PMC:7060038 / 23126-24681 JSONTXT

{"project":"LitCovid-PubTator","denotations":[{"id":"178","span":{"begin":91,"end":96},"obj":"Disease"},{"id":"179","span":{"begin":100,"end":105},"obj":"Disease"},{"id":"180","span":{"begin":479,"end":484},"obj":"Disease"},{"id":"181","span":{"begin":876,"end":881},"obj":"Disease"},{"id":"182","span":{"begin":894,"end":907},"obj":"Disease"},{"id":"183","span":{"begin":1341,"end":1346},"obj":"Disease"},{"id":"184","span":{"begin":1428,"end":1436},"obj":"Disease"},{"id":"185","span":{"begin":1466,"end":1471},"obj":"Disease"}],"attributes":[{"id":"A178","pred":"tao:has_database_id","subj":"178","obj":"MESH:D005334"},{"id":"A179","pred":"tao:has_database_id","subj":"179","obj":"MESH:D003371"},{"id":"A180","pred":"tao:has_database_id","subj":"180","obj":"MESH:D005334"},{"id":"A181","pred":"tao:has_database_id","subj":"181","obj":"MESH:D005334"},{"id":"A182","pred":"tao:has_database_id","subj":"182","obj":"MESH:D005334"},{"id":"A183","pred":"tao:has_database_id","subj":"183","obj":"MESH:D005334"},{"id":"A184","pred":"tao:has_database_id","subj":"184","obj":"MESH:D007239"},{"id":"A185","pred":"tao:has_database_id","subj":"185","obj":"MESH:D005334"}],"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":"A second crucial uncertainty is the proportion of subclinical cases, which lack detectable fever or cough even after the onset of symptoms. We considered scenarios in which 5%, 25% and 50% of cases are subclinical, representing a best, middle and worst-case scenario, respectively. The middle and worst-case scenarios have predictable and discouraging consequences for the effectiveness of traveller screening, since they render large fractions of the population undetectable by fever screening (Figure 2). Furthermore, subclinical cases who are unaware of their exposure risk are never detectable, by any means. This is manifested as the bright red ‘undetectable’ region which persists well beyond the mean incubation period. For a screening program combining departure and arrival screening, as shown in Figure 2, the greatest contributor to case detection is the departure fever screen. The arrival fever screen is the next greatest contributor, with its value arising from two factors: the potential to detect cases whose symptom onset occurred during travel, and the potential to catch cases missed due to imperfect instrument sensitivity in non-contact infrared thermal scanners used in traveller screening (Table 1). Considering the effectiveness of departure or arrival screening only (Figure 2—figures supplement 1, 2), we see that fever screening is the dominant contributor in each case, but that the risk of missing infected travellers due to undetected fever is substantially higher when there is no redundancy from two successive screenings."}

{"project":"LitCovid-PD-CLO","denotations":[{"id":"T79","span":{"begin":0,"end":1},"obj":"http://purl.obolibrary.org/obo/CLO_0001020"},{"id":"T80","span":{"begin":228,"end":229},"obj":"http://purl.obolibrary.org/obo/CLO_0001020"},{"id":"T81","span":{"begin":731,"end":732},"obj":"http://purl.obolibrary.org/obo/CLO_0001020"},{"id":"T82","span":{"begin":1121,"end":1131},"obj":"http://purl.obolibrary.org/obo/OBI_0000968"}],"text":"A second crucial uncertainty is the proportion of subclinical cases, which lack detectable fever or cough even after the onset of symptoms. We considered scenarios in which 5%, 25% and 50% of cases are subclinical, representing a best, middle and worst-case scenario, respectively. The middle and worst-case scenarios have predictable and discouraging consequences for the effectiveness of traveller screening, since they render large fractions of the population undetectable by fever screening (Figure 2). Furthermore, subclinical cases who are unaware of their exposure risk are never detectable, by any means. This is manifested as the bright red ‘undetectable’ region which persists well beyond the mean incubation period. For a screening program combining departure and arrival screening, as shown in Figure 2, the greatest contributor to case detection is the departure fever screen. The arrival fever screen is the next greatest contributor, with its value arising from two factors: the potential to detect cases whose symptom onset occurred during travel, and the potential to catch cases missed due to imperfect instrument sensitivity in non-contact infrared thermal scanners used in traveller screening (Table 1). Considering the effectiveness of departure or arrival screening only (Figure 2—figures supplement 1, 2), we see that fever screening is the dominant contributor in each case, but that the risk of missing infected travellers due to undetected fever is substantially higher when there is no redundancy from two successive screenings."}

{"project":"LitCovid-PD-HP","denotations":[{"id":"T28","span":{"begin":91,"end":96},"obj":"Phenotype"},{"id":"T29","span":{"begin":100,"end":105},"obj":"Phenotype"},{"id":"T30","span":{"begin":479,"end":484},"obj":"Phenotype"},{"id":"T31","span":{"begin":876,"end":881},"obj":"Phenotype"},{"id":"T32","span":{"begin":902,"end":907},"obj":"Phenotype"},{"id":"T33","span":{"begin":1341,"end":1346},"obj":"Phenotype"},{"id":"T34","span":{"begin":1466,"end":1471},"obj":"Phenotype"}],"attributes":[{"id":"A28","pred":"hp_id","subj":"T28","obj":"http://purl.obolibrary.org/obo/HP_0001945"},{"id":"A29","pred":"hp_id","subj":"T29","obj":"http://purl.obolibrary.org/obo/HP_0012735"},{"id":"A30","pred":"hp_id","subj":"T30","obj":"http://purl.obolibrary.org/obo/HP_0001945"},{"id":"A31","pred":"hp_id","subj":"T31","obj":"http://purl.obolibrary.org/obo/HP_0001945"},{"id":"A32","pred":"hp_id","subj":"T32","obj":"http://purl.obolibrary.org/obo/HP_0001945"},{"id":"A33","pred":"hp_id","subj":"T33","obj":"http://purl.obolibrary.org/obo/HP_0001945"},{"id":"A34","pred":"hp_id","subj":"T34","obj":"http://purl.obolibrary.org/obo/HP_0001945"}],"text":"A second crucial uncertainty is the proportion of subclinical cases, which lack detectable fever or cough even after the onset of symptoms. We considered scenarios in which 5%, 25% and 50% of cases are subclinical, representing a best, middle and worst-case scenario, respectively. The middle and worst-case scenarios have predictable and discouraging consequences for the effectiveness of traveller screening, since they render large fractions of the population undetectable by fever screening (Figure 2). Furthermore, subclinical cases who are unaware of their exposure risk are never detectable, by any means. This is manifested as the bright red ‘undetectable’ region which persists well beyond the mean incubation period. For a screening program combining departure and arrival screening, as shown in Figure 2, the greatest contributor to case detection is the departure fever screen. The arrival fever screen is the next greatest contributor, with its value arising from two factors: the potential to detect cases whose symptom onset occurred during travel, and the potential to catch cases missed due to imperfect instrument sensitivity in non-contact infrared thermal scanners used in traveller screening (Table 1). Considering the effectiveness of departure or arrival screening only (Figure 2—figures supplement 1, 2), we see that fever screening is the dominant contributor in each case, but that the risk of missing infected travellers due to undetected fever is substantially higher when there is no redundancy from two successive screenings."}

{"project":"LitCovid-sentences","denotations":[{"id":"T140","span":{"begin":0,"end":139},"obj":"Sentence"},{"id":"T141","span":{"begin":140,"end":281},"obj":"Sentence"},{"id":"T142","span":{"begin":282,"end":506},"obj":"Sentence"},{"id":"T143","span":{"begin":507,"end":612},"obj":"Sentence"},{"id":"T144","span":{"begin":613,"end":726},"obj":"Sentence"},{"id":"T145","span":{"begin":727,"end":889},"obj":"Sentence"},{"id":"T146","span":{"begin":890,"end":1223},"obj":"Sentence"},{"id":"T147","span":{"begin":1224,"end":1555},"obj":"Sentence"}],"namespaces":[{"prefix":"_base","uri":"http://pubannotation.org/ontology/tao.owl#"}],"text":"A second crucial uncertainty is the proportion of subclinical cases, which lack detectable fever or cough even after the onset of symptoms. We considered scenarios in which 5%, 25% and 50% of cases are subclinical, representing a best, middle and worst-case scenario, respectively. The middle and worst-case scenarios have predictable and discouraging consequences for the effectiveness of traveller screening, since they render large fractions of the population undetectable by fever screening (Figure 2). Furthermore, subclinical cases who are unaware of their exposure risk are never detectable, by any means. This is manifested as the bright red ‘undetectable’ region which persists well beyond the mean incubation period. For a screening program combining departure and arrival screening, as shown in Figure 2, the greatest contributor to case detection is the departure fever screen. The arrival fever screen is the next greatest contributor, with its value arising from two factors: the potential to detect cases whose symptom onset occurred during travel, and the potential to catch cases missed due to imperfect instrument sensitivity in non-contact infrared thermal scanners used in traveller screening (Table 1). Considering the effectiveness of departure or arrival screening only (Figure 2—figures supplement 1, 2), we see that fever screening is the dominant contributor in each case, but that the risk of missing infected travellers due to undetected fever is substantially higher when there is no redundancy from two successive screenings."}