PMC:7175914 / 8590-10222 JSONTXT

{"project":"LitCovid-PubTator","denotations":[{"id":"63","span":{"begin":35,"end":43},"obj":"Disease"},{"id":"64","span":{"begin":213,"end":221},"obj":"Disease"},{"id":"65","span":{"begin":229,"end":237},"obj":"Disease"},{"id":"68","span":{"begin":496,"end":569},"obj":"Gene"},{"id":"69","span":{"begin":572,"end":575},"obj":"Gene"},{"id":"71","span":{"begin":928,"end":936},"obj":"Disease"}],"attributes":[{"id":"A63","pred":"tao:has_database_id","subj":"63","obj":"MESH:C000657245"},{"id":"A64","pred":"tao:has_database_id","subj":"64","obj":"MESH:D007239"},{"id":"A65","pred":"tao:has_database_id","subj":"65","obj":"MESH:C000657245"},{"id":"A69","pred":"tao:has_database_id","subj":"69","obj":"Gene:5375"},{"id":"A71","pred":"tao:has_database_id","subj":"71","obj":"MESH:C000657245"}],"namespaces":[{"prefix":"Tax","uri":"https://www.ncbi.nlm.nih.gov/taxonomy/"},{"prefix":"MESH","uri":"https://id.nlm.nih.gov/mesh/"},{"prefix":"Gene","uri":"https://www.ncbi.nlm.nih.gov/gene/"},{"prefix":"CVCL","uri":"https://web.expasy.org/cellosaurus/CVCL_"}],"text":"Methodology\nIn this study, for the COVID-19 variations, we focus on the cumulative confirmed cases and confirmed cases. The largest value of the cumulative confirmed cases means the total number of the population infected by the COVID-19 disease. The disease extinction time is defined as the day with no confirmed case which is the time of I q(t) = 0.\nThe initial values and parameters can be obtained from the Text methodology of the supplementary information. The baseline parameters noted as (A, B, p 1, p 2, p 3, q 1, q 2, q 3, α, β, ν, σ, γ) = (A* , B  * , p 1  * , p 2  * , p 3  * , q 1  * , q 2  * , q 3  *, α* , β  * , ν  *, σ  * , γ  *) is obtained from the simulation result of the cumulative confirmed cases, the daily new confirmed cases, the confirmed cases and the recovered cases.\nTo compare with the baseline results, three aspects from the perspectives of the input population and quarantine strategies on the COVID-19 variations are analyzed: (1) aspect 1, effects of the input population at different scenarios; (2) aspect 2, effects of quarantine rates at different scenarios and (3) aspect 3, effects of both input population and quarantine rates at different scenarios. To evaluate the accuracy of our model, five statistical indices are applied, including the absolute error (AE), relative error (RE), mean absolute percentage error (MAPE), determinant coefficient R  *  2 which is the square of correlation coefficient R* and distance between indices of simulation and observation (DISO) ([Hu et al., 2016], [Hu et al., 2019]). The details are displayed in Text methodology of the supplementary information."}

{"project":"LitCovid-PMC-OGER-BB","denotations":[{"id":"T63","span":{"begin":35,"end":43},"obj":"SP_7"},{"id":"T64","span":{"begin":229,"end":237},"obj":"SP_7"},{"id":"T65","span":{"begin":928,"end":936},"obj":"SP_7"}],"text":"Methodology\nIn this study, for the COVID-19 variations, we focus on the cumulative confirmed cases and confirmed cases. The largest value of the cumulative confirmed cases means the total number of the population infected by the COVID-19 disease. The disease extinction time is defined as the day with no confirmed case which is the time of I q(t) = 0.\nThe initial values and parameters can be obtained from the Text methodology of the supplementary information. The baseline parameters noted as (A, B, p 1, p 2, p 3, q 1, q 2, q 3, α, β, ν, σ, γ) = (A* , B  * , p 1  * , p 2  * , p 3  * , q 1  * , q 2  * , q 3  *, α* , β  * , ν  *, σ  * , γ  *) is obtained from the simulation result of the cumulative confirmed cases, the daily new confirmed cases, the confirmed cases and the recovered cases.\nTo compare with the baseline results, three aspects from the perspectives of the input population and quarantine strategies on the COVID-19 variations are analyzed: (1) aspect 1, effects of the input population at different scenarios; (2) aspect 2, effects of quarantine rates at different scenarios and (3) aspect 3, effects of both input population and quarantine rates at different scenarios. To evaluate the accuracy of our model, five statistical indices are applied, including the absolute error (AE), relative error (RE), mean absolute percentage error (MAPE), determinant coefficient R  *  2 which is the square of correlation coefficient R* and distance between indices of simulation and observation (DISO) ([Hu et al., 2016], [Hu et al., 2019]). The details are displayed in Text methodology of the supplementary information."}

{"project":"LitCovid-PD-MONDO","denotations":[{"id":"T31","span":{"begin":35,"end":43},"obj":"Disease"},{"id":"T32","span":{"begin":229,"end":237},"obj":"Disease"},{"id":"T33","span":{"begin":928,"end":936},"obj":"Disease"}],"attributes":[{"id":"A31","pred":"mondo_id","subj":"T31","obj":"http://purl.obolibrary.org/obo/MONDO_0100096"},{"id":"A32","pred":"mondo_id","subj":"T32","obj":"http://purl.obolibrary.org/obo/MONDO_0100096"},{"id":"A33","pred":"mondo_id","subj":"T33","obj":"http://purl.obolibrary.org/obo/MONDO_0100096"}],"text":"Methodology\nIn this study, for the COVID-19 variations, we focus on the cumulative confirmed cases and confirmed cases. The largest value of the cumulative confirmed cases means the total number of the population infected by the COVID-19 disease. The disease extinction time is defined as the day with no confirmed case which is the time of I q(t) = 0.\nThe initial values and parameters can be obtained from the Text methodology of the supplementary information. The baseline parameters noted as (A, B, p 1, p 2, p 3, q 1, q 2, q 3, α, β, ν, σ, γ) = (A* , B  * , p 1  * , p 2  * , p 3  * , q 1  * , q 2  * , q 3  *, α* , β  * , ν  *, σ  * , γ  *) is obtained from the simulation result of the cumulative confirmed cases, the daily new confirmed cases, the confirmed cases and the recovered cases.\nTo compare with the baseline results, three aspects from the perspectives of the input population and quarantine strategies on the COVID-19 variations are analyzed: (1) aspect 1, effects of the input population at different scenarios; (2) aspect 2, effects of quarantine rates at different scenarios and (3) aspect 3, effects of both input population and quarantine rates at different scenarios. To evaluate the accuracy of our model, five statistical indices are applied, including the absolute error (AE), relative error (RE), mean absolute percentage error (MAPE), determinant coefficient R  *  2 which is the square of correlation coefficient R* and distance between indices of simulation and observation (DISO) ([Hu et al., 2016], [Hu et al., 2019]). The details are displayed in Text methodology of the supplementary information."}

{"project":"LitCovid-PD-CLO","denotations":[{"id":"T52","span":{"begin":59,"end":64},"obj":"http://purl.obolibrary.org/obo/CLO_0009985"},{"id":"T53","span":{"begin":497,"end":498},"obj":"http://purl.obolibrary.org/obo/CLO_0001020"},{"id":"T54","span":{"begin":500,"end":501},"obj":"http://purl.obolibrary.org/obo/CLO_0001021"},{"id":"T55","span":{"begin":503,"end":506},"obj":"http://purl.obolibrary.org/obo/CLO_0008285"},{"id":"T56","span":{"begin":503,"end":506},"obj":"http://purl.obolibrary.org/obo/CLO_0008286"},{"id":"T57","span":{"begin":508,"end":511},"obj":"http://purl.obolibrary.org/obo/CLO_0008307"},{"id":"T58","span":{"begin":551,"end":552},"obj":"http://purl.obolibrary.org/obo/CLO_0001020"},{"id":"T59","span":{"begin":556,"end":557},"obj":"http://purl.obolibrary.org/obo/CLO_0001021"},{"id":"T60","span":{"begin":563,"end":566},"obj":"http://purl.obolibrary.org/obo/CLO_0008285"},{"id":"T61","span":{"begin":563,"end":566},"obj":"http://purl.obolibrary.org/obo/CLO_0008286"},{"id":"T62","span":{"begin":572,"end":575},"obj":"http://purl.obolibrary.org/obo/CLO_0008307"},{"id":"T63","span":{"begin":1300,"end":1302},"obj":"http://purl.obolibrary.org/obo/CLO_0051456"}],"text":"Methodology\nIn this study, for the COVID-19 variations, we focus on the cumulative confirmed cases and confirmed cases. The largest value of the cumulative confirmed cases means the total number of the population infected by the COVID-19 disease. The disease extinction time is defined as the day with no confirmed case which is the time of I q(t) = 0.\nThe initial values and parameters can be obtained from the Text methodology of the supplementary information. The baseline parameters noted as (A, B, p 1, p 2, p 3, q 1, q 2, q 3, α, β, ν, σ, γ) = (A* , B  * , p 1  * , p 2  * , p 3  * , q 1  * , q 2  * , q 3  *, α* , β  * , ν  *, σ  * , γ  *) is obtained from the simulation result of the cumulative confirmed cases, the daily new confirmed cases, the confirmed cases and the recovered cases.\nTo compare with the baseline results, three aspects from the perspectives of the input population and quarantine strategies on the COVID-19 variations are analyzed: (1) aspect 1, effects of the input population at different scenarios; (2) aspect 2, effects of quarantine rates at different scenarios and (3) aspect 3, effects of both input population and quarantine rates at different scenarios. To evaluate the accuracy of our model, five statistical indices are applied, including the absolute error (AE), relative error (RE), mean absolute percentage error (MAPE), determinant coefficient R  *  2 which is the square of correlation coefficient R* and distance between indices of simulation and observation (DISO) ([Hu et al., 2016], [Hu et al., 2019]). The details are displayed in Text methodology of the supplementary information."}

{"project":"LitCovid-PD-CHEBI","denotations":[{"id":"T10","span":{"begin":1300,"end":1302},"obj":"Chemical"}],"attributes":[{"id":"A10","pred":"chebi_id","subj":"T10","obj":"http://purl.obolibrary.org/obo/CHEBI_61565"}],"text":"Methodology\nIn this study, for the COVID-19 variations, we focus on the cumulative confirmed cases and confirmed cases. The largest value of the cumulative confirmed cases means the total number of the population infected by the COVID-19 disease. The disease extinction time is defined as the day with no confirmed case which is the time of I q(t) = 0.\nThe initial values and parameters can be obtained from the Text methodology of the supplementary information. The baseline parameters noted as (A, B, p 1, p 2, p 3, q 1, q 2, q 3, α, β, ν, σ, γ) = (A* , B  * , p 1  * , p 2  * , p 3  * , q 1  * , q 2  * , q 3  *, α* , β  * , ν  *, σ  * , γ  *) is obtained from the simulation result of the cumulative confirmed cases, the daily new confirmed cases, the confirmed cases and the recovered cases.\nTo compare with the baseline results, three aspects from the perspectives of the input population and quarantine strategies on the COVID-19 variations are analyzed: (1) aspect 1, effects of the input population at different scenarios; (2) aspect 2, effects of quarantine rates at different scenarios and (3) aspect 3, effects of both input population and quarantine rates at different scenarios. To evaluate the accuracy of our model, five statistical indices are applied, including the absolute error (AE), relative error (RE), mean absolute percentage error (MAPE), determinant coefficient R  *  2 which is the square of correlation coefficient R* and distance between indices of simulation and observation (DISO) ([Hu et al., 2016], [Hu et al., 2019]). The details are displayed in Text methodology of the supplementary information."}

{"project":"LitCovid-sentences","denotations":[{"id":"T52","span":{"begin":0,"end":11},"obj":"Sentence"},{"id":"T53","span":{"begin":12,"end":119},"obj":"Sentence"},{"id":"T54","span":{"begin":120,"end":246},"obj":"Sentence"},{"id":"T55","span":{"begin":247,"end":352},"obj":"Sentence"},{"id":"T56","span":{"begin":353,"end":462},"obj":"Sentence"},{"id":"T57","span":{"begin":463,"end":796},"obj":"Sentence"},{"id":"T58","span":{"begin":797,"end":1192},"obj":"Sentence"},{"id":"T59","span":{"begin":1193,"end":1552},"obj":"Sentence"},{"id":"T60","span":{"begin":1553,"end":1632},"obj":"Sentence"}],"namespaces":[{"prefix":"_base","uri":"http://pubannotation.org/ontology/tao.owl#"}],"text":"Methodology\nIn this study, for the COVID-19 variations, we focus on the cumulative confirmed cases and confirmed cases. The largest value of the cumulative confirmed cases means the total number of the population infected by the COVID-19 disease. The disease extinction time is defined as the day with no confirmed case which is the time of I q(t) = 0.\nThe initial values and parameters can be obtained from the Text methodology of the supplementary information. The baseline parameters noted as (A, B, p 1, p 2, p 3, q 1, q 2, q 3, α, β, ν, σ, γ) = (A* , B  * , p 1  * , p 2  * , p 3  * , q 1  * , q 2  * , q 3  *, α* , β  * , ν  *, σ  * , γ  *) is obtained from the simulation result of the cumulative confirmed cases, the daily new confirmed cases, the confirmed cases and the recovered cases.\nTo compare with the baseline results, three aspects from the perspectives of the input population and quarantine strategies on the COVID-19 variations are analyzed: (1) aspect 1, effects of the input population at different scenarios; (2) aspect 2, effects of quarantine rates at different scenarios and (3) aspect 3, effects of both input population and quarantine rates at different scenarios. To evaluate the accuracy of our model, five statistical indices are applied, including the absolute error (AE), relative error (RE), mean absolute percentage error (MAPE), determinant coefficient R  *  2 which is the square of correlation coefficient R* and distance between indices of simulation and observation (DISO) ([Hu et al., 2016], [Hu et al., 2019]). The details are displayed in Text methodology of the supplementary information."}