibrary.org/obo/CLO_0001020"},{"id":"T34","span":{"begin":324,"end":325},"obj":"http://purl.obolibrary.org/obo/CLO_0001020"},{"id":"T35","span":{"begin":514,"end":515},"obj":"http://purl.obolibrary.org/obo/CLO_0001020"},{"id":"T36","span":{"begin":542,"end":543},"obj":"http://purl.obolibrary.org/obo/CLO_0001020"},{"id":"T37","span":{"begin":596,"end":597},"obj":"http://purl.obolibrary.org/obo/CLO_0001020"},{"id":"T38","span":{"begin":733,"end":734},"obj":"http://purl.obolibrary.org/obo/CLO_0001020"}],"text":"In a first step, we initialised simulations with one index case. For each primary case, we generated secondary cases according to a negative-binomial offspring distribution with mean R0 and dispersion k [7,8]. The dispersion parameter k quantifies the variability in the number of secondary cases, and can be interpreted as a measure of the impact of superspreading events (the lower the value of k, the higher the impact of superspreading). The generation time interval D was assumed to be gamma-distributed with a shape parameter of 2, and a mean that varied between 7 and 14 days. We explored a wide range of parameter combinations (Table) and ran 1,000 stochastic simulations for each individual combination. This corresponds to a total of 3.52 million one-index-case simulations that were run on UBELIX (http://www.id.unibe.ch/hpc), the high performance computing cluster at the University of Bern, Switzerland."}

{"project":"LitCovid-PD-CHEBI","denotations":[{"id":"T2","span":{"begin":491,"end":496},"obj":"Chemical"}],"attributes":[{"id":"A2","pred":"chebi_id","subj":"T2","obj":"http://purl.obolibrary.org/obo/CHEBI_30212"}],"text":"In a first step, we initialised simulations with one index case. For each primary case, we generated secondary cases according to a negative-binomial offspring distribution with mean R0 and dispersion k [7,8]. The dispersion parameter k quantifies the variability in the number of secondary cases, and can be interpreted as a measure of the impact of superspreading events (the lower the value of k, the higher the impact of superspreading). The generation time interval D was assumed to be gamma-distributed with a shape parameter of 2, and a mean that varied between 7 and 14 days. We explored a wide range of parameter combinations (Table) and ran 1,000 stochastic simulations for each individual combination. This corresponds to a total of 3.52 million one-index-case simulations that were run on UBELIX (http://www.id.unibe.ch/hpc), the high performance computing cluster at the University of Bern, Switzerland."}

{"project":"LitCovid-sentences","denotations":[{"id":"T24","span":{"begin":0,"end":64},"obj":"Sentence"},{"id":"T25","span":{"begin":65,"end":209},"obj":"Sentence"},{"id":"T26","span":{"begin":210,"end":441},"obj":"Sentence"},{"id":"T27","span":{"begin":442,"end":583},"obj":"Sentence"},{"id":"T28","span":{"begin":584,"end":712},"obj":"Sentence"},{"id":"T29","span":{"begin":713,"end":916},"obj":"Sentence"}],"namespaces":[{"prefix":"_base","uri":"http://pubannotation.org/ontology/tao.owl#"}],"text":"In a first step, we initialised simulations with one index case. For each primary case, we generated secondary cases according to a negative-binomial offspring distribution with mean R0 and dispersion k [7,8]. The dispersion parameter k quantifies the variability in the number of secondary cases, and can be interpreted as a measure of the impact of superspreading events (the lower the value of k, the higher the impact of superspreading). The generation time interval D was assumed to be gamma-distributed with a shape parameter of 2, and a mean that varied between 7 and 14 days. We explored a wide range of parameter combinations (Table) and ran 1,000 stochastic simulations for each individual combination. This corresponds to a total of 3.52 million one-index-case simulations that were run on UBELIX (http://www.id.unibe.ch/hpc), the high performance computing cluster at the University of Bern, Switzerland."}

{"project":"2_test","denotations":[{"id":"32019669-16292310-29338348","span":{"begin":204,"end":205},"obj":"16292310"},{"id":"32019669-25932579-29338349","span":{"begin":206,"end":207},"obj":"25932579"}],"text":"In a first step, we initialised simulations with one index case. For each primary case, we generated secondary cases according to a negative-binomial offspring distribution with mean R0 and dispersion k [7,8]. The dispersion parameter k quantifies the variability in the number of secondary cases, and can be interpreted as a measure of the impact of superspreading events (the lower the value of k, the higher the impact of superspreading). The generation time interval D was assumed to be gamma-distributed with a shape parameter of 2, and a mean that varied between 7 and 14 days. We explored a wide range of parameter combinations (Table) and ran 1,000 stochastic simulations for each individual combination. This corresponds to a total of 3.52 million one-index-case simulations that were run on UBELIX (http://www.id.unibe.ch/hpc), the high performance computing cluster at the University of Bern, Switzerland."}

{"project":"MyTest","denotations":[{"id":"32019669-16292310-29338348","span":{"begin":204,"end":205},"obj":"16292310"},{"id":"32019669-25932579-29338349","span":{"begin":206,"end":207},"obj":"25932579"}],"namespaces":[{"prefix":"_base","uri":"https://www.uniprot.org/uniprot/testbase"},{"prefix":"UniProtKB","uri":"https://www.uniprot.org/uniprot/"},{"prefix":"uniprot","uri":"https://www.uniprot.org/uniprotkb/"}],"text":"In a first step, we initialised simulations with one index case. For each primary case, we generated secondary cases according to a negative-binomial offspring distribution with mean R0 and dispersion k [7,8]. The dispersion parameter k quantifies the variability in the number of secondary cases, and can be interpreted as a measure of the impact of superspreading events (the lower the value of k, the higher the impact of superspreading). The generation time interval D was assumed to be gamma-distributed with a shape parameter of 2, and a mean that varied between 7 and 14 days. We explored a wide range of parameter combinations (Table) and ran 1,000 stochastic simulations for each individual combination. This corresponds to a total of 3.52 million one-index-case simulations that were run on UBELIX (http://www.id.unibe.ch/hpc), the high performance computing cluster at the University of Bern, Switzerland."}