PMC:7102659 / 16403-17316 JSONTXT

{"project":"LitCovid-PD-MONDO","denotations":[{"id":"T54","span":{"begin":579,"end":588},"obj":"Disease"},{"id":"T55","span":{"begin":636,"end":644},"obj":"Disease"},{"id":"T56","span":{"begin":649,"end":658},"obj":"Disease"}],"attributes":[{"id":"A54","pred":"mondo_id","subj":"T54","obj":"http://purl.obolibrary.org/obo/MONDO_0005812"},{"id":"A55","pred":"mondo_id","subj":"T55","obj":"http://purl.obolibrary.org/obo/MONDO_0100096"},{"id":"A56","pred":"mondo_id","subj":"T56","obj":"http://purl.obolibrary.org/obo/MONDO_0005812"}],"text":"We avoid to fit model to data in conventional way. Instead, we use a simple model framework to discuss what elements might be needed. For instance, in order to achieve a good fitting performance, one obviously needs to include a time-varying report rate (as we reconstructed in Figure 4b), which was caused by the availability of medical supplies, hospital capacities and changing testing/reporting policies. Thus it would be challenging given a relatively short time series, and several other unknown parameters to be estimated. We employ some parameter estimates from the 1918 influenza pandemic, given the similar characteristics of COVID-19 and influenza (most cases are mild) and the similar level of mitigation. Transmission from asymptotically infected cases is reported but the contribution of asymptomatic transmission is unclear (presumably small), which shall be further investigated in future studies."}

{"project":"LitCovid-PD-CLO","denotations":[{"id":"T76","span":{"begin":67,"end":68},"obj":"http://purl.obolibrary.org/obo/CLO_0001020"},{"id":"T77","span":{"begin":168,"end":169},"obj":"http://purl.obolibrary.org/obo/CLO_0001020"},{"id":"T78","span":{"begin":227,"end":228},"obj":"http://purl.obolibrary.org/obo/CLO_0001020"},{"id":"T79","span":{"begin":381,"end":388},"obj":"http://purl.obolibrary.org/obo/UBERON_0000473"},{"id":"T80","span":{"begin":444,"end":445},"obj":"http://purl.obolibrary.org/obo/CLO_0001020"}],"text":"We avoid to fit model to data in conventional way. Instead, we use a simple model framework to discuss what elements might be needed. For instance, in order to achieve a good fitting performance, one obviously needs to include a time-varying report rate (as we reconstructed in Figure 4b), which was caused by the availability of medical supplies, hospital capacities and changing testing/reporting policies. Thus it would be challenging given a relatively short time series, and several other unknown parameters to be estimated. We employ some parameter estimates from the 1918 influenza pandemic, given the similar characteristics of COVID-19 and influenza (most cases are mild) and the similar level of mitigation. Transmission from asymptotically infected cases is reported but the contribution of asymptomatic transmission is unclear (presumably small), which shall be further investigated in future studies."}

{"project":"LitCovid-sentences","denotations":[{"id":"T136","span":{"begin":0,"end":50},"obj":"Sentence"},{"id":"T137","span":{"begin":51,"end":133},"obj":"Sentence"},{"id":"T138","span":{"begin":134,"end":408},"obj":"Sentence"},{"id":"T139","span":{"begin":409,"end":529},"obj":"Sentence"},{"id":"T140","span":{"begin":530,"end":717},"obj":"Sentence"},{"id":"T141","span":{"begin":718,"end":913},"obj":"Sentence"}],"namespaces":[{"prefix":"_base","uri":"http://pubannotation.org/ontology/tao.owl#"}],"text":"We avoid to fit model to data in conventional way. Instead, we use a simple model framework to discuss what elements might be needed. For instance, in order to achieve a good fitting performance, one obviously needs to include a time-varying report rate (as we reconstructed in Figure 4b), which was caused by the availability of medical supplies, hospital capacities and changing testing/reporting policies. Thus it would be challenging given a relatively short time series, and several other unknown parameters to be estimated. We employ some parameter estimates from the 1918 influenza pandemic, given the similar characteristics of COVID-19 and influenza (most cases are mild) and the similar level of mitigation. Transmission from asymptotically infected cases is reported but the contribution of asymptomatic transmission is unclear (presumably small), which shall be further investigated in future studies."}

{"project":"LitCovid-PubTator","denotations":[{"id":"136","span":{"begin":636,"end":644},"obj":"Disease"},{"id":"137","span":{"begin":751,"end":759},"obj":"Disease"}],"attributes":[{"id":"A136","pred":"tao:has_database_id","subj":"136","obj":"MESH:C000657245"},{"id":"A137","pred":"tao:has_database_id","subj":"137","obj":"MESH:D007239"}],"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":"We avoid to fit model to data in conventional way. Instead, we use a simple model framework to discuss what elements might be needed. For instance, in order to achieve a good fitting performance, one obviously needs to include a time-varying report rate (as we reconstructed in Figure 4b), which was caused by the availability of medical supplies, hospital capacities and changing testing/reporting policies. Thus it would be challenging given a relatively short time series, and several other unknown parameters to be estimated. We employ some parameter estimates from the 1918 influenza pandemic, given the similar characteristics of COVID-19 and influenza (most cases are mild) and the similar level of mitigation. Transmission from asymptotically infected cases is reported but the contribution of asymptomatic transmission is unclear (presumably small), which shall be further investigated in future studies."}