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PMC:7039910 / 1966-26049 JSONTXT

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LitCovid-PubTator

Id Subject Object Predicate Lexical cue tao:has_database_id
48 13-35 Species denotes 2019 Novel coronavirus Tax:2697049
49 37-46 Species denotes 2019-nCoV Tax:2697049
50 47-57 Species denotes SARS-CoV-2 Tax:2697049
51 349-357 Species denotes Patients Tax:9606
52 812-818 Species denotes People Tax:9606
53 92-107 Disease denotes viral pneumonia
54 206-230 Disease denotes Coronavirus Disease 2019 MESH:C000657245
55 232-240 Disease denotes COVID-19 MESH:C000657245
56 398-403 Disease denotes fever MESH:D005334
57 405-410 Disease denotes cough MESH:D003371
58 412-431 Disease denotes shortness of breath MESH:D004417
59 433-444 Disease denotes muscle ache MESH:D063806
60 457-465 Disease denotes headache MESH:D006261
61 467-478 Disease denotes sore throat MESH:D010608
62 480-491 Disease denotes rhinorrhoea
63 493-503 Disease denotes chest pain MESH:D002637
64 505-513 Disease denotes diarrhea MESH:D003967
65 519-525 Disease denotes nausea MESH:D009325
66 530-538 Disease denotes vomiting MESH:D014839
67 712-718 Disease denotes deaths MESH:D003643
72 1195-1205 Disease denotes infections MESH:D007239
73 1224-1232 Disease denotes infected MESH:D007239
74 1370-1378 Disease denotes infected MESH:D007239
75 1801-1809 Disease denotes COVID-19 MESH:C000657245
82 2269-2277 Disease denotes COVID-19 MESH:C000657245
83 2426-2434 Disease denotes zoonotic MESH:D015047
84 2511-2519 Disease denotes COVID-19 MESH:C000657245
85 2715-2724 Disease denotes infection MESH:D007239
86 2824-2832 Disease denotes COVID-19 MESH:C000657245
87 3026-3036 Disease denotes infections MESH:D007239
96 3243-3252 Species denotes 2019-nCoV Tax:2697049
97 3253-3263 Species denotes SARS-CoV-2 Tax:2697049
98 3317-3325 Species denotes SARS-CoV Tax:694009
99 3500-3508 Species denotes patients Tax:9606
100 3358-3378 Disease denotes secondary infections MESH:D060085
101 3445-3449 Disease denotes SARS MESH:D045169
102 3529-3538 Disease denotes infection MESH:D007239
103 3577-3581 Disease denotes SARS MESH:D045169
106 4041-4050 Species denotes 2019-nCoV Tax:2697049
107 4058-4073 Disease denotes CoV-2 infection MESH:C000657245
109 4964-4972 Disease denotes COVID-19 MESH:C000657245
111 5120-5128 Disease denotes COVID-19 MESH:C000657245
114 4667-4677 Disease denotes infections MESH:D007239
115 4739-4747 Disease denotes COVID-19 MESH:C000657245
117 5503-5513 Disease denotes infections MESH:D007239
119 5896-5906 Disease denotes infections MESH:D007239
122 6030-6048 Disease denotes infectious disease MESH:D003141
123 6293-6303 Disease denotes infections MESH:D007239
125 6855-6863 Disease denotes COVID-19 MESH:C000657245
128 6983-6991 Disease denotes COVID-19 MESH:C000657245
129 7096-7104 Disease denotes COVID-19 MESH:C000657245
131 7318-7326 Disease denotes COVID-19 MESH:C000657245
134 7446-7454 Disease denotes COVID-19 MESH:C000657245
135 7559-7567 Disease denotes COVID-19 MESH:C000657245
137 6702-6712 Disease denotes infections MESH:D007239
140 8142-8148 Disease denotes Deaths MESH:D003643
141 8184-8190 Disease denotes Deaths MESH:D003643
144 8002-8008 Disease denotes deaths MESH:D003643
145 8012-8020 Disease denotes COVID-19 MESH:C000657245
147 8252-8258 Disease denotes deaths MESH:D003643
152 7761-7767 Disease denotes deaths MESH:D003643
153 7829-7835 Disease denotes deaths MESH:D003643
154 7853-7859 Disease denotes deaths MESH:D003643
155 7931-7937 Disease denotes deaths MESH:D003643
160 8324-8330 Disease denotes deaths MESH:D003643
161 8447-8453 Disease denotes deaths MESH:D003643
162 8481-8487 Disease denotes deaths MESH:D003643
163 8559-8565 Disease denotes deaths MESH:D003643
170 8662-8670 Disease denotes COVID-19 MESH:C000657245
171 8933-8943 Disease denotes infections MESH:D007239
172 9160-9168 Disease denotes COVID-19 MESH:C000657245
173 9347-9357 Disease denotes infections MESH:D007239
174 9485-9495 Disease denotes infections MESH:D007239
175 9671-9681 Disease denotes infections MESH:D007239
179 9827-9840 Species denotes coronaviruses Tax:11118
180 9765-9773 Disease denotes COVID-19 MESH:C000657245
181 10112-10120 Disease denotes zoonotic MESH:D015047
188 11708-11713 Species denotes human Tax:9606
189 11717-11722 Species denotes human Tax:9606
190 11942-11948 Species denotes people Tax:9606
191 12389-12395 Species denotes people Tax:9606
192 12452-12458 Species denotes people Tax:9606
193 12556-12564 Disease denotes COVID-19 MESH:C000657245
201 13399-13407 Species denotes patients Tax:9606
202 13147-13155 Disease denotes COVID-19 MESH:C000657245
203 13285-13301 Disease denotes pulmonary lesion MESH:D008171
204 13316-13325 Disease denotes pneumonia MESH:D011014
205 13685-13695 Disease denotes infections MESH:D007239
206 13878-13886 Disease denotes COVID-19 MESH:C000657245
207 13887-13896 Disease denotes infection MESH:D007239
215 14155-14163 Species denotes patients Tax:9606
216 14349-14357 Species denotes patients Tax:9606
217 13921-13927 Disease denotes deaths MESH:D003643
218 14099-14108 Disease denotes mortality MESH:D003643
219 14412-14418 Disease denotes deaths MESH:D003643
220 14509-14515 Disease denotes deaths MESH:D003643
221 14601-14607 Disease denotes deaths MESH:D003643
225 15629-15634 Species denotes human Tax:9606
226 15638-15643 Species denotes human Tax:9606
227 15208-15218 Disease denotes infections MESH:D007239
232 16638-16642 Disease denotes SARS MESH:D045169
233 16989-16999 Disease denotes infections MESH:D007239
234 17651-17661 Disease denotes infections MESH:D007239
235 17956-17964 Disease denotes COVID-19 MESH:C000657245
237 18300-18309 Disease denotes infection MESH:D007239
244 18885-18890 Species denotes Ebola Tax:1570291
245 18544-18562 Disease denotes infectious disease MESH:D003141
246 18648-18656 Disease denotes COVID-19 MESH:C000657245
247 18734-18752 Disease denotes infectious disease MESH:D003141
248 18845-18864 Disease denotes infectious diseases MESH:D003141
249 18895-18899 Disease denotes SARS MESH:D045169
257 19697-19698 Gene denotes N Gene:43740575
258 19712-19713 Gene denotes N Gene:43740575
259 19342-19347 Disease denotes death MESH:D003643
260 19391-19397 Disease denotes deaths MESH:D003643
261 19523-19531 Disease denotes infected MESH:D007239
262 19788-19796 Disease denotes infected MESH:D007239
263 20633-20642 Disease denotes infection MESH:D007239
269 21631-21639 Species denotes patients Tax:9606
270 21754-21762 Species denotes patients Tax:9606
271 21266-21274 Disease denotes zoonotic MESH:D015047
272 21530-21538 Disease denotes COVID-19 MESH:C000657245
273 21921-21931 Disease denotes infections MESH:D007239
281 22391-22399 Species denotes SARS-CoV Tax:694009
282 22431-22439 Species denotes patients Tax:9606
283 22315-22325 Disease denotes infections MESH:D007239
284 22342-22347 Disease denotes fever MESH:D005334
285 22351-22359 Disease denotes COVID-19 MESH:C000657245
286 22404-22422 Disease denotes MERS-CoV infection MESH:D018352
287 22519-22524 Disease denotes fever MESH:D005334
290 23462-23473 Chemical denotes Huoshenshan
291 23512-23523 Chemical denotes Leishenshan

LitCovid-PD-FMA-UBERON

Id Subject Object Predicate Lexical cue fma_id
T1 433-439 Body_part denotes muscle http://purl.org/sig/ont/fma/fma32558
T2 472-478 Body_part denotes throat http://purl.org/sig/ont/fma/fma228738
T3 493-498 Body_part denotes chest http://purl.org/sig/ont/fma/fma9576
T4 2551-2557 Body_part denotes genome http://purl.org/sig/ont/fma/fma84116
T5 9572-9576 Body_part denotes hand http://purl.org/sig/ont/fma/fma9712
T6 13082-13087 Body_part denotes chest http://purl.org/sig/ont/fma/fma9576

LitCovid-PD-UBERON

Id Subject Object Predicate Lexical cue uberon_id
T1 472-478 Body_part denotes throat http://purl.obolibrary.org/obo/UBERON_0000341
T2 493-498 Body_part denotes chest http://purl.obolibrary.org/obo/UBERON_0001443
T3 9572-9576 Body_part denotes hand http://purl.obolibrary.org/obo/UBERON_0002398
T4 13082-13087 Body_part denotes chest http://purl.obolibrary.org/obo/UBERON_0001443
T5 19234-19239 Body_part denotes scale http://purl.obolibrary.org/obo/UBERON_0002542

LitCovid-PD-HP

Id Subject Object Predicate Lexical cue hp_id
T2 98-107 Phenotype denotes pneumonia http://purl.obolibrary.org/obo/HP_0002090
T3 398-403 Phenotype denotes fever http://purl.obolibrary.org/obo/HP_0001945
T4 405-410 Phenotype denotes cough http://purl.obolibrary.org/obo/HP_0012735
T5 412-431 Phenotype denotes shortness of breath http://purl.obolibrary.org/obo/HP_0002098
T6 433-444 Phenotype denotes muscle ache http://purl.obolibrary.org/obo/HP_0003326
T7 457-465 Phenotype denotes headache http://purl.obolibrary.org/obo/HP_0002315
T8 467-478 Phenotype denotes sore throat http://purl.obolibrary.org/obo/HP_0033050
T9 493-503 Phenotype denotes chest pain http://purl.obolibrary.org/obo/HP_0100749
T10 505-513 Phenotype denotes diarrhea http://purl.obolibrary.org/obo/HP_0002014
T11 519-525 Phenotype denotes nausea http://purl.obolibrary.org/obo/HP_0002018
T12 13316-13325 Phenotype denotes pneumonia http://purl.obolibrary.org/obo/HP_0002090
T13 22342-22347 Phenotype denotes fever http://purl.obolibrary.org/obo/HP_0001945
T14 22519-22524 Phenotype denotes fever http://purl.obolibrary.org/obo/HP_0001945

LitCovid-PD-MONDO

Id Subject Object Predicate Lexical cue mondo_id
T15 47-55 Disease denotes SARS-CoV http://purl.obolibrary.org/obo/MONDO_0005091
T16 92-107 Disease denotes viral pneumonia http://purl.obolibrary.org/obo/MONDO_0006012
T17 98-107 Disease denotes pneumonia http://purl.obolibrary.org/obo/MONDO_0005249
T18 206-230 Disease denotes Coronavirus Disease 2019 http://purl.obolibrary.org/obo/MONDO_0100096
T19 232-240 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T20 467-478 Disease denotes sore throat http://purl.obolibrary.org/obo/MONDO_0002258
T21 505-513 Disease denotes diarrhea http://purl.obolibrary.org/obo/MONDO_0001673
T22 1195-1205 Disease denotes infections http://purl.obolibrary.org/obo/MONDO_0005550
T23 1801-1809 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T24 2269-2277 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T25 2511-2519 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T26 2824-2832 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T27 3026-3036 Disease denotes infections http://purl.obolibrary.org/obo/MONDO_0005550
T28 3253-3261 Disease denotes SARS-CoV http://purl.obolibrary.org/obo/MONDO_0005091
T29 3317-3321 Disease denotes SARS http://purl.obolibrary.org/obo/MONDO_0005091
T30 3368-3378 Disease denotes infections http://purl.obolibrary.org/obo/MONDO_0005550
T31 3445-3449 Disease denotes SARS http://purl.obolibrary.org/obo/MONDO_0005091
T32 3529-3538 Disease denotes infection http://purl.obolibrary.org/obo/MONDO_0005550
T33 3577-3581 Disease denotes SARS http://purl.obolibrary.org/obo/MONDO_0005091
T34 4053-4061 Disease denotes SARS-CoV http://purl.obolibrary.org/obo/MONDO_0005091
T35 4064-4073 Disease denotes infection http://purl.obolibrary.org/obo/MONDO_0005550
T36 4667-4677 Disease denotes infections http://purl.obolibrary.org/obo/MONDO_0005550
T37 4739-4747 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T38 4964-4972 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T39 5120-5128 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T40 5503-5516 Disease denotes infections in http://purl.obolibrary.org/obo/MONDO_0005550
T41 5896-5906 Disease denotes infections http://purl.obolibrary.org/obo/MONDO_0005550
T42 6030-6048 Disease denotes infectious disease http://purl.obolibrary.org/obo/MONDO_0005550
T43 6293-6303 Disease denotes infections http://purl.obolibrary.org/obo/MONDO_0005550
T44 6702-6712 Disease denotes infections http://purl.obolibrary.org/obo/MONDO_0005550
T45 6855-6863 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T46 6983-6991 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T47 7096-7104 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T48 7203-7213 Disease denotes infectious http://purl.obolibrary.org/obo/MONDO_0005550
T49 7318-7326 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T50 7446-7454 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T51 7559-7567 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T52 7666-7676 Disease denotes infectious http://purl.obolibrary.org/obo/MONDO_0005550
T53 8012-8020 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T54 8662-8670 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T55 8933-8943 Disease denotes infections http://purl.obolibrary.org/obo/MONDO_0005550
T56 8978-8988 Disease denotes Infectious http://purl.obolibrary.org/obo/MONDO_0005550
T57 9160-9168 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T58 9347-9357 Disease denotes infections http://purl.obolibrary.org/obo/MONDO_0005550
T59 9485-9495 Disease denotes infections http://purl.obolibrary.org/obo/MONDO_0005550
T60 9671-9681 Disease denotes infections http://purl.obolibrary.org/obo/MONDO_0005550
T61 9765-9773 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T62 12556-12564 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T63 13147-13155 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T64 13316-13325 Disease denotes pneumonia http://purl.obolibrary.org/obo/MONDO_0005249
T65 13685-13695 Disease denotes infections http://purl.obolibrary.org/obo/MONDO_0005550
T66 13878-13886 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T67 13887-13896 Disease denotes infection http://purl.obolibrary.org/obo/MONDO_0005550
T68 15208-15218 Disease denotes infections http://purl.obolibrary.org/obo/MONDO_0005550
T69 16638-16642 Disease denotes SARS http://purl.obolibrary.org/obo/MONDO_0005091
T70 16989-16999 Disease denotes infections http://purl.obolibrary.org/obo/MONDO_0005550
T71 17651-17664 Disease denotes infections in http://purl.obolibrary.org/obo/MONDO_0005550
T72 17956-17964 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T73 18300-18309 Disease denotes infection http://purl.obolibrary.org/obo/MONDO_0005550
T74 18544-18562 Disease denotes infectious disease http://purl.obolibrary.org/obo/MONDO_0005550
T75 18648-18656 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T76 18734-18752 Disease denotes infectious disease http://purl.obolibrary.org/obo/MONDO_0005550
T77 18845-18855 Disease denotes infectious http://purl.obolibrary.org/obo/MONDO_0005550
T78 18885-18890 Disease denotes Ebola http://purl.obolibrary.org/obo/MONDO_0005737
T79 19544-19554 Disease denotes infectious http://purl.obolibrary.org/obo/MONDO_0005550
T80 19557-19567 Disease denotes infectious http://purl.obolibrary.org/obo/MONDO_0005550
T81 20543-20547 Disease denotes SI∕N http://purl.obolibrary.org/obo/MONDO_0024475
T82 20555-20559 Disease denotes SI∕N http://purl.obolibrary.org/obo/MONDO_0024475
T83 20633-20642 Disease denotes infection http://purl.obolibrary.org/obo/MONDO_0005550
T84 20757-20767 Disease denotes infectious http://purl.obolibrary.org/obo/MONDO_0005550
T85 21530-21538 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T86 21921-21931 Disease denotes infections http://purl.obolibrary.org/obo/MONDO_0005550
T87 22315-22325 Disease denotes infections http://purl.obolibrary.org/obo/MONDO_0005550
T88 22351-22359 Disease denotes COVID-19 http://purl.obolibrary.org/obo/MONDO_0100096
T89 22391-22399 Disease denotes SARS-CoV http://purl.obolibrary.org/obo/MONDO_0005091

LitCovid-PD-CLO

Id Subject Object Predicate Lexical cue
T2 59-62 http://purl.obolibrary.org/obo/CLO_0051582 denotes has
T3 161-173 http://purl.obolibrary.org/obo/OBI_0000245 denotes Organization
T4 184-187 http://purl.obolibrary.org/obo/CLO_0051582 denotes has
T5 433-439 http://purl.obolibrary.org/obo/UBERON_0001630 denotes muscle
T6 433-439 http://purl.obolibrary.org/obo/UBERON_0005090 denotes muscle
T7 433-439 http://www.ebi.ac.uk/efo/EFO_0000801 denotes muscle
T8 433-439 http://www.ebi.ac.uk/efo/EFO_0001949 denotes muscle
T9 493-498 http://www.ebi.ac.uk/efo/EFO_0000965 denotes chest
T10 567-568 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T11 685-686 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T12 1009-1012 http://purl.obolibrary.org/obo/CLO_0051582 denotes has
T13 1033-1034 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T14 1147-1148 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T15 1149-1154 http://purl.obolibrary.org/obo/NCBITaxon_10239 denotes virus
T16 1523-1528 http://purl.obolibrary.org/obo/CLO_0008697 denotes R > 1
T17 1523-1528 http://purl.obolibrary.org/obo/CLO_0052381 denotes R > 1
T18 1633-1638 http://purl.obolibrary.org/obo/CLO_0008697 denotes R < 1
T19 1633-1638 http://purl.obolibrary.org/obo/CLO_0052381 denotes R < 1
T20 2279-2280 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T21 2460-2462 http://purl.obolibrary.org/obo/CLO_0053733 denotes 11
T22 2773-2782 http://purl.obolibrary.org/obo/CLO_0001658 denotes activated
T23 3194-3197 http://purl.obolibrary.org/obo/CLO_0051582 denotes has
T24 3264-3267 http://purl.obolibrary.org/obo/CLO_0051582 denotes has
T25 3606-3608 http://purl.obolibrary.org/obo/CLO_0001022 denotes Li
T26 3606-3608 http://purl.obolibrary.org/obo/CLO_0007314 denotes Li
T27 3751-3752 http://purl.obolibrary.org/obo/CLO_0001020 denotes A
T28 5433-5434 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T29 6476-6477 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T30 8847-8848 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T31 9551-9552 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T32 9913-9918 http://purl.obolibrary.org/obo/NCBITaxon_10239 denotes virus
T33 10015-10016 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T34 10173-10174 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T35 10725-10730 http://purl.obolibrary.org/obo/NCBITaxon_10239 denotes virus
T36 10961-10964 http://purl.obolibrary.org/obo/CLO_0051582 denotes has
T37 10971-10972 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T38 11144-11149 http://purl.obolibrary.org/obo/NCBITaxon_10239 denotes virus
T39 11281-11284 http://purl.obolibrary.org/obo/CLO_0051582 denotes has
T40 11384-11387 http://purl.obolibrary.org/obo/CLO_0051582 denotes has
T41 11444-11457 http://purl.obolibrary.org/obo/OBI_0000245 denotes organizations
T42 11708-11713 http://purl.obolibrary.org/obo/NCBITaxon_9606 denotes human
T43 11717-11722 http://purl.obolibrary.org/obo/NCBITaxon_9606 denotes human
T44 11835-11836 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T45 12850-12851 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T46 13082-13087 http://www.ebi.ac.uk/efo/EFO_0000965 denotes chest
T47 13195-13198 http://purl.obolibrary.org/obo/CLO_0051582 denotes has
T48 13389-13390 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T49 13451-13452 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T50 13520-13527 http://purl.obolibrary.org/obo/UBERON_0000473 denotes testing
T51 13651-13652 http://purl.obolibrary.org/obo/CLO_0001020 denotes A
T52 13815-13818 http://purl.obolibrary.org/obo/CLO_0051582 denotes has
T53 14031-14033 http://purl.obolibrary.org/obo/CLO_0053733 denotes 11
T54 14247-14252 http://purl.obolibrary.org/obo/NCBITaxon_10239 denotes virus
T55 14375-14376 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T56 14530-14531 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T57 15456-15459 http://purl.obolibrary.org/obo/CLO_0051582 denotes has
T58 15485-15486 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T59 15629-15634 http://purl.obolibrary.org/obo/NCBITaxon_9606 denotes human
T60 15638-15643 http://purl.obolibrary.org/obo/NCBITaxon_9606 denotes human
T61 16068-16071 http://purl.obolibrary.org/obo/CLO_0051582 denotes has
T62 16134-16135 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T63 16779-16780 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T64 16861-16862 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T65 17037-17044 http://purl.obolibrary.org/obo/NCBITaxon_33208 denotes animals
T66 17081-17082 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T67 17606-17607 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T68 18492-18497 http://purl.obolibrary.org/obo/NCBITaxon_10239 denotes virus
T69 18693-18694 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T70 18760-18763 http://purl.obolibrary.org/obo/CLO_0051582 denotes has
T71 18764-18765 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T72 18794-18797 http://purl.obolibrary.org/obo/CLO_0051582 denotes has
T73 18826-18827 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T74 19177-19184 http://purl.obolibrary.org/obo/NCBITaxon_33208 denotes animals
T75 19809-19810 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T76 19862-19863 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T77 20546-20550 http://purl.obolibrary.org/obo/CLO_0008147 denotes N,dE
T78 21202-21204 http://purl.obolibrary.org/obo/CLO_0053733 denotes 11
T79 21320-21322 http://purl.obolibrary.org/obo/CLO_0008935 denotes s9
T80 21470-21472 http://purl.obolibrary.org/obo/CLO_0001022 denotes Li
T81 21470-21472 http://purl.obolibrary.org/obo/CLO_0007314 denotes Li
T82 21799-21801 http://purl.obolibrary.org/obo/CLO_0050510 denotes 18
T83 21827-21829 http://purl.obolibrary.org/obo/CLO_0050510 denotes 18
T84 21867-21869 http://purl.obolibrary.org/obo/CLO_0008935 denotes s9
T85 21938-21940 http://purl.obolibrary.org/obo/CLO_0050510 denotes 18
T86 22285-22286 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T87 22501-22508 http://purl.obolibrary.org/obo/CLO_0009985 denotes focused
T88 22771-22772 http://purl.obolibrary.org/obo/CLO_0001020 denotes a
T89 22873-22875 http://purl.obolibrary.org/obo/CLO_0008935 denotes s9
T90 23223-23225 http://purl.obolibrary.org/obo/CLO_0008935 denotes s9
T91 23712-23714 http://purl.obolibrary.org/obo/CLO_0008935 denotes s9

LitCovid-PD-CHEBI

Id Subject Object Predicate Lexical cue chebi_id
T1 840-843 Chemical denotes NHC http://purl.obolibrary.org/obo/CHEBI_51369
T2 2628-2636 Chemical denotes reagents http://purl.obolibrary.org/obo/CHEBI_33893
T3 3606-3608 Chemical denotes Li http://purl.obolibrary.org/obo/CHEBI_30145
T4 12962-12965 Chemical denotes NHC http://purl.obolibrary.org/obo/CHEBI_51369
T5 14893-14896 Chemical denotes NHC http://purl.obolibrary.org/obo/CHEBI_51369
T6 17255-17258 Chemical denotes NHC http://purl.obolibrary.org/obo/CHEBI_51369
T7 20269-20273 Chemical denotes beta http://purl.obolibrary.org/obo/CHEBI_10545
T8 20324-20328 Chemical denotes beta http://purl.obolibrary.org/obo/CHEBI_10545
T9 20411-20416 Chemical denotes gamma http://purl.obolibrary.org/obo/CHEBI_30212
T10 20458-20463 Chemical denotes gamma http://purl.obolibrary.org/obo/CHEBI_30212
T11 20475-20479 Chemical denotes beta http://purl.obolibrary.org/obo/CHEBI_10545
T12 20501-20506 Chemical denotes gamma http://purl.obolibrary.org/obo/CHEBI_30212
T13 20543-20545 Chemical denotes SI http://purl.obolibrary.org/obo/CHEBI_90326
T14 20555-20557 Chemical denotes SI http://purl.obolibrary.org/obo/CHEBI_90326
T15 21470-21472 Chemical denotes Li http://purl.obolibrary.org/obo/CHEBI_30145

LitCovid-PD-GO-BP

Id Subject Object Predicate Lexical cue
T1 1090-1102 http://purl.obolibrary.org/obo/GO_0000003 denotes reproduction
T2 1291-1303 http://purl.obolibrary.org/obo/GO_0000003 denotes reproduction
T3 1414-1426 http://purl.obolibrary.org/obo/GO_0000003 denotes reproduction
T4 2571-2592 http://purl.obolibrary.org/obo/GO_0001171 denotes reverse transcription
T5 2579-2592 http://purl.obolibrary.org/obo/GO_0006351 denotes transcription
T6 11879-11889 http://purl.obolibrary.org/obo/GO_0006810 denotes transports
T7 11927-11937 http://purl.obolibrary.org/obo/GO_0006810 denotes transports

LitCovid-sentences

Id Subject Object Predicate Lexical cue
T15 0-12 Sentence denotes Introduction
T16 13-147 Sentence denotes 2019 Novel coronavirus (2019-nCoV/SARS-CoV-2) has given rise to an outbreak of viral pneumonia in Wuhan, China since December 20191,2.
T17 148-243 Sentence denotes World Health Organization (WHO) now has named the disease Coronavirus Disease 2019 (COVID-19)3.
T18 244-348 Sentence denotes Most cases from the initial cluster had an epidemiological link to the Huanan Seafood Wholesale Market4.
T19 349-542 Sentence denotes Patients have clinical manifestations, including fever, cough, shortness of breath, muscle ache, confusion, headache, sore throat, rhinorrhoea, chest pain, diarrhea, and nausea and vomiting5,6.
T20 543-864 Sentence denotes As of 17 February 2020, a cumulative total of 72,436 confirmed cases (including 11,741 currently severe cases), 6242 currently suspect cases, a cumulative total of 1868 deaths and 12,552 cases discharged from hospital were reported by National Health Commission of the People’s Republic of China (NHC) in mainland China7.
T21 865-1085 Sentence denotes The significant increases in the number of confirmed cases in China and abroad led to the announcement made by WHO on 30 January that the event has already constituted a Public Health Emergency of International Concern8.
T22 1086-1443 Sentence denotes The reproduction number, R, measures the transmissibility of a virus, representing the average number of new infections generated by each infected person, the initial constant of which is called the basic reproduction number, R09, and the actual average number of secondary cases per infected case at time t is called effective reproduction number, Rt10–12.
T23 1444-1522 Sentence denotes Rt shows time-dependent variation with the implementation of control measures.
T24 1523-1739 Sentence denotes R > 1 indicates that the outbreak is self-sustaining unless effective control measures are implemented, while R < 1 indicates that the number of new cases decreases over time and, eventually, the outbreak will stop9.
T25 1740-1881 Sentence denotes Over the past month, several groups reported estimated R0 of COVID-19 and generated valuable prediction for the early phase of this outbreak.
T26 1882-2037 Sentence denotes In particular, Imai et al.9 provided the first estimation, using R0 of 2.6 and based on the number of cases in China and those detected in other countries.
T27 2038-2104 Sentence denotes Other authors estimated R0 to be 3.813, 6.4714, 2.215, and 2.6816.
T28 2105-2237 Sentence denotes These predictions were very alerting and suggestions have been made for very strict public health measures to contain the epidemics.
T29 2238-2337 Sentence denotes In response to the outbreak of COVID-19, a series of prompt public health measures have been taken.
T30 2338-2456 Sentence denotes On 1 January, the Huanan Seafood Wholesale Market was closed in the hope of eliminating zoonotic source of the virus5.
T31 2457-2727 Sentence denotes On 11 January, upon isolation of the viral strain for COVID-19 and establishment of its whole-genome sequences17, reverse transcription-polymerase chain reaction (RT-PCR) reagents were developed and provided to Wuhan, which ensured the fast ascertainment of infection15.
T32 2728-2844 Sentence denotes On 21 January, Emergency Response System was activated to better provide ongoing support to the COVID-19 response18.
T33 2845-2988 Sentence denotes Ever since the outbreak, the work of intensive surveillance, epidemiological investigations, and isolation of suspect cases gradually improved.
T34 2989-3108 Sentence denotes Those having had close contacts with infections were asked to receive medical observation and quarantine for 14 days19.
T35 3109-3238 Sentence denotes Travel from and to Wuhan City as well as other medium-sized cities in Hubei Province has been restricted since 23 January 202020.
T36 3239-3330 Sentence denotes The 2019-nCoV/SARS-CoV-2 has at least 79.5% similarity in genetic sequence to SARS-CoV5,17.
T37 3331-3479 Sentence denotes Riley21 estimated that 2.7 secondary infections were generated per case on average (R0 = 2.7) at the start of the SARS epidemic without controlling.
T38 3480-3602 Sentence denotes After isolating the patients and controlling the infection by the authority, the value of Rt for SARS decreased to 0.2522.
T39 3603-3750 Sentence denotes As Li et al.15 mentioned, it is possible that subsequent control measures in Wuhan, and elsewhere in mainland China, have reduced transmissibility.
T40 3751-3947 Sentence denotes A new estimation of the epidemic dynamics taking the unprecedentedly strict prevention and control measures in China into consideration is required to better guide the future prevention decisions.
T41 3948-4183 Sentence denotes In this article, we intended to make phase-adjusted estimation of the epidemic trend for the 2019-nCoV / SARS-CoV-2 infection transmission in Wuhan, China under two assumptions of Rt (maintaining high >1 or gradually decreasing to <1).
T42 4184-4432 Sentence denotes We hope to depict two types of epidemic dynamics to provide potential evaluation standard for the effects of current prevention and control measures, and to provide theoretical basis for future prevention decisions of the current epidemic in China.
T43 4434-4441 Sentence denotes Results
T44 4443-4558 Sentence denotes Estimation of the epidemic trend assuming that the prevention and control measures are insufficient in Wuhan, China
T45 4559-4709 Sentence denotes Assuming the epidemic continues to develop with R0 = 1.9, 2.6, and 3.19 from 1 December 2019, the number of infections will continue to rise (Fig. 1).
T46 4710-4849 Sentence denotes By the end of February 2020, COVID-19 cases would be 11,044, 70,258, and 227,989 in Wuhan, China with R0 = 1.9, 2.6, and 3.1, respectively.
T47 4850-4928 Sentence denotes Detailed calculation process is included in the Materials and methods section.
T48 4929-5049 Sentence denotes Fig. 1 Estimation of the number of COVID-19 cases in Wuhan, China (December 2019–February 2020, R0 = 1.9, 2.6, and 3.1).
T49 5050-5222 Sentence denotes In all, 11,044, 70,258, and 227,989 represent the estimated number of COVID-19 cases by the end of February 2020 in Wuhan, China, with R0 = 1.9, 2.6, and 3.1, respectively.
T50 5224-5337 Sentence denotes Estimation of the epidemic trend assuming that the prevention and control measures are sufficient in Wuhan, China
T51 5338-5388 Sentence denotes The first phase (1 December 2019–23 January 2020):
T52 5389-5488 Sentence denotes It was the early phase of the epidemic when a few prevention and control measures were implemented.
T53 5489-5592 Sentence denotes The number of infections in Wuhan, China reached 17,656–25,875 by the end of this phase with R0 as 3.1.
T54 5593-5644 Sentence denotes The second phase (24 January 2020–2 February 2020):
T55 5645-5771 Sentence denotes From 23 January 2020 on, public transportations to and from Wuhan, as well as public transportation within Wuhan were stopped.
T56 5772-5881 Sentence denotes While gathering events inside Wuhan was banned, quarantine and isolation were gradually established in Wuhan.
T57 5882-5973 Sentence denotes The number of infections was 32,061–46,905 by the end of this phase as Rt decreased to 2.6.
T58 5974-6025 Sentence denotes The third phase (3 February 2020–15 February 2020):
T59 6026-6203 Sentence denotes New infectious disease hospitals and mobile cabin hospitals came into service and many medical and public health teams from other provinces and cities in China arrived in Wuhan.
T60 6204-6278 Sentence denotes The quarantine and isolation at the community level were further enhanced.
T61 6279-6373 Sentence denotes The number of infections would reach 53,070–77,390 if Rt could be reduced sequentially to 1.9.
T62 6374-6418 Sentence denotes The fourth phase (from 15 February 2020 on):
T63 6419-6519 Sentence denotes All of the most restrict public health measures may need a longest incubation period to take effect.
T64 6520-6687 Sentence denotes If Rt could be gradually reduced to 0.9 or 0.5 in the fourth phase, the epidemic peaks and inflection points might occur in Wuhan, China on 23 February or 19 February.
T65 6688-6794 Sentence denotes The number of infections would be 58,077–84,520 or 55,869–81,393 with Rt = 0.9 or 0.5, respectively (Figs.
T66 6795-6804 Sentence denotes 2 and 3).
T67 6805-6927 Sentence denotes Fig. 2 Phase-adjusted estimation of the number of COVID-19 cases in Wuhan, China (1 December 2019–30 April 2020, E = 20I).
T68 6928-7267 Sentence denotes In all, 55,869 represents the estimated peak number of COVID-19 cases on 19 February 2020 in Wuhan, China with R0 = 0.5; 58,077 represents the estimated peak number of COVID-19 cases on 23 February 2020 in Wuhan, China with R0 = 0.9; E: number of exposed cases; I: number of infectious cases; E was assumed to be 20 times of I at baseline.
T69 7268-7390 Sentence denotes Fig. 3 Phase-adjusted estimation of the number of COVID-19 cases in Wuhan, China (1 December 2019–30 April 2020, E = 30I).
T70 7391-7730 Sentence denotes In all, 81,393 represents the estimated peak number of COVID-19 cases on 19 February 2020 in Wuhan, China with R0 = 0.5; 84,520 represents the estimated peak number of COVID-19 cases on 23 February 2020 in Wuhan, China with R0 = 0.9; E: number of exposed cases; I: number of infectious cases; E was assumed to be 30 times of I at baseline.
T71 7731-7906 Sentence denotes Our model predicted 2323–3381 deaths in Wuhan, China when we assumed Rt as 0.9 and the percent of deaths as 4%; 2235–3256 deaths when we assumed Rt as 0.5 at the fourth phase.
T72 7907-7968 Sentence denotes An average of 2279–3318 deaths were also estimated (Table 1).
T73 7969-8061 Sentence denotes Table 1 Estimating the number of deaths of COVID-19 cases in Wuhan, China (Rt = 0.9 or 0.5).
T74 8062-8087 Sentence denotes Rt = 0.9 Rt = 0.5 Average
T75 8088-8141 Sentence denotes Total cases 58,077–84,520 55,869–81,393 56,973–82,957
T76 8142-8183 Sentence denotes Deaths (4%) 2323–3381 2235–3256 2279–3318
T77 8184-8226 Sentence denotes Deaths (10%) 5808–8452 5587–8139 5697–8296
T78 8227-8278 Sentence denotes The estimated percent of deaths is about 4–10%6,24.
T79 8279-8534 Sentence denotes When we assumed Rt as 0.9 and the percent of deaths 10% based on calculation of case fatality rate (CFR) at early stage of the epidemic6, our model predicted 5808–8452 deaths in Wuhan, China; 5587–8139 deaths when we assumed Rt as 0.5 at the fourth phase.
T80 8535-8586 Sentence denotes An average of 5697–8296 deaths were also estimated.
T81 8588-8598 Sentence denotes Discussion
T82 8599-8905 Sentence denotes Estimations of the transmission risk and the epidemic trend of COVID-19 are of great importance because these can arouse the vigilance of the policy makers, health professionals, and the whole society so that enough resources would be mobilized in a speedy and efficient way for both control and treatment.
T83 8906-9185 Sentence denotes We estimated the number of infections using SEIR (Susceptible, Exposed, Infectious, and Removed) model under two assumptions of Rt (Rt maintaining to be >1 or Rt gradually decreasing to <1) in the purpose of depicting various possible epidemic trends of COVID-19 in Wuhan, China.
T84 9186-9387 Sentence denotes Two estimations provide an approach for evaluating the sufficiency of the current measures taken in China, depending on whether or not the peak of the number of infections would occur in February 2020.
T85 9388-9558 Sentence denotes Assuming the current control measures were ineffective and insufficient, the estimated number of infections would continue to increase throughout February without a peak.
T86 9559-9725 Sentence denotes On the other hand, assuming the current control measures were effective and sufficient, the estimated number of infections would reach the peak in late February 2020.
T87 9726-9841 Sentence denotes According to Read’s research13, R0 for COVID-19 outbreak is much higher compared with other emergent coronaviruses.
T88 9842-9919 Sentence denotes It might be very difficult to contain or control the spreading of this virus.
T89 9920-10186 Sentence denotes If the prevention and control measures were not sufficient or some new factors occurred (e.g., a large proportion of cases with mild or none symptoms existed in the community; there were more zoonotic sources), the epidemic might continue to develop at a high speed.
T90 10187-10432 Sentence denotes Therefore, we depicted first the epidemic dynamics of the relatively unsatisfying circumstance based on the R0 estimated before the unprecedented efforts of China in the containment of the epidemics occurred and the newest documented parameters.
T91 10433-10628 Sentence denotes The curve continued to go up throughout February without any indication of dropping, indicating the need for further enhancement of public health measures for containment of the current outbreak.
T92 10629-11259 Sentence denotes However, as mentioned by WHO in the statement on 30 January, “it is still possible to interrupt virus spread, provided that countries put in place strong measures to detect disease early, isolate and treat cases, trace contacts, and promote social-distancing measures commensurate with the risk.”8 Responding to the outbreak, China has taken a series of unprecedentedly strict measures regardless of economic losses, including daily contact with WHO and comprehensive multi-sectoral approaches to fight against the virus and prevent further spread, showing the sense of responsibility of China to its citizens and the whole world.
T93 11260-11371 Sentence denotes Epidemic information has been released in an open, transparent, responsible, and timely manner home and abroad.
T94 11372-11458 Sentence denotes Cooperation has been established with other countries and international organizations.
T95 11459-11546 Sentence denotes These measures have won full recognition of the international community, including WHO.
T96 11547-11698 Sentence denotes Specifically in Wuhan, in the early phase from beginning of December 2019 to 23 January 2020, there was no limitation of population flow and gathering.
T97 11699-11831 Sentence denotes When the human-to-human transmission was confirmed, an important decision was made to isolate Wuhan from other parts of the country.
T98 11832-11995 Sentence denotes As a result, since 24 January 2020, all public transports from and to Wuhan, as well as public transports and people’s gathering events within Wuhan, were stopped.
T99 11996-12343 Sentence denotes Since 2 February 2020, strict public health measures were taken to prevent population flow among distinct communities, whereas since 9 February 2020, public health interventions including quarantine of each building in the urban area and each village in the rural area were implemented in order to block the transmission chain among the household.
T100 12344-12574 Sentence denotes Therefore, strong efforts of authorities and people in Wuhan with the support of the central government and people from all over China, as well as the WHO and the international society, may have gradually braked COVID-19 outbreak.
T101 12575-12674 Sentence denotes Rt is therefore assumed to decrease gradually from 3.1 to 0.5 in Wuhan, China in the current study.
T102 12675-12769 Sentence denotes The trend of the estimated cases is in accordance with the trend of currently confirmed cases.
T103 12770-12948 Sentence denotes The relatively big difference in number may be due to the possible existence of a large number of mild and asymptomatic cases and the imperfection of current diagnostic measures.
T104 12949-13156 Sentence denotes According to NHC, before 12 February 2020, the confirmed cases were diagnosed according to contact history, clinical manifestations, chest X-ray, or computer-assisted tomography (CT) and RT-PCR for COVID-19.
T105 13157-13410 Sentence denotes Since 12 February 2020, the diagnosis has been mainly based on contact history, clinical manifestation, and imaging evidence of pulmonary lesion suggestive of pneumonia, while viral detection with RT-PCR is still being performed in a part of patients23.
T106 13411-13650 Sentence denotes After the diagnosis method was changed, a large number of cases that were previously missed and piled up for testing were reported in Wuhan, which greatly increased the number of existing cases and made it approaching our estimated number.
T107 13651-13747 Sentence denotes A peak of the estimated number of infections would occur in late February under this assumption.
T108 13748-13906 Sentence denotes If the peak does occur in February, the very strong measures China has taken may have already received success in controlling the COVID-19 infection in Wuhan.
T109 13907-13997 Sentence denotes The number of deaths in the current study was estimated based on previously reported CFRs.
T110 13998-14093 Sentence denotes Chen et al.6 calculated it to be 11% based on 99 cases at the very early stage of the outbreak.
T111 14094-14268 Sentence denotes This mortality rate might not be representative of the whole patients’ population due to the relatively small sample size and scarce knowledge about the virus at early stage.
T112 14269-14397 Sentence denotes More recently, Yang et al.24 estimated the overall adjusted CFR among confirmed patients to be 3.06% with a sample size of 8866.
T113 14398-14476 Sentence denotes The number of deaths estimated accordingly might be more close to the reality.
T114 14477-14579 Sentence denotes Our estimation of the number of deaths only provides a possible range based on currently reported CFR.
T115 14580-14754 Sentence denotes The actual number of deaths might be lower with more mild and asymptomatic cases being detected and the improvement of clinical care and treatment as the epidemic progresses.
T116 14755-14910 Sentence denotes Hubei Province, of which Wuhan is the capital city, accounts for more than 80% of newly confirmed cases all over the country according to NHC daily report.
T117 14911-14989 Sentence denotes The current epidemic trend in Hubei Province is similar to that in Wuhan City.
T118 14990-15307 Sentence denotes Considering the high number of confirmed cases in the province, the currently strict measures should be continuously implemented both in Wuhan and other cities in Hubei Province no matter whether the peak of number of infections would occur or not, in order to reduce Rt to an ideal level and to control the epidemic.
T119 15308-15591 Sentence denotes Owing to the timely transportation restriction in Hubei Province and other measures, the number of newly confirmed cases remains relatively low and has decreased for 13 days in a row in other provinces, autonomous regions, and municipalities in mainland China outside Hubei Province.
T120 15592-15772 Sentence denotes However, independent self-sustaining human-to-human spread is estimated to already present in multiple major Chinese cities, including Beijing, Shanghai, Guangzhou, and Shenzhen16.
T121 15773-15947 Sentence denotes In addition, pressure on transmission control caused by the population migration after Spring Festival holidays may occur soon, especially in some densely populated cities25.
T122 15948-16057 Sentence denotes Necessary strict measures should still be maintained even when the current measures turn out to be effective.
T123 16058-16089 Sentence denotes Our study has some limitations.
T124 16090-16168 Sentence denotes Firstly, the SEIR model was set up based on a number of necessary assumptions.
T125 16169-16283 Sentence denotes For example, we assumed that no super-spreaders exist in the model, but there is currently no supportive evidence.
T126 16284-16416 Sentence denotes Secondly, the accuracy of the estimation model depends largely on the accuracy of the parameters it used, such as incubation period.
T127 16417-16530 Sentence denotes With more precise parameters obtained as the epidemic progresses, our estimation model will also be more precise.
T128 16531-16651 Sentence denotes Our estimates of the reproductive number from 3.1 to 0.5 are based on previous studies and experience from SARS control.
T129 16652-16763 Sentence denotes However, this measure may change substantially over the course of this epidemic and as additional data arrives.
T130 16764-16881 Sentence denotes Besides, using a fixed Rt value in each phase may incur potential bias because Rt is essentially a dynamic parameter.
T131 16882-16967 Sentence denotes Thirdly, these estimated data may not be sustained if unforeseeable factors occurred.
T132 16968-17099 Sentence denotes For example, if some infections were caused by multiple exposures to animals, these estimates will be exposed to a big uncertainty.
T133 17100-17273 Sentence denotes Fourthly, the epidemic trend shows great difference between Wuhan and Hubei Province and regions in mainland China outside Hubei Province according to the NHC reported data.
T134 17274-17390 Sentence denotes It is thus inappropriate to generalize the estimations in Wuhan to regions in mainland China outside Hubei Province.
T135 17391-17521 Sentence denotes The dynamics model for the other locations in mainland China remains to be developed and specific parameters need to be redefined.
T136 17522-17591 Sentence denotes Lastly, we do not provide model fit information in the current study.
T137 17592-17676 Sentence denotes SEIR model is a prediction model forecasting the number of infections in the future.
T138 17677-17822 Sentence denotes The data corresponding to actual situation in the future cannot be determined and this makes model fitting almost impossible during the outbreak.
T139 17823-17997 Sentence denotes We would carry out model fitting according to the real data in pace with more information and knowledge about the characteristics of COVID-19 and the epidemics in the future.
T140 17998-18182 Sentence denotes Despite the limitations mentioned above, the current study is the first to provide estimation for epidemic trend after strict prevention and control measures were implemented in China.
T141 18183-18334 Sentence denotes Whether current prevention and control measures are sufficient or not may be evaluated through the occurrence of the infection number peak in February.
T142 18335-18498 Sentence denotes Rigorous measures should still be maintained even when the current measures turn out to be effective by the end of February to prevent further spread of the virus.
T143 18500-18521 Sentence denotes Materials and methods
T144 18523-18528 Sentence denotes Model
T145 18529-18679 Sentence denotes We employed an infectious disease dynamics model (SEIR model) for the purpose of modeling and predicting the number of COVID-19 cases in Wuhan, China.
T146 18680-18908 Sentence denotes The model is a classic epidemic method to analyze the infectious disease, which has a definite latent period, and has proved to be predictive for a variety of acute infectious diseases in the past such as Ebola and SARS22,26–31.
T147 18909-19139 Sentence denotes Application of the mathematical model is of great guiding significance to assess the impact of isolation of symptomatic cases as well as observation of asymptomatic contact cases and to promote evidence-based decisions and policy.
T148 19140-19398 Sentence denotes We assumed no new transmissions from animals, no differences in individual immunity, the time-scale of the epidemic is much faster than characteristic times for demographic processes (natural birth and death), and no differences in natural births and deaths.
T149 19399-19669 Sentence denotes In this model, individuals are classified into four types: susceptible (S; at risk of contracting the disease), exposed (E; infected but not yet infectious), infectious (I; capable of transmitting the disease), and removed (R; those who recover or die from the disease).
T150 19670-19730 Sentence denotes The total population size (N) is given by N = S + E + I + R.
T151 19731-19889 Sentence denotes It is assumed that susceptible individuals who have been infected first enter a latent (exposed) stage, during which they may have a low level of infectivity.
T152 19890-20775 Sentence denotes The differential equations of the SEIR model are given as:32,33\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\begin{array}{l}{\mathrm{d}}S/{\mathrm{d}}t = - {\beta}\,{S}\,{I}/{N},\\ {\mathrm{d}}E/{\mathrm{d}}t = {\beta}\,{S}\,{I}/{N} - {\sigma}\,{E},\\ {\mathrm{d}}I/{\mathrm{d}}t = {\sigma}\,{E} - {\gamma}\,{I},\\ {\mathrm{d}}R/{\mathrm{d}}t = {\gamma}\,{I},\\ {\beta} = {R}_{\mathrm{0}}{\gamma},\end{array}$$\end{document}dS∕dt=−βSI∕N,dE∕dt=βSI∕N−σE,dI∕dt=σE−γI,dR∕dt=γI,β=R0γ,where β is the transmission rate, σ is the infection rate calculated by the inverse of the mean latent period, and γ is the recovery rate calculated by the inverse of infectious period.
T153 20776-20875 Sentence denotes R software (version 3.6.2) was applied for all the calculations and estimates in the current study.
T154 20877-20913 Sentence denotes Data collection and parameter values
T155 20915-21009 Sentence denotes Estimation of the epidemic trend assuming the prevention and control measures are insufficient
T156 21010-21134 Sentence denotes We first estimated the epidemic trend in Wuhan, China assuming the current prevention and control measures are insufficient.
T157 21135-21219 Sentence denotes In this process, S was assumed to be the population of Wuhan City (11 million)15,34.
T158 21220-21334 Sentence denotes The initial assumed number of cases caused by zoonotic exposure was 40 (I) according to Imai et al.’s9 estimation.
T159 21335-21399 Sentence denotes We proposed E at 20 times of I in accordance with Read et al.13.
T160 21400-21554 Sentence denotes R was set as 0. σ was set as 1/5.2 according to the latest article by Li et al.15, which calculated the mean incubation period of COVID-19 to be 5.2 days.
T161 21555-21664 Sentence denotes Chen et al.6 calculated the average hospitalization period of 31 discharged patients to be 12.39 ± 4.77 days.
T162 21665-21831 Sentence denotes Yang et al.24 calculated the median time from disease onset to diagnosis among confirmed patients to be 5. γ was accordingly set as 1/18 (ceiling of 12.39 ± 5 is 18).
T163 21832-21949 Sentence denotes R0 was chosen based on Imai et al.’s9 estimation 2.6 (1.9–3.1) assuming 4000 (1000–9700) infections as of 18 January.
T164 21951-22043 Sentence denotes Estimation of the epidemic trend assuming the prevention and control measures are sufficient
T165 22044-22145 Sentence denotes This section discussed the scenario where the current prevention and control measures are sufficient.
T166 22146-22326 Sentence denotes The set of S, E, I, R, σ, and γ is the same as the first section except that we also explored the model with E at 30 times of I to provide a possible range of number of infections.
T167 22327-22425 Sentence denotes The absence of fever in COVID-19 cases is more frequent than in SARS-CoV and MERS-CoV infection35.
T168 22426-22535 Sentence denotes Such patients may be missed since the current surveillance case definition focused mainly on fever detection.
T169 22536-22606 Sentence denotes Accordingly, the possibility of E at 30 times of I cannot be excluded.
T170 22607-22647 Sentence denotes R0 in this section was chosen by phases.
T171 22648-22826 Sentence denotes The first phase ranges from 1 December 2019 to 23 January 2020 and can be regarded as the early phase of the epidemic when a few prevention and control measures were implemented.
T172 22827-22914 Sentence denotes R0 was set as 3.1 consistent with Imai et al.’s9 estimation of high transmission level.
T173 22915-23131 Sentence denotes On 23 January 2020, airplanes, trains, and other public transportation within the city were restricted and other prevention and control measures such as quarantine and isolation were gradually established in Wuhan20.
T174 23132-23268 Sentence denotes So, the second phase began on 24 January and Rt was set as 2.6 consistent with Imai et al.’s9 estimation of moderate transmission level.
T175 23269-23429 Sentence denotes Second February was the last day of the extended Spring Festival holiday and Chinese authorities mobilized more medical resources to support Wuhan ever since36.
T176 23430-23570 Sentence denotes The newly constructed hospital “Huoshenshan” came into service on this day37 and “Leishenshan,” mobile cabin hospitals several days later38.
T177 23571-23622 Sentence denotes Also, more and more medical teams arrived in Wuhan.
T178 23623-23752 Sentence denotes So the third phase began on 3 February and Rt was set as 1.9 consistent with Imai et al.’s9 estimation of low transmission level.
T179 23753-23829 Sentence denotes All of these measures may need one longest incubation period to take effect.
T180 23830-24083 Sentence denotes So, the last phase began on 16 February and Rt was set as 0.9 and 0.5, respectively, assuming the prevention and control measures are sufficient and effective to depict two different levels of effect of the measures in reducing transmission probability.

2_test

Id Subject Object Predicate Lexical cue
32133152-31953166-19616451 538-539 31953166 denotes 5
32133152-12590749-19616452 1437-1439 12590749 denotes 10
32133152-31953166-19616453 2454-2455 31953166 denotes 5
32133152-31953166-19616454 3325-3326 31953166 denotes 5
32133152-12766206-19616455 3336-3338 12766206 denotes 21
32133152-17282008-19616456 18902-18904 17282008 denotes 26
32133152-24012502-19616456 18902-18904 24012502 denotes 26
32133152-28466232-19616456 18902-18904 28466232 denotes 26
32133152-19289133-19616456 18902-18904 19289133 denotes 26
32133152-17254982-19616457 19948-19950 17254982 denotes 32
32133152-15178190-19616458 19951-19953 15178190 denotes 33