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PMC:7224658 / 16549-17707 JSONTXT

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LitCovid-PubTator

Id Subject Object Predicate Lexical cue tao:has_database_id
139 51-59 Disease denotes COVID-19 MESH:C000657245
141 832-840 Disease denotes COVID-19 MESH:C000657245
143 764-772 Disease denotes COVID-19 MESH:C000657245
148 211-219 Disease denotes COVID-19 MESH:C000657245
149 354-362 Disease denotes COVID-19 MESH:C000657245
150 572-580 Disease denotes COVID-19 MESH:C000657245
151 693-701 Disease denotes COVID-19 MESH:C000657245

LitCovid-PD-MONDO

Id Subject Object Predicate Lexical cue mondo_id
T51 51-59 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T52 211-219 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T53 354-362 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T54 572-580 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T55 693-701 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T56 764-772 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T57 832-840 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096

LitCovid-PD-CLO

Id Subject Object Predicate Lexical cue
T66 278-279 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T67 453-460 http://purl.obolibrary.org/obo/CLO_0009985 denotes focused
T68 528-529 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T69 945-952 http://purl.obolibrary.org/obo/CLO_0009985 denotes focused

LitCovid-sentences

Id Subject Object Predicate Lexical cue
T150 0-59 Sentence denotes Types of relationship between regional traffic and COVID-19
T151 60-250 Sentence denotes In Table 3 the analyses in Table 2, Figure 4, and Figure 5 have been classified into types for each region, based on whether the trends in traffic and COVID-19 were increasing or decreasing.
T152 251-382 Sentence denotes Incheon was categorized as a region requiring strong control (Type 1), with increasing trends for both COVID-19 spread and traffic.
T153 383-587 Sentence denotes Gyeonggi and Seoul were categorized as regions in the early stages of focused control or requiring control (Type 2), with increasing traffic but a relatively stable trend for new confirmed COVID-19 cases.
T154 588-709 Sentence denotes The other regions were categorized as stable (Type 3), with increasing traffic but decreasing trends for COVID-19 spread.
T155 710-789 Sentence denotes Table 3 The level of relationship between traffic and COVID-19 in cities, 2020.
T156 790-817 Sentence denotes Trend in 2020 Specific City
T157 818-840 Sentence denotes Level Traffic COVID-19
T158 841-887 Sentence denotes 1 + + (Danger) Strong control required Incheon
T159 888-976 Sentence denotes 2 0 (Caution) Control required, or in the early stage of focused control Gyeonggi, Seoul
T160 977-1116 Sentence denotes 3 − (Stable) Under stable control Daegu, Busan, Gwangju, Daejeon, Ulsan, Sejong, Chungbuk, Chungnam, Jeonbuk, Jeonnam, Gyeongbuk, Gyeongnam
T161 1117-1158 Sentence denotes + = increasing; 0 = same; − = decreasing.